research paper topics on memory

201 Memory Research Topics & Essay Examples

Memory is a fascinating brain function. Together with abstract thinking and empathy, memory is the thing that makes us human.

❓ Memory Research Questions

🏆 best memory topic ideas & essay examples, 💭 exciting memory research topics, 💫 interesting memory topics for essays, 👍 research topics about memory in psychology, 🕑 learning & memory research topics, 💡 easy memory essay ideas.

In your essay about memory, you might want to compare its short-term and long-term types. Another idea is to discuss the phenomenon of false memories. The connection between memory and the quality of sleep is also exciting to explore.

If you’re looking for memory topics to research & write about, you’re in the right place. In this article, you’ll find 174 memory essay topics, ideas, questions, and sample papers related to the concept of memory.

• How does sensory memory work?
• How is short-term memory different from long-term memory?
• What memory-training techniques are the most effective?
• What are the reasons for memory failures?
• Memory and aging: what is the connection?
• What are the key types of memory disorders?
• How to improve memory?
• Memory Chart Stages in Psychology For instance, the brain uses the procedural memory to encode procedural skills and tasks that an individual is involved in. The stages of memory are very complex and often pass unrecognized.
• Computer’s Memory Management Memory management is one of the primary responsibilities of the OS, a role that is achieved by the use of the memory management unit.
• Memory for Designs Test The examination of the functioning of the memory of an individual cannot be limited to only one memory test, and as a result, there are a variety of assessments that target the various features of […]
• Memory Model of Teaching and Its Effectiveness The main objective of the research study was to find out the difference in the effect of the memory model and the traditional method of teaching on students’ performance.
• “The Sorrow of War” by Bao Ninh: Memory as a Central Idea The image of soldier Kien in The Sorrow of War demonstrates the difficulties of the Vietnamese people before, through and after this war.
• Memory Test The two controversies determine the classification of memory depending on the form of information processing that occurs in the brain and the different types of memories in relation to the accessibility.
• Long and Short Term Memory The procedure of conveying information from STM to LTM entails the encoding and consolidation of information: it is not a task of time; the more the data resides in STM it increases the chances of […]
• Review of Wordfast: Strengths and Weaknesses of This Translation Memory Tool Recognizing the variety of benefits of using Wordfast in the translation process, it should be noted that the use of this ACT program can have a number of unintended negative implications for the quality of […]
• Love and Memory From a Psychological Point of View The commonly known love types include affection, passionate love, friendship, infatuation, puppy love, sexual love, platonic love, romantic love and many other terms that could be coined out to basically describe love.
• Free and Serial Memory Recalls in Experiments In the study, the experimenters changed the order in which the items were presented to the participants before each trial to test the ability of the subject to recognize these words it was observed that […]
• Memory Strategies Examples and How They Work A good strategy for memory is the one that improves information encoding, necessitates storage of data in a memorable state and enables the mind to easily retrieve information. Indeed, a malfunction in retrieval of stored […]
• Biopsychology of Learning and Memory The hippocampus is a brain region in the form of a horseshoe that plays an essential role in the transformation of information from the short-term memory to the long-term memory.
• Chauri Chaura Incident in History and Memory The book’s first half was a reconstruction, a narrative in historical view of the burning of the chowki or station and the account of the trial that focused on the testimony of the principal prosecution […]
• The Effect of Sleep Quality and IQ on Memory Therefore, the major aim of sleep is to balance the energies in the body. However, the nature of the activity that an individual is exposed to determines the rate of memory capture.
• Shape Memory Alloys (SMAs) The first mentioning of shape memory materials was with the discovery of martensite in 1890, which was the first step for phenomenal discovery of the shape memory effect.
• Community Gatherings and Collective Memory The objective of this paper is to examine some of the gatherings that take place in the community and how these gatherings are related to time.
• Memory Acquisition and Information Processing The problem of disagreeing with memories can be explained by a closer look at the process of memory acquisition. Most part of the sensory information is not encoded due to selective attention.
• Improving Memory and Study Power Study power and memory are important aspects of the learning process and improving them is necessary for success. Working the brain is important in improvement of memory and study power.
• False Memory Syndrome: Is It Real? Freud’s findings bring the idea that some of the memories that are categorized to be false memories that emanates from the unconscious memory.
• Information Processing and Improving Learning and Memory Information processing theory is a method of studying cognitive development that arose from the American experimental psychology tradition.
• Fabricating the Memory: War Museums and Memorial Sites Due to the high international criticism, a very tiny portion of the East Wing is dedicated to explain the context, yet visitors easily overlook the section after the dense display of tragedies after a-bomb in […]
• How Memory and Intelligence Change as We Age The central argument of the paper is that intelligence and memory change considerably across the lifespan, but these alterations are different in the two concepts. The article by Ofen and Shing is a valuable contribution […]
• Concreteness of Words and Free Recall Memory The study hypothesized that the free recall mean of concrete words is not statistically significantly higher than that of abstract words.
• Rivermead Behavioural Memory Test and Cognistat Rivermead Behavioural Memory Test and the Cognistat are the assessment tools employed by the occupational therapists in order to determine the levels of impairment in their mental function that directly impact the individuals’ executive abilities […]
• Brain and Memory Evidence suggests that the amygdala and the hippocampus regions of the brain interact during the formation of verbal and visual memory.
• Amnesia and Long-Term Memory These factors interfere with the function of hippocampus, the section of the human brain that is responsible for the development of memory, storing and organizing information.
• Factors of Learners’ and Adults’ Working Memory An individual’s working memory refers to their ability to access and manipulate bits of data in their mind for a short period.
• Statistics: The Self-Reference Effect and Memory After the distraction part was over, the participants were asked to recall the twelve adjectives they rated from a list of 42 words. This brings the question of whether the results would be different if […]
• Memory Mechanisms: Cognitive Load Theory The teacher’s task is not only to give information but also to explain the principles of learning and to work with it.
• The Self-Reference Effect and Memory Accordingly, the analysis has the following hypotheses: the SRE should enhance recognition of words that participants can relate to themselves, and people should feel more confident about their memory under the SRE.
• Henry Molaison and Memory Lessons The case of Henry Molaison serves as a poignant reminder of the complexity of memory and the importance of understanding its various components.
• Memory and Attention as Aspects of Cognition It has specific definitions, such as “consideration with a view to action,” “a condition of readiness involving a selective narrowing or focusing of consciousness and receptivity,” and “the act or state of applying the mind […]
• Intergenerational Trauma and Traumatic Memory The exploration of interconnected issues of intergenerational trauma and traumatic memory in society with historical data of collective violence across the world sensitizes to the importance of acknowledging trauma.
• The Role of Memory Cells in Cellular Immunity Therefore, when a bacterium gets into the body for a second time, the response is swift because the body has fought it before. Thus, a healthy body can recognize and get rid of chronic microorganisms […]
• Psychological Conditions in Addition to Highly Superior Autobiographical Memory The authors, who have many papers and degrees in the field, have noted the features of the brain structure and the differences between HSAM.
• Cognitive Psychology: The Effects of Memory Conformity The experiment’s control conditions did not allow the witnesses to discuss the event seen in the videos, while in the other condition, the witnesses were encouraged to discuss the event.
• Survival and Memory in Music of the Ghosts by Ratner When it comes to individual memory of Teera’s childhood, the author explains the connection between her memories of her father and musical instruments: “Perhaps it’s because as a child she grew up listening to her […]
• Concept for Teaching Memory in Primary School Students Teaching is one of the most demanding and demanding jobs in the world because it is the job that holds the future generation together.
• ”The Mystery of Memory” Documentary by Gray & Schwarz The documentary examines the brain’s ability to form and retrieve a memory, highlights the importance of neurobiology, and focuses on the problems of PTSD treatment and neuroscience backwardness, concluding that human memory is still a […]
• Draw It or Lose It Memory and Storage Considerations Since the size of the biggest component of this data is known and the additional component can be reasonably estimated, memory for it can be assigned at load time.
• The Multi-Storage Memory Model by Atkinson and Schiffrin The function of the is to track the stimuli in the input register and to provide a place to store the information coming from the LTS.
• Emotions: The Influence on Memory At the same time, the influence of positive and negative feelings on the process of memorization and reproduction is different. In conclusion, it should be said that the process of the influence of emotions on […]
• Civility, Democracy, Memory in Sophocles’ Antigone In Sophocles’ Antigone, the narrative flow makes the audience empathize with the tragic fate of the characters, deepening the emotional involvement of the readers and viewers.
• The Psychological Nature of Memory Using the numerical representation of the participants’ results, the researchers calculated the dependence of the memory and theory of mind in the process of recalling the interlocutors.
• Functioning of Human Memory Schemas Consecutively, the study aimed to identify the relation between the facilitation of prior knowledge schemas and memories and the ability to form new schemas and inferences in older adults.
• Enhancing Individual and Collaborative Eyewitness Memory Considering the positive results of research utilizing category clustering recall and the reported benefits of group memory, a question arises whether the use of category clustering recall might diminish the negative effects of group inhibition.
• Memory: Its Functions, Types, and Stages of Storage First, information is processed in sensory memory, which perceives sensory events for a couple of seconds to determine whether the information is valuable and should be kept for a longer period. As information goes through […]
• The Relationship Between the Working Memory and Non-Conscious Experiences The structure of the proposal follows the logical layout, beginning from the background of the issue through the methodology to problem significance and research innovation.
• Consciousness: The Link Between Working Memory and Unconscious Experience The present study seeks to address the gap in the research regarding the executive function of VWM and consciousness. This study will follow a modified structure of Bergstrom and Eriksson experiment on non-conscious WM to […]
• The Role of Image Color in Association With the Memory Functions Memory is the cornerstone of human cognition that enables all of its profound mechanisms, and the instrument of knowledge acquisition and exchange.
• The Memory Formation Process: Key Issues Hippocampus plays an essential role in the memory formation process because it is the part of the brain where short-term memories become long-term memories.
• Memory Techniques in Learning English Vocabulary ‘Word’ is defined by Merriam Webster Dictionary as follows: “1a: something that is said b plural: the text of a vocal musical composition c: a brief remark or conversation 2a: a speech sound or series […]
• Covalent Modification of Deoxyribonucleic Acid Regulates Memory Formation The article by Miller and Sweatt examines the possible role of DNA methylation as an epigenetic mechanism in the regulation of memory in the adult central nervous system.
• Repressed Memory in Childhood Experiences The suffering often affects a child’s psychological coping capacity in any respect, and one of the only ways of dealing with it is to force the memory out of conscious perception.
• Adaptive Memory and Survival Subject Correlation The results of the study have revealed that the participants found it slightly easier to recall the words related to the notion of survival.
• Developmental Differences in Memory Over Lifespan While growth refers to the multiplication of the number of individual units or cells in the body, maturation on the other hand can be defined as the successive progress of the individual’s appendage land organs […]
• Memory, the Working-Memory Impairments, and Impacts on Memory The first important argument for a thorough discussion on how ADHD could affect brain functioning and working memory impairments is the existence of prominent factors that could create a link between the disorder and the […]
• Working Memory in 7 &13 Years Aged Children However, it was hypothesized that children with AgCC will show similar performance improvement in verbal working memory task performance from 7 to 13 years of age as indicated in the study with CVLT.
• Working Memory & Agenesis of the Corpus Callosum However, it was hypothesized that children with AgCC will show similar improvement in performance on verbal working memory task performance from 7 to 13 years of age as indicated in the study with CVLT.
• Lifespan Memory Decline, Memory Lapses and Forgetfulness The purpose of the research by Henson et al.was to deepen the understanding of differential aging of the brain on differential patterns of memory loss.
• Elaborative Process and Memory Performance The process is significant in the study and retention of data. In addition, the application of the concepts in the author’s learning process will be highlighted.
• The Essence of Context Dependent Memory The results ought to show that the context in which eyewitnesses observed an event is important in the recall memory of the participants.
• “Neural Processing Associated With True and False Memory Retrieval” by Yoko The researchers noted that both true and distorted memories activate activities in the left parental and left frontal areas of the brain. Parahippocampal gyrus- Is the area of the brain that is responsible for processing […]
• Dementia and Memory Retention Art therapy is an effective intervention in the management of dementia because it stimulates reminiscence and enhances memory retention among patients with dementia.
• Biological Psychology: Memory By and large, there is a general agreement that molecular events are involved in the storage of information in the nervous system. It is about to differentiate different kinds of memory, one which is short-term […]
• The Memory of Silence and Lucy: A Detailed Analysis From damaging relationships to her hope to come back to the native land, Lucy has all kinds of issues to address, but the bigger issue is that Lucy’s progress is cyclical, and she has to […]
• Two Tutorials on the Virtual Memory Subject: Studytonight and Tutorials Point The explanation of the demand paging term leads to the concept of a page fault. It is a phrase that characterizes an invalid memory reference that occurs as a result of a program addressing a […]
• The Relationship Between Memory and Oblivion The purpose of this essay is to discuss the relationship between memory and oblivion, private and public recollection of events, and the way these concepts are reflected in the works of Walid Raad, Christo, and […]
• Music and Memory: Discussion Future research should focus on addressing the limitations of the study and exploring the effect of other types of music. The findings of the study are consistent with the current body of knowledge about the […]
• Fuzzy-Trace Theory and False Memory The writers set out to show the common ground for all these varied scenarios and convincingly show that false memories are a result of an interaction between memory and the cognitive process of reasoning. The […]
• Individual Differences in Learning and Memory In the following paper, the variety of learning styles will be evaluated in relation to theories of human learning and memory retrieval on the basis of the findings currently made by academic researchers.
• The Difference Between Females and Males Memory The hippocampus is of importance when it comes to memory formation and preservation and is relatively larger in females than males, giving the females advantage in memory cognition.
• The Nature of False Memory Postevent information is one of the reasons that provoke the phenomenon of misinformation. The participants watched a video of a hockey collision and were asked to estimate the speed of the players.
• Organizational Memory and Intellectual Capital The main emphasis here concerns modalities of motivating the retrieval and use of information and experiences in the OM. The source of intellectual capital arises from the managers’ ability to welcome new information and experiences, […]
• Advertising and Memory: Interaction and Effect An advert sticks into one’s memory when it focuses on the characteristic of the material being advertised, other advertisements competing for the same market niche, and the kind of people it targets.
• The Internet and Autobiographical Memory Allie Young’s blog or journal is a perfect illustration of the impact that social sites and blogs have, since for her autobiographic memory; she uses a blog site to write about issues affecting her life.
• Creativity and Memory Effects in Advertising A study was conducted in China to establish the kind of effects agency creativity has on the total outcome of the advertising campaign.
• Memory, Thinking, and Human Intelligence As Kurt exposits, “The effects of both proactive and retroactive inferences while one is studying can be counteracted in order to maximize absorption of all the information into the long-term memory”.
• Psychological Issues: Self-Identity and Sexual Meaning Issues, and Memory Processing Most sex surveys are run by firms dealing in other products and the motives of the surveys are for marketing of their primary products.
• Human Memory as a Biopsychology Area This paper is going to consider the idea that electrical activity measures of the brain of a human being can be utilized as a great means for carrying out the study of the human memory.
• Biopsychology: Learning and Memory Relationship Memorization involves an integral function of the brain which is the storage of information. Memorization is directly linked to learning through the processes of encoding, storage, and retrieval of information.
• Apiculture: Memory in Honeybees They have a sharp memory to recall the previous locations of food, the scent, and the color where they can get the best nectar and pollen.
• Collective Memory as “Time Out”: Repairing the Time-Community Link The essay will first give an account of how time helps to shape a community, various events that have been formulated in order to keep the community together and the effectiveness of these events in […]
• “The Memory Palace of Matteo Ricci” by Jonathan D. Spence: Concept of Memory Palaces The information concerning Matteo Ricci’s concept of memory palaces presented in the book is generalized to the extent that it is necessary to search for an explanation and some clarifications in the additional sources; “His […]
• Psychology: Memory, Thinking, and Intelligence Information which serves as the stimuli moves from the sensory memory to the short term memory and finally to the long term memory for permanent storage.
• Working With Working Memory Even if we can only make a connection of something we see with a sound, it is easier to remember something we can speak, because the auditory memory helps the visual memory.
• Operant Conditioning, Memory Cue and Perception Operant conditioning through the use of punishment can be used to prevent or decrease a certain negative behavior, for example, when a child is told that he/she will lose some privileges in case he/she misbehaves, […]
• Human Memory: Serial Learning Experiment The background of the current research was stated in Ebbinghaus’ psychological study, and reveals the fact, that if e series of accidental symbols is offered for memorizing, the human memory will be able to memorize […]
• Hot and Cold Social Cognitions and Memory What is mentioned in biology text books and journals about the human brain is so small and almost insignificant compared to the myriad functions and parts of the brain that are yet to be explored.
• Memory Consolidation and Reconsolidation After Sleep The memory consolidation of the visual skill tasks is related to the REM sleep and the short wave component of the NREM.
• Attention, Perception and Memory Disorders Analysis Teenage is the time for experimentation, with a desire to be independent and try new and forbidden things like drugs or indulge in indiscrete sexual activity.
• Autobiographical Memory and Cognitive Development During this stage important cognitive processes take place and are fundamental towards the development of autobiographical memory in the infants. This help the infants to have important memory cues that form part of the autobiographical […]
• Sensory and Motor Processes, Learning and Memory There are three processes involved in the sensory function of the eyes: the mechanical process, the chemical process, and the electrical process. The mechanical process starts as the stimuli passes through the cornea and […]
• Repressed Memory and Developing Teaching Strategies The author aims to emphasize the “importance, relevance, and potential to inform the lay public as well as our future attorneys, law enforcement officers, therapists, and current or future patients of therapists” with regards to […]
• Hippocampus: Learning and Memory The limbic cortex, amygdala, and hippocampus are considered the processing parts of the limbic system while the output part comprises the septal nuclei and the hypothalamus.
• The Implications of False Memory and Memory Distortion The former refers to the manner of impressing into our minds the memories which we have acquired while the former refers to the manner by which a person reclaims the memories which have been stored […]
• Memory Comprehension Issue Review To sum up, studying with the background of loud music is counterproductive, as it is also an information channel that interferes with the comprehension and memorization of more important information.
• The Interaction of Music and Memory Therefore, the research is of enormous significance for the understanding of individual differences in the connection between memory and music. Therefore, the research contributes to the understanding of the interaction of age with music and […]
• The Effect of Memory, Intelligence and Personality on Employee Performance and Behaviour The present paper will seek to explain the theoretical background on memory, intelligence and personality and evaluate the influence of these factors on work performance and employee behaviours.
• Elderly Dementia: Holistic Approaches to Memory Care The CMAI is a nursing-rated questionnaire that evaluates the recurrence of agitation in residents with dementia. Since the research focuses on agitation, the CMAI was utilized to evaluate the occurrence of agitation at baseline.
• The Conceptual Relationship Between Memory and Imagination In particular, the scholar draws parallels between these processes by addressing the recorded activity of specific brain structures when “remembering the past and imagining the future”.
• “How Reliable Is Your Memory?” by Elizabeth Loftus Regardless of how disturbing and sorrowful it may be, and even when pointed out that this certain memory is false, a person may be unable to let it go.
• Chocolate Consumption and Working Memory in Men and Women In this study, the independent variable was chocolate intake, while the dependent variable was the effect of chocolate on the memory of different genders.
• Varlam Shalamov on Memory and Psychological Resilience The soldiers sent to therapists such as Rivers and Yealland in Regeneration had one problem in common they were unable to forget the traumatic and frightening experiences that had affected them in the past.
• Learning Activity and Memory Improvement The easiest way to explain the difference between implicit and explicit types of learning is to think of the latter as active learning and of the former – as passive one.
• Surrealism and Dali’s “The Persistence of Memory” Of course, The Persistence of Memory is one of the best-known works, which is often regarded as one of the most conspicuous illustrations of the movement.
• Psychology: Short-Term and Working Memory The thing is that the term short-term memory is used to describe the capacity of the mind to hold a small piece of information within a very short period, approximately 20 seconds.
• Dealing With the Limitations of Flash Memory Implanted medical chip technology can help to reduce the amount of medical misdiagnosis that occur in hospitals and can also address the issue of the amount of money that Jones Corp.pays out to its clients […]
• Collective Memory and Patriotic Myth in American History However, to think that colonists and early Americans pursued a general policy of killing or driving out the native Indians is incorrect.
• When the Desire Is Not Enough: Flash Memory As a result, a number of rather uncomfortable proposals were made to the founders of Flash, but the company’s members had to accept certain offers for the financing to continue and the firm not to […]
• Effects of Marijuana on Memory of Long-Term Users The pivotal aim of the proposed study is to evaluate the impact of marijuana use on long-term memory of respondents. The adverse impact of marijuana after the abstinent syndrome refers to significant changes in prefrontal […]
• Amphetamines and Their Effects on Memory The scope of the problem of stimulant abuse is quite important in nowadays medicine since the application of amphetamine is not explored in an in-depth manner.
• Memory Retrieval, Related Processes and Secrets The resulting impression of having experienced what is portrayed in the picture leads to the creation of false memories. The authors of the study make it clear that placing one in specific visual and spatial […]
• Mnemonics for Memory Improvement in Students The selected participants will be split into two groups that will be asked to memorize a set of words from a story with the help of the suggested technique.
• The Public Memory of the Holocaust In addition to his pain, Levi concerns the increasing temporal distance and habitual indifference of hundreds of millions of people towards the Holocaust and the survivors1 It causes the feeling of anxiety that was fuelled […]
• Memory Formation and Maintenance The first similarity between working memory and long term memory is that in both cases, tasks retrieve information from secondary memory, although sometimes working memory tasks retrieve information from the primary memory. After completion of […]
• Working Memory Training and Its Controversies As a result, a range of myths about WM has been addressed and subverted successfully, including the one stating that WM related training cannot be used to improve one’s intellectual abilities and skills.
• Music and Human Memory Connection The effects of music on people vary considerably, and this project should help to understand the peculiar features of the connection between human memory and music.
• Music Role in Memory and Learning Processes As such, the study purposed to test the differences in visuospatial abilities between men and women bearing in mind that the former is perceived to demonstrate greater memory capabilities compared to the latter As such, […]
• Working Memory Training: Benefits and Biases The research results indicate that the effects of stereotyping on the development of WM and the relevant skills are direct and rather drastic.
• Memory, Thoughts, and Motivation in Learning Moreover, using the knowledge acquired from various sources of information, students can interpret the contents of their various environments and apply them to their advantage.
• Working Memory Concept The central executive, as the name implies, is the primary component of the working memory system; every other component is subservient to it.
• False Memory and Emotions Experiment The hypothesis was as follows: a list of associate words creates a false memory by remembering a critical lure when the list is presented to a subject and a recall test done shortly after that.
• Building of Memory: Managing Creativity Through Action It could be important for the team to understand Kornfield’s vision of the project, the main and secondary tasks, the project timeline, and the general outline of it. The third technique is to ensure face-to-face […]
• Stroop Effect on Memory Function The aim of the study was to examine the Stroop effect on memory function of men and women. The aim of the study was to examine Stroop effect on men and women’s cognitive functions.
• Misinformation Effect and Memory Impairment It is important to determine the science behind the misinformation effect, because the implication of the study goes beyond the confines of psychology.
• Memory Distortions Develop Over Time Memory is the ability to recall what happened in the past or the process through which one’s brain stores events and reproduce them in the future. Simpson were put on a scoreboard to analyze the […]
• Working Memory Load and Problem Solving The present research focuses on the way working memory load affects problem solving ability and the impact working memory capacity has on problem solving ability of people.
• Sensory Memory Duration and Stimulus Perception Cognitive psychologists argue that perceived information takes one second in the sensory memory, one minute in the short-term memory and a life-time in the long-term memory.
• Memory Study: Mnemonics Techniques Having carried out two experiments, Oberauer comes to the conclusion that information in working memory is highly organized and has its own structure and understanding of this structure can help to improve the work of […]
• Memory Study: Different Perspectives Having carried out two experiments, Oberauer comes to the conclusion that information in working memory is highly organized and has its own structure and understanding of this structure can help to improve the work of […]
• Working Memory Concept: Psychological Views To begin with, the findings support the use of the Working-Memory Model because it offers a clear distinction between the subordinate memory systems and the “central executive” memory.
• Memory Strategies and Their Effects on the Body Memory problems are a common concern in the society due to the increased rate of memory problems among the individuals. This is a strategy that uses chemicals to suppress the adverse effects of memory problems.
• George Santayana’s Philosophy Views on Historical Memory To Plato, democracy was the worst form of governance because it was the tyranny of the multitude. Furthermore, the effects of the war were hard to take because people lost everything they had.
• Cognitive Stimulation on Patients With Impaired Memory Cognitive stimulation therapy is effective in mitigating the effects of dementia. As a result, the researchers tested cognitive stimulation therapy in clinical trials.
• Memory and Emotions in Personal Experience I tried to convince Sherry that the kind of life she led will not do good to her. I thought that Sherry is a grown-up person who would understand the mistakes she had done and […]
• Face Recognition and Memory Retention It is imperative to mention that cognitive process is very significant in face recognition especially due to its role in storage and retrieval of information from long-term memory.
• False Memory Condition: Experimental Studies It is therefore important to conduct some experiments to see the differences between the correct memory and the false memory. The distracters and words to be identified were the variables that were independent.
• Memory Capacity and Age Correlation Since young adults have high levels of positive emotions and low levels of negative emotions, the positive emotions enable them to enhance their memory capacity for positive information.
• Conflict at Walt Disney Company: A Distant Memory? The conflict between Michael Eisner and the Weinstein brothers, the two board members, and Steve Jobs was related to a dysfunctional form of conflict.
• Eye-Path and Memory-Prediction Framework Online marketing and advertising actively develop nowadays, and modern advertisers need to focus on the customers’ attitudes and behaviours in the context of the effectiveness of the advertisement’s location on the web page.
• Long Term Memory and Retrieval The mode of presenting the items in sequence in the first presentation has great impact on the results and validity of the study.
• Denying the Holocaust: The Growing Assault on Truth and Memory by Deborah Lipstadt The book is divided into chapters that focus on the history and methods that are used to distort the truth and the memory of the Holocaust.
• Power, Memory and Spectacle on Saddam Hussein’s Death His rational was that the only way to unite the country was to eliminate the elements of division who in his opinion were the opposition.
• Theoretical Models in Understanding Working Memory The second model for understanding the processes involved in working memory is the Baddeley and Hitch multi-component model which states that working memory operates via a system of “slave systems” and a central controller which […]
• Semantic Memory and Language Production From the foregoing discussions, it can be deduced that the nature and function of semantic memory is closely related to the process of language comprehension. Moreover, lexical retrieval of the semantic memory and phonological facilitation […]
• Basic Functions of Memory and Language The area of semantic memory involves stored information regarding the features and characteristics, which determine the processes of retrieving, using, and producing information in various cognitive processes such as thought and language comprehension/production.
• The Concept of Autobiographical Memory The research findings show that memory phenomenology determined the relationship between attachment avoidance and depression, while the negative affective content of the autobiographical memory determined the link between attachment anxiety and depression. The concept of […]
• Neuroimaging Experiments and Memory Loss Studies This is because it enables the examination of the cognitive and affective processes. This is relative to the effects of alcohol consumption.
• Semantic Memory and Language Production Relationship In the brain, information is arranged both in short-term and long-term memory and this is independent of whether the language in context is first language or a second one.
• Chinese Novellas: The Role of Memory and Perception This is one of the details that attract attention of the readers, and one can say that it is important for understanding the passage and the short story, in general.
• Memory Lane and Morality In the first experiment where participants were expected to remember their childhood experience, those memories aided the experimenter more than they let the participants take control.
• Autonoetic Consciousness in Autobiographical Memory One characteristic of AEM is the mental time travelling on the subjective time in order to connect the past with the current memory status.
• Memory by Analogy: Hiroshima Mon Amour It is quite painful to recall the events that took place in Japan during the Second World War in the aftermath of the atomic bombing of the cities of Nagasaki and Hiroshima.
• Film About Hirosima Memory by Analogy She uses her memory of the human tragedy she witnesses in Hiroshima as a means to forget the pain she has felt since the demise of her lover.
• Memory Theories in Developing Marketing Strategies of the iPad The apple’s communication that was used in marketing the iphone and the ipod is the one to be used in marketing the ipad.
• Definition of Storage Locations in Memory This particular experience can be classified as a type of retrieval mechanism which we all use on a daily yet it is surprisingly similar to the way in which people utilize their local library however […]
• Establishing False Memory in Humans The rate at which the observers included nonexistent words in their recollection of the initial study list was explored and represented in the experiment.
• Constructive Nature of Memory Some of the common symptoms of this disease include loss of speech and the ability to classify objects in the immediate environment of an individual.
• Comparison and Contrast Assignment on “Paradoxical Effects of Presentation Modality on False Memory,” Article and “Individual Differences in Learning and Remembering Music.” In the first block, study list were presented audibly as the experimenter sat in front of the computer and read them aloud while the screen was blinded form the participants. In the second experiment, the […]
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IvyPanda . "201 Memory Research Topics & Essay Examples." March 2, 2024. https://ivypanda.com/essays/topic/memory-essay-topics/.

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Human Memory and Cognition Lab

Research topics.

• Benjamin, A. S. (2008). Memory is more than just remembering: Strategic control of encoding, accessing memory, and making decisions. In A. S. Benjamin & B. H. Ross (Eds.),  The Psychology of Learning and Motivation: Skill and Strategy in Memory Use  (Vol. 48; pp.175-223). London: Academic Press.
• Finley, J. R., Tullis, J. G., & Benjamin, A. S. (2010). Metacognitive control of learning and remembering. In M. S. Khine & I. Saleh (Eds.),  New science of learning: cognition, computers and collaboration in education  (pp. 108-132) . New York: Springer.
• Benjamin, A. S. & Ross, B. H. (2008). Introduction and overview. In A. S. Benjamin & B. H. Ross (Eds.),  The Psychology of Learning and Motivation: Skill and Strategy in Memory Use  (Vol. 48; pp. xi-xiv). London: Academic Press.

Memory and Decision Making We use recognition memory and related tasks as a test bed for developing computational models of memory decisions. In one line of work, we extend decision models based on signal-detection theory to include variable decision noise and to describe more varied memory tasks, including multivariate tasks that involve multiple memory decisions.  For example, querying memory for an event often involves attempts at retrieving information about the event itself (item memory) as well as information about contextual details accompanying that event (source memory) — such as the gender of a speaker, the color a word was printed in, or the physical surroundings of a pictured object.  We also develop process models of recognition judgments in order to test how global deficits in memory fidelity can yield selective deficits on empirical tasks such as source memory judgments. Selected publications on this topic:

• Benjamin, A. S., Diaz, M. L., & Wee, S. (2009). Signal detection with criterion noise: Applications to recognition memory.  Psychological Review, 116 , 84-115.
• Benjamin, A. S. & Bawa, S. (2004). Distractor plausibility and criterion placement in recognition.  Journal of Memory & Language, 51 , 159-172.

Metacognition and metamemory Efficient memory use requires accurate metamemory: the processes that monitor states of learning, knowledge, and skill, and also control the deployment of mnemonic and other cognitive processes to achieve desired states. That is, one must be able to make accurate judgments about one’s current memory state and predictions about future states, and exercise judicious control over the various options at one’s disposal, including encoding and retrieval strategies, study time allocation, item selection, and scheduling of study repetitions. Our research investigates the monitoring and control processes that comprise metamemory by focusing on factors that moderate metamemory performance, such as: prior knowledge, task goals and expectations, time pressure, and stimulus characteristics. For example, we are interested in the conditions under which one exhibits “learning to learn”–adaptively calibrating metamemory in order to more effectively assess and deploy memory resources in the context of a specific task. Our interests also concern the development of ever more sophisticated and rigorous approaches to the analysis and measurement of metamemory. Selected publications on this topic:

• Tullis, J. G. & Benjamin, A. S. (2011). On the effectiveness of self-paced learning.  Journal of Memory and Language ,  64 , 109-118.
• Finley, J. R., Tullis, J. G., & Benjamin, A. S. (2010). Metacognitive control of learning and remembering. In M. S. Khine & I. Saleh (Eds.),  New science of learning: cognition, computers and collaboration in education  (pp. 108-132) . New York: Springer.

Aging and memory The human memory system is constantly changing and adapting throughout the lifespan. Some of these changes result because of the ever growing body of knowledge and experience acquired over a lifetime. The system has to adapt to maintain fluent access to an ever-growing knowledge base. Other changes occur in order to compensate for biological changes that occur with aging. The goal of our research is to understand what aspects of memory and metamemory change across the lifespan and to understand what aspects remain the same. Our basic perspective is that aging involves a global deficit in memory that reveals a landscape of the relative resistance of tasks to disruption.  Further, we investigate changes in older learners’ metamnemonic monitoring and how older learners compensate (or fail to compensate) for changes in memory ability through the use of metamnemonic strategies and behaviors. Selected publications on this topic:

• Benjamin, A. S. (2010). Representational explanations of “process” dissociations in recognition: The DRYAD theory of aging and memory judgments.  Psychological Review, 117 , 1055-1079.
• Benjamin, A. S. & Craik, F. I. M. (2001). Parallel effects of aging and time pressure on memory for source: Evidence from the spacing effect.  Memory & Cognition, 29,  691-697.

Reminding By bringing relevant knowledge to bear in novel circumstances, remindings allow us to thrive in a complex and ever-changing world.  Remindings play a significant role in higher cognition (e.g., problem solving, understanding, generalization, classification, and number representation), but their role in memory has largely been ignored.  We have proposed a reminding theory arguing that remindings play a fundamental role in memory, underlying the effects of both repetition and spacing (Benjamin & Tullis, 2010).  We are currently investigating hypotheses derived from reminding theory concerning remindings’ basic mnemonic effects.  Preliminary results hint that remindings enhance the memory for individual instances in associated pairs, as predicted by reminding theory.  Reminding may be an effective technique to capitalize on the innate strengths of human memory system while minimizing the efforts learners must expend. Selected publications on this topic:

• Benjamin, A. S. & Ross, B. H. (2010). The causes and consequences of reminding. In A. S. Benjamin (Ed.),  Successful remembering and successful forgetting: A Festschrift in honor of Robert A. Bjork  (pp. 71-88). New York, NY: Psychology Press.
• Benjamin, A. S. & Tullis, J. G. (2010). What makes distributed practice effective?  Cognitive Psychology, 61 , 228-247.

Language and memory The goal of our research in language and memory is to understand how linguistic cues can influence memory for words, sentences, or larger texts.  Words contain both semantic information (meaning) and surface form information (the letters or sounds in the words), and these different kinds of cues may remind us of different information or be forgotten at different rates.  Another important cue is the emphasis placed on particular words.  For example, if a speaker emphasizes the word “NEWSPAPER” in the sentence “The NEWSPAPER won an award for covering the fire,” we may focus our memory on different information (that the newspaper won the award, rather what the award was for) or even bring to mind different ideas (who else might have won the award instead of the newspaper?).  Our general view is that linguistic contexts can powerfully influence encoding strategies, which in turn affect memory performance. Selected publications on this topic:

• Matzen, L. E. & Benjamin, A. S. (2009). Remembering words not presented in sentences: How study context changes patterns of false memories.  Memory & Cognition, 37 , 52-64.
• Fraundorf, S. H., Watson, D. G., & Benjamin, A. S. (2010).  Recognition memory reveals just how CONTRASTIVE contrastive accenting really is.  Journal of Memory and Language, 63,  367-386.

Memory for Faces The ability of humans to recognize the faces of recently encountered individuals has generated a vast amount of research. Surprisingly, there is almost no research examining whether we are able to make accurate predictions about our own ability to recognize faces. A well-replicated finding is that people are better at recognizing faces more like their own–their own race, their own age–relative to faces from other groups. We are interested in examining the cognitive and metacognitive processes underlying this bias in face memory: Do people spend less time studying other-race faces relative to own-race faces? Are predictions about later recognition more accurate for own-race faces than for other-race faces? Can individuals use metacognitive information to change their encoding strategy and improve recognition of other-race faces? We are also examining how social information can bias the encoding and recognition of ambiguous race faces. Selected publications on this topic:

• Hourihan, K. L., Benjamin, A. S., & Gronlund, S. D. (2010, November). An own-group bias in metamnemonic accuracy for faces. Poster presented at the annual meeting of the Psychonomic Society, St. Louis, MO.

Journal of Applied Research in Memory and Cognition

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• Journal snapshot

Journal scope statement

The Journal of Applied Research in Memory and Cognition (JARMAC) publishes the highest-quality applied research in memory and cognition, in the format of empirical reports, review articles, and target papers with invited peer commentary. The goal of this unique journal is to reach psychological scientists and other researchers working in this field and related areas, as well as professionals and practitioners who seek to understand and apply research on memory and cognition. In pursuit of these aims, we encourage submissions of original and rigorous work that examines memory and cognitive processes and mechanisms and that informs policies and practices. We further encourage brevity and crisp, lively prose that appeals to a wide audience. Each paper also includes a general audience summary, clearly describing the paper and its practical implications in language accessible to non-specialists.

Empirical reports should convey significant experimental findings. The combined number of words in the introduction and discussion sections should not exceed 2,200 words for single-study reports and 3,000 words for multiple studies (counting the introduction and discussion for each study). These are upper bounds, and authors are expected to keep the report as succinct as possible. This limit is not set for the entire manuscript because the journal seeks to encourage a detailed description of method and a results section that reports outcomes from all tasks.

Target articles should not exceed 10,000 words. Authors considering a target article should contact the editor prior to submission.

JARMAC is an official journal of Society for Applied Research in Memory & Cognition .

Calls for papers

• Call for letters of intent: Autobiographical processing and psychopathology
• Call for letters of intent: A special forum of JARMAC: Applied cognitive science around the globe

Editor’s Choice

One article from each issue of Journal of Applied Research in Memory and Cognition will be highlighted as an “ Editor’s Choice ” article. Selection is based on the recommendations of the associate editors, the paper’s potential impact to the field, the distinction of expanding the contributors to, or the focus of, the science, or its discussion of an important future direction for science. Editor’s Choice articles are featured alongside articles from other APA published journals in a bi-weekly newsletter and are temporarily made freely available to newsletter subscribers.

Author and editor spotlights

Explore journal highlights : free article summaries, editor interviews and editorials, journal awards, mentorship opportunities, and more.

Prior to submission, please carefully read and follow the submission guidelines detailed below. Manuscripts that do not conform to the submission guidelines may be returned without review.

Please complete the author formatting checklist before submitting your manuscript.

To submit to the editorial office of Qi Wang, please submit manuscripts electronically through the Manuscript Submission Portal in Microsoft Word format (.doc) or LaTex (.tex) as a zip file with an accompanied Portable Document Format (.pdf) of the manuscript file.

Double space all copy. Prepare manuscripts according to the Publication Manual of the American Psychological Association using the 7 th edition. Manuscripts may be copyedited for bias-free language (see Chapter 5 of the Publication Manual ). APA Style and Grammar Guidelines for the 7 th edition are available.

Submit Manuscript

Manuscript types

Empirical articles should report significant experimental findings. The combined number of words in the introduction and discussion sections should not exceed 2,200 words for single-study reports and 3,000 words for multiple studies (counting the introduction and discussion of each study). These are upper bounds, and authors are expected to keep the report as succinct as possible. The limit is not set for the entire manuscript because we want to encourage detailed description of method and a results section that reports outcomes from all tasks. The editor may consider exceptions to these limits if special circumstances are justified in the cover letter, but these exceptions will be rare.

Review articles should critically review a topic or topics of importance to the readership of JARMAC , and have no restrictions on length.

Target articles and related peer commentaries are typically invited by the editor. Authors may suggest topics by writing a précis and sending it to the editorial office for consideration. Target articles should not exceed 10,000 words. Authors considering a target article should contact the editor prior to submission.

In Memoriam section An annual In Memoriam section of the journal will celebrate the life and contributions of SARMAC members who have contributed significantly to research in any area of applied cognition and memory. Submissions should be authored by individuals who personally knew or collaborated with the honoree; collaborative contributions are encouraged. Contributions should not exceed 1,000 words and include three to five recommended readings that are selected from the honoree’s contributions. A black-and-white photograph of the honoree may be included. Submissions will be peer-reviewed by scholars familiar with the honoree’s work prior to publication.

Double masked review and the option to bypass

To prepare for (double) masked review (where the names of the authors are withheld from the reviewers and vice versa), authors should make every effort to remove any identifying information from the manuscript and references. All information pertaining to identification, title, institutional affiliation, etc. should be included on the title page, which is submitted separately; only the title of the manuscript should appear on the first page of the manuscript. Alternatively , authors who choose not to have their identities concealed may simply keep the title page as part of the manuscript, submit a blank page as a separate title page, and eschew the other means of removing identifying content. Authors should indicate which option they are choosing in their cover letter.

Authors may submit the names and email addresses of two potential referees. Also indicate whether you believe any potential referees should be excluded. Note that the action editor retains the sole right to decide whether or not the suggested reviewers are used or excluded.

Title. Concise and informative. Titles are often used in information-retrieval systems. Avoid abbreviations and formulae where possible.

Author names and affiliations Please clearly indicate the given name(s) and family name(s) of each author and check that all names are accurately spelled. Present the authors' affiliations (where the actual work was done, including the country name). Indicate all affiliations with a lower- case superscript letter immediately after the author's name and in front of the appropriate address. If the manuscript is by a single author or if all authors are from the same institution, there is no need to use superscripts.

Corresponding author. Clearly indicate who will handle correspondence at all stages of refereeing publication, and post-publication. Provide the email and full postal address of the corresponding author. Ensure that contact details are kept up to date by the corresponding author.

Present/permanent address. If an author has moved since the work described in the article was done, or was visiting at the time, a 'Present address' (or 'Permanent address') may be indicated as a footnote to that author's name. The address at which the author actually did the work must be retained as the main, affiliation address. Superscript Arabic numerals are used for such footnotes.

Word count. For all articles, please declare the word count of your manuscript (upon first submission as well as resubmission). For empirical articles, please also declare the word count of sections identifiable as introduction and discussion.

Abstract and keywords

A concise and factual abstract is required and must contain 150 words or fewer, presented in paragraph form on a separate page (page 2 of the manuscript). The abstract should state briefly the purpose of the research, method, principal results, and major conclusions. An abstract is often presented separately from the article, so it must be able to stand alone. For this reason, references should be avoided, but if essential, then cite the author(s) and year(s). Also, nonstandard or uncommon abbreviations should be avoided, but if essential they must be defined at their first mention in the abstract itself.

Immediately after the abstract, provide a maximum of 6 keywords, using US spelling and avoiding general terms, plural terms, and multiple concepts (e.g., ones connected by conjunctions and prepositions). Be sparing with abbreviations: only abbreviations firmly established in the field may be eligible. These keywords will be used for indexing purposes.

General audience summary

On a separate page, between the abstract and the introduction, type a summary of the research that can be understood by generally educated adults with no particular experience with experimental design and statistical analyses. The paragraph should capture the issue under investigation, the method, the most important outcome, and its implication for or application to real-world settings. This summary, limited to 300 words, should be suitable for circulation to popular media. Like the abstract, the general audience summary will ALSO be uploaded as a separate document during submission, but please do not forget to include both in the document or pdf of your submitted manuscript.

Please read the Guidance for translational abstracts and public significance statements  page to help you write this text.

Research transparency and openness

Data and materials sharing.

The policy of the Journal of Applied Research in Memory and Cognition is to publish papers in which data, methods used in the analysis, and materials used to conduct the research are clearly and precisely documented and are maximally available to any researcher for purposes of reproducing the results or replicating the procedure. Recommended repositories include APA’s repository on the Open Science Framework (OSF), or authors can access a full list of other recommended repositories .

Authors must share their data, analytic methods, and research materials and provide a repository link in their manuscript and during the submission process. If the data and materials on which study conclusions are based are unavailable, the authors should note their legal or ethical reasons for not doing so and are expected to abide by APA’s data preservation policies, specified below under “Ethical Principles.”

For example:

• All data have been made publicly available at the [repository name] and can be accessed at [persistent URL or DOI].
• Materials and analysis code for this study are available by emailing the corresponding author.
• Materials and analysis code for this study are not available.
• The code behind this analysis/simulation has been made publicly available at the [repository name] and can be accessed at [persistent URL or DOI].

Authors must disclose any prior uses of data reported in the manuscript in the author note and in the cover letter, which should include a complete reference list of these articles as well as a description of the extent and nature of any overlap between the present submission and the previous work.

Funding support and conflict of interest

Authors must disclose all sources of financial support for the conduct of the research (e.g., "This research was supported by NIDA grant X") in the author note. If the funding source was involved in any other aspects of the research (e.g., study design, analysis, interpretation, writing), then clearly state the role. If the funding source had no other involvement other than financial support, then simply state that the funding source had no other role other than financial support. Also provide a conflict-of-interest statement disclosing any real or potential conflict(s) of interest, including financial, personal, or other relationships with other organizations or companies that may inappropriately impact or influence the research and interpretation of the findings. If there are no conflicts of interest, this should be clearly stated.

Informed consent and institutional review board approval

Authors must include a statement describing how informed consent was obtained from the participants (or their parents/guardians) and indicate that the study was conducted in compliance with an appropriate Institutional Review Board (IRB). If approval was not obtained, the authors must provide a detailed statement explaining why it was not needed.

Open science badges

JARMAC articles are eligible for open science badges recognizing publicly available data, materials, and/or preregistration plans and analyses. These badges are awarded on a self-disclosure basis .

Applying for open science badges is optional.

Articles are eligible for open science badges recognizing publicly available data, materials, and/or preregistered plans and analyses. These badges are awarded on a self-disclosure basis.

At submission, authors must confirm that criteria have been fulfilled in a signed badge disclosure form (PDF, 42KB) that must be submitted as supplemental material. If all criteria are met as confirmed by the editor, the form will then be published with the article as supplemental material.

Authors should also note their eligibility for the badge(s) in the cover letter.

For all badges, items must be made available on an open-access repository with a persistent identifier in a format that is time-stamped, immutable, and permanent. For the preregistered badge, this is an institutional registration system.

Data and materials must be made available under an open license allowing others to copy, share, and use the data, with attribution and copyright as applicable. Available badges are:

Manuscript preparation

Submission checklist.

Please complete the author formatting checklist before submitting your manuscript. The list will be useful during the final checking of an article prior to sending it to the journal for review. Please consult this Guide for Authors for further details of any item.

Journal Article Reporting Standards

Authors should review the APA Style Journal Article Reporting Standards (JARS) for quantitative , qualitative , and mixed methods . Updated in 2018, the standards offer ways to improve transparency in reporting to ensure that readers have the information necessary to evaluate the quality of the research and to facilitate collaboration and replication.

The new JARS:

• recommend the division of hypotheses, analyses, and conclusions into primary, secondary, and exploratory groupings to allow for a full understanding of quantitative analyses presented in a manuscript and to enhance reproducibility;
• offer modules for authors reporting on replications, clinical trials, longitudinal studies, and observational studies, as well as the analytic methods of structural equation modeling and Bayesian analysis; and
• include guidelines on reporting on of study preregistration (including making protocols public); participant characteristics (including demographic characteristics; inclusion and exclusion criteria) psychometric characteristics of outcome measures and other variables, and planned data diagnostics and analytic strategy.

The guidelines focus on transparency in methods reporting, recommending descriptions of how the researcher’s own perspective affected the study, as well as the contexts in which the research and analysis took place.

Introduction

Describe the objectives of the work and provide an adequate background, but avoid a detailed literature survey or a summary of the results. Begin the first page with the title of the article, not the word Introduction. Remember that the page count applies to all introductory and discussion sections.

Provide sufficient detail to allow the work to be reproduced. Methods already published can be reported by citing the original report and describing modifications. Regardless, authors must include enough detail to make the report comprehensible. Authors must also state their method for determining sample size and report all tasks and procedures conducted prior to the last measure to be analyzed. Procedures not directly relevant to the research question can be described briefly, but they should not be omitted.

Report participant age, gender, race/ethnicity, and other relevant demographic information regarding sample characteristics.

Results should be clear and concise. Describe the outcome both in terms of the statistical analyses and in the language of the research. Include exact p values for statistical tests, measures of effect size, and confidence intervals when appropriate. For experimental reports, effects should be accompanied by their corresponding means and standard deviations, either within the text or in a table. Correlational reports should also include these descriptive statistics. Please consult the APA Style recommendations for reporting all statistical outcomes. Take care to report all experimental conditions and dependent variables associated with the research design, although less central outcomes can be described briefly in summary form or footnotes. Report all data exclusions and the method of determining sample size. Sections that are entitled "Results and Discussion" should minimize discussion. Avoid excessive use of tables and figures. Put nonessential material in "Supplementary Material."

This section should begin with a brief summary of the results in the context of the research issue and continue with a more detailed discussion of their meaning. Be sure to describe the implications of your research for both theoretical concerns and real-world situations and applications. Address important limitations in each domain, as well.

Use of inclusive language

Inclusive language acknowledges diversity, conveys respect to all people, is sensitive to differences, and promotes equal opportunities. Content should make no assumptions about the beliefs or commitments of any reader; contain nothing which might imply that one individual is superior to another on the grounds of age, gender, race, ethnicity, culture, sexual orientation, disability or health condition; and use inclusive language throughout. Authors should ensure that writing is free from bias, stereotypes, slang, reference to dominant culture and/or cultural assumptions. We advise to seek gender neutrality by using plural nouns ("clinicians, patients/clients") as default/wherever possible to avoid using "he, she," or "he/she." We recommend avoiding the use of descriptors that refer to personal attributes such as age, gender, race, ethnicity, culture, sexual orientation, disability or health condition unless they are relevant and valid. These guidelines are meant as a point of reference to help identify appropriate language but are by no means exhaustive or definitive.

Author contribution statements using CRediT

The APA Publication Manual ( 7th ed. ) , which stipulates that "authorship encompasses…not only persons who do the writing but also those who have made substantial scientific contributions to a study." In the spirit of transparency and openness, Journal of Applied Research in Memory and Cognition has adopted the Contributor Roles Taxonomy (CRediT) to describe each author's individual contributions to the work. CRediT offers authors the opportunity to share an accurate and detailed description of their diverse contributions to a manuscript.

Submitting authors will be asked to identify the contributions of all authors at initial submission according to the CRediT taxonomy. If the manuscript is accepted for publication, the CRediT designations will be published as an author contributions statement in the author note of the final article. All authors should have reviewed and agreed to their individual contribution(s) before submission.

CRediT includes 14 contributor roles, as described below:

• Conceptualization : Ideas; formulation or evolution of overarching research goals and aims.
• Data curation : Management activities to annotate (produce metadata), scrub data and maintain research data (including software code, where it is necessary for interpreting the data itself) for initial use and later re-use.
• Formal analysis : Application of statistical, mathematical, computational, or other formal techniques to analyze or synthesize study data.
• Funding acquisition : Acquisition of the financial support for the project leading to this publication.
• Investigation : Conducting a research and investigation process, specifically performing the experiments, or data/evidence collection.
• Methodology : Development or design of methodology; creation of models.
• Project administration : Management and coordination responsibility for the research activity planning and execution.
• Resources : Provision of study materials, reagents, materials, patients, laboratory samples, animals, instrumentation, computing resources, or other analysis tools.
• Software : Programming, software development; designing computer programs; implementation of the computer code and supporting algorithms; testing of existing code components.
• Supervision : Oversight and leadership responsibility for the research activity planning and execution, including mentorship external to the core team.
• Validation : Verification, whether as a part of the activity or separate, of the overall replication/reproducibility of results/experiments and other research outputs.
• Visualization : Preparation, creation and/or presentation of the published work, specifically visualization/data presentation.
• Writing — original draft : Preparation, creation and/or presentation of the published work, specifically writing the initial draft (including substantive translation).
• Writing — review and editing : Preparation, creation and/or presentation of the published work by those from the original research group, specifically critical review, commentary or revision: including pre- or post-publication stages.

Authors can claim credit for more than one contributor role, and the same role can be attributed to more than one author.

Math formulae and display equations

We strongly encourage you to use MathType (third-party software) or Equation Editor 3.0 (built into pre-2007 versions of Word) to construct your equations, rather than the equation support that is built into Word 2007 and Word 2010. Equations composed with the built-in Word 2007/Word 2010 equation support are converted to low-resolution graphics when they enter the production process and must be rekeyed by the typesetter, which may introduce errors.

To construct your equations with MathType or Equation Editor 3.0:

• Go to the Text section of the Insert tab and select Object.
• Select MathType or Equation Editor 3.0 in the drop-down menu.

If an equation has already been produced using Microsoft Word 2007 or 2010 and authors have access to the full version of MathType 6.5 or later, they can convert this equation to MathType by clicking on MathType Insert Equation. Copy the equation from Microsoft Word and paste it into the MathType box. Verify that the equation is correct, click File, and then click Update. The equation has now been inserted into your Word file as a MathType Equation.

Use Equation Editor 3.0 or MathType only for equations or for formulas that cannot be produced as Word text using the Times or Symbol font.

Computer code

Because altering computer code in any way (e.g., indents, line spacing, line breaks, page breaks) during the typesetting process could alter its meaning, we treat computer code differently from the rest of the article in the production process. Supply separate files for computer code.

In online supplemental material

Runnable source code should be included as supplemental material to the article. For more information, visit supplementing your article with online material .

In the text of the article

If authors would like to include code in the text of the published article, submit a separate file with your code exactly as it should appear, using Courier New font with a type size of 8 points. An image will be made of each segment of code in your article that exceeds 40 characters in length. (Shorter snippets of code that appear in text will be typeset in Courier New and run in with the rest of the text.) If an appendix contains a mix of code and explanatory text, please submit a file that contains the entire appendix, with the code keyed in 8-point Courier New.

Use Word's insert table function when you create tables. Using spaces or tabs in your table will create problems when the table is typeset and may result in errors.

Review APA's  Journal Manuscript Preparation Guidelines  before submitting your article. Tables can be placed either next to the relevant text in the article, or on separate page(s) at the end.

Preferred formats for graphics files are TIFF and JPG, and preferred format for vector-based files is EPS. Graphics downloaded or saved from web pages are not acceptable for publication. Multipanel figures (i.e., figures with parts labeled a, b, c, d, etc.) should be assembled into one file. When possible, please place symbol legends below the figure instead of to the side.

• All color line art and halftones: 300 DPI
• Black and white line tone and gray halftone images: 600 DPI

Line weights

• Color (RGB, CMYK) images: 2 pixels
• Grayscale images: 4 pixels
• Stroke weight: 0.5 points

APA offers authors the option to publish their figures online in color without the costs associated with print publication of color figures.

The same caption will appear on both the online (color) and print (black and white) versions. To ensure that the figure can be understood in both formats, authors should add alternative wording (e.g., “the red (dark gray) bars represent”) as needed.

For authors who prefer their figures to be published in color both in print and online, original color figures can be printed in color at the editor's and publisher's discretion provided the author agrees to pay:

• $900 for one figure
• An additional $600 for the second figure
• An additional $450 for each subsequent figure

Academic writing and English language editing services

Authors who feel that their manuscript may benefit from additional academic writing or language editing support prior to submission are encouraged to seek out such services at their host institutions, engage with colleagues and subject matter experts, and/or consider several vendors that offer discounts to APA authors .

Please note that APA does not endorse or take responsibility for the service providers listed. It is strictly a referral service. Use of such service is not mandatory for publication in an APA journal. Use of one or more of these services does not guarantee selection for peer review, manuscript acceptance, or preference for publication in any APA journal.

Submitting supplemental materials

APA can place supplemental materials online, available via the published article in the APA PsycArticles ® database. Please see supplementing your article with online material for more details.

List references in alphabetical order. Each listed reference should be cited in text, and each text citation should be listed in the references section.

Examples of basic reference formats:

Journal article

McCauley, S. M., & Christiansen, M. H. (2019). Language learning as language use: A cross-linguistic model of child language development. Psychological Review , 126 (1), 1–51. https://doi.org/10.1037/rev0000126

Authored book

Brown, L. S. (2018). Feminist therapy (2nd ed.). American Psychological Association. https://doi.org/10.1037/0000092-000

Chapter in an edited book

Balsam, K. F., Martell, C. R., Jones. K. P., & Safren, S. A. (2019). Affirmative cognitive behavior therapy with sexual and gender minority people. In G. Y. Iwamasa & P. A. Hays (Eds.), Culturally responsive cognitive behavior therapy: Practice and supervision (2nd ed., pp. 287–314). American Psychological Association. https://doi.org/10.1037/0000119-012

Data set citation

Alegria, M., Jackson, J. S., Kessler, R. C., & Takeuchi, D. (2016). Collaborative Psychiatric Epidemiology Surveys (CPES), 2001–2003 [Data set]. Inter-university Consortium for Political and Social Research. https://doi.org/10.3886/ICPSR20240.v8

Software/Code citation

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Working memory and attention – a conceptual analysis and review.

• Klaus Oberauer

There is broad agreement that working memory is closely related to attention. This article delineates several theoretical options for conceptualizing this link, and evaluates their viability in light of their theoretical implications and the empirical support they received. A first divide exists between the concept of attention as a limited resource, and the concept of attention as selective information processing. Theories conceptualizing attention as a resource assume that this resource is responsible for the limited capacity of working memory. Three versions of this idea have been proposed: Attention as a resource for storage and processing, a shared resource for perceptual attention and memory maintenance, and a resource for the control of attention. The first of these three is empirically well supported, but the other two are not. By contrast, when attention is understood as a selection mechanism, it is usually not invoked to explain the capacity limit of working memory – rather, researchers ask how different forms of attention interact with working memory, in two areas. The first pertains to attentional selection of the contents of working memory, controlled by mechanisms of filtering out irrelevant stimuli, and removing no-longer relevant representations from working memory. Within working memory contents, a single item is often selected into the focus of attention for processing. The second area pertains to the role of working memory in cognitive control. Working memory contributes to controlling perceptual attention – by holding templates for targets of perceptual selection – and controlling action – by holding task sets to implement our current goals.

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There is a broad consensus that working memory and attention are intimately linked ( Awh, Jonides, & Reuter-Lorenz, 1998 ; Baddeley, 1993 ; Chun, 2011 ; Cowan, 1995 ; Gazzaley & Nobre, 2012 ; Kane, Bleckley, Conway, & Engle, 2001 ; Kiyonaga & Egner, 2014 ; Oberauer, 2009 ; Olivers, 2008 ). But what is it that we agree upon? Both working memory and attention can be conceptualized in different ways, resulting in a broad array of theoretical options for linking them. The purpose of this review is to propose a map for organizing these theoretical options, delineate their implications, and to evaluate the evidence for each of them.

The meaning of the concept working memory (WM) depends on the theory in which the concept figures. The definitions reviewed by Cowan ( 2017 ) differ primarily in the substantive assumptions they include (e.g., whether or not WM consists of multiple storage modules, and to what extent it includes long-term memory). Beyond these differences in theoretical assumptions, however, there is a broad consensus on what the term working memory refers to: The mechanisms and processes that hold the mental representations currently most needed for an ongoing cognitive task available for processing.

The meanings of the term attention are more diverse, as they reflect distinctions not only of definitions but also of different referents of the term: Attention is not a unitary entity ( Chun, Golomb, & Turk-Browne, 2011 ). Conceptualizations of attention can be distinguished along several dimensions that provide a coordinate system for our conceptual map. A first distinction pertains to how attention is defined. One definition of attention characterizes it as a limited resource for information processing (e.g., Wickens, 1980 ). Another concept of attention is as a process of (or mechanism for) selection of information to be processed with priority (e.g., Chun et al., 2011 ; Desimone & Duncan, 1995 ). These two concepts of attention play different roles in theorizing about working memory, and I will discuss them in turn below.

A second distinction pertains to what we attend to. I find it useful to distinguish the possible objects of attention along two dimensions (see Table 1 ). 1 First, we can distinguish between attention to our currently perceived environment (e.g., attention to visual objects or auditory streams) from attention to information currently not perceived, such as attention to remembered episodes or concepts that we think about. 2 Second, we can distinguish between attention to things and events in the world around us on the one hand, and attention to our own goals and (mental or overt) actions on the other. The latter form of attention includes selection of our current goal or task set and shielding it from distraction ( Kane & Engle, 2003 ; Monsell, 2003 ), selection of one of several possible actions ( Pashler, 1994 ), and monitoring of our actions and their outcomes ( Yeung, Botvinick, & Cohen, 2004 ).

A Taxonomy of Attention.

Note: Descriptions pertaining to attention as selection/prioritization are printed in regular font; descriptions pertaining to attention as a resource in italics.

A third distinction pertains to the forces that determine what we attend to – this is the distinction between controlled and automatic deployment of attention ( Shiffrin & Schneider, 1977 ). Attention is controlled when it is directed according to our current goals. The influence of current goals on attention is often referred to as “top-down”. Attention is automatic to the extent that its direction is influenced by forces independent of our current goals – these include the “bottom-up” attraction of attention by perceived properties of the stimuli (e.g., their “salience”) as well as influences of our learning history on what we attend to, for instance when attention is drawn to information that we have learned to be relevant ( Awh, Belopolsky, & Theeuwes, 2012 ; Theeuwes, 2018 ).

The concept of executive attention is often used when discussing the relation between attention and working memory. Executive attention is a term that is notoriously poorly defined ( Jurado & Rosselli, 2007 ). It is used on the one hand to refer to attention directed to one’s own goals and (mental or overt) actions, including response selection ( Szmalec, Vandierendonck, & Kemps, 2005 ), action planning, protecting the pursuit of our current goal from distractions and temptations, as well as switching from one task to another. On the other hand, executive attention is also used to refer to the top-down control of attention, including attention to things and events in the environment – for keeping our attention on the relevant stimuli or features and avoiding distraction by irrelevant ones, as in the Stroop task and the flanker task. As such, the term executive attention is used to denote one pole on each of two dimensions in my proposed taxonomy, one pertaining to the objects of attention (things and events in the world vs. our own goals and actions), the other pertaining to what determines the orientation of attention (controlled vs. automatic). The first meaning assigns executive attention a function in controlling our thoughts and actions (including what we attend to) whereas the second states that executive attention is itself controlled. One way to perhaps bring together the two meanings is by assuming that we attend to (i.e., select, assign resources to) our own goals and actions – including the action of attending to some object – in order to control them. Nevertheless, I find the term executive attention disquietingly ambiguous, and therefore will use instead the terms attention to (cognitive) action and controlled attention to refer to the two aspects of executive attention, respectively.

I organize the review by the two definitions of attention – as a resource or as a selection mechanism – because they have different implications for how attention and working memory are related. Within each section I will discuss the different objects of attention, and the different modes of control.

Attention as a Resource

The idea of attention as a resource is that the cognitive system has a limited resource that can be used for carrying out so-called attention-demanding processes. The resource is assumed to be a continuous quantity that can be split arbitrarily and allotted to different processes, depending on task demands. Processing efficiency (i.e., speed, accuracy) is a positive monotonic function of the amount of resource assigned to a process ( Navon & Gopher, 1979 ). The assumption that WM capacity reflects a limited resource has a long tradition ( Anderson, Reder, & Lebiere, 1996 ; Case, 1972 ; Just & Carpenter, 1980 ; Ma, Husain, & Bays, 2014 ). Authors linking WM to an attentional resource are endorsing the view that the limited capacity of WM reflects a limited resource, and that this resource also serves some (or all) functions commonly ascribed to attention. Three versions of this idea can be distinguished by which functions the attentional resource is assumed to be needed for: (1) storage and processing of information (e.g., Just & Carpenter, 1992 ), (2) perceptual attention and memory maintenance (e.g., Ester, Fukuda, May, Vogel, & Awh, 2014 ; Kiyonaga & Egner, 2014 ), or (3) the control of attention (e.g., Allen, Baddeley, & Hitch, 2006 ; Baddeley, 1993 , 1996 ; Lavie, 2005 ).

Attention for Storage and Processing

Many theorists discussing the relation between working memory and attention characterize attention as a limited resource for maintaining representations in an “active”, available state ( Cowan, 2005 ). Often this resource is assumed to be shared between “storage” and “processing” ( Case, Kurland, & Goldberg, 1982 ; Cowan et al., 2005 ; Just & Carpenter, 1992 ). According to this view, the same attentional resource is required for keeping representations available and for carrying out certain basic cognitive processes such as selecting a response to a stimulus. A prediction from this theory is that attention-demanding cognitive processes compete with concurrent storage ( Z. Chen & Cowan, 2009 ).

There are two variants of this theoretical idea. One is that a share of the resource needs to be continuously assigned to a representation to keep it in WM ( Case et al., 1982 ). The other is that attention is required directly only for processing, not storage. In this view attention indirectly contributes to memory maintenance because it is needed for refreshing WM representations, which would otherwise decay ( Barrouillet, Bernardin, & Camos, 2004 ). Barrouillet and colleagues further specify the resource required for refreshing as the limited resource for so-called central processes, such as response selection ( Barrouillet, Bernardin, Portrat, Vergauwe, & Camos, 2007 ). Dual-task studies with variants of the PRP (psychological refractory period) paradigm have established a strong capacity limit on central processes ( Pashler, 1994 ), which has been explained by a limited central-attentional resource ( Navon & Miller, 2002 ; Tombu & Jolicoeur, 2003 ).

Theorists linking WM to attention as resource commonly assume that there is a single, content-general attentional resource. It follows that storage and processing compete with each other whether or not they share any contents. This assumption leads to the prediction of dual-task costs when WM storage and processing demands from very different contents are combined with each other. There is considerable evidence confirming this prediction ( Chein, Moore, & Conway, 2011 ; Morey & Bieler, 2012 ; Saults & Cowan, 2007 ; Vergauwe, Barrouillet, & Camos, 2010 ), lending support to the notion that WM capacity is limited by an attentional resource. There is also evidence that storage and processing compete for central processing capacity: The extent to which maintenance in WM is impaired by concurrent processing is a monotonic function of cognitive load , defined as the proportion of time during which central attention is engaged by the processing demand ( Barrouillet et al., 2007 ).

One problem for the assumption of a shared resource for storage and processing is that, although a memory load reduces the efficiency of concurrent response-selection tasks, that dual-task cost diminishes substantially over the first few seconds of the retention interval ( Jolicoeur & Dell’Acqua, 1998 ; Thalmann, Souza, & Oberauer, 2019 ; Vergauwe, Camos, & Barrouillet, 2014 ), and is often not observed at all when there is an unfilled interval of a few seconds between encoding of the memory set and commencement of the processing task ( Hazeltine & Witfall, 2011 ; Klapp, Marshburn, & Lester, 1983 ; Oberauer, Demmrich, Mayr, & Kliegl, 2001 ). This observation has already led Klapp and colleagues ( 1983 ) to question the idea of a shared resource for storage and processing: To uphold this idea we would have to assume that the resource demand of maintenance dwindles to a negligible level within a few seconds. This would be compatible with the assumption that a central processing resource is required for short-term consolidation of information in working memory ( Jolicoeur & Dell’Acqua, 1998 ; Nieuwenstein & Wyble, 2014 ; Ricker & Hardman, 2017 ) but not with the assumption that a resource is needed for maintenance throughout the retention interval.

As mentioned above, the assumption of shared resources for storage and processing comes in two variants: The first, traditional one is that a representation needs a share of the resource assigned to it to be in WM, and the same resource is needed for carrying out cognitive operations. The second variant is that maintenance processing such as refreshing share a limited resource with other cognitive operations ( Barrouillet et al., 2004 ). The second variant rests on the premise that without refreshing the representations in WM decay – only on that assumption does the processing resource assigned to refreshing become essential for WM maintenance. The decay assumption, however, is probably not true, at least for verbal materials ( Oberauer & Lewandowsky, 2013 , 2014 ).

The first variant has a conceptual problem: Simultaneous maintenance and processing compete for a shared resource only until the processing task is completed – after that, the full resource can be re-assigned to the representations in WM. Why then should memory performance suffer from a concurrent processing task although memory is tested only after the processing task is done? (for a more detailed treatment see Oberauer, Farrell, Jarrold, & Lewandowsky, 2016 ). The problem is illustrated by a study that, according to the authors, reveals the neuronal basis of resource sharing: Watanabe and Funahashi ( 2014 ) recorded from multiple neurons in the lateral pre-frontal cortex (LPFC) while monkeys did a spatial attention task, a spatial WM task, or a dual-task combination of the two. The two tasks recruited largely overlapping LPFC neurons, which showed spatial selectivity when each task was done alone. While both tasks were done simultaneously, the LPFC neurons lost most of their spatial selectivity, and collectively their firing rate pattern contained less information about the attended location and the remembered location during that period. After the attention task was completed, however, the information about the location in memory was “reawakened” in the firing pattern of the LPFC neurons, reaching the same strength as in the single-task condition. The authors did observe a (small) performance decrement in the dual-task relative to the single-task condition, but that dual-task cost is not explained by their neural data – looking at the neural data, we would expect no detrimental effect on memory by the concurrent attention task.

To conclude, the assumption of a shared resource for memory retention and central processes has received much empirical support. At the same time, it is challenged by the finding that dual-task costs on processing speed tend to vanish over time, and – depending on the version endorsed – the lack of evidence for decay, and the problem of how to explain that the competition between processing and storage affects memory performance after the competition has ended.

Attention for Perception and Memory

A resource shared between “storage” and “processing” spans both sides of the distinction between attention to things and events (i.e., the information to be stored), and attention to goals and actions (i.e., to the task sets guiding the processing operations). We can also ask whether the same resource applies to both sides of another distinction, the one between perceptual attention and attention to not-perceived objects. Most task paradigms for studying WM require retention of information in the absence of perceptual input. There is evidence, however, that the limited capacity of WM applies not only to information in memory but equally to information still in view. Tsubomi, Fukuda, Watanabe, and Vogel ( 2013 ) measured the contralateral delay activity (CDA), a neural marker of the number of objects a person holds in visual WM ( Luria, Balaban, Awh, & Vogel, 2016 ; Vogel & Machizawa, 2004 ) while participants attended to a variable number of color patches still in view, or attempted to remember them after their offset. In both cases, the CDA amplitude increased with set size up to about 3 items and then levelled off. Individual CDA amplitudes correlated with performance on a test of one randomly selected item regardless of whether that item remained in view until the time of test or had to be retained in memory for a second.

The study of Tsubomi et al. ( 2013 ) shows striking similarities between the capacity limits for attending to perceptual stimuli and for maintaining stimuli in memory (see also Ester et al., 2014 ). Still, these two functions could rely on separate resources that happen to bear similarities to each other. If the same limited resource underlies perceptual attention and maintenance in WM, then demanding both at the same time should incur a substantial dual-task cost, such that when the load of one task is increased, performance on the other suffers. The evidence for this prediction is mixed. Fougnie and Marois ( 2006 ) found load-dependent dual-task costs when combining a visual WM task with a visual attention task (simultaneous tracking of multiple moving objects, or monitoring multiple parallel streams of rapidly presented visual stimuli for a target) but these costs were less than the cost of combining two visual WM tasks. Souza and Oberauer ( 2017 ) found only negligible dual-task costs when inserting a visual attention task (monitoring a stimulus for a subtle brightness change) in the retention interval of a visual WM task. Several studies investigated dual-task costs between WM and visual search. These dual-task costs increase with the load on each of the two tasks – as expected on the assumption of a shared resource – only when the contents of WM were spatial locations (for a review see Woodman & Chun, 2006 ). To conclude, although attending to perceptual information and maintaining information in WM after it disappeared from the environment have much in common, the evidence that they share a limited resource is not yet convincing.

Controlled Attention

The concept of attention as a limited resource is often linked specifically to controlled attention, whereas automatic attention is thought not to be resource demanding ( Schneider & Shiffrin, 1977 ; Shiffrin & Schneider, 1977 ). There are two ways in which this link can be spelled out: (a) Attention that is allocated in a controlled manner – according to “top down” influences from our current goals – underlies a resource limit but attention that is automatically attracted to some information independent of its relevance for our current goal does not underlie that resource limit. Stated in this way we face the awkward conclusion that allocating attention to the same object (e.g., a red traffic light in a street scene, or a word we hold in WM) does or does not rely on a limited resource depending on what forces led attention to that object. The same cognitive function – prioritizing processing of the attended information – would be resource consuming or not depending on how it was invoked.

In my view, a less awkward interpretation is: (b) Paying attention to an object does not require a resource per se – rather the process of controlling attention in a top-down manner consumes the limited resource. This interpretation reflects how Shiffrin and Schneider ( 1977, p. 156 ) explain why controlled processes are capacity limited: These processes need to be controlled by continuously paying attention to them, and attention cannot be allocated to more than one process at a time. In other words, the attentional resource imposes a bottleneck on the control processes, not on the controlled processes. The limitation is on how many different (cognitive or overt) actions we can attend to at the same time in order to control them. For instance, in visual search, perceptual attention can be drawn to some stimuli automatically, and theoretically there is no limit on how many such forces exert their pull in parallel. Perceptual attention can also be directed in a controlled manner – by attending to the action of deploying attention to visual stimuli – and this control process is limited to one action at a time. The limitation does not rest with the controlled attention – a limit on how many visual stimuli can be attended at the same time – but with the controlling attention.

This conception of an attentional resource differs from the preceding two. The notion of a resource for storage and processing and the idea of a shared attentional resource for perception and memory share the assumption that the resource is allocated to representations of objects and events that we perceive or hold in WM. In contrast, the “attentional control” idea assumes a resource for the control of what we attend to, and more generally, of what we think and do. These conceptualizations have different implications when we apply them to WM. For instance, consider a situation in which WM receives an overload of information, some of which is relevant and some of which is irrelevant. Examples of this scenario are the complex-span paradigm ( Daneman & Carpenter, 1980 ), in which to-be-remembered items alternate with stimuli to be processed but not retained, or the filtering paradigm ( Vogel, McCollough, & Machizawa, 2005 ), in which participants see an array of visual stimuli and need to remember a pre-defined subset (e.g., only the red objects). According to theories assuming a limited resource allocated to representations in WM, attention limits how much of the given information can be retained, and a separate parameter determines the filtering efficiency, that is, the extent to which the cognitive system manages to keep the distractor information out of WM, so that it does not consume part of the valuable storage resource. These theories predict that individuals with lower WM capacity maintain a smaller amount of both relevant and irrelevant information, but their proportion, reflecting filtering efficiency, should be independent of WM capacity. According to the controlled-attention view, by contrast, the attentional resource determines the filtering efficiency. Hence, individuals with lower WM capacity retain the same amount of information as those with higher capacity, but people differing in WM capacity differ in the ratio of relevant to irrelevant information that they retain.

Paradoxes lurk when we try to combine the two notions of attentional resources, assuming that the same limited resource is required for both storage and control: According to this fusion version of the attentional-resource idea, keeping some irrelevant piece of information out of WM, or removing it from WM, consumes attentional resource (because it is an act of control over what we attend to) and at the same time frees up attentional resource (because it reduces the amount of information that is held in WM). In the same manner, stopping a cognitive process costs attentional resource but at the same time frees up attentional resource. With such a conception, it becomes virtually impossible to say whether some cognitive process – such as filtering or deleting information from WM – renders a net cost or a net gain in resource. As a consequence, the theory becomes untestable. This problem needs to be kept in mind when attempts are made to reconcile the two versions of attentional-resource theories of WM (e.g., Cowan, Fristoe, Elliott, Brunner, & Saults, 2006 ). 3

If WM and the control of attention share a limited resource, we should expect substantial dual-task costs when an attention-control demand is combined with WM maintenance. Evidence for such a dual-task cost comes from studies demonstrating that a load on WM increases people’s susceptibility to distraction, for instance by the irrelevant stimuli in a flanker task ( Kelley & Lavie, 2011 ; Lavie, Hirst, de Fockert, & Viding, 2004 ). Interpretation of this result is complicated by the observation that only a verbal WM load increases the flanker effect – a visual WM load has the opposite effect ( Konstantinou, Beal, King, & Lavie, 2014 ; Konstantinou & Lavie, 2013 ). Konstantinou et al. ( 2014 ) explain this dissociation by assuming that visual WM contents place a load on a visual perceptual resource, and increasing the load on perceptual resources has been shown to reduce flanker interference ( Lavie, 2005 ). In contrast, verbal WM relies on rehearsal for maintenance, and rehearsal competes for a shared attentional-control resource with the control of visual attention. The latter assumption is at odds with the position of most other resource theorists, who assume that rehearsal requires little, if any such resource ( Baddeley, 1986 ; Camos, Lagner, & Barrouillet, 2009 ; Cowan, 2001 ). Other studies provide further evidence that a load on WM can both increase and decrease people’s distractability by a flanker stimulus during a perceptual comparison task: When the category of stimuli held in WM matched that of the targets of the comparison task (but not that of the flankers), the flanker compatibility effect increased, but when the WM contents matched the category of the flankers, and not the targets, then the flanker compatibility effect decreased under load compared to no load ( Kim, Kim, & Chun, 2005 ; Park, Kim, & Chun, 2007 ). Taken together, there is no convincing evidence that loading WM depletes a resource needed for the control of attention.

We can also ask whether concurrent demands on the control of attention impair performance in a WM task. This appears not to be the case. The effect of concurrent processing on memory is larger when the processing task requires more attention control (e.g., task switching vs. task repetition, incongruent vs. neutral Stroop trials), but that effect is entirely accounted for by the longer duration of response selection in the more difficult conditions ( Barrouillet, Portrat, & Camos, 2011 ; Liefooghe, Barrouillet, Vandierendonck, & Camos, 2008 ). Hence, the dual-task cost of concurrent processing for memory is a function of the demand on central attention for action selection, not the demand on the control of attention. Moreover, Lawrence, Myerson, Oonk, and Abrams ( 2001 ) found that when people had to make saccades to irrelevant locations during the retention interval, memory performance is impaired, in particular for spatial information. That effect was equally large for reflexive saccades towards a suddenly appearing target and for controlled anti-saccades away from a target, contrary to the assumption that the control of attention in the anti-saccade condition competes for WM resources. Bunting, Cowan, and Colflesh ( 2008 ) used a manual analog of the anti-saccade task as distractor activity during the retention interval, and found significantly worse performance in the anti-press than the pro-press condition in only 3 out of 12 experimental conditions.

A second prediction from the assumption that WM maintenance and controlled attention share a resource is that measures of the efficiency of the two should be correlated across individuals. This prediction has been tested with regard to two forms of control over the contents of WM ( Hasher, Zacks, & May, 1999 ): Filtering irrelevant stimuli at encoding so that they never enter WM, and removal of no-longer relevant stimuli from WM after they have been encoded. Support for the prediction comes from studies measuring filtering efficiency in visual change-detection tasks through the effect of irrelevant stimuli on the CDA ( Vogel et al., 2005 ). Individual differences in filtering efficiency are strongly correlated with accuracy in change detection ( Luria et al., 2016 ). However, when Mall, Morey, Wolff, and Lehnert ( 2014 ) measured filtering efficiency through behavioral indicators – the performance gain from being able to ignore half the stimuli in the array, and the proportion of time people fixated on locations of irrelevant stimuli during encoding and retention – they found no correlation with people’s WM capacity, measured through complex-span tasks. One possible interpretation is that controlled attention (as indexed by filtering) and WM maintenance share a resource that is not domain general but rather specific to visual stimuli. Removal efficiency has been measured through the speed with which people remove to-be-updated information from WM in an updating paradigm ( Ecker, Lewandowsky, & Oberauer, 2014 ). Whereas this first study showed no correlation of removal efficiency with WM capacity, a subsequent study measuring removal efficiency through a larger set of updating tasks observed a small positive correlation ( Singh, Gignac, Brydges, & Ecker, 2018 ). This result could reflect a shared resource for WM maintenance and attentional control. Alternatively, it could mean that people who efficiently remove no-longer relevant information from WM are better at reducing interference from that information in WM, which improves their ability to retrieve the relevant information ( Oberauer, Lewandowsky, Farrell, Jarrold, & Greaves, 2012 ).

Other research investigated the correlation between WM capacity and measures of attentional control outside the context of WM tasks, for instance the ability to attend to relevant and ignore irrelevant stimuli or features in perceptual decision tasks (e.g., the Stroop, flanker, or Simon task), the ability to suppress a strong action tendency (e.g., moving the eyes away from a suddenly appearing stimulus in the anti-saccade task), or the ability to stop an already prepared action (i.e., the stop-signal paradigm). Numerous studies have found positive correlations between WM capacity and these measures of attention control (e.g., Chuderski, 2014 ; McVay & Kane, 2012 ; Shipstead, Lindsey, Marshall, & Engle, 2014 ; Unsworth, 2015 ; Unsworth, Fukuda, Awh, & Vogel, 2014 ), whereas a few others failed to find such a relationship ( Keye, Wilhelm, Oberauer, & van Ravenzwaaij, 2009 ; Wilhelm, Hildebrandt, & Oberauer, 2013 ). Additional support comes from findings of a positive correlation between WM capacity and people’s self-reported mind wandering in response to thought probes during a cognitive task ( McVay & Kane, 2009 , 2012 ; Randall, Oswald, & Beier, 2014 ).

Taken together, the evidence for a close relation between WM and the control of attention is mixed. The most convincing evidence comes from correlational studies linking WM capacity to indicators of attention control from tasks without a memory demand. There is some evidence that WM capacity is also correlated with the efficiency of controlling the contents of WM through filtering and removal, but it is yet too weak and inconsistent to draw strong conclusions. This correlational evidence, however, can be explained without invoking the notion of a shared resource, as I’ll discuss below (in the section “How is WM related to the control of attention and action?”). The experimental evidence from dual-task costs speaks against competition between WM maintenance and attention control for a shared resource.

I have considered three theoretical options for spelling out the idea of WM as relying on an attentional resource: (1) a shared resource for “storage” and “processing”, (2) a shared resource for perceptual attention and WM, and (3) a shared resource for attention control and WM. Of these three, the first option has received the most convincing empirical support, but it also suffers from empirical challenges, and from the conceptual problem of explaining how the competition for resources between storage and processing can have an impact on memory performance after the competition is over. I do not see these challenges as fatal – it is probably still too early to announce the “demise” ( Klapp et al., 1983 ) of the idea that WM is limited by an attentional resource – but theorists working with this concept should aim to address these challenges. In the remainder of this article I discuss the relation of WM to attention from the perspective that attention is the selection and prioritization of information, which does not entail a commitment to a limited resource.

Attention as Selection

A different perspective on the relation between WM and attention emerges when attention is defined not as a resource but as a mechanism for selecting and prioritizing representations. In this perspective, attention does not explain the capacity limit of WM. Rather, we should consider WM as an instance of attention – specifically, WM is attention to memory representations. Holding a set of representations in WM means selecting them from among all the representations that our mind is capable of, thereby rendering them available as input for cognitive operations. As such, WM meets the definition of attention as a mechanism of selection ( Oberauer, 2009 ). In this perspective, the relationship between the concept of WM and the concept of attention is not an empirical but a conceptual one.

Nevertheless, we can ask several empirical questions about how WM is related to attention as a selection mechanism: (1) How is information selected into WM? (2) How is information selected within WM? (3) What is the relation between attention to memory and attention to perceived stimuli – are they the same, and if not, how do they influence each other? (4) How is WM related to the control of attention and action? I next address these questions in turn.

How is Information Selected into Working Memory?

Information can be selected to be brought into WM from perception or from long-term memory. This selection is to a large extent controlled: People are very good, though not perfect, at letting only relevant information into WM. Moreover, people also have control over which information to keep in WM and which to remove.

Filtering Perceptual Information. With regard to perceived information, perceptual attention arguably plays an important role in selecting which stimuli are encoded into WM. Stimuli that are known to be irrelevant from the start, and are easy to discriminate from relevant stimuli, can be filtered out very effectively ( Baddeley, Papagno, & Andrade, 1993 ), though not always perfectly ( Ueno, Allen, Baddeley, Hitch, & Saito, 2011 ; Vogel et al., 2005 ); children and older adults seem to have more difficulty with filtering irrelevant stimuli at encoding ( Sander, Werkle-Bergner, & Lindenberger, 2011 ). A question discussed in the context of visual WM is whether people can selectively encode relevant features but not irrelevant features of the same visual object. Some experiments show that relevant and irrelevant features of the same object have similar behavioral effects on memory performance ( Marshall & Bays, 2013 ) and attentional capture ( Gao et al., 2016 ; see the section on effects of WM on perceptual attention for an explanation of this effect). However, one fMRI study found that the relevant but not the irrelevant feature of a visual object could be reconstructed from the pattern of BOLD activity during the retention interval ( Yu & Shim, 2017 ). Logie, Brockmole, and Jaswal ( 2011 ) have tested the effects of changes in irrelevant features on change-detection accuracy and found that such changes impair performance for retention intervals up to about 2 s but not thereafter. They propose that irrelevant features are initially encoded and subsequently removed from WM. This could explain why irrelevant features are not detectable in the sluggish BOLD signal that aggregates information over several seconds.

Filtering could be accomplished by perceptual selection – not attending to the irrelevant stimuli – but it could also be a separate selection step, such that a stimulus, even though selected for perceptual attention, is not encoded into WM. The latter possibility would imply that perceptual attention might be necessary, but is not sufficient for encoding them into WM. Evidence for this possibility comes from several sources. A series of experiments by H. Chen and Wyble ( 2015a , 2015b ) used stimuli as attentional cues for a perceptual decision task, and after several trials inserted a surprise memory test for a feature of the cue. Although they have arguably attended to the cue because it was relevant for the decision task, people had poor memory for its features only a few seconds after its disappearance, suggesting that the stimulus, or at least the feature probed in the memory test, was not encoded into WM. When people expected the memory test, their performance was much better. In a related experiment H. Chen, Swan, and Wyble ( 2016 ) had participants visually track several moving target objects among distractors. To avoid confusing the targets with distractors participants had to continuously attend to them while they moved. Yet, in a surprise memory test they had little memory for the target’s colors.

A second source of evidence suggesting that attention is not sufficient to encode stimuli into WM comes from some of my experiments ( Oberauer, 2018 ): Participants saw six words presented one by one in different screen locations; each word was followed by a cue to remember or forget it. The cue appeared only after word offset so that people had to attend to each word in case they would have to remember it. I also varied the time interval between each forget cue and the onset of the next word to manipulate how much time people had to remove a to-be-forgotten word from WM. The to-be-forgotten words had no effect on memory performance regardless of the cue-word interval, implying that they did not contribute at all to the load on WM.

These findings could mean that information, although attended, is not encoded into WM. Alternatively, the visual stimuli of Chen and Wyble, or the to-be-forgotten words in my experiments, could be encoded into WM but then removed very quickly so that their accessibility, and their effect on WM load, was not measurable even a few seconds later (see the section below on Removal). Perhaps neurophysiological markers of WM load with high temporal resolution, such as the CDA, could be leveraged to distinguish between these possibilities.

One limitation for efficient filtering (or removal) arises when people have to process the distracting material. When participants in my experiments ( Oberauer, 2018 ) had to make a judgment on each word while it was on the screen, they could not entirely prevent encoding to-be-forgotten words into WM, though they were still able to diminish their effect on WM load relative to to-be-remembered words. Marshall and Bays ( 2013 ) found that comparing two stimuli during the retention interval of a visual WM task impaired WM performance as much as adding two more stimuli to the memory set, suggesting that encoding of these stimuli into WM could not be prevented at all.

Selective Retrieval from Long-Term Memory. Much of the information we process in WM comes from long-term memory. For the WM system to work effectively, it has to retrieve information from long-term memory selectively, so that only information useful for the current task enters WM ( Oberauer, 2009 ). A demonstration of the effectiveness of this gating mechanism comes from experiments investigating the effect of previously acquired long-term memories on WM performance ( Oberauer, Awh, & Sutterer, 2017 ). We had participants learn 120 associations between everyday objects and randomly selected colors. In a subsequent WM test they had to maintain three object-color conjunctions on each trial, and reproduce each object’s color by selecting it on a color wheel. Some of the objects in the WM test were objects for which they had learned an associated color before. These objects could reoccur in the WM test with their learned color – in which case retrieving the associated color should facilitate WM performance – whereas others reoccurred with a new random color – in which case retrieving the color from long-term memory should interfere with WM performance. We found evidence for proactive facilitation, but against proactive interference, implying that information from long-term memory is used if and only if the information in WM was so poor that drawing on long-term memory could only make things better.

Removal of Information from WM. The selection of which information to hold in WM is also controlled after encoding: Information no longer relevant must be rapidly removed so that it does not clutter WM ( Hasher et al., 1999 ). There is a body of evidence showing that people can selectively remove no-longer relevant information from WM (for a review see Lewis-Peacock, Kessler, & Oberauer, 2018 ).

Removing an entire memory set when replacing it with a new one is a seamless and rapid process, though – as filtering – it is not perfect: Traces of the old memory set remain in WM, creating some mild proactive interference when items in the two sets are similar to each other ( Ralph et al., 2011 ; Tehan & Humphreys, 1998 ), and a congruency benefit when the two sets partially overlap, sharing the same items in the same contexts ( Oberauer, Souza, Druey, & Gade, 2013 ). Removal of a single item from the current memory set has been isolated experimentally as a process involved in WM updating ( Ecker, Oberauer, & Lewandowsky, 2014 ). By contrast, removal is much less efficient when it comes to removing more than one item from a memory set but less than all of them: People find it difficult to remove a random subset of several items from a memory set. For instance, when informed, after encoding a list of six words, that the words in positions 2, 3, and 5 could be forgotten, there was no evidence that they did so – successful removal of a subset of three words was found only when they were already clearly marked as a separate subset at encoding ( Oberauer, 2018 ). In sum, the efficiency of removal is limited by the ability to discriminate between to-be-maintained and to-be-removed contents of WM.

To conclude, the WM system is equipped with very efficient – though not perfect – mechanisms for controlling its contents through filtering perceptual input, selectively retrieving information from LTM, and removing no-longer relevant materials. Through these selection processes the cognitive system manages to usually have only the most relevant information for the current goal in WM.

How is Information selected within WM?

Selecting information to be held in WM is a form of selection, but it not necessarily selection of one piece of information at the exclusion of all others: We often hold multiple separate items in WM simultaneously. Sometimes we have to select a single item from the set currently held in WM as the input for a process, or as the object of mental manipulation. Our ability to select individual items from the set currently held in WM points to a selection mechanism that I refer to as the focus of attention in WM ( Oberauer, 2002 ; Oberauer & Hein, 2012 ). Evidence for the operation of such a narrow selection mechanism within WM comes from three observations: (1) In short-term recognition tests the last-presented item in a list is accessed at a faster rate than preceding items, and this has been interpreted as showing that the last-encoded item remains in the focus of attention (for a review McElree, 2006 ). (2) When an item in WM is needed as input for a cognitive operation (e.g., adding or subtracting a number from a particular digit in WM), or when one item needs to be selected as the object of an updating operation (e.g., replacing an item in WM by a new stimulus), then operating on the same WM item again in the next step takes less time than selecting another item from the memory set for the next operation. This item-switch cost (or item-repetition benefit) has been explained by assuming that the object of a cognitive operation remains in the focus of attention after the operation has been completed, and therefore does not need to be selected again when the same object is required for the next operation ( Garavan, 1998 ; Oberauer, 2003 ). (3) After encoding a set of stimuli into WM, a retro-cue presented one to several seconds into the retention interval can guide attention to one item and thereby improve memory performance when that item is tested – often at the expense of performance when another item is tested ( Griffin & Nobre, 2003 ; Landman, Spekreijse, & Lamme, 2003 ; for a review see Souza & Oberauer, 2016 ).

Whereas most of these empirical demonstrations come from situations in which a single item in WM needs to be selected, it has been argued that the focus of attention can hold more than one item ( Gilchrist & Cowan, 2011 ). From the perspective of attention as selection, this should be feasible to the extent that selecting multiple items simultaneously does not undercut the purpose of selection. For instance, if the task is to update one out of several digits in WM through an arithmetic operation, selecting more than that one digit into the focus of attention would only lead to confusion – but if the task is to add two digits in WM together, selecting both of them into the focus of attention at the same time is arguably useful because then they could be used simultaneously as retrieval cues for the relevant arithmetic fact ( Oberauer, 2013 ). Another situation in which it is functional to select two items into the focus simultaneously is when two tasks must be carried out simultaneously, one on each item, and the two items are sufficiently different to not risk cross-talk between the two tasks ( Göthe, Oberauer, & Kliegl, 2016 ; Oberauer & Bialkova, 2011 ).

Using the retro-cue paradigm, neuroscience research has revealed a distinction between attended and unattended information in WM 4 : Whereas the attended information can be decoded from neural signals such as the pattern of BOLD activity over voxels, or the pattern of EEG activity over electrodes, the unattended information cannot – it remains neurally silent, but can be brought back into a neurally active state later by a retro-cue drawing attention to it ( LaRocque, Lewis-Peacock, Drysdale, Oberauer, & Postle, 2013 ; Lewis-Peacock, Drysdale, Oberauer, & Postle, 2011 ; Sprague, Ester, & Serences, 2016 ) or by an uninformative strong input to the cortex ( Rose et al., 2016 ; Wolff, Jochim, Akyürek, & Stokes, 2017 ). One recent study, however, paints a more differentiated picture: Decoding of orientations maintained in VWM from fMRI signals in visual cortex was again good for attended and absent for unattended items, but decoding from signals in parietal cortex (IPS and frontal eye fields) was equally good for both attended and unattended items – though much weaker than decoding of attended items in visual cortex ( Christophel, Iamshchinina, Yan, Allefeld, & Haynes, 2018 ).

Behavioral evidence shows that retro-cues can be used to select not just individual items but also subsets of several items within WM ( Oberauer, 2001 , 2005 ), and selection of a subset can be followed by selection of an item within that subset ( Oberauer, 2002 ). Therefore, we can distinguish three levels of selection in WM: (1) Selecting information to be in WM, constituting the current memory set, (2) selecting a subset of the memory set, and (3) selecting a single item from that subset. I have referred to these three levels as (1) the activated part of long-term memory, (2) the region of direct access, and (3) the focus of attention, respectively (see Oberauer, 2009 , for a detailed discussion of the 3-level framework and evidence supporting it; and Oberauer et al., 2013 , for a computational implementation). It is currently not clear whether more than one WM representation is neurally active (i.e., decodable from neural activity during the retention interval) at the same time, so we do not know whether the state of being neurally active characterizes the second or the third level of selection. One possibility is that during WM maintenance multiple representations – those in the direct-access region – are active at the same time, such that their pattern of neural activity is superimposed. Another possibility is that only one item – the one in the focus of attention – is neurally active at any time. If the focus of attention circulates among the items in WM, it would still be possible to decode several items from neural activation patterns ( Emrich, Rigall, LaRocque, & Postle, 2013 ) because the temporal resolution of decoding from BOLD signals is lower than the speed at which the focus of attention shifts from one item to another (i.e., about 300 ms; Oberauer, 2003 ).

Univariate neural correlates of WM load, most notably the amplitude of the CDA ( Vogel & Machizawa, 2004 ) and the BOLD activation in the inter-parietal sulcus (IPS) ( Todd & Marois, 2004 , 2005 ; Xu & Chun, 2006 ), imply that at least some form of persistent neural activity increases with the number of items maintained in WM. These neural measures, however, do not carry information about the content of WM, and therefore we do not know whether they reflect neurally active representations or some neural activity reflecting control processes that are involved in maintaining items selected. Another open question is whether these univariate measures of WM load reflect the first or the second level of selection – to find out we need studies that track these neural indicators of WM load while a retro-cue asks participants to select a subset of the current memory set: Does the neural marker track the set size of the subset or of the entire memory set? One study asking this question found that BOLD activation in IPS reflects the size of the entire memory set before the retro-cue but the size of the cued subset afterwards ( Lepsien, Thornton, & Nobre, 2011 ), suggesting that IPS activation reflects the second level of selection, the direct-access region. In that study, however, participants were not asked to still maintain the not-cued subset in memory, so we don’t know whether they maintained it (at the third selection level, the activated part of LTM) or just removed it from WM.

A somewhat speculative hypothesis on how to reconcile all these findings is that univariate markers of WM load track the amount of information selected at the second level (i.e., the direct-access region). This information is maintained in WM through temporary bindings between contents and contexts through which they are accessible, probably in parietal cortex. These bindings are neurally silent – either because they are implemented through rapid synaptic plasticity ( Mongillo, Barak, & Tsodyks, 2008 ) or because they are implemented in a pattern of neural activity that bears no similarity to the bound contents, such as a circular convolution of each content with its context ( Eliasmith, 2013 ; Plate, 2003 ), so that they cannot be identified through decoding of the WM contents. However, neural activity patterns corresponding to the contents of the direct-access region could be re-activated during the retention interval by feeding non-specific activation into the contexts that act as retrieval cues for these contents, so that they could (faintly) be decoded from parietal cortical areas ( Bettencourt & Xu, 2016 ; Christophel et al., 2018 ). This non-specific activation could be spontaneous noise in the neural network ( Oberauer & Lin, 2017 ), or an attentional mechanism that selectively activates all contexts to which the contents of the direct-access region are bound. The content (or contents) selected for the third level of selection, the focus of attention, is represented in a neurally active fashion, probably in the prefrontal cortex ( Bichot, Heard, DeGennaro, & Desimone, 2015 ; Mendoza-Halliday & Martinez-Trujillo, 2017 ), and this representation re-activates the corresponding sensory representation in those sensory cortical areas involved in its initial processing, so that the information in the focus of attention can be decoded from neural activity in those areas.

A prediction from this hypothesis is that when two to-be-remembered stimuli are presented sequentially, univariate markers such as the CDA should add up to reflect the combined load of both stimuli, whereas the decodability of the first stimulus should be substantially impaired by the encoding of the second, because the focus of attention abandons the first to encode the second stimulus. Evidence for the first assumption comes from studies showing that the CDA reflects the combined load of two successively presented parts of a memory set ( Feldmann-Wüstefeld, Vogel, & Awh, 2018 ; Ikkai, McCollough, & Vogel, 2010 ); the second prediction remains to be tested.

What is the Relation between WM and Perceptual Attention?

An extreme position would be that WM and perceptual attention are the same: By virtue of attending to a perceived stimulus, it is selected into WM. Maintaining stimuli in WM that are no longer present in the environment differs from perceptual attention only in the absence of the physical stimulus. The cognitive state is still the same, with the only difference that the representation in WM is arguably weaker and less precise due to the lack of informative sensory input. This extreme position is attractive due to its parsimony, but it is almost certainly wrong. We have already seen that perceptual attention to stimuli during the retention interval of a visual WM task leads to less interference than adding the same stimuli to WM ( Fougnie & Marois, 2006 ). I have also discussed instances where stimuli were attended to and yet they leave hardly any trace in WM (H. Chen et al., 2016 ; H. Chen & Wyble, 2015a , 2015b ; Oberauer, 2018 ). Moreover, single-cell recordings from monkey LPFC neurons showed partial but not complete overlap between the neurons responding selectively to a feature while it is perceptually attended and those doing so while the feature is being held in WM ( Mendoza-Halliday & Martinez-Trujillo, 2017 ). If we accept that perceptual attention and WM are different entities, we can meaningfully ask how they causally affect each other.

How does perceptual attention affect WM? Some authors have argued that perceptual attention can be used to rehearse visual or spatial WM contents. The evidence for this idea is mixed. Some studies found a correlation between spontaneous eye movements during the retention interval – which presumably track visual attention – and recall success for sequences of spatial locations ( Tremblay, Saint-Aubin, & Jalberg, 2006 ), but no such correlation was found for change detection in visual arrays ( Williams, Pouget, Boucher, & Woodman, 2013 ). Directing people to attend to individual items in a visual array improves memory for those items relative to not-attended items in the array ( Souza, Rerko, & Oberauer, 2015 ; Souza, Vergauwe, & Oberauer, 2018 ). However, it is not clear whether this effect relies on perceptual attention. Engaging perceptual attention by a secondary task during the retention interval (i.e., detection of a slight brightness change in the fixation cross) impaired performance in a visual change-detection task ( Williams et al., 2013 ), but had at best a negligible effect on errors in a visual continuous-reproduction task, whereas engaging central attention impaired continuous reproduction more severely ( Souza & Oberauer, 2017 ).

As discussed above in the section on Filtering, perceptual attention is probably necessary but not sufficient for encoding of stimuli into WM. Yet, filtering is not perfect, so that attended information is sometimes encoded into WM to some extent even when this is not desired. To the extent that this happens, we can expect that distractors presented during the retention interval of a WM task interfere with the to-be-remembered information, thereby impairing memory performance.

Evidence for such interference comes from studies of spatial WM. Van der Stigchel, Merten, Meeter, and Theeuwes ( 2007 ) found that recall of locations is biased towards the location of a suddenly appearing irrelevant stimulus on the screen, suggesting that this stimulus was inadvertently encoded into WM. Lawrence, Myerson, and Abrams ( 2004 ) had participants identify and compare two symbols during the retention interval of a WM task, which either appeared at fixation or in the periphery (left or right of fixation). When the symbols appeared in the periphery, spatial (but not verbal) WM performance was impaired more than for centrally displayed symbols. This suggests that attending to additional locations entails encoding these locations into WM to some degree, thereby interfering with memory for other locations. The interfering effect was stronger when participants were instructed to move their eyes to the peripheral symbols than when they were instructed to maintain fixation, in line with other findings showing that processing distractors enforces stronger encoding into WM than merely attending to them ( Oberauer, 2018 ). Both studies unfortunately lack a control condition in which irrelevant stimuli are presented but not attended, so it is not clear how much perceptual attention contributes to their encoding into WM.

Does attending to a stimulus in the environment distract the focus of attention from information in WM? Two observations indicate that it might not: The beneficial effect of a retro-cue directing the focus of attention to one item in WM is not diminished by a subsequent task engaging perceptual attention ( Hollingworth & Maxcey-Richard, 2013 ; Rerko, Souza, & Oberauer, 2014 ). Likewise, the object-repetition benefit in a spatial WM updating task was not diminished by requiring people to focus visual attention on a stimulus in the periphery in between updating steps ( Hedge, Oberauer, & Leonards, 2015 ). However, the retro-cue effect probably arises in part from strengthening of the cued item’s binding to its context, and this effect lasts after the focus of attention has moved away from the cued item ( Rerko et al., 2014 ; Souza et al., 2015 ). The same could be true for the object-repetition benefit: The item to be updated is selected into the focus of attention, and this strengthens the item’s binding to its context as a side effect, leaving that item temporarily more accessible than other items even if the focus of attention moves away from it. Evidence suggesting that attending to perceptual stimuli does distract the focus of attention comes from studies using multivariate neural signals to read out the information in the pattern of neural activity. The decodability of a single item in WM is drastically diminished – at least temporarily – by the onset of an irrelevant stimulus, or just by the person attending to a location in anticipation of a stimulus, during the retention interval ( Bettencourt & Xu, 2016 ; van Moorselaar et al., 2017 ). However, in these studies the irrelevant stimulus hardly affected memory performance. Therefore, an alternative possibility is that the content of the focus of attention is represented in pre-frontal cortex ( Bichot et al., 2015 ), and the corresponding sensory representations are merely epiphenomenal, so that the elimination of the latter does not imply a distraction of the focus of attention in WM.

To conclude, surprisingly little can be said with confidence: Perceptual attention to stimuli often – but not always – leads to them being encoded into WM to some extent, so that they interfere with similar information. The use of perceptual attention for rehearsal has not been demonstrated convincingly. Whether the focus of attention can stay on an item in WM while perceptual attention engages with a different stimulus in the environment is still unclear.

How does information in WM affect perceptual attention? It appears plausible that holding some information in WM tends to draw perceptual attention to similar information in the environment, thereby facilitating its processing. Initial evidence for that assumption comes from experiments by Awh et al. ( 1998 ): Holding the spatial location of an object in WM facilitates processing of other stimuli appearing in the same location during the retention interval. A subsequent similar study taking additional measures to discourage eye movements, however, failed to replicate this finding ( Belopolsky & Theeuwes, 2009 ).

A more specific version of the same idea is the assumption that the item held in the focus of attention in WM – usually a single item – functions as a “search template”, guiding perceptual attention to matching stimuli ( Olivers, Peters, Houtkamp, & Roelfsema, 2011 ). This idea has received considerable empirical support from studies of the “attentional capture” effect in visual search: When people are asked to hold an item in WM – for instance a color, or just a color word – and carry out a visual search task during the retention interval, attention is drawn to stimuli in the search display matching the item in WM ( Soto, Hodsoll, Rotshtein, & Humphreys, 2008 ). When more than one item is held in WM and one of them is retro-cued, then only the retro-cued item causes attentional capture ( Mallett & Lewis-Peacock, 2018 ; van Moorselaar, Battistoni, Theeuwes, & Olivers, 2014 ; van Moorselaar, Theeuwes, & Olivers, 2014 ). This finding provides further evidence for the special functional status of representations in the focus of attention (i.e., the third level of selection).

How is WM related to the control of attention and action?

Some theorists argue for a close relation of WM specifically to controlled attention ( Kane et al., 2001 ; McVay & Kane, 2009 ; Unsworth et al., 2014 ). The evidence for this link comes primarily from correlations between measures of WM capacity and controlled attention (reviewed above in the section on resources for attention control). There are at least two interpretations of this correlation. One is that people with high ability to control their attention are good at keeping irrelevant contents out of WM ( Hasher & Zacks, 1988 ), either by filtering them out at encoding ( Vogel et al., 2005 ) or by removing them once they are no longer relevant ( Oberauer et al., 2012 ), and therefore they make better use of their WM capacity. This account has difficulties explaining why measures of controlled attention were found to correlate substantially also with measures of (visual) WM in which no irrelevant stimuli were presented, and no contents need to be removed from WM ( Unsworth et al., 2014 ).

A second explanation, which I believe to be more promising, implies the reverse direction of causality. It starts from the assumption that the main function of WM is to hold representations that control what we think and do, including what we direct our attention to ( Oberauer, 2009 ). For instance, in visual search perceptual attention can be controlled by holding a template of the search target in the focus of attention in WM ( Olivers et al., 2011 ). Selection of responses to stimuli in accordance with the currently relevant task goal is accomplished by holding a task set – a representation of the relevant stimulus categories, the response options, and the mapping between them – in WM ( Monsell, 2003 ; Oberauer et al., 2013 ). In both cases, control could also rely on representations in long-term memory. For the case of visual search, Woodman, Carlisle, and Reinhart ( 2013 ) present strong evidence that search targets that repeat across successive trials are held in WM only for the first few trials, after which search is controlled by target representations in long-term memory. The finding that search becomes more efficient with practice when the same set of stimuli is consistently used as targets or distractors further underscores the role of long-term memory in controlling perceptual attention in search tasks ( Shiffrin & Schneider, 1977 ). For the case of response selection, practicing a task with consistent stimulus-response mappings leads to long-term learning of these mappings, greatly improving task performance. Representations in WM are necessary for control when we want to do something new – searching for a new target, or carrying out a new task that we just learned from instruction. WM representations are particularly important when the new action is inconsistent with one that we have learned – for instance, searching for a target that used to consistently figure as distractor, or switching from one task to another that maps the same stimuli to new responses. In these cases, WM provides a medium for building and maintaining new representations that control our cognitive processes and actions, if necessary countermanding our long-term knowledge. On these assumptions, the correlation between WM capacity and performance in controlled-attention tasks arises because people with better WM capacity have better (i.e., more robust, more precise) representations in WM of the (cognitive or overt) action they intend to carry out, such as search templates and task sets.

To conclude, I argue that WM plays a crucial role in controlling attention and action by holding the representations that guide attention and action. The control process consists of selecting these representations into WM – once they are established in WM, they have their influence on attention and action automatically: Perceptual attention is “captured” by stimuli matching the content of the focus of attention even when this is only detrimental to performance in the current task ( Foerster & Schneider, 2018 ; Gao et al., 2016 ); newly instructed tasks, once implemented as task sets in WM, function like a “prepared reflex”, influencing response selection even when they are currently not relevant ( Meiran, Liefooghe, & De Houwer, 2017 ).

Conclusions

Attention is closely related to WM. Unpacking this relationship reveals many different ways in which the WM-attention link can be spelled out. A first divide is between theoretical ideas about attention as a resource on the one hand, and about attention as a mechanism for selecting and prioritizing information on the other. The first approach entails the theoretical commitment that a limited attentional resource is at least in part responsible for the capacity limit of WM. This assumption has considerable empirical support but also significant weaknesses (for a review see Oberauer et al., 2016 ), so that researchers should not endorse it as a default. The second approach does not imply a commitment to any assumptions about WM or attention, and therefore offers a more neutral starting point for asking how the two are related. From the theoretical considerations and the evidence reviewed here I conclude that the following assertions about specific relations between attention and WM are justified:

• By virtue of holding a selected subset of all available representations in memory, WM is by definition a form of attention.
• The selection of information to be held in WM is a form of controlled attention: The selection of stimuli to be encoded into WM is controlled by a filtering mechanism set according to our intentions; the retrieval of long-term memory information into WM is gated to admit only information relevant for our current goals, and information no longer relevant for our current goal is removed from WM.
• Attending to a perceived stimulus probably facilitates encoding of that stimulus into WM, but does not mandate it. Even attended information can be, to a large extent, filtered out.
• Within the contents of WM the focus of attention can be directed to individual items, or subsets of items, selected for manipulating them, or as input for processes (e.g., mental arithmetic, visual search).
• Control of attention and action relies on representations in WM that guide attention and action, such as search templates and task sets, especially when these are new and in conflict with knowledge in long-term memory. Once established in WM, these representations control attention and action independently of our intentions.

Unsurprisingly, there are also many things we don’t know. Table 2 presents a non-exhaustive list of open questions that I believe future research should address with high priority. I hope that this effort will lead to an increasingly more precise and nuanced picture of how WM is related to attention.

Open Questions.

I will use the term object (of attention) in a broad sense, referring to every entity that we can pay attention to (e.g., physical objects, events, people, concepts and ideas, goals and actions, …).  

Chun et al. ( 2011 ) refer to this distinction as “internal” vs. “external” attention. I find this terminology misleading: The memory of a tree is not more internal than the perception of a tree: Both are internal representations of external objects.  

Another paradoxical implication of the fusion account is that, once the resource is completely absorbed for storage purposes, there is no resource left for control processes clearing irrelevant material from WM, and once an ongoing process monopolizes the entire attentional resource, there is no way of stopping it. A meta-control process is necessary to ensure that there is always enough resource left for control processes. If the meta-control process needs a share of the resource for itself, we are on the way to an infinite regress.  

The term “unattended” is to be understood relative to the “attended” content of WM. At the same time, all contents of WM are prioritized over all other memory representations, and as such are attended, though on a broader level of selection.  

Ethics and Consent

This article reports no original research, so no ethics approval is required.

Funding Information

The work on this article was supported by a grant from the Swiss National Science Foundation (SNSF, grant number 100014_135002). Thanks to Peter Shepherdson and Claudia von Bastian for their comments on a previous version of this manuscript.

Competing Interests

The author has no competing interests to declare.

Allen, R. J., Baddeley, A. D., & Hitch, G. J. (2006). Is the binding of visual features in working memory resource-demanding? Journal of Experimental Psychology: General , 135, 298–313. DOI: https://doi.org/10.1037/0096-3445.135.2.298  

Anderson, J. R., Reder, L. M., & Lebiere, C. (1996). Working memory: Activation limits on retrieval. Cognitive Psychology , 30, 221–256. DOI: https://doi.org/10.1006/cogp.1996.0007  

Awh, E., Belopolsky, A. V., & Theeuwes, J. (2012). Top-down versus bottom-up attentional control: a failed theoretical dichotomy. Trends in Cognitive Sciences , 16, 437–443. DOI: https://doi.org/10.1016/j.tics.2012.06.010  

Awh, E., Jonides, J., & Reuter-Lorenz, P. A. (1998). Rehearsal in spatial working memory. Journal of Experimental Psychology: Human Perception and Performance , 24, 780–790. DOI: https://doi.org/10.1037/0096-1523.24.3.780  

Baddeley, A. D. (1986). Working memory . Oxford: Clarendon Press.  

Baddeley, A. D. (1993). Working memory or working attention? In: A. Baddeley, & L. Weiskrantz (Eds.), Attention: Selection, awareness, and control , (pp. 152–170). Oxford: Clarendon.  

Baddeley, A. D. (1996). Exploring the central executive. Quarterly Journal of Experimental Psychology , 49A, 5–28. DOI: https://doi.org/10.1080/713755608  

Baddeley, A. D., Papagno, C., & Andrade, J. (1993). The sandwich effect: The role of attentional factors in serial recall. Journal of Experimental Psychology: Learning, Memory and Cognition , 19, 862–870. DOI: https://doi.org/10.1037/0278-7393.19.4.862  

Barrouillet, P., Bernardin, S., & Camos, V. (2004). Time constraints and resource sharing in adults’ working memory spans. Journal of Experimental Psychology: General , 133, 83–100. DOI: https://doi.org/10.1037/0096-3445.133.1.83  

Barrouillet, P., Bernardin, S., Portrat, S., Vergauwe, E., & Camos, V. (2007). Time and cognitive load in working memory. Journal of Experimental Psychology: Learning, Memory & Cognition , 33, 570–585. DOI: https://doi.org/10.1037/0278-7393.33.3.570  

Barrouillet, P., Portrat, S., & Camos, V. (2011). On the law relating processing to storage in working memory. Psychological Review , 118, 175–192. DOI: https://doi.org/10.1037/a0022324  

Belopolsky, A. V., & Theeuwes, J. (2009). No functional role of attention-based rehearsal in maintenance of spatial working memory representations. Acta Psychologica , 132, 124–135. DOI: https://doi.org/10.1016/j.actpsy.2009.01.002  

Bettencourt, K. C., & Xu, Y. (2016). Decoding the content of visual short-term memory under distraction in occipital and parietal areas. Nature Neuroscience , 19, 150–157. DOI: https://doi.org/10.1038/nn.4174  

Bichot, N. P., Heard, M. T., DeGennaro, E. M., & Desimone, R. (2015). A Source for Feature-Based Attention in the Prefrontal Cortex. Neuron , 88(4), 832–844. DOI: https://doi.org/10.1016/j.neuron.2015.10.001  

Bunting, M. F., Cowan, N., & Colflesh, G. J. H. (2008). The deployment of attention in short-term memory tasks: Trade-offs between immediate and delayed deployment. Memory & Cognition , 36, 799–812. DOI: https://doi.org/10.3758/MC.36.4.799  

Camos, V., Lagner, P., & Barrouillet, P. (2009). Two maintenance mechanisms of verbal information in working memory. Journal of Memory and Language , 61, 457–469. DOI: https://doi.org/10.1016/j.jml.2009.06.002  

Case, R. (1972). Validation of a neo-Piagetian mental capacity construct. Journal of Experimental Child Psychology , 14, 287–302. DOI: https://doi.org/10.1016/0022-0965(72)90051-3  

Case, R., Kurland, M., & Goldberg, J. (1982). Operational efficiency and the growth of short-term memory span. Journal of Experimental Child Psychology , 33, 386–404. DOI: https://doi.org/10.1016/0022-0965(82)90054-6  

Chein, J. M., Moore, A. B., & Conway, A. R. A. (2011). Domain-general mechanisms of complex working memory span. NeuroImage , 54, 550–559. DOI: https://doi.org/10.1016/j.neuroimage.2010.07.067  

Chen, H., Swan, G., & Wyble, B. (2016). Prolonged focal attention without binding: Trackng a ball for half a minute without remembering its color. Cognition , 147, 144–148. DOI: https://doi.org/10.1016/j.cognition.2015.11.014  

Chen, H., & Wyble, B. (2015a). Amnesia for object attributes: Failure to report attended information that had just reached conscious awareness. Psychological Science , 26, 203–210. DOI: https://doi.org/10.1177/0956797614560648  

Chen, H., & Wyble, B. (2015b). The location but not the attributes of visual cues are automatically encoded into working memory. Vision Research , 107, 76–85. DOI: https://doi.org/10.1016/j.visres.2014.11.010  

Chen, Z., & Cowan, N. (2009). How verbal memory loads consume attention. Memory & Cognition , 37, 829–836. DOI: https://doi.org/10.3758/MC.37.6.829  

Christophel, T. B., Iamshchinina, P., Yan, C., Allefeld, C., & Haynes, J.-D. (2018). Cortical specialization for attended versus unattended working memory. Nature Neuroscience , 21, 494–496. DOI: https://doi.org/10.1038/s41593-018-0094-4  

Chuderski, A. (2014). The relational integration task explains fluid reasoning above and beyond other working memory tasks. Memory & Cognition , 42, 448–463. DOI: https://doi.org/10.3758/s13421-013-0366-x  

Chun, M. M. (2011). Visual working memory as visual attention sustained internally over time. Neuropsychologia , 49(6), 1407–1409. DOI: https://doi.org/10.1016/j.neuropsychologia.2011.01.029  

Chun, M. M., Golomb, J. D., & Turk-Browne, N. B. (2011). A taxonomy of external and internal attention. Annual Review of Psychology , 62, 73–101. DOI: https://doi.org/10.1146/annurev.psych.093008.100427  

Cowan, N. (1995). Attention and memory: An integrated framework . New York: Oxford University Press.  

Cowan, N. (2001). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral and Brain Sciences , 24, 87–185. DOI: https://doi.org/10.1017/S0140525X01003922  

Cowan, N. (2005). Working memory capacity . New York: Psychology Press.  

Cowan, N. (2017). The many faces of working memory and short-term storage. Psychonomic Bulletin & Review , 24, 1158–1170. DOI: https://doi.org/10.3758/s13423-016-1191-6  

Cowan, N., Elliott, E. M., Saults, J. S., Morey, C. C., Mattox, S., Hismjatullina, A., & Conway, A. R. A. (2005). On the capacity of attention: its estimation and its role in working memory and cognitive aptitudes. Cognitive Psychology , 51, 42–100. DOI: https://doi.org/10.1016/j.cogpsych.2004.12.001  

Cowan, N., Fristoe, N., Elliott, E. M., Brunner, R. P., & Saults, J. S. (2006). Scope of attention, control of attention, and intelligence in children and adults. Memory & Cognition , 34, 1754–1768. DOI: https://doi.org/10.3758/BF03195936  

Daneman, M., & Carpenter, P. A. (1980). Individual differences in working memory and reading. Journal of Verbal Learning and Verbal Behavior , 19, 450–466. DOI: https://doi.org/10.1016/S0022-5371(80)90312-6  

Desimone, R., & Duncan, J. (1995). Neural mechanisms of selective visual attention. Annual Review of Neuroscience , 18, 193–222. DOI: https://doi.org/10.1146/annurev.ne.18.030195.001205  

Ecker, U. K. H., Lewandowsky, S., & Oberauer, K. (2014). Removal of information from working memory: A specific updating process. Journal of Memory and Language , 74, 77–90. DOI: https://doi.org/10.1016/j.jml.2013.09.003  

Ecker, U. K. H., Oberauer, K., & Lewandowsky, S. (2014). Working memory updating involves item-specific removal. Journal of Memory & Language , 74, 1–15. DOI: https://doi.org/10.1016/j.jml.2014.03.006  

Eliasmith, C. (2013). How to build a brain: A neural architecture for biological cognition . New York, NY: Oxford University Press. DOI: https://doi.org/10.1093/acprof:oso/9780199794546.001.0001  

Emrich, S. M., Rigall, A. C., LaRocque, J. J., & Postle, B. R. (2013). Distributed patterns of activity in sensory cortex reflect the precision of multiple items maintained in visual short-term memory. Journal of Neuroscience , 33, 6516–6523. DOI: https://doi.org/10.1523/JNEUROSCI.5732-12.2013  

Ester, E. F., Fukuda, K., May, L. M., Vogel, E. K., & Awh, E. (2014). Evidence for a fixed capacity limit in attending multiple locations. Cognitive, Affective, & Behavioral Neuroscience , 14, 62–77. DOI: https://doi.org/10.3758/s13415-013-0222-2  

Feldmann-Wüstefeld, T., Vogel, E. K., & Awh, E. (2018). Contralateral delay activity indexes working memory storage, not the current focus of spatial attention. Journal of Cognitive Neuroscience , 30(8), 1185–1196. DOI: https://doi.org/10.1162/jocn_a_01271  

Foerster, R. M., & Schneider, W. X. (2018). Involuntary top-down control by search-irrelevant features: Visual working memory biases attention in an object-based manner. Cognition , 172, 37–45. DOI: https://doi.org/10.1016/j.cognition.2017.12.002  

Fougnie, D., & Marois, R. (2006). Distinct capacity limits for attention and working memory. Psychological Science , 17, 526–534. DOI: https://doi.org/10.1111/j.1467-9280.2006.01739.x  

Gao, Z., Yu, S., Zhu, C., Shui, R., Weng, X., Li, P., & Shen, M. (2016). Object-based encoding in visual working memory: Evidence from memory-driven attentional capture. Scientific Reports , 6. DOI: https://doi.org/10.1038/srep22822  

Garavan, H. (1998). Serial attention within working memory. Memory & Cognition , 26, 263–276. DOI: https://doi.org/10.3758/BF03201138  

Gazzaley, A., & Nobre, A. C. (2012). Top-down modulation: bridging selective attention and working memory. Trends in Cognitive Sciences , 16, 129–135. DOI: https://doi.org/10.1016/j.tics.2011.11.014  

Gilchrist, A. L., & Cowan, N. (2011). Can the focus of attention accommodate multiple, separate items? Journal of Experimental Psychology: Learning, Memory, and Cognition , 37, 1484–1502. DOI: https://doi.org/10.1037/a0024352  

Göthe, K., Oberauer, K., & Kliegl, R. (2016). Eliminating dual-task costs by minimizing crosstalk between tasks: The role of modality and feature pairings. Cognition , 150, 92–108. DOI: https://doi.org/10.1016/j.cognition.2016.02.003  

Griffin, I. C., & Nobre, A. C. (2003). Orienting attention to locations in internal representations. Journal of Cognitive Neuroscience , 15, 1176–1194. DOI: https://doi.org/10.1162/089892903322598139  

Hasher, L., & Zacks, R. T. (1988). Working memory, comprehension, and aging: A review and a new view. In: G. H. Bower (Ed.), The Psychology of Learning and Motivation , 22, (pp. 193–225). New York: Academic Press. DOI: https://doi.org/10.1016/S0079-7421(08)60041-9  

Hasher, L., Zacks, R. T., & May, C. P. (1999). Inhibitory control, circadian arousal, and age. In: D. Gopher, & A. Koriat (Eds.), Attention and Performance , (pp. 653–675). Cambridge, MA: MIT Press.  

Hazeltine, E., & Witfall, T. (2011). Searching working memory for the source of dual-task costs. Psychological Research , 75, 466–475. DOI: https://doi.org/10.1007/s00426-011-0343-6  

Hedge, C., Oberauer, K., & Leonards, U. (2015). Selection in spatial working memory is independent of perceptual selective attention, but they interact in a shared spatial priority map. Attention, Perception & Psychophysics , 77, 26653–22668. DOI: https://doi.org/10.3758/s13414-015-0976-4  

Hollingworth, A., & Beck, V. M. (2016). Memory-based attention capture when multiple items are maintained in visual working memory. Journal of Experimental Psychology: Human Perception and Performance , 42, 911–917. DOI: https://doi.org/10.1037/xhp0000230  

Hollingworth, A., & Maxcey-Richard, A. M. (2013). Selective maintenance in visual working memory does not require sustained visual attention. Journal of Experimental Psychology: Human Perception and Performance , 39, 1047–1058. DOI: https://doi.org/10.1037/a0030238  

Ikkai, A., McCollough, A. W., & Vogel, E. K. (2010). Contralateral delay activity provides a neural measure of the number of representations in visual working memory. Journal of Neurophysiology , 103, 1963–1968. DOI: https://doi.org/10.1152/jn.00978.2009  

Jolicoeur, P., & Dell’Acqua, R. (1998). The demonstration of short-term consolidation. Cognitive Psychology , 36, 138–202. DOI: https://doi.org/10.1006/cogp.1998.0684  

Jurado, M. B., & Rosselli, M. (2007). The elusive nature of executive functions: A review of our current understanding. Neuropsychology Review , 17, 213–233. DOI: https://doi.org/10.1007/s11065-007-9040-z  

Just, M. A., & Carpenter, P. A. (1980). A theory of reading: From eye fixations to comprehension. Psychological Review , 87, 329–354. DOI: https://doi.org/10.1037/0033-295X.87.4.329  

Just, M. A., & Carpenter, P. A. (1992). A capacity theory of comprehension: Individual differences in working memory. Psychological Review , 99, 122–149. DOI: https://doi.org/10.1037/0033-295X.99.1.122  

Kane, M. J., Bleckley, M. K., Conway, A. R. A., & Engle, R. W. (2001). A controlled-attention view of working-memory capacity. Journal of Experimental Psychology: General , 130, 169–183. DOI: https://doi.org/10.1037/0096-3445.130.2.169  

Kane, M. J., & Engle, R. W. (2003). Working-memory capacity and the control of attention: The contributions of goal neglect, response competition, and task set to Stroop interference. Journal of Experimental Psychology: General , 132(47–70). DOI: https://doi.org/10.1037/0096-3445.132.1.47  

Kelley, T. A., & Lavie, N. (2011). Working Memory Load Modulates Distractor Competition in Primary Visual Cortex. Cerebral Cortex , 21(3), 659–665. DOI: https://doi.org/10.1093/cercor/bhq139  

Keye, D., Wilhelm, O., Oberauer, K., & van Ravenzwaaij, D. (2009). Individual differences in conflict-monitoring: Testing means and covariance hypothesis about the Simon and the Eriksen Flanker task. Psychological Research-Psychologische Forschung , 73(6), 762–776. DOI: https://doi.org/10.1007/s00426-008-0188-9  

Kim, S.-Y., Kim, M.-S., & Chun, M. M. (2005). Concurrent working memory load can reduce distraction. Proceedings of the National Academy of Sciences , 102, 16524–16529. DOI: https://doi.org/10.1073/pnas.0505454102  

Kiyonaga, A., & Egner, T. (2014). Working memory as internal attention: Toward an integrative account of internal and external selection processes. Psychonomic Bulletin & Review . DOI: https://doi.org/10.3758/s13423-012-0359-y  

Klapp, S. T., Marshburn, E. A., & Lester, P. T. (1983). Short-term memory does not involve the “working memory” of information processing: The demise of a common assumption. Journal of Experimental Psychology: General , 112, 240–264. DOI: https://doi.org/10.1037/0096-3445.112.2.240  

Konstantinou, N., Beal, E., King, J.-R., & Lavie, N. (2014). Working memory load and distraction: Dissociable effects of visual maintenance and cognitive control. Attention, Perception & Psychophysics , 76, 1985–1997. DOI: https://doi.org/10.3758/s13414-014-0742-z  

Konstantinou, N., & Lavie, N. (2013). Dissociable roles of different types of working memory load in visual detection. Journal of Experimental Psychology: Human Perception and Performance , 39, 919–924. DOI: https://doi.org/10.1037/a0033037  

Landman, R., Spekreijse, H., & Lamme, V. A. F. (2003). Large capacity storage of integrated objects before change blindness. Vision Research , 43(149–164). DOI: https://doi.org/10.1016/S0042-6989(02)00402-9  

LaRocque, J. J., Lewis-Peacock, J. A., Drysdale, A. T., Oberauer, K., & Postle, B. R. (2013). Decoding attended information in short-term memory: An EEG study. Journal of Cognitive Neuroscience , 25(1), 127–142. DOI: https://doi.org/10.1162/jocn_a_00305  

Lavie, N. (2005). Distracted and confused?: Selective attention under load. Trends in Cognitive Sciences , 9, 75–82. DOI: https://doi.org/10.1016/j.tics.2004.12.004  

Lavie, N., Hirst, A., de Fockert, J. W., & Viding, E. (2004). Load theory of selective attention and cognitive control. Journal of Experimental Psychology: General , 133, 339–354. DOI: https://doi.org/10.1037/0096-3445.133.3.339  

Lawrence, B. M., Myerson, J., & Abrams, R. A. (2004). Interference with spatial working memory: An eye movement is more than a shift of attention. Psychonomic Bulletin & Review , 11, 488–494. DOI: https://doi.org/10.3758/BF03196600  

Lawrence, B. M., Myerson, J., Oonk, H. M., & Abrams, R. A. (2001). The effects of eye and limb movements on working memory. Memory , 9, 433–444. DOI: https://doi.org/10.1080/09658210143000047  

Lepsien, J., Thornton, I., & Nobre, A. C. (2011). Modulation of working-memory maintenance by directed attention. Neuropsychologia , 49, 1569–1577. DOI: https://doi.org/10.1016/j.neuropsychologia.2011.03.011  

Lewis-Peacock, J. A., Drysdale, A. T., Oberauer, K., & Postle, B. R. (2011). Neural evidence for a distinction between short-term memory and the focus of attention. Journal of Cognitive Neuroscience , 24, 61–79. DOI: https://doi.org/10.1162/jocn_a_00140  

Lewis-Peacock, J. A., Kessler, Y., & Oberauer, K. (2018). The removal of information from working memory. Annals of the New York Academy of Science , 1424, 33–44. DOI: https://doi.org/10.1111/nyas.13714  

Liefooghe, B., Barrouillet, P., Vandierendonck, A., & Camos, V. (2008). Working memory costs of task switching. Journal of Experimental Psychology: Learning, Memory, and Cognition , 34, 478–494. DOI: https://doi.org/10.1037/0278-7393.34.3.478  

Logie, R. H., Brockmole, J. B., & Jaswal, S. (2011). Feature binding in visual short-term memory is unaffected by task-irrelevant changes of location, shape, and color. Memory & Cognition , 39, 24–36. DOI: https://doi.org/10.3758/s13421-010-0001-z  

Luria, R., Balaban, H., Awh, E., & Vogel, E. K. (2016). The contralateral delay activity as a neural measure of visual working memory. Neuroscience and Biobehavioral Reviews , 62, 100–108. DOI: https://doi.org/10.1016/j.neubiorev.2016.01.003  

Ma, W. J., Husain, M., & Bays, P. M. (2014). Changing concepts of working memory. Nature Neuroscience Reviews , 17, 347–356. DOI: https://doi.org/10.1038/nn.3655  

Mall, J. T., Morey, C. C., Wolff, M. J., & Lehnert, F. (2014). Visual selective attention is equally functional for individuals with low and high working memory capacity: Evidence from accuracy and eye movements. Attention, Perception & Psychophysics . DOI: https://doi.org/10.3758/s13414-013-0610-2  

Mallett, R., & Lewis-Peacock, J. A. (2018). Behavioral decoding of working memory items inside and outside the focus of attention. Annals of the New York Academy of Sciences , 1424(1), 256–267. DOI: https://doi.org/10.1111/nyas.13647  

Marshall, L., & Bays, P. M. (2013). Obligatory encoding of task-irrelevant features depletes working memory resources. Journal of Vision , 13, 1–13. DOI: https://doi.org/10.1167/13.2.21  

McElree, B. (2006). Accessing recent events. In: B. H. Ross (Ed.), The Psychology of Learning and Motivation , 46, (pp. 155–200). San Diego: Academic Press. DOI: https://doi.org/10.1016/S0079-7421(06)46005-9  

McVay, J. C., & Kane, M. J. (2009). Conducting the train of thought: Working memory capacity, goal neglect, and mind wandering in an executive-control task. Journal of Experimental Psychology: Learning, Memory, and Cognition , 35, 196–204. DOI: https://doi.org/10.1037/a0014104  

McVay, J. C., & Kane, M. J. (2012). Why does working memory capacity predict variation in reading comprehension? On the influence of mind wandering and executive attention. Journal of Experimental Psychology: General , 141, 302–320. DOI: https://doi.org/10.1037/a0025250  

Meiran, N., Liefooghe, B., & De Houwer, J. (2017). Powerful instructions: Automaticity without practice. Current Directions in Psychological Science , 26, 509–514. DOI: https://doi.org/10.1177/0963721417711638  

Mendoza-Halliday, D., & Martinez-Trujillo, J. C. (2017). Neuronal population coding of perceived and memorized visual features in the lateral prefrontal cortex. nature Communications , 8, 15471. DOI: https://doi.org/10.1038/ncomms15471  

Mongillo, G., Barak, O., & Tsodyks, M. (2008). Synaptic theory of working memory. Science , 319, 1543–1546. DOI: https://doi.org/10.1126/science.1150769  

Monsell, S. (2003). Task switching. Trends in Cognitive Sciences , 7, 134–140. DOI: https://doi.org/10.1016/S1364-6613(03)00028-7  

Morey, C. C., & Bieler, M. (2012). Visual short-term memory always requires general attention. Psychonomic Bulletin & Review , 20, 163–170. DOI: https://doi.org/10.3758/s13423-012-0313-z  

Navon, D., & Gopher, D. (1979). On the economy of the human-processing system. Psychological Review , 86, 214–255. DOI: https://doi.org/10.1037/0033-295X.86.3.214  

Navon, D., & Miller, J. (2002). Queuing or sharing? A critical evaluation of the single-bottleneck notion. Cognitive Psychology , 44, 193–251. DOI: https://doi.org/10.1006/cogp.2001.0767  

Nieuwenstein, M., & Wyble, B. (2014). Beyond a mask and against the bottleneck: Retroactive dual-task interference during working memory consolidation of a masked visual target. Journal of Experimental Psychology: General , 143, 1409–1427. DOI: https://doi.org/10.1037/a0035257  

Oberauer, K. (2001). Removing irrelevant information from working memory: A cognitive aging study with the modified Sternberg task. Journal of Experimental Psychology-Learning Memory and Cognition , 27(4), 948–957. DOI: https://doi.org/10.1037/0278-7393.27.4.948  

Oberauer, K. (2002). Access to information in working memory: Exploring the focus of attention. Journal of Experimental Psychology: Learning, Memory, and Cognition , 28(3), 411–421. DOI: https://doi.org/10.1037/0278-7393.28.3.411  

Oberauer, K. (2003). Selective attention to elements in working memory. Experimental Psychology , 50(4), 257–269. DOI: https://doi.org/10.1026//1618-3169.50.4.257  

Oberauer, K. (2005). Control of the contents of working memory – A comparison of two paradigms and two age groups. Journal of Experimental Psychology: Learning, Memory, and Cognition , 31(4), 714–728. DOI: https://doi.org/10.1037/0278-7393.31.4.714  

Oberauer, K. (2009). Design for a working memory. Psychology of Learning and Motivation: Advances in Research and Theory , 51, 45–100. DOI: https://doi.org/10.1016/S0079-7421(09)51002-X  

Oberauer, K. (2013). The focus of attention in working memory – from metaphors to mechanisms. frontiers in human neuroscience , 7. DOI: https://doi.org/10.3389/fnhum.2013.00673  

Oberauer, K. (2018). Removal of irrelevant information from working memory: Sometimes fast, sometimes slow, and sometimes not at all. Annals of the New York Academy of Science , 1424, 239–255. DOI: https://doi.org/10.1111/nyas.13603  

Oberauer, K., Awh, E., & Sutterer, D. W. (2017). The role of long-term memory in a test of visual working memory: Proactive facilitation but no proactive interference. Journal of Experimental Psychology: Learning, Memory and Cognition , 43, 1–22. DOI: https://doi.org/10.1037/xlm0000302  

Oberauer, K., & Bialkova, S. (2011). Serial and parallel processes in working memory after practice. Journal of Experimental Psychology: Human Perception and Performance , 37(2), 606–614. DOI: https://doi.org/10.1037/a0020986  

Oberauer, K., Demmrich, A., Mayr, U., & Kliegl, R. (2001). Dissociating retention and access in working memory: An age-comparative study of mental arithmetic. Memory & Cognition , 29(1), 18–33. DOI: https://doi.org/10.3758/BF03195737  

Oberauer, K., Farrell, S., Jarrold, C., & Lewandowsky, S. (2016). What limits working memory capacity? Psychological Bulletin , 142, 758–799. DOI: https://doi.org/10.1037/bul0000046  

Oberauer, K., & Hein, L. (2012). Attention to information in working memory. Current Directions in Psychological Science , 21, 164–169. DOI: https://doi.org/10.1177/0963721412444727  

Oberauer, K., & Lewandowsky, S. (2013). Evidence against decay in verbal working memory. Journal of Experimental Psychology: General , 142, 380–411. DOI: https://doi.org/10.1037/a0029588  

Oberauer, K., & Lewandowsky, S. (2014). Further evidence against decay in working memory. Journal of Memory and Language , 73, 15–30. DOI: https://doi.org/10.1016/j.jml.2014.02.003  

Oberauer, K., Lewandowsky, S., Farrell, S., Jarrold, C., & Greaves, M. (2012). Modeling working memory: An interference model of complex span. Psychonomic Bulletin & Review , 19, 779–819. DOI: https://doi.org/10.3758/s13423-012-0272-4  

Oberauer, K., & Lin, H.-Y. (2017). An interference model of visual working memory. Psychological Review , 124, 21–59. DOI: https://doi.org/10.1037/rev0000044  

Oberauer, K., Souza, A. S., Druey, M., & Gade, M. (2013). Analogous mechanisms of selection and updating in declarative and procedural working memory: Experiments and a computational model. Cognitive Psychology , 66, 157–211. DOI: https://doi.org/10.1016/j.cogpsych.2012.11.001  

Olivers, C. N. L. (2008). Interactions between visual working memory and visual attention. Frontiers in Bioscience , 13, 1182–1191. DOI: https://doi.org/10.2741/2754  

Olivers, C. N. L., Peters, J., Houtkamp, R., & Roelfsema, P. R. (2011). Different states in visual working memory: When it guides attention and when it does not. Trends in Cognitive Sciences , 15, 327–334. DOI: https://doi.org/10.1016/j.tics.2011.05.004  

Park, S., Kim, M.-S., & Chun, M. M. (2007). Concurrent working memory load can facilitate selective attention: Evidence for specialized load. Journal of Experimental Psychology: Human Perception and Performance , 33(1062–1075). DOI: https://doi.org/10.1037/0096-1523.33.5.1062  

Pashler, H. (1994). Dual-task interference in simple tasks: Data and theory. Psychological Bulletin , 116, 220–244. DOI: https://doi.org/10.1037/0033-2909.116.2.220  

Plate, T. A. (2003). Convolution-based memory models. In: L. Nadel (Ed.), Encyclopedia of cognitive science , (pp. 824–828). London: Nature Publishing Group.  

Ralph, A., Walters, J. N., Stevens, A., Fitzgerald, K. J., Tehan, G., Surprenant, A. M., Turcotte, J., et al. (2011). Immunity to proactive interference is not a property of the focus of attention in working memory. Memory & Cognition , 39, 217–230. DOI: https://doi.org/10.3758/s13421-010-0030-7  

Randall, J. G., Oswald, F. L., & Beier, M. E. (2014). Mind-wandering, cognition, and performance: A theory-driven meta-analysis of attention regulation. Psychological Bulletin , 140, 1411–1431. DOI: https://doi.org/10.1037/a0037428  

Rerko, L., Souza, A. S., & Oberauer, K. (2014). Retro-cue benefits in working memory without sustained attention. Memory & Cognition , 42, 712–728. DOI: https://doi.org/10.3758/s13421-013-0392-8  

Ricker, T. J., & Hardman, K. O. (2017). The nature of short-term consolidation in visual working memory. Journal of Experimental Psychology: General . DOI: https://doi.org/10.1037/xge0000346  

Rose, N. S., LaRocque, J. J., Riggall, A. C., Gosseries, O., Starrett, M. J., Meyering, E. E., & Postle, B. R. (2016). Reactivation of latent working memories with transcranial magnetic stimulation. Science , 354, 1136–1139. DOI: https://doi.org/10.1126/science.aah7011  

Sander, M. C., Werkle-Bergner, M., & Lindenberger, U. (2011). Binding and strategic selection in working memory: A lifespan dissociation. Psychology and Aging , 26, 612–624. DOI: https://doi.org/10.1037/a0023055  

Saults, J. S., & Cowan, N. (2007). A central capacity limit to the simultaneous storage of visual and auditory arrays in working memory. Journal of Experimental Psychology: General , 136, 663–684. DOI: https://doi.org/10.1037/0096-3445.136.4.663  

Schneider, W., & Shiffrin, R. M. (1977). Controlled and automatic human information processing: I. Detection, search, and attention. Psychological Review , 84, 1–66. DOI: https://doi.org/10.1037/0033-295X.84.1.1  

Shiffrin, R. M., & Schneider, W. (1977). Controlled and automatic human information processing: II. Perceptual learning, automatic attending, and a general theory. Psychological Review , 84, 127–190. DOI: https://doi.org/10.1037/0033-295X.84.2.127  

Shipstead, Z., Lindsey, D. R. B., Marshall, R. L., & Engle, R. E. (2014). The mechanisms of working memory capacity: Primary memory, secondary memory, and attention control. Journal of Memory and Language , 72, 116–141. DOI: https://doi.org/10.1016/j.jml.2014.01.004  

Singh, K. A., Gignac, G. E., Brydges, C. R., & Ecker, U. K. H. (2018). Working memory capacity mediates the relationship between removal and fluid intelligence. Journal of Memory and Language , 101, 18–36. DOI: https://doi.org/10.1016/j.jml.2018.03.002  

Soto, D., Hodsoll, J., Rotshtein, P., & Humphreys, G. W. (2008). Automatic guidance of attention from working memory. Trends in Cognitive Sciences , 12, 342–348. DOI: https://doi.org/10.1016/j.tics.2008.05.007  

Souza, A. S., & Oberauer, K. (2016). In search of the focus of attention in working memory: 13 years of the retro-cue effect. Attention, Perception & Psychophysics . DOI: https://doi.org/10.3758/s13414-016-1108-5  

Souza, A. S., & Oberauer, K. (2017). The contributions of visual and central attention to visual working memory. Attention, Perception & Psychophysics , 79, 1897–1916. DOI: https://doi.org/10.3758/s13414-017-1357-y  

Souza, A. S., Rerko, L., & Oberauer, K. (2015). Refreshing memory traces: Thinking of an item improves retrieval from visual working memory. Annals of the New York Academy of Sciences , 1339, 20–31. DOI: https://doi.org/10.1111/nyas.12603  

Souza, A. S., Vergauwe, E., & Oberauer, K. (2018). Where to attend next: Guiding refreshing of visual, spatial, and verbal representations in working memory. Annals of the New York Academy of Science . DOI: https://doi.org/10.1111/nyas.13621  

Sprague, T. C., Ester, E. F., & Serences, J. T. (2016). Restoring latent visual working memory representations in human cortex. Neuron , 91, 694–707. DOI: https://doi.org/10.1016/j.neuron.2016.07.006  

Szmalec, A., Vandierendonck, A., & Kemps, E. (2005). Response selection involves executive control: Evidence from the selective interference paradigm. Memory & Cognition , 33, 531–541. DOI: https://doi.org/10.3758/BF03193069  

Tehan, G., & Humphreys, M. S. (1998). Creating proactive interference in immediate recall: Building a DOG from a DART, a MOP, and a FIG. Memory & Cognition , 26, 477–489. DOI: https://doi.org/10.3758/BF03201157  

Thalmann, M., Souza, A. S., & Oberauer, K. (2019). Revisiting the attentional demands of rehearsal in working-memory tasks. Journal of Memory and Language , 105, 1–18. DOI: https://doi.org/10.1016/j.jml.2018.10.005  

Theeuwes, J. (2018). Visual selection: Usually fast and automatic; seldom slow and volitional. Journal of Cognition , 1, 1–15. DOI: https://doi.org/10.5334/joc.13  

Todd, J. J., & Marois, R. (2004). Capacity limit of visual short-term memory in human posterior parietal cortex. Nature , 428, 751–753. DOI: https://doi.org/10.1038/nature02466  

Todd, J. J., & Marois, R. (2005). Posterior parietal cortex activity predicts individual differences in visual short-term memory capacity. Cognitive, Affective, & Behavioral Neuroscience , 5, 144–155. DOI: https://doi.org/10.3758/CABN.5.2.144  

Tombu, M., & Jolicoeur, P. (2003). A central capacity sharing model of dual-task performance. Journal of Experimental Psychology: Human Perception and Performance , 29, 3–18. DOI: https://doi.org/10.1037/0096–1523.29.1.3  

Tremblay, S., Saint-Aubin, J., & Jalberg, A. (2006). Rehearsal in serial memory for visual-spatial information: Evidence from eye movements. Psychonomic Bulletin & Review , 13, 452–457. DOI: https://doi.org/10.3758/BF03193869  

Tsubomi, H., Fukuda, K., Watanabe, K., & Vogel, E. K. (2013). Neural limits to representing objects still within view. Journal of Neuroscience , 33, 8257–8263. DOI: https://doi.org/10.1523/JNEUROSCI.5348-12.2013  

Ueno, T., Allen, R. J., Baddeley, A. D., Hitch, G. J., & Saito, S. (2011). Disruption of visual feature binding in working meemory. Memory & Cognition , 39, 12–23. DOI: https://doi.org/10.3758/s13421-010-0013-8  

Unsworth, N. (2015). Consistency of attentional control as an important cognitive trait: A latent variable analysis. Intelligence , 49, 110–128. DOI: https://doi.org/10.1016/j.intell.2015.01.005  

Unsworth, N., Fukuda, K., Awh, E., & Vogel, E. K. (2014). Working memory and fluid intelligence: Capacity, attention control, and secondary memory retrieval. Cognitive Psychology , 71, 1–26. DOI: https://doi.org/10.1016/j.cogpsych.2014.01.003  

Van der Stigchel, S., Merten, H., Meeter, M., & Theeuwes, J. (2007). The effects of a task-irrelevant visual event on spatial working memory. Psychonomic Bulletin & Review , 14, 1066–1071. DOI: https://doi.org/10.3758/BF03193092  

van Moorselaar, D., Battistoni, E., Theeuwes, J., & Olivers, C. N. L. (2014). Rapid influences of cued visual memories on attentional guidance. Annals of the New York Academy of Sciences . DOI: https://doi.org/10.1111/nyas.12574  

van Moorselaar, D., Foster, J. J., Sutterer, D. W., Theeuwes, J., Olivers, C. N. L., & Awh, E. (2017). Spatially selective alpha oscillations reveal moment-by-moment trade-offs between working memory and attention. Journal of Cognitive Neuroscience , 30, 256–266. DOI: https://doi.org/10.1162/jocn_a_01198  

van Moorselaar, D., Theeuwes, J., & Olivers, C. N. L. (2014). In competition for the attentional template: Can multiple items within visual working memory guide attention? Journal of Experimental Psychology: Human Perception and Performance , 40, 1450–1464. DOI: https://doi.org/10.1037/a0036229  

Vergauwe, E., Barrouillet, P., & Camos, V. (2010). Do mental processes share a domain-general resource? Psychological Science , 21, 384–390. DOI: https://doi.org/10.1177/0956797610361340  

Vergauwe, E., Camos, V., & Barrouillet, P. (2014). The impact of storage on processing: How is information maintained in working memory? Journal of Experimental Psychology: Learning, Memory, and Cognition , 40, 1072–1095. DOI: https://doi.org/10.1037/a0035779  

Vogel, E. K., & Machizawa, M. G. (2004). Neural activity predicts individual differences in visual working memory capacity. Nature , 428, 748–751. DOI: https://doi.org/10.1038/nature02447  

Vogel, E. K., McCollough, A. W., & Machizawa, M. G. (2005). Neural measures reveal individual differences in controlling access to working memory. Nature , 438(24), 500–503. DOI: https://doi.org/10.1038/nature04171  

Watanabe, K., & Funahashi, S. (2014). Neural mechanisms of dual-task interference and cognitive capacity limitation in the prefrontal cortex. Nature Neuroscience , 17, 601–611. DOI: https://doi.org/10.1038/nn.3667  

Wickens, C. D. (1980). The structure of attentional ressources. In: R. S. Nickerson (Ed.), Attention & Performance , VIII, (pp. 239–257). Hillsdale, N.J.: Erlbaum.  

Wilhelm, O., Hildebrandt, A., & Oberauer, K. (2013). What is working memory capacity, and how can we measure it? frontiers in Psychology , 4. DOI: https://doi.org/10.3389/fpsyg.2013.00433  

Williams, M., Pouget, P., Boucher, L., & Woodman, G. F. (2013). Visual-spatial attention aids the maintenance of object representations in visual working memory. Memory & Cognition , 41, 698–715. DOI: https://doi.org/10.3758/s13421-013-0296-7  

Wolff, M. J., Jochim, J., Akyürek, E. G., & Stokes, M. G. (2017). Dynamic hidden states underlying working-memory-guided behavior. Nature Neuroscience , 20, 864–871. DOI: https://doi.org/10.1038/nn.4546  

Woodman, G. F., Carlisle, N. B., & Reinhart, R. M. G. (2013). Where do we store the memory representations that guide attention? Journal of Vision , 13, 1–17. DOI: https://doi.org/10.1167/13.3.1  

Woodman, G. F., & Chun, M. M. (2006). The role of working memory and long-term memory in visual search. Visual Cognition , 14, 808–830. DOI: https://doi.org/10.1080/13506280500197397  

Xu, Y., & Chun, M. M. (2006). Dissociable neural mechanisms supporting visual short-term memory for objects. Nature , 440, 91–94. DOI: https://doi.org/10.1038/nature04262  

Yeung, N., Botvinick, M., & Cohen, J. D. (2004). The neural basis of error detection: Conflict monitoring and the error-related negativity. Psychological Review , 111, 931–959. DOI: https://doi.org/10.1037/0033-295X.111.4.931  

Yu, Q., & Shim, W. M. (2017). Occipital, parietal, and frontal cortices selectively maintain task-relevant features of multi-feature objects in visual working memory. NeuroImage , 157, 97–107. DOI: https://doi.org/10.1016/j.neuroimage.2017.05.055  

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Research Article

Long-term memory effects on working memory updating development

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Validation, Visualization, Writing – original draft

* E-mail: [email protected]

Affiliation University of Urbino, Urbino, Italy

Roles Conceptualization, Funding acquisition, Methodology, Project administration, Resources, Supervision, Validation, Writing – review & editing

Affiliation University of Pavia, Pavia, Italy

• Caterina Artuso, 
• Paola Palladino

• Published: May 31, 2019
• https://doi.org/10.1371/journal.pone.0217697
• Reader Comments

Long-term memory (LTM) associations appear as important to cognition as single memory contents. Previous studies on updating development have focused on cognitive processes and components, whereas our investigation examines how contents, associated with different LTM strength (strong or weak), might be differentially updated at different ages. To this end, we manipulated association strength of information given at encoding, in order to focus on updating pre-existing LTM associations; specifically, associations for letters. In particular, we controlled for letters usage frequency at the sub-lexical level. We used a task where we dissociated inhibition online (i.e., RTs for updating and controlling inhibition from the same set) and offline (i.e., RTs for controlling inhibition from previously updated sets). Mixed-effect analyses were conducted and showed a substantial behavioural cost when strong associations had to be dismantled online (i.e., longer RTs), compared to weak ones; here, in primary school age children. Interestingly, this effect was independent of age; in fact, children from 7–8 to 9–10 years were comparably sensitive to the strength of LTM associations in updating. However, older children were more effective in offline inhibitory control.

Citation: Artuso C, Palladino P (2019) Long-term memory effects on working memory updating development. PLoS ONE 14(5): e0217697. https://doi.org/10.1371/journal.pone.0217697

Editor: Burcu Arslan, Educational Testing Service, UNITED STATES

Received: November 26, 2018; Accepted: May 16, 2019; Published: May 31, 2019

Copyright: © 2019 Artuso, Palladino. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: This work was supported by Blue Sky Research (BRS) 2017 Established Investigator awarded to PP. The funder played no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Working memory (WM) is a capacity limited system, able to maintain actively sets of representations useful in complex cognitive skills such as reading [ 1 , 2 ] or text comprehension [ 3 , 4 ]. WM performance improves substantially over childhood with linear increases [ 5 , 6 ]. These developmental improvements may be driven by increases in storage capacity [ 7 ], rehearsal strategies [ 8 ], or also updating processes [ 9 ].

In fact, given capacity limits and the continuous flow of information to be processed, it is important to explore a mechanism that potentially allows WM content to be updated constantly via maintenance of relevant information and inhibition of irrelevant information. Updating investigation is usually applied to memory contents [ 10 ]. However, usually, updating tasks are based on binding and unbinding processes between memory contents (e.g., [ 11 ]). Binding updating (but not content updating) is a more sensitive measure in accounting for performance in accuracy-based updating tasks [ 12 ]. In addition, the role of associative contextual bindings in episodic memory retrieval was also supported [ 13 ]. Overall, it appears that the monitoring of associative bindings between contents is a specific challenge for the updating process (see also [ 14 , 15 ]).

In the current paper, we aimed to study how updating of long-term memory (LTM) bindings (or LTM associations) develops in primary school children (in particular from third to fifth grade). First, we briefly review development of updating components and the role of LTM representations in WM tasks through childhood; in particular, lexical-semantic and sub-lexical representations. Next, we will focus on sub-lexical LTM representations and how these are updated specifically, introducing the aims of the current study.

Updating processes, components and development

Development of the WM updating function is a recent research topic that has arisen from adult studies and modelling research. In a recent developmental study, an accuracy-based updating task modelled after the one developed by [ 4 ] was administered to children [ 9 ]; here, they were able to differentiate between inhibition (i.e., ability to suppress same-lists intrusions) and proactive interference (PI) control (i.e., ability to suppress previous-lists intrusions). They showed that memory performance improves with age, together with development of inhibitory process efficiency. However, the most interesting finding here, is that these two components are relatively dissociable. The inhibition of information explained a considerable amount of variance, but of a similar percentage magnitude at ages 7, 11 and 15 years (42%, 49% and 46%, respectively); thus, its developmental contribution is less pronounced. On the other hand, the PI control component explained smaller amounts of variance across all ages, but especially at 7 years (25%), at 11 years (17%) and at 15 years (13%; [ 9 ]); thus its developmental role appeared more pronounced.

This two-component model of updating development is consistent with other models that emphasize additional features of updating and/or investigate alternative mechanisms [ 16 ]; here, the authors decomposed the updating process, individuating at least three components: retrieval (i.e., searching for a specific representation among many competing elements maintained in the region of direct access; see also [ 17 ]); transformation (i.e., modifying a representation maintained in WM); and the most distinctive component, item-removal (i.e., replacement of previously relevant content -now irrelevant- with new relevant information; [ 16 , 18 ]).

Within this theoretical framework, age-related differences through development, from 8 years to adulthood were found [ 19 ]. They found that only the retrieval component has age-related effects, with clear development from 8 years; no differences were observed for transformation or item-removal, despite their crucial role in updating.

LTM associations and WM development

The role of LTM associations in WM performance has been previously explored in order to understand how enduring properties of verbal material affects ongoing performance, mainly through simple WM tasks involving recall (e.g., [ 20 , 21 ]). The impact of informational organization in LTM on WM performance can be observed at different processing levels, e.g., lexical, sub-lexical and semantic.

In general, it has been shown that LTM associations interact with recall, facilitating the process; the more strongly items are associated in LTM, the more WM performance will benefit. That said, few studies have investigated the influence of lexical/semantic LTM representations on verbal WM performance in children, although previous research seems to suggest that effects are similar in children and adults (e.g., [ 22 , 23 , 24 ]).

Semantically-related information enhanced WM performance more than descriptive or unrelated information [ 22 ]. Similar lexico-semantic effects to adults across development were reported [ 23 ]. In an immediate serial recall task with words, they found replication of effects observed in adults, (e.g., lexicality, word frequency and imageability) from 6 to 22 years. These were accounted for by similar redintegration processes that would operate effectively on high frequency words because their phonological representations are more easily accessed by partial information. Accordingly, item frequency effects on recall are observed with the relevant item only, and occur at the time the individual item is retrieved/recalled (see also [ 20 , 21 , 25 ]).

How LTM lexical/semantic knowledge (such as lexicality and language familiarity effects) impacts on WM performance was examined by [ 24 ]. They compared children aged 5 and 9 years in tasks of immediate serial recall, finding evidence of the semantic-similarity effect in 5 year-olds. In fact, the specific organization of semantic LTM was found to enhance recall performance.

Overall, these studies have focused on WM recall tasks (i.e., entailing temporary maintenance of information in WM; [ 2 ]) and suggest that the more associated the information is, the better memory performance will be. In addition, studies suggest that developmental changes of the LTM system happens between the age of 5 and 11 years [ 24 ]; thus, interactions between LMT and WM recall are linked to developmental changes in WM capacity and efficiency [ 6 ]. In contrast, here, we focused on the interaction between LTM and updating; here, a complex WM function comprising not only temporary maintenance of information, but also inhibition and item-removal [ 9 , 16 , 18 ].

How LTM associations are updated

To the best of our knowledge, few studies have investigated the updating of LTM associations between verbal materials [ 14 , 26 ]. Indeed, updating can be distinguished from recall, as it allows memory focus to remain attuned to the most relevant information in any specific moment.

In an initial study, the strength of association between LTM stimuli was manipulated [ 26 ]; and how strength might modulate the updating process itself. Following the literature on the beneficial effects of highly-associated LTM information (e.g., [ 20 , 25 ]), Artuso and Palladino [ 26 ] investigated whether strong or weak associations were updated differently. Strength was represented by the frequency of sub-lexical associations between consonants. Association strength was manipulated at encoding, in order to observe how strong and weak associations were updated subsequently. Overall, it was shown that the stronger the LTM association, the longer latencies (i.e., to substitute information and to control for irrelevant information) were required. Therefore, a processing cost was found for updating; this is in direct opposition to recall, which is boosted by association strength [ 14 ].

In a further study, the association strength was manipulated at both encoding and updating, and added two conditions (i.e., strong associations that were updated to strong, and weak associations updated to strong), in order to gain a more complete view of accumulation and disruption of specific associations [ 14 ]. Here, the data supported the view that as pre-existing associations became stronger, they became harder to dismantle (i.e., longer RTs). In addition, when a strong association had to be recreated, this was usually enhanced (i.e., with shorter RTs from weak to strong association). The result was observed for both processing speed (inhibition process) and interference control (i.e., of a previously activated strong association). In particular, it was shown that inhibitory control requested was greater for items strongly associated, indicating, in turn, the long lasting of the pre-existing LTM association. Those experiments demonstrated clearly that associations from LTM modulate the updating process. In fact, these results suggested that, on the one hand, strong associations are dismantled and updated with greater difficulty (i.e., they require longer RTs), and on the other, that strong associations are activated more easily (i.e., requiring shorter RTs). This evidence supported the idea that the nature of updating rests in the interplay between dismantling and reconstructing bindings via different memory systems such as WM [ 11 , 24 ] and episodic LTM [ 13 ].

In the numerical domain, it was found that numerical similarity produces facilitation during updating of information. When the numbers involved in updating were near as far as concern numerical distance, or similar through sharing a digit, substitution occurred more quickly [ 27 , 28 ]. There, it was proposed that updating is a function of the overlapping features [ 29 ] between numbers to update and those stored in LTM; the greater the amount of overlap, the quicker the update will be, as both numbers share many (already activated) features. In summary, if, as well as inhibition [ 9 ], item-removal in LTM association is a distinctive updating component [ 16 ], it is important to investigate how the strength of this inter- item association retained in LTM affects WM processing (e.g., updating, [ 14 ]).

The current study

As previously described, studies on updating development have focused on processes and components [ 9 , 19 ], whereas our aim is to examine the associative effects of updating through development. In particular, given that LTM inter-item associations seem as important as single contents [ 14 ], we aimed to investigate whether associated information modulates updating performance in development.

Hence, we manipulated LTM associations for letters as they represent initial elements of learning and therefore, should be highly familiar to children, in addition to their established use in many studies on their role across cognition. In particular, we controlled for their frequency of use at the sub-lexical level. Broad evidence has shown recall accuracy is greater for words containing high frequency phoneme combinations in English (“phonotactic effect”, see [ 25 ]). Performance would likely benefit from use of stored phonotactic representations for familiar words to fill in incomplete traces prior to output. In contrast, for unfamiliar words, no stored representations are available to reconstruct partial traces, and this will lead to diminished accuracy at recall. In addition, recall is better for high phonotactic frequency of the language in WM. As fully described in [ 25 ] the “phonotactic effect” elicits better recall for ‘consonant-vowel-consonant’ non-words containing ‘consonant-vowel’ and ‘vowel-consonant’ combinations, common in the language’s native phonology, than for non-words containing low probability ‘consonant-vowel’ combinations. Such effect would reflect the influence of phonotactic knowledge about properties of that language [ 25 ].

With this aim, we administered an updating task previously used with both children [ 30 ] and adults [ 12 , 31 ], focused on active item-removal of information shown to be the most distinctive component of updating [ 14 , 16 ]; but see also [ 19 ]. In particular, this task allows collection of both online response times (RTs) during updating (i.e., dismantling of an item-set) and offline accuracy/RTs after updating of a memory set, in order to ensure updating effectiveness and inhibition of irrelevant information [ 31 ].

Therefore, we believe this task could include at least two different types of inhibition, that is online (i.e., inhibition within the same set) as well as offline (i.e., inhibition of the previously updated set of information). Thus, the specific object of our investigation is how information, associated with different strength in LTM, i.e., strongly or weakly, might be differently updated at various ages. To this end, we manipulated association strength of the information at encoding (but not updating), in order to focus on the specific function of dismantling pre-existing LTM associations rather than reconstruction of new associations. We hypothesize that, in line with adult studies (e.g., [ 23 ]), we should observe similar effects with children, as soon as LTM representations are strengthened and consolidated (i.e., with a behavioural cost for updating strongly associated information). In particular, we should observe an increase in online updating RTs when inhibiting and dismantling a strong pre-existing association (once encoded), and a decrease when dismantling a weak pre-existing association (once encoded). Accordingly, offline, we predict greater difficulty in inhibiting items from strong LTM associations, relative to weak ones).

Participants

The initial sample was of 90 children. At the end of the testing phase, we were informed from teachers that one child had received a diagnosis of learning disorder. We therefore decided to not include his data in the final sample. Thus, a sample of 89 children took part in the study. They did not present any specific learning, neurological or psychiatric disorder. Children were divided into two groups: 44 younger children (aged 7–8 years) and 45 older children (aged 9–10 years). These specific ages were chosen as they represent the most crucial steps for children to become more and more skilled in reading and writing, and access to meaning of written texts is more automatized. In addition, and in line with previous studies suggesting the relevance of the specific age range 5–11 years (e.g., [ 6 , 24 ]), we chose two central and crucial steps that are coherent with previous research and allow comparison. All children were Italian native speaker. See breakdown of participants’ characteristics in Table 1 .

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Descriptive statistics (mean, standard deviations for accuracy rate and score range) for the Italian vocabulary and nonverbal reasoning test. SDs are in brackets.

https://doi.org/10.1371/journal.pone.0217697.t001

Children came from a public school located in Northern Italy, within an urban environment and mixed socio-economic background. All children had normal or corrected-to-normal vision. The study was conducted in accordance with the Ethical Standards laid down in the 1964 Declaration of Helsinki and the standard ethical procedures recommended by the Italian Psychological Association (AIP). The study was reviewed and approved by the IRB (ethical committee) of the University of Pavia/IUSS before the study began. Written informed parental consent (as well as oral informed child assent) was obtained prior to participating, according to the ethical norms in our university.

Children were administered two tasks to assess general cognitive abilities (see following method sections for full description). Descriptive statistics for the two general cognitive abilities administered to the two age groups are displayed in Table 1 . Analyses on the accuracy scores (independent sample t-tests) showed age-related differences in the vocabulary test, t( 87) = 2.09, p = .04, with older children better scoring than younger children, but no differences in the visuospatial reasoning test, t( 88) = 1.02, p = .31.

Materials and procedures

In order to verify that children’s general cognitive performance adhered to the average for their age, they were presented with two measures: a standardized Italian vocabulary test and a nonverbal reasoning test. In particular, the vocabulary can be taken as an index of crystallized intelligence, whereas the nonverbal reasoning test is held to measure fluid intelligence.

In addition, a computerized letter updating task was administered. The vocabulary test and the nonverbal reasoning test were administered in a classroom-based group session. The updating task was administered individually at school, in a quiet room. The group session lasted on average 15 minutes, and the updating task lasted about 20–25 minutes. The two sessions were non-consecutive, in order to avoid possible fatigue effects.

Italian vocabulary and nonverbal reasoning

The vocabulary and nonverbal reasoning subtests, taken from the Primary Mental Aptitude Battery [ 32 ] were presented to the whole class group during a school day; both have a four alternative multiple-choice structure. The vocabulary subtest has 30 items and the nonverbal reasoning subtest, 25 items. Participants had time constraints for both subtests; specifically, 5 minutes for the vocabulary and 6 minutes for the nonverbal reasoning.

Letter updating task

The task we used in the current paper was described in detail previously, in [ 14 ]. As in [ 14 ] the stimuli were sub-lexical units between two consonants of the Latin alphabet. The association was based on LTM consonant representation; that is, on the basis of their combined frequency in the spoken Italian language. We evaluated this from the lexicon of frequency of Italian spoken language [ 33 ], a corpus of about 490,000 lemmas collected in four main Italian cities, emerging from different subgroups of discourse. High and low frequency lemmas were selected. Low frequency ranged from 0 to 2 (i.e., lemmas with less than 3 occurrences in the corpus). High frequency lemmas had at least 3 occurrences in the corpus.

Next, we inferred strong and weak sub-lexical associations between consonants, based on the lemmas’ frequency. That said, we should note there is no specific frequency information for consonant couples, only for lemmas of the corpus. So, for example, from the lemma “ ardere” which is low frequency, we inferred the low frequency sub-lexical association “ rd ”. In addition, low frequency associations, typically, were in the middle of the lemma, whereas high frequency lemmas were at the beginning of the lemma. In addition, we checked the corpus to find occurrences of low frequency sub-lexical associations in different lemmas, in order to preclude their presence in high frequency lemmas. We included in the low frequency sub-lexical associations those one occurring in low frequency lemmas only.

We employed the following set of consonants: B C D F G H L N P R S T. Strong associations were: T-R, S-P, P-R, N-T, B-R, C-H, G-R, F-R. Weak ones were: F-L, S-N, G-H, P-S, G-L, R-D, N-D, L-T. Strong and weak associations between consonants were controlled in order to avoid obviously familiar or meaningful couplets. Each association was legal, and thus possible at the sub-lexical level of the Italian language [ 14 ].

As described in [ 14 ] and in order to avoid ceiling (i.e., with two items) or floor effects (i.e., with four items), we used memory sets composed of three letters (i.e., triplets), which have been established as being within average memory span [ 34 ]. Some letters were overrepresented relative to others, but we controlled for this bias by randomizing these across association strengths. Further, the position of the sub-lexical unit within the triplet (i.e., in positions 1/2 or 2/3 ) was randomized between trials. We did not control for potential position effects, as it was shown in a previous experiment that position did not interact with either updating or strength (see [ 14 ], Experiment 2)

The third letter of each triplet was another consonant, which was always unrelated to the other two. Specifically, the link between the sub-lexical unit and the third letter was always linguistically impossible in Italian (e.g., see example from Fig 1 where C-H is a strong association, and the link between H and B (H-B) is impossible in Italian). This was done in order to avoid any LTM (strong or weak) or some other meaningful way association between these letters.

After encoding the first triplet ( CHB ), participants had to maintain it actively in memory (pre-updating maintenance process: + + +). Next, they were instructed to update part of the association, that is, to remove the item C and substitute the G . Thus, the triplet they were now maintaining was GHB . Lastly, they had to maintain the recently updated triplet (post-updating maintenance process). At recognition, a single red probe was displayed: here, participants had to recognize if the probed item belonged to the most recent studied/updated item or not. In the example, a target probe was presented ( B ), to which they had to give a positive answer.

https://doi.org/10.1371/journal.pone.0217697.g001

Design and analyses

A three factor mixed design was implemented: Strength and Phase were within-participants factors, and Age group between-participants. The variable Strength had two levels: strong-to-weak and weak-to-weak. ‘Strong-to-weak’ represented associations between letters where the association was strong at encoding, but modified with a weak one upon updating (e.g., from C-H to G-H). Weak-to-weak represented associations between letters occurred where the association was weak at encoding and updated with another weak association (e.g., from P-S to P-R). For each trial, we considered two main phases of encoding (i.e., studying/encoding the initial triplet), and updating (i.e., partial into the triplet). Although the trial was constituted of four phases, only encoding and updating phases (i.e., phases that produce effects on RTs, see [ 31 ]) were entered into the analysis.

In addition, to make the task less predictable and ensure participants were engaged, we included several control trials (approximately 20% of the total number). Here, no updating occurred, and maintenance alone was required throughout the trials. These data were not included in further analyses, but were checked to ensure that all updating trials had longer RTs than controls ( p < .05 for each comparison; control vs. strong-to-weak, and weak-to-weak; [ 14 ]).

Procedure was described in detail previously [ 14 , 26 ]. The task was administered on a standard PC and consisted of four phase subject-paced trials, where participants pressed the spacebar to start each trial, and after each phase, in order to proceed with the task.

In each phase, triplets were always displayed in the centre of the screen. Each trial started with an encoding phase (Phase 1; see an example with letters in Fig 1 , where a strong-to-weak association is represented), where participants had to memorize the first triplet of consonants (e.g., C-H-B). A pre-updating maintenance phase followed (Phase 2), where three pluses were displayed; this indicated that the previously encoded triplet had to be actively maintained. Then, at updating (Phase 3), participants had to substitute the no-longer-relevant information (here, C) with newly relevant information (here, G). Concurrently, they needed to maintain previously relevant detail (here, H-B), thus, updating the triplet (i.e., from C-H-B to G-H-B). Finally, a post-updating maintenance (Phase 4) ended the sequence, to control for recency biases. See also Fig 1 .

Only one letter of the triplet had to be updated; this letter could be presented in any position of the triplet (i.e., left letter, right letter, or center). Position was balanced across trials, and only new consonants were presented across each phase. When a consonant did not change, a plus symbol was presented, in order to encourage active maintenance of previously encoded/memorized information.

At the end of each trial (Phase 5), participants were presented with a probe recognition task: a single red consonant was displayed in the centre of the screen. Here, they had to indicate whether this belonged to the most-recently studied triplet or not. They responded by pressing one of two keys on the keyboard; one (M for Yes ) for target probes requiring a positive answer (i.e., belonging to the final triplet of the trial); another one (Z for No ) for probes requiring a negative answer (i.e., not previously presented in the trial. For these, we included both lures i.e., (probes encoded in the trial, then substituted at updating step) and negative probes (i.e., probes not presented in that trial), mixed within the trial. Half the probes were targets (50%); the other half was equally shared between lures (25%) and negative probes (25%).

Afterwards, each participant was presented with a practice block of eight trials to familiarize themselves with the task. One hundred and twenty trials were then presented shared equally in four blocks. We recorded subject-paced RT at each of the four phases, in addition to probe recognition accuracy at Phase 5.

Results and discussion

Updating task: accuracy and data treatment.

Participants performed accurately on an average of 92.80% of trials. As expected, participants were very good in completing the task and very few errors were produced. Accuracy was analysed to verify adequate performance, but the main focus of the analysis was on RT. We ran a mixed 2 x 3 ANOVA, with Strength (weak-to-weak, strong-to-weak) as within-participants factor and Age Group (younger children, older children) as between-participants factor on mean accuracy rates of target, lures and negative responses. A main effect of Age Group reached significance, F (1, 87) = 8.38, p = .005. Accuracy rate was significantly lower in younger children (116/120 correct trials) than in older children (118/120 correct trials). Only subject-paced RTs for trials that ended with correct probe recognition were analysed. Trials with RTs of less than 150 ms, or exceeding a participant’s mean RT for each condition by more than three intra-individual standard deviations, were considered outliers, and therefore excluded from further analyses (3.92%).

In addition, updating measures (in particular, indexes of RT at the updating step), were highly inter-correlated, suggesting good reliability of the task. In particular, RTs for weak-to-weak associations were strongly correlated, r (89) = .84, p < .001, to RTs for strong-to-weak.

Overview of the statistical analyses

We used a mixed-effects model approach to test our hypotheses; the most important advantage of such models is that they allow simultaneous consideration of all factors that may contribute to understanding the structure of the data [ 35 ]. Raw RTS were logarithmically transformed to normalize them. These factors comprise not only the standard fixed-effects factors controlled by the experimenter (in our case, age group and strength) but also random-effects factors; that is, factors whose levels are drawn at random from a population (in our case, children). To test the effect of age group (younger children, older children) and strength (strong-to-weak, weak-to-weak) on the variables of online RT, and offline RT three mixed-models were used: one for online RT (with encoding and updating phases as additional factors), another one for RT of correctly detected target probes, and a third for RT of correctly rejected lures. See specific details in the subsections below.

All analyses were performed using the R software [ 36 ]; for generalized mixed-effect models, the R package lme4 was used [ 37 ]; and the lmer test package was used to obtain Type III ANOVA Tables. Results for each dependent variable are presented below. For planned comparisons, Tukey correction was used to control the Type I error rate.

Online RT analyses

A linear mixed-effects model was constructed with 3-way interactions between Age Group (younger children, older children), Strength (strong-to-weak, weak-to-weak), and Phase (encode, update). The model revealed a significant effect of Age Group, F (1, 87) = 8.11, p = .006. Overall, older children ( M = 2709.26 ms, SD = 67 ms) were faster than younger children ( M = 2960.22 ms, SD = 66 ms). Moreover, Strength affected the online processing, F (1, 261) = 5.71, p = .01; strong-to-weak associations ( M = 2898.36 ms, SD = 65 ms) were hardly updated than weak-to-weak ones ( M = 2768.30 ms, SD = 68 ms).

In addition, the Phase by Strength interaction reached significance, F (1, 261) = 7.18, p = .008. Post-hoc comparisons showed no differences at encode across associations, t( 261) = -0.21, p = .83; in contrast, at updating, strong-to-weak associations showed longer RTs compared to weak-to-weak associations, t( 261) = 3.59, p = .004, as shown in Fig 2 . No other interaction reached significance.

Plot dots represent mean predicted RTs (ms) and bars represent 95% CIs.

https://doi.org/10.1371/journal.pone.0217697.g002

Offline RT analyses: Target probes

A linear mixed-effects model was constructed with 2-way interactions between Age Group (younger children, older children) and Strength (strong-to-weak, weak-to-weak). The model revealed a significant effect of Strength, F (1, 87.353) = 11.13, p = .001. Indeed, we found significantly longer RTs for correct recognition of a target probe from strong-to-weak associations ( M = 2058.33 ms, SD = 58 ms), compared to weak-to-weak associations ( M = 1867.85 ms, SD = 43 ms). No other effect reached significance.

Offline RT analyses: Lures

First, we conducted a control analysis with Strength (weak-to-weak, strong-to-weak), and Probe (lure, negative) as within-participant factors and Age Group (younger children, older children) as between-participant factor, for lures vs. negative probe RTs. Importantly here, we found a main effect of Probe, F (1, 87) = 8.61, p = .004, showing longer RTs to recognize and respond to lures ( M = 2395.68 ms, SD = 52 ms) than to negative probes ( M = 2208.06 ms, SD = 44 ms).

In addition, to test our hypotheses more specifically, a linear mixed-effects model was constructed with 2-way interactions between Age Group (younger children, older children) and Strength (strong-to-weak, weak-to-weak) and was run on lures only, as these represent a measure of the ability to inhibit irrelevant information once completed the updating task. The model revealed a significant effect of Age Group, F (1, 85.250) = 16.92, p < .001. In addition, we found a main effect of Strength, F (1, 87.394) = 45.75, p < .001.

The two-way Strength by Age Group interaction reached significance, F (1, 87.394) = 25.57, p < .001. Subsequently, post-hoc comparisons showed that rejection of a lure from a strong-to-weak association needed longer RTs (compared to weak-to-weak association), but only for older children, t (87.39) = 8.41, p < .001. Rejection of a lure from a strong-to-weak association did not differ from a weak-to-weak condition in younger children, t (87.39) = 1.20, p = .23, as shown in Fig 3 .

Plot dots represent mean predicted RTs (ms) at lure rejection and bars represent 95% CIs.

https://doi.org/10.1371/journal.pone.0217697.g003

We believe our task is mainly based on phonological/orthographic knowledge and less on lexico-semantic knowledge (see also [ 30 ]). In fact, in order to engage with the task rapidly and effectively, the child should have developed an automatic access to orthographic/letter form representation. Therefore, we do not predict any specific vocabulary-related effect. However, in order to control for the role of vocabulary in the process examined, we ran the same mixed-effect models, covarying for vocabulary. Overall, the results did not change, showing the same effects and significance levels for both target probes (main effect of Strength, p = .002) and lures (Age group, Strength, and two-ways interaction, all ps < .001).

Conclusions

In this study, our aim was to investigate how LTM associations affect updating development. Updating is a complex activity that involves inhibition at different levels such as from the same lists set, or from previous lists [ 9 ], with the distinguishing component of the item-removal process [ 16 , 18 ]. More specifically here, we analysed how the strength of LTM association between items affects updating from a developmental perspective.

Typically, the literature on adults shows enhanced recall for strongly associated items; the stronger the pre-existing association in LTM, the better the performance in WM. For updating, a somewhat different process is indicated (i.e. not only maintenance of information in the short term, but also removal of irrelevant information). In this case, the opposite was shown: the stronger the pre-existing association, the harder it is to dismantle it [ 26 ].

In addition, the first notable difference between updating and recall (i.e., slowing of RTs in the former) could be related to the number of cognitive operations required in the task. Indeed, recall involves maintenance of information only; whereas updating entails a further item-removal component. Therefore, it is reasonable to assume that an additional operation (i.e., item-removal) will add a cost in terms of longer processing latencies. However, results comparing updating performance compared to recall have demonstrated the reverse effect; that is a cost rather than a benefit. This difference is likely to be due to the nature of updating, an essential process in adaptation of WM content to new elements. In other words, updating involves integration of new elements, as well as new bindings between elements (after disrupting previous ones), thus inhibiting and removing/substituting irrelevant information [ 11 , 16 ].

A recent model of updating [ 9 ] showed that updating develops via two main components of inhibition, one more related to control of inhibition from same lists; another one of inhibition from previous lists. The former, shows fewer developmental differences, the latter (also called PI control in [ 9 ]) shows greater age-related differences. In our view, the task used here with children is suitable for consideration of both components in terms of processing speed (an index useful in studying development via more subtle and fine-grained measurement). In fact, in the current task, each participant needs to maintain information and inhibit it, when no longer relevant, by substituting with new information during the tasks (same list inhibition component). Further, to ensure effective updating, s/he has to control for interference from previously studied items which are no longer relevant (i.e., inhibition from previously studied items set).

In particular, in accordance with [ 9 ] model, we found different outcomes consistent with the measures considered. Accordingly, the online RT showed a global age-related effect (older children faster than younger children), but not specific for strength with which letter were associated (in fact, no interaction). This finding could be accounted for, if we consider the development of self-monitoring (i.e., the ability to control one own’s behaviour) in children. That is, monitoring skills develop between 7 to 10 years, and subtle but important improvements are found over the primary school years [ 38 ]. Our self-paced task, where the child had to press the spacebar when s/he thinks to have memorized/updated a given mental set, requires a self-judgment of performance from the child him/herself. In particular, it has been shown that children (from 8 years of age) are more accurate in judgment of learning when given after a delay of about 2 minutes, than immediately after study [ 39 ]. Thus our task (which requires self-monitoring of learning during the study/updating phases, and immediately after, in order to press the spacebar) might not enhance an appropriate child self-regulation. For this reason, we believe we did not find age-related effects relative to strength for self-paced RTs and thus, failed to replicate the effects found with adults [ 14 , 26 ].

Conversely, for offline inhibitory control (i.e., lure recognition), we found more pronounced developmental effects, with significant differences; older children took more time to reject strong lures than weak, whereas no difference was observed for younger children ( Fig 3 ). Therefore, we found that online inhibition component was less affected by developmental change: younger children are able to perform updating tasks successfully. The real challenge in updating (i.e., due to control for previously relevant information) elicits significantly better performance from 10 years onwards. Here, in fact there is no need for self-regulation (i.e., as in the probe recognition task) as the task is not self-paced. The modulation of association strength development in older children (but not in younger) could be well accounted by the development of both lexico-orthographic knowledge and executive mechanisms that can work simultaneously [ 5 , 6 ].

This finding supports claims that the ability to inhibit irrelevant information is a fundamental mechanism that underlines many other developmental changes [ 40 , 41 , 42 ]. In particular, decreased susceptibility to interference is observable as age increases; 7/8 years olds children were shown to be more susceptible to interference than 9/10 years old [ 40 ], as we found in our study. However, we believe the novelty of the current study lies in the specificity of the experimental manipulation. Notably, these results indicated that, from 10 years onward, children found highly familiar stimuli (such as letters) more intrusive and difficult to control when strongly associated. Therefore, although we find that older children are less susceptible to interference, it seems that they are more sensitive to strong and weakly associated stimuli, similarly to performance in adults [ 14 , 26 ].

Future studies should further investigate any additional benefits/costs in updating strong and weak LTM associations, by also manipulating the strength of the item-association at updating [ 14 ]. Through this further manipulation, a more fine-grained examination of the dismantling and recreation of associations during updating would be enabled, including analysis of the relative ease/difficulty of the process. In addition, it could be useful to administer the task to children with specific learning disorders in order to show possible modulation of WM performance by LTM knowledge. Specifically, the task could then be useful to implement ad hoc measures to train children to remediate identified weaknesses, both in educational and clinical settings. We might also speculate that, as we found that strong LTM associations are more difficult to modify, this could in turn indicate the importance of correct support for the child, so that s/he will not act to strengthen incorrect sub-lexical/phonotactic associations. Indeed, it is likely that the more those incorrect associations are reinforced, the harder will be to modify/update them.

In conclusion, the present study demonstrated how WM updating is affected by LTM strength of association in a developmental sample. A significant cost of dismantling and updating strong associations was shown, and this effect was independent from age; all children from 7 to 10 years were comparably sensitive to association strength. In addition, results allowed us to differentiate age-related effects for interference control in updating of strong LTM associations; older children (but not younger) were more susceptible to interference from strongly-associated information.

Supporting information

S1 data. dataset online rts..

https://doi.org/10.1371/journal.pone.0217697.s001

S2 Data. Dataset recognition probe RTs.

https://doi.org/10.1371/journal.pone.0217697.s002

Acknowledgments

We wish to thank all children and schools participating in the study. We also thank Beatrice Colombani for her help with data collection.

• View Article
• Google Scholar
• PubMed/NCBI
• 32. Thurstone L. L. & Thurstone T. G. (1963). Italian edition 1981. PMA : Batteria delle attitudini mentali primarie , 7–11 anni [PMA : Primary mental abilities , 7–11 years ]. Edizioni Giunti OS: Firenze.
• 33. De Mauro T., Mancini F., Vedovelli M. & Voghera M. (1993). Lessico di frequenza dell'italiano parlato. [Frequency Lexicon of Spoken Italian Language] Milano: Etas Libri.
• 36. R Development Core Team. (2010). R: A language and environment for statistical computing. Vienna, Austria: R foundation for statistical computing.

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This page provides a comprehensive list of cognitive psychology research paper topics , curated to inspire and assist students in their exploration of how humans perceive, remember, think, speak, and solve problems. Cognitive psychology, a discipline pivotal to understanding the intricacies of the human mind, encompasses a wide array of fascinating topics that delve into the mental processes underlying our daily functioning and well-being. From investigating the mechanisms of memory and the complexities of language acquisition to exploring the influence of emotion on cognition and the application of cognitive principles in technology, these topics offer students a rich terrain for academic inquiry. Designed to cater to a broad spectrum of interests and academic objectives, this list serves as a starting point for students aiming to contribute meaningful insights into the cognitive processes that define human experience.

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Cognitive psychology stands at the forefront of exploring the vast capabilities and intricacies of the human mind, offering profound insights into our thoughts, emotions, and behaviors. This branch of psychology delves into how people understand, diagnose, and interact with the world around them, influencing various aspects of human functioning and societal development. The research topics within cognitive psychology are as varied as they are dynamic, reflecting the continuous evolution of the field in response to new scientific discoveries and technological advancements. From the fundamental processes of perception and memory to the complex interplay between emotion and cognition, these topics not only contribute to our scientific knowledge but also have practical applications in education, mental health, artificial intelligence, and beyond.

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• Pragmatics and cognitive implications of language use
• The role of language in categorization and concept formation
• Sign language and cognitive processing
• Cognitive aspects of language evolution
• Cognitive strategies in problem-solving
• Decision-making processes and biases
• The psychology of judgment and choice
• Heuristics and cognitive shortcuts
• The role of intuition in decision-making
• Problem-solving in groups versus individually
• Cognitive biases and their impact on decision quality
• Risk assessment and decision-making under uncertainty
• The neuroscience of decision-making
• Creativity and cognitive processes in problem-solving
• Stages of cognitive development in children
• Cognitive theories of learning and instruction
• The role of play in cognitive development
• Adolescent cognitive development and risk-taking behavior
• Adult learning and cognitive change
• The impact of cognitive styles on learning outcomes
• Cognitive development in aging populations
• The role of technology in cognitive learning processes
• Cognitive enhancers and their impact on learning
• Metacognition and self-regulated learning
• Cognitive aspects of Alzheimer’s disease
• The neuropsychology of Parkinson’s disease
• Cognitive impairments in traumatic brain injury
• Neurocognitive deficits in schizophrenia
• Attention deficit hyperactivity disorder (ADHD) in adults
• Autism spectrum disorders and cognitive functioning
• The impact of stroke on cognitive functions
• Dementia and cognitive interventions
• Mild cognitive impairment and its progression
• Cognitive rehabilitation techniques for neurocognitive disorders
• The influence of emotion on cognitive processes
• Cognitive appraisal theories of emotion
• The role of cognition in emotional regulation
• Emotional intelligence and cognitive abilities
• The neuroscience of emotions and feelings
• Mood disorders and cognitive functioning
• The impact of stress on cognitive performance
• Emotion-cognition interactions in decision-making
• The cognitive psychology of happiness and well-being
• Emotional memory and its persistence
• Cognitive biases in social judgment and perception
• Theory of mind and perspective-taking
• Social cognition in interpersonal relationships
• The role of stereotypes in cognitive processing
• Cognitive underpinnings of prejudice and discrimination
• Social identity and cognition
• Moral reasoning and cognitive psychology
• The cognitive basis of empathy and altruism
• Social cognition and group dynamics
• Cognitive approaches to understanding social influence
• Cognitive psychology in human-computer interaction
• Virtual reality and its cognitive implications
• The impact of social media on cognition and social behavior
• Cognitive psychology principles in user experience design
• Artificial intelligence and cognitive modeling
• Gaming and cognitive skill development
• Cognitive training apps and their effectiveness
• Neurotechnology and cognitive enhancement
• The role of cognitive psychology in digital education
• Wearable technology and cognitive monitoring

The exploration of cognitive psychology research paper topics presents an unparalleled opportunity to delve into the mechanisms that underpin human cognition and behavior. Each category and topic not only contributes to the rich tapestry of cognitive psychology but also holds the potential for groundbreaking research that can influence educational practices, therapeutic approaches, and policy development. Students are encouraged to engage deeply with these topics, leveraging their curiosity and analytical skills to advance the field and contribute valuable insights into the complex world of human cognition.

What is Cognitive Psychology

Cognitive Psychology as a Discipline

The development of cognitive psychology marked a significant shift from the behaviorist perspective that dominated psychology for much of the early 20th century, which largely ignored mental processes. Instead, cognitive psychology focuses on understanding internal mental states and processes, utilizing this understanding to explain behavioral patterns. This focus on the internal workings of the mind has not only expanded the scope of psychological research but has also had practical applications in various fields such as education, mental health, artificial intelligence, and more, demonstrating the discipline’s broad impact.

The Importance of Research in Expanding Our Understanding of Cognitive Processes

Research in cognitive psychology plays a crucial role in expanding our understanding of the human mind and behavior. Through empirical studies, experiments, and longitudinal research, cognitive psychologists seek to build a body of knowledge about how cognitive processes work, how they change over time, and how they can be improved or altered. This research is fundamental to developing new theories of cognition that can explain complex human behaviors and cognitive anomalies.

One of the key contributions of cognitive psychology research is the development of models that describe various cognitive processes. For example, research on memory has led to the formulation of the multi-store model, which outlines how information flows from sensory memory to short-term memory and finally to long-term memory. Similarly, studies on decision-making and problem-solving have introduced several cognitive biases that influence human judgment, such as confirmation bias and availability heuristic. These models and theories are crucial for understanding the limitations and capabilities of human cognition, informing approaches in education, cognitive therapy, and even interface design in technology.

Moreover, cognitive psychology research has a significant impact on diagnosing and treating cognitive disorders. Studies on neurocognitive disorders, such as Alzheimer’s disease and attention deficit hyperactivity disorder (ADHD), provide insights into their cognitive underpinnings, leading to better diagnostic criteria and treatment options. Research in this field also supports the development of cognitive rehabilitation techniques and cognitive-behavioral therapies, demonstrating its vital role in improving mental health and cognitive function.

The Variety of Research Topics within Cognitive Psychology and Their Relevance to Real-World Applications

Cognitive psychology encompasses a wide array of research topics, each with direct implications for real-world applications. For instance, research in perception and sensation enhances our understanding of how sensory information is interpreted by the brain, influencing fields such as marketing, design, and even virtual reality development. Studies on attention and information processing have led to improvements in educational strategies, helping to develop teaching methods that align with cognitive load theory and the attentional needs of students.

Language and cognition research has profound implications for language teaching methodologies, speech therapy, and understanding language disorders. Insights from this research help in designing interventions for individuals with dyslexia or aphasia, facilitating better communication and learning outcomes. Additionally, the study of problem-solving and decision-making is pivotal for the development of artificial intelligence, providing algorithms with models of human cognition that can be simulated in computational systems.

The exploration of memory and recall has applications in legal settings, especially in eyewitness testimony and the reliability of memory. Cognitive psychology’s findings on the malleability of human memory and the conditions under which memories are accurately or inaccurately recalled are crucial for informing judicial processes and policies. Furthermore, the study of social cognition, which examines how individuals perceive, think about, and interact with others, is essential for understanding social behavior, improving interpersonal relationships, and addressing societal issues such as prejudice and discrimination.

Recent Advancements in Cognitive Psychology Research

Recent advancements in cognitive psychology research have been facilitated by technological innovations, allowing for more sophisticated exploration of cognitive processes. Neuroimaging techniques such as fMRI and PET scans have provided insights into the neural substrates of various cognitive functions, bridging the gap between cognitive psychology and neuroscience. These advancements have led to a deeper understanding of how different brain regions are involved in specific cognitive tasks, such as memory recall or language processing.

Additionally, the integration of machine learning and artificial intelligence in cognitive research has opened new avenues for analyzing large datasets, leading to more nuanced understandings of cognitive patterns and anomalies. This intersection of cognitive psychology and computational modeling has also advanced the development of intelligent systems capable of mimicking human cognitive functions, from language understanding to pattern recognition.

Another significant advancement is in the realm of cognitive enhancement, where research is exploring ways to improve cognitive functions through pharmacological means, cognitive training exercises, and even non-invasive brain stimulation techniques. These studies hold the potential for significant impacts on education, mental health treatment, and the general enhancement of cognitive abilities in healthy individuals.

Ethical Issues Inherent in Cognitive Psychology Research

Cognitive psychology research, while offering vast potential for understanding and enhancing human cognition, also presents several ethical considerations. Issues such as informed consent, privacy, and the potential for misuse of cognitive data are paramount concerns. The use of neuroimaging and other biometric data, for instance, raises questions about the privacy of mental states and the potential for such information to be used in ways that could infringe on individual rights or autonomy.

Additionally, the ethical implications of cognitive enhancement and the potential societal impacts of creating disparities between those who have access to cognitive enhancement technologies and those who do not are areas of ongoing debate. Cognitive psychology researchers must navigate these ethical waters carefully, ensuring that their work promotes the welfare and dignity of all individuals while advancing scientific knowledge.

Future Directions for Research in Cognitive Psychology

The future of cognitive psychology research promises further integration with neuroscience, the application of advanced computational models, and the exploration of how cognitive processes evolve in a rapidly changing digital world. An exciting direction for future research is the investigation of how digital technologies, such as smartphones and social media, are affecting cognitive development, attention spans, and social cognition. Understanding these impacts is crucial for developing strategies to mitigate potential negative effects while harnessing technology’s power to enhance cognitive function.

Another area of future research is the exploration of individual differences in cognition, understanding how genetic, environmental, and cultural factors contribute to the diversity of cognitive processes among individuals. This line of research holds the promise of personalizing educational and therapeutic approaches to cater to individual cognitive profiles.

The Transformative Potential of Research in Cognitive Psychology

Research in cognitive psychology holds transformative potential for numerous aspects of human life, from education and mental health to technology and social interaction. By continuing to explore the intricacies of cognitive processes and their neural underpinnings, cognitive psychology can contribute to a deeper understanding of what it means to be human. The ongoing exploration of cognitive phenomena not only enriches our knowledge of the mind but also translates into practical applications that can improve individual well-being and societal health. As cognitive psychology advances, its research continues to shape our world, demonstrating the enduring power of understanding the human mind.

iResearchNet’s Writing Services

In the intricate and evolving field of cognitive psychology, where the depth and breadth of research topics extend far into the understanding of the human mind, iResearchNet stands as a beacon of support for students embarking on their academic journey. Recognizing the challenges students face in navigating the complex landscape of cognitive psychology research, iResearchNet offers bespoke writing services tailored to meet the unique needs of each research endeavor. Our mission is to facilitate your academic success by providing customized, high-quality research papers that reflect the latest advancements and ethical standards in cognitive psychology.

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Working memory articles from across Nature Portfolio

Working memory is the active and robust retention of multiple bits of information over the time-scale of a few seconds. It is distinguished from short-term memory by the involvement of executive or attentional control that makes the information flexible yet resistant to interference.

Latest Research and Reviews

Dynamic layer-specific processing in the prefrontal cortex during working memory

Layer-specific imaging of the human dorsolateral prefrontal cortex reveals distinct laminar responses to working memory load and dynamic coding of working memory trial phases.

• Jonas Karolis Degutis
• Denis Chaimow
• Romy Lorenz

Correlative comparison of visual working memory paradigms and associated models

• Fatemeh Hojjati
• Ali Motahharynia
• Mehdi Sanayei

Interaction between BDNF Val66Met polymorphism and mismatch negativity for working memory capacity in schizophrenia

• Wenpeng Hou
• Xiangqin Qin
• Chuanyue Wang

Developing a fair and interpretable representation of the clock drawing test for mitigating low education and racial bias

• Jiaqing Zhang
• Sabyasachi Bandyopadhyay
• Parisa Rashidi

Timescales of learning in prefrontal cortex

The prefrontal cortex is critical for working memory, over a timescale of seconds. In this Review, Miller and Constantinidis examine how the prefrontal cortex facilitates the integration of memory systems across other timescales as well. In this framework of prefrontal learning, short-term memory and long-term memory interact to serve goal-directed behaviour.

• Jacob A. Miller
• Christos Constantinidis

Discriminating orientation information with phase consistency in alpha and low-gamma frequency bands: an EEG study

• Alireza Khadir
• Shamim Sasani Ghamsari
• Borhan Beigzadeh

News and Comment

Reply to ‘efficiency and capacity mechanisms can coexist in cognitive training’.

• Claudia C. von Bastian
• Sylvie Belleville
• Tilo Strobach

Efficiency and capacity mechanisms can coexist in cognitive training

• Da-Wei Zhang
• Bruno Sauce

Labels aid visual working memory

• Teresa Schubert

A frequency location to remember

Neuromodulation with specific frequencies at specific brain locations selectively enhances either working memory or long-term memory in older adult humans.

• Jake Rogers

Revisiting mixture models of memory

Probabilistic mixture models have contributed significantly to advancements in visual working memory research in recent decades. In a new paper, Schurgin and colleagues revisit the basic assumptions of mixture models and suggest that we cannot understand memory without first considering perception.

• Blaire Dube
• Julie D. Golomb

Random connections in memory

• Anne-Marike Schiffer

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• In AI Mysteries

Top Machine Learning Research Papers

• by Dr. Nivash Jeevanandam

Advances in machine learning and deep learning research are reshaping our technology. Machine learning and deep learning have accomplished various astounding feats, and key research articles have resulted in technical advances used by billions of people. The research in this sector is advancing at a breakneck pace and assisting you to keep up. Here is a collection of the most important scientific study papers in machine learning.

Rebooting ACGAN: Auxiliary Classifier GANs with Stable Training

The authors of this work examined why ACGAN training becomes unstable as the number of classes in the dataset grows. The researchers revealed that the unstable training occurs due to a gradient explosion problem caused by the unboundedness of the input feature vectors and the classifier’s poor classification capabilities during the early training stage. The researchers presented the Data-to-Data Cross-Entropy loss (D2D-CE) and the Rebooted Auxiliary Classifier Generative Adversarial Network to alleviate the instability and reinforce ACGAN (ReACGAN). Additionally, extensive tests of ReACGAN demonstrate that it is resistant to hyperparameter selection and is compatible with a variety of architectures and differentiable augmentations.

This article is ranked #1 on CIFAR-10 for Conditional Image Generation.

For the research paper, read here .

For code, see here .

Dense Unsupervised Learning for Video Segmentation

The authors presented a straightforward and computationally fast unsupervised strategy for learning dense spacetime representations from unlabeled films in this study. The approach demonstrates rapid convergence of training and a high degree of data efficiency. Furthermore, the researchers obtain VOS accuracy superior to previous results despite employing a fraction of the previously necessary training data. The researchers acknowledge that the research findings may be utilised maliciously, such as for unlawful surveillance, and that they are excited to investigate how this skill might be used to better learn a broader spectrum of invariances by exploiting larger temporal windows in movies with complex (ego-)motion, which is more prone to disocclusions.

This study is ranked #1 on DAVIS 2017 for Unsupervised Video Object Segmentation (val).

Temporally-Consistent Surface Reconstruction using Metrically-Consistent Atlases

The authors offer an atlas-based technique for producing unsupervised temporally consistent surface reconstructions by requiring a point on the canonical shape representation to translate to metrically consistent 3D locations on the reconstructed surfaces. Finally, the researchers envisage a plethora of potential applications for the method. For example, by substituting an image-based loss for the Chamfer distance, one may apply the method to RGB video sequences, which the researchers feel will spur development in video-based 3D reconstruction.

This article is ranked #1 on ANIM in the category of Surface Reconstruction. 

EdgeFlow: Achieving Practical Interactive Segmentation with Edge-Guided Flow

The researchers propose a revolutionary interactive architecture called EdgeFlow that uses user interaction data without resorting to post-processing or iterative optimisation. The suggested technique achieves state-of-the-art performance on common benchmarks due to its coarse-to-fine network design. Additionally, the researchers create an effective interactive segmentation tool that enables the user to improve the segmentation result through flexible options incrementally.

This paper is ranked #1 on Interactive Segmentation on PASCAL VOC

Learning Transferable Visual Models From Natural Language Supervision

The authors of this work examined whether it is possible to transfer the success of task-agnostic web-scale pre-training in natural language processing to another domain. The findings indicate that adopting this formula resulted in the emergence of similar behaviours in the field of computer vision, and the authors examine the social ramifications of this line of research. CLIP models learn to accomplish a range of tasks during pre-training to optimise their training objective. Using natural language prompting, CLIP can then use this task learning to enable zero-shot transfer to many existing datasets. When applied at a large scale, this technique can compete with task-specific supervised models, while there is still much space for improvement.

This research is ranked #1 on Zero-Shot Transfer Image Classification on SUN

CoAtNet: Marrying Convolution and Attention for All Data Sizes

The researchers in this article conduct a thorough examination of the features of convolutions and transformers, resulting in a principled approach for combining them into a new family of models dubbed CoAtNet. Extensive experiments demonstrate that CoAtNet combines the advantages of ConvNets and Transformers, achieving state-of-the-art performance across a range of data sizes and compute budgets. Take note that this article is currently concentrating on ImageNet classification for model construction. However, the researchers believe their approach is relevant to a broader range of applications, such as object detection and semantic segmentation.

This paper is ranked #1 on Image Classification on ImageNet (using extra training data).

SwinIR: Image Restoration Using Swin Transformer

The authors of this article suggest the SwinIR image restoration model, which is based on the Swin Transformer . The model comprises three modules: shallow feature extraction, deep feature extraction, and human-recognition reconstruction. For deep feature extraction, the researchers employ a stack of residual Swin Transformer blocks (RSTB), each formed of Swin Transformer layers, a convolution layer, and a residual connection.

This research article is ranked #1 on Image Super-Resolution on Manga109 – 4x upscaling.

Artificial Replay: A Meta-Algorithm for Harnessing Historical Data in Bandits

Ways to incorporate historical data are still unclear: initialising reward estimates with historical samples can suffer from bogus and imbalanced data coverage, leading to computational and storage issues—particularly in continuous action spaces. The paper addresses the obstacles by proposing ‘Artificial Replay’, an algorithm to incorporate historical data into any arbitrary base bandit algorithm. 

Read the full paper here . 

Bootstrapped Meta-Learning

Author(s) – Sean R. Sinclair et al.

The paper proposes an algorithm in which the meta-learner teaches itself to overcome the meta-optimisation challenge. The algorithm focuses on meta-learning with gradients, which guarantees performance improvements. Furthermore, the paper also looks at how bootstrapping opens up possibilities. 

Read the full paper here .

LaMDA: Language Models for Dialog Applications

Author(s) – Sebastian Flennerhag et al.

The research describes the LaMDA system which caused chaos in AI this summer when a former Google engineer claimed that it had shown signs of sentience. LaMDA is a family of large language models for dialogue applications based on Transformer architecture. The interesting feature of the model is its fine-tuning with human-annotated data and the possibility of consulting external sources. This is a very interesting model family, which we might encounter in many applications we use daily. 

Competition-Level Code Generation with AlphaCode

Author(s) – Yujia Li et al.

Systems can help programmers become more productive. The following research addresses the problems with incorporating innovations in AI into these systems. AlphaCode is a system that creates solutions for problems that require deeper reasoning. 

Privacy for Free: How does Dataset Condensation Help Privacy?

Author(s) – Tian Dong et al.

The paper focuses on Privacy Preserving Machine Learning, specifically deducting the leakage of sensitive data in machine learning. It puts forth one of the first propositions of using dataset condensation techniques to preserve the data efficiency during model training and furnish membership privacy.

Why do tree-based models still outperform deep learning on tabular data?

Author(s) – Léo Grinsztajn, Edouard Oyallon and Gaël Varoquaux

The research answers why deep learning models still find it hard to compete on tabular data compared to tree-based models. It is shown that MLP-like architectures are more sensitive to uninformative features in data compared to their tree-based counterparts. 

Multi-Objective Bayesian Optimisation over High-Dimensional Search Spaces 

Author(s) – Samuel Daulton et al.

The paper proposes ‘MORBO’, a scalable method for multiple-objective BO as it performs better than that of high-dimensional search spaces. MORBO significantly improves the sample efficiency and, where existing BO algorithms fail, MORBO provides improved sample efficiencies over the current approach. 

A Path Towards Autonomous Machine Intelligence Version 0.9.2

Author(s) – Yann LeCun

The research offers a vision about how to progress towards general AI. The study combines several concepts: a configurable predictive world model, behaviour driven through intrinsic motivation, and hierarchical joint embedding architectures trained with self-supervised

learning. 

TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data

Author(s) –  Shreshth Tuli, Giuliano Casale and Nicholas R. Jennings

This is a specialised paper applying transformer architecture to the problem of unsupervised anomaly detection in multivariate time series. Many architectures which were successful in other fields are, at some point, also being applied to time series. The research shows improved performance on some known data sets. 

Differentially Private Bias-Term only Fine-tuning of Foundation Models

Author(s) – Zhiqi Bu et al. 

In the paper, researchers study the problem of differentially private (DP) fine-tuning of large pre-trained models—a recent privacy-preserving approach suitable for solving downstream tasks with sensitive data. Existing work has demonstrated that high accuracy is possible under strong privacy constraints yet requires significant computational overhead or modifications to the network architecture.

ALBERT: A Lite BERT

Usually, increasing model size when pretraining natural language representations often result in improved performance on downstream tasks, but the training times become longer. To address these problems, the authors in their work presented two parameter-reduction techniques to lower memory consumption and increase the training speed of BERT. The authors also used a self-supervised loss that focuses on modelling inter-sentence coherence and consistently helped downstream tasks with multi-sentence inputs. According to results, this model established new state-of-the-art results on the GLUE, RACE, and squad benchmarks while having fewer parameters compared to BERT-large. 

Check the paper here .

Beyond Accuracy: Behavioral Testing of NLP Models with CheckList

Microsoft Research, along with the University of Washington and the University of California, in this paper, introduced a model-agnostic and task agnostic methodology for testing NLP models known as CheckList. This is also the winner of the best paper award at the ACL conference this year. It included a matrix of general linguistic capabilities and test types that facilitate comprehensive test ideation, as well as a software tool to generate a large and diverse number of test cases quickly. 

Linformer is a Transformer architecture for tackling the self-attention bottleneck in Transformers. It reduces self-attention to an O(n) operation in both space- and time complexity. It is a new self-attention mechanism which allows the researchers to compute the contextual mapping in linear time and memory complexity with respect to the sequence length. 

Read more about the paper here .

Plug and Play Language Models

Plug and Play Language Models ( PPLM ) are a combination of pre-trained language models with one or more simple attribute classifiers. This, in turn, assists in text generation without any further training. According to the authors, model samples demonstrated control over sentiment styles, and extensive automated and human-annotated evaluations showed attribute alignment and fluency. 

Reformer 

The researchers at Google, in this paper , introduced Reformer. This work showcased that the architecture of a Transformer can be executed efficiently on long sequences and with small memory. The authors believe that the ability to handle long sequences opens the way for the use of the Reformer on many generative tasks. In addition to generating very long coherent text, the Reformer can bring the power of Transformer models to other domains like time-series forecasting, music, image and video generation. 

An Image is Worth 16X16 Words

The irony here is that one of the popular language models, Transformers have been made to do computer vision tasks. In this paper , the authors claimed that the vision transformer could go toe-to-toe with the state-of-the-art models on image recognition benchmarks, reaching accuracies as high as 88.36% on ImageNet and 94.55% on CIFAR-100. For this, the vision transformer receives input as a one-dimensional sequence of token embeddings. The image is then reshaped into a sequence of flattened 2D patches. The transformers in this work use constant widths through all of its layers.

Unsupervised Learning of Probably Symmetric Deformable 3D Objects

Winner of the CVPR best paper award, in this work, the authors proposed a method to learn 3D deformable object categories from raw single-view images, without external supervision. This method uses an autoencoder that factored each input image into depth, albedo, viewpoint and illumination. The authors showcased that reasoning about illumination can be used to exploit the underlying object symmetry even if the appearance is not symmetric due to shading.

Generative Pretraining from Pixels

In this paper, OpenAI researchers examined whether similar models can learn useful representations for images. For this, the researchers trained a sequence Transformer to auto-regressively predict pixels, without incorporating knowledge of the 2D input structure. Despite training on low-resolution ImageNet without labels, the researchers found that a GPT-2 scale model learns strong image representations as measured by linear probing, fine-tuning, and low-data classification. On CIFAR-10, it achieved 96.3% accuracy with a linear probe, outperforming a supervised Wide ResNet, and 99.0% accuracy with full fine-tuning and matching the top supervised pre-trained models. An even larger model, trained on a mixture of ImageNet and web images, is competitive with self-supervised benchmarks on ImageNet, achieving 72.0% top-1 accuracy on a linear probe of their features.

Deep Reinforcement Learning and its Neuroscientific Implications

In this paper, the authors provided a high-level introduction to deep RL , discussed some of its initial applications to neuroscience, and surveyed its wider implications for research on brain and behaviour and concluded with a list of opportunities for next-stage research. Although DeepRL seems to be promising, the authors wrote that it is still a work in progress and its implications in neuroscience should be looked at as a great opportunity. For instance, deep RL provides an agent-based framework for studying the way that reward shapes representation, and how representation, in turn, shapes learning and decision making — two issues which together span a large swath of what is most central to neuroscience. 

Dopamine-based Reinforcement Learning

Why humans doing certain things are often linked to dopamine , a hormone that acts as the reward system (think: the likes on your Instagram page). So, keeping this fact in hindsight, DeepMind with the help of Harvard labs, analysed dopamine cells in mice and recorded how the mice received rewards while they learned a task. They then checked these recordings for consistency in the activity of the dopamine neurons with standard temporal difference algorithms. This paper proposed an account of dopamine-based reinforcement learning inspired by recent artificial intelligence research on distributional reinforcement learning. The authors hypothesised that the brain represents possible future rewards not as a single mean but as a probability distribution, effectively representing multiple future outcomes simultaneously and in parallel. 

Lottery Tickets In Reinforcement Learning & NLP

In this paper, the authors bridged natural language processing (NLP) and reinforcement learning (RL). They examined both recurrent LSTM models and large-scale Transformer models for NLP and discrete-action space tasks for RL. The results suggested that the lottery ticket hypothesis is not restricted to supervised learning of natural images, but rather represents a broader phenomenon in deep neural networks.

What Can Learned Intrinsic Rewards Capture

In this paper, the authors explored if the reward function itself can be a good locus of learned knowledge. They proposed a scalable framework for learning useful intrinsic reward functions across multiple lifetimes of experience and showed that it is feasible to learn and capture knowledge about long-term exploration and exploitation into a reward function. 

AutoML- Zero

The progress of AutoML has largely focused on the architecture of neural networks, where it has relied on sophisticated expert-designed layers as building blocks, or similarly restrictive search spaces. In this paper , the authors showed that AutoML could go further with AutoML Zero, that automatically discovers complete machine learning algorithms just using basic mathematical operations as building blocks. The researchers demonstrated this by introducing a novel framework that significantly reduced human bias through a generic search space.

Rethinking Batch Normalization for Meta-Learning

Batch normalization is an essential component of meta-learning pipelines. However, there are several challenges. So, in this paper, the authors evaluated a range of approaches to batch normalization for meta-learning scenarios and developed a novel approach — TaskNorm. Experiments demonstrated that the choice of batch normalization has a dramatic effect on both classification accuracy and training time for both gradient-based and gradient-free meta-learning approaches. The TaskNorm has been found to be consistently improving the performance.

Meta-Learning without Memorisation

Meta-learning algorithms need meta-training tasks to be mutually exclusive, such that no single model can solve all of the tasks at once. In this paper, the authors designed a meta-regularisation objective using information theory that successfully uses data from non-mutually-exclusive tasks to efficiently adapt to novel tasks.

Understanding the Effectiveness of MAML

Model Agnostic Meta-Learning (MAML) consists of optimisation loops, from which the inner loop can efficiently learn new tasks. In this paper, the authors demonstrated that feature reuse is the dominant factor and led to ANIL (Almost No Inner Loop) algorithm — a simplification of MAML where the inner loop is removed for all but the (task-specific) head of the underlying neural network. 

Your Classifier is Secretly an Energy-Based Model

This paper proposed attempts to reinterpret a standard discriminative classifier as an energy-based model. In this setting, wrote the authors, the standard class probabilities can be easily computed. They demonstrated that energy-based training of the joint distribution improves calibration, robustness, handout-of-distribution detection while also enabling the proposed model to generate samples rivalling the quality of recent GAN approaches. This work improves upon the recently proposed techniques for scaling up the training of energy-based models. It has also been the first to achieve performance rivalling the state-of-the-art in both generative and discriminative learning within one hybrid model.

Reverse-Engineering Deep ReLU Networks

This paper investigated the commonly assumed notion that neural networks cannot be recovered from its outputs, as they depend on its parameters in a highly nonlinear way. The authors claimed that by observing only its output, one could identify the architecture, weights, and biases of an unknown deep ReLU network. By dissecting the set of region boundaries into components associated with particular neurons, the researchers showed that it is possible to recover the weights of neurons and their arrangement within the network.

Cricket Analytics and Predictor

Authors: Suyash Mahajan,  Salma Shaikh, Jash Vora, Gunjan Kandhari,  Rutuja Pawar,

Abstract:   The paper embark on predicting the outcomes of Indian Premier League (IPL) cricket match using a supervised learning approach from a team composition perspective. The study suggests that the relative team strength between the competing teams forms a distinctive feature for predicting the winner. Modeling the team strength boils down to modeling individual player‘s batting and bowling performances, forming the basis of our approach.

Research Methodology: In this paper, two methodologies have been used. MySQL database is used for storing data whereas Java for the GUI. The algorithm used is Clustering Algorithm for prediction. The steps followed are as

• Begin with a decision on the value of k being the number of clusters.
• Put any initial partition that classifies the data into k clusters.
• Take every sample in the sequence; compute its distance from centroid of each of the clusters. If sample is not in the cluster with the closest centroid currently, switch this sample to that cluster and update the centroid of the cluster accepting the new sample and the cluster losing the sample.

For the research paper, read here

2.Real Time Sleep / Drowsiness Detection – Project Report

Author : Roshan Tavhare

Institute : University of Mumbai

Abstract : The main idea behind this project is to develop a nonintrusive system which can detect fatigue of any human and can issue a timely warning. Drivers who do not take regular breaks when driving long distances run a high risk of becoming drowsy a state which they often fail to recognize early enough.

Research Methodology : A training set of labeled facial landmarks on an image. These images are manually labeled, specifying specific (x, y) -coordinates of regions surrounding each facial structure.

• Priors, more specifically, the probability on distance between pairs of input pixels. The pre-trained facial landmark detector inside the dlib library is used to estimate the location of 68 (x, y)-coordinates that map to facial structures on the face.

A Study of Various Text Augmentation Techniques for Relation Classification in Free Text

Authors: Chinmaya Mishra Praveen Kumar and Reddy Kumar Moda,  Syed Saqib Bukhari and Andreas Dengel

Institute: German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany

Abstract: In this paper, the researchers explore various text data augmentation techniques in text space and word embedding space. They studied the effect of various augmented datasets on the efficiency of different deep learning models for relation classification in text.

Research Methodology: The researchers implemented five text data augmentation techniques (Similar word, synonyms, interpolation, extrapolation and random noise method)  and explored the ways in which we could preserve the grammatical and the contextual structures of the sentences while generating new sentences automatically using data augmentation techniques.

Smart Health Monitoring and Management Using Internet of Things, Artificial Intelligence with Cloud Based Processing

Author : Prateek Kaushik

Institute : G D Goenka University, Gurugram

Abstract : This research paper described a personalised smart health monitoring device using wireless sensors and the latest technology.

Research Methodology: Machine learning and Deep Learning techniques are discussed which works as a catalyst to improve the  performance of any health monitor system such supervised machine learning algorithms, unsupervised machine learning algorithms, auto-encoder, convolutional neural network and restricted boltzmann machine .

Internet of Things with BIG DATA Analytics -A Survey

Author : A.Pavithra,  C.Anandhakumar and V.Nithin Meenashisundharam

Institute : Sree Saraswathi Thyagaraja College,

Abstract : This article we discuss about Big data on IoT and how it is interrelated to each other along with the necessity of implementing Big data with IoT and its benefits, job market

Research Methodology : Machine learning, Deep Learning, and Artificial Intelligence are key technologies that are used to provide value-added applications along with IoT and big data in addition to being used in a stand-alone mod.

Single Headed Attention RNN: Stop Thinking With Your Head 

Author: Stephen Merity

In this work of art, the Harvard grad author, Stephen “Smerity” Merity, investigated the current state of NLP, the models being used and other alternate approaches. In this process, he tears down the conventional methods from top to bottom, including etymology.

The author also voices the need for a Moore’s Law for machine learning that encourages a minicomputer future while also announcing his plans on rebuilding the codebase from the ground up both as an educational tool for others and as a strong platform for future work in academia and industry.

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

Authors: Mingxing Tan and Quoc V. Le 

In this work, the authors propose a compound scaling method that tells when to increase or decrease depth, height and resolution of a certain network.

Convolutional Neural Networks(CNNs) are at the heart of many machine vision applications. 

EfficientNets are believed to superpass state-of-the-art accuracy with up to 10x better efficiency (smaller and faster).

Deep Double Descent By OpenAI

Authors: Mikhail Belkin, Daniel Hsu, Siyuan Ma, Soumik Mandal

In this paper , an attempt has been made to reconcile classical understanding and modern practice within a unified performance curve. 

The “double descent” curve overtakes the classic U-shaped bias-variance trade-off curve by showing how increasing model capacity beyond the point of interpolation results in improved performance. 

The Lottery Ticket Hypothesis

Authors: Jonathan Frankle, Michael Carbin

Neural network pruning techniques can reduce the parameter counts of trained networks by over 90%, decreasing storage requirements and improving computational performance of inference without compromising accuracy. 

The authors find that a standard pruning technique naturally uncovers subnetworks whose initializations made them capable of training effectively. Based on these results, they introduce the “lottery ticket hypothesis:”

On The Measure Of Intelligence 

Authors: Francois Chollet

This work summarizes and critically assesses the definitions of intelligence and evaluation approaches, while making apparent the historical conceptions of intelligence that have implicitly guided them.

The author, also the creator of keras, introduces a formal definition of intelligence based on Algorithmic Information Theory and using this definition, he also proposes a set of guidelines for what a general AI benchmark should look like. 

Zero-Shot Word Sense Disambiguation Using Sense Definition Embeddings via IISc Bangalore & CMU

Authors: Sawan Kumar, Sharmistha Jat, Karan Saxena and Partha Talukdar

Word Sense Disambiguation (WSD) is a longstanding  but open problem in Natural Language Processing (NLP).  Current supervised WSD methods treat senses as discrete labels  and also resort to predicting the Most-Frequent-Sense (MFS) for words unseen  during training.

The researchers from IISc Bangalore in collaboration with Carnegie Mellon University propose  Extended WSD Incorporating Sense Embeddings (EWISE), a supervised model to perform WSD  by predicting over a continuous sense embedding space as opposed to a discrete label space.

Deep Equilibrium Models 

Authors: Shaojie Bai, J. Zico Kolter and Vladlen Koltun 

Motivated by the observation that the hidden layers of many existing deep sequence models converge towards some fixed point, the researchers at Carnegie Mellon University present a new approach to modeling sequential data through deep equilibrium model (DEQ) models. 

Using this approach, training and prediction in these networks require only constant memory, regardless of the effective “depth” of the network.

IMAGENET-Trained CNNs are Biased Towards Texture

Authors: Robert G, Patricia R, Claudio M, Matthias Bethge, Felix A. W and Wieland B

Convolutional Neural Networks (CNNs) are commonly thought to recognise objects by learning increasingly complex representations of object shapes. The authors in this paper , evaluate CNNs and human observers on images with a texture-shape cue conflict. They show that ImageNet-trained CNNs are strongly biased towards recognising textures rather than shapes, which is in stark contrast to human behavioural evidence.

A Geometric Perspective on Optimal Representations for Reinforcement Learning 

Authors: Marc G. B , Will D , Robert D , Adrien A T , Pablo S C , Nicolas Le R , Dale S, Tor L, Clare L

The authors propose a new perspective on representation learning in reinforcement learning

based on geometric properties of the space of value functions. This work shows that adversarial value functions exhibit interesting structure, and are good auxiliary tasks when learning a representation of an environment. The authors believe this work to open up the possibility of automatically generating auxiliary tasks in deep reinforcement learning.

Weight Agnostic Neural Networks 

Authors: Adam Gaier & David Ha

In this work , the authors explore whether neural network architectures alone, without learning any weight parameters, can encode solutions for a given task. In this paper, they propose a search method for neural network architectures that can already perform a task without any explicit weight training. 

Stand-Alone Self-Attention in Vision Models 

Authors: Prajit Ramachandran, Niki P, Ashish Vaswani,Irwan Bello Anselm Levskaya, Jonathon S

In this work, the Google researchers verified that content-based interactions can serve the vision models . The proposed stand-alone local self-attention layer achieves competitive predictive performance on ImageNet classification and COCO object detection tasks while requiring fewer parameters and floating-point operations than the corresponding convolution baselines. Results show that attention is especially effective in the later parts of the network. 

High-Fidelity Image Generation With Fewer Labels 

Authors: Mario Lucic, Michael Tschannen, Marvin Ritter, Xiaohua Z, Olivier B and Sylvain Gelly 

Modern-day models can produce high quality, close to reality when fed with a vast quantity of labelled data. To solve this large data dependency, researchers from Google released this work , to demonstrate how one can benefit from recent work on self- and semi-supervised learning to outperform the state of the art on both unsupervised ImageNet synthesis, as well as in the conditional setting.

The proposed approach is able to match the sample quality of the current state-of-the-art conditional model BigGAN on ImageNet using only 10% of the labels and outperform it using 20% of the labels.

ALBERT: A Lite BERT for Self-Supervised Learning of Language Representations

Authors: Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin G, Piyush Sharma and Radu S

The authors present two parameter-reduction techniques to lower memory consumption and increase the training speed of BERT and to address the challenges posed by increasing model size and GPU/TPU memory limitations, longer training times, and unexpected model degradation

As a result, this proposed model establishes new state-of-the-art results on the GLUE, RACE, and SQuAD benchmarks while having fewer parameters compared to BERT-large.

GauGANs-Semantic Image Synthesis with Spatially-Adaptive Normalization 

Author: Taesung Park, Ming-Yu Liu, Ting-Chun Wang and Jun-Yan Zhu

Nvidia in collaboration with UC Berkeley and MIT proposed a model which has a spatially-adaptive normalization layer for synthesizing photorealistic images given an input semantic layout.

This model retained visual fidelity and alignment with challenging input layouts while allowing the user to control both semantic and style.

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• v.15(2); 2014 Dec

Evidence-Based Strategies to Improve Memory and Learning

Review of:  Make It Stick: The Science of Successful Learning;  Peter C. Brown, Henry L. Roediger, III, Mark A. McDaniel ; (  2014).  Belknap Press,  Cambridge, MA.  336 pages. 

At some point you’ve likely heard a student in your introductory science course complain, “I don’t understand what went wrong…I studied a lot for this test, knew all the material, and still got a poor grade on the exam.” While talking with the student, you learn that his studying consisted of hours of reading, rereading, and highlighting the text and class notes a few days before the exam. How do we mentor this student to develop study habits that promote deep, long-lasting conceptual learning rather than surface-level, short-term memorization?

In the book Make it Stick: The Science of Successful Learning, authors Henry Roediger and Mark McDaniel, cognitive scientists specializing in the study of learning and memory, together with novelist Peter Brown, tell engaging stories of how people learn in a way that allows them to successfully apply their knowledge and skills. At the same time, they aptly introduce the scientific evidence for highly-effective learning strategies.

Throughout the book, the authors describe how some commonly-used study strategies are unproductive in the long term and suggest alternative, research-based learning strategies. For example, the student described above used massed practice to cram for an exam by rereading the text soon after the first reading. This gives one the impression of mastery of a subject because the text becomes familiar. In contrast, research indicates that this study method involves short-term memory rather than deep learning. A more beneficial study strategy that is supported by research is retrieval practice, which involves recalling information from memory. To implement this strategy, while reading a text, a student should describe main ideas in his own words, frequently ask questions about what was just read, self-quiz, and attempt to connect new ideas with what was learned previously. Although this recommended approach seems unproductive to the student because it is slower and requires more effort, retrieval practice that is spaced and interleaved (mixed with other topics) involves some forgetting, and the increased cognitive effort required to re-learn leads to higher levels of conceptual learning and application. Teachers can promote retrieval practice by asking questions during class and by implementing frequent announced quizzes. Moreover, if the quizzes are cumulative and include corrective feedback, students will be motivated to continually retrieve previous course concepts, helping with memory.

In addition to intertwining personal stories with relevant research on memory and learning, the authors provide a brief “takeaway” section of key ideas at the conclusion of each chapter as well as notes about the empirical research and references for further reading at the end of the book. The final chapter includes descriptions of instructors who find improvements in student learning from implementing the evidence-based learning strategies in the book, as well as a useful summary of learning tips for students, life-long learners (all of us), teachers, and trainers. For example, the authors recommend that teachers explain to students how people learn, teach students how to study, use frequent announced low-stakes quizzes and practice exercises that include both new and previously covered concepts, and include opportunities for reflection. In addition to clear benefits to the students, these strategies benefit the teacher as students display improved attendance, better class preparation, and improved attention during class. Furthermore, frequent quizzes provide valuable feedback on student performance for the teacher to adjust instruction. Make it Stick is an excellent book on learning and memory, and I recommend it for both teachers and students who want to better understand how learning occurs and how to study effectively.