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What is cognitive psychology (a definition)​, why is cognitive psychology important​.

• Psychotherapy: Cognitive psychology led to the development of cognitive behavior therapy , one of the most widely used types of therapy used today. It uses a combination of behavioral and cognitive techniques focusing on examining and modifying our unhelpful thought processes and behaviors (Gaudiano, 2008).  
• Education: Because of its focus on learning, attention, and memory, cognitive psychology has made important contributions to education. For example, research shows that teachers should present information in a way that creates meaning by connecting it to existing knowledge, thus making it easier to remember (Regehr & Normal, 1996).
• Decision-making: We make decisions according to our perceptions, attention, and memory—all subjects that cognitive psychology studies. Cognitive psychology has also made significant contributions to understanding how and why we use biases (stereotyping) and heuristics (simple rules of thumb) in decision-making. Understanding our use of biases and heuristics helps us develop strategies to overcome them and make more informed decisions. This has practical applications in relationships, business, law, economics, and public policy. 
• Artificial Intelligence (AI): Studying our mental processes allows researchers to design AI systems that mimic human intelligence which makes them better at interacting with people. To create even more effective AI, researchers also aim to recreate the way humans process subjective mental experiences like emotion  (Zhao et al., 2022). In addition, discoveries from cognitive psychology help researchers create more intuitive interfaces that align with our cognitive capabilities.  ​

History of Cognitive Psychology

• In 1870, German psychologist Wilhelm Wundt was the first to approach psychology as a science.  Before then, the mind was considered from a philosophical standpoint. Wundt attempted to investigate the mind through introspection , by systematically observing conscious experiences, the same way scientists in other fields observe things in the world (Braisby & Galletly, 2012). By observing patterns in reported experiences, researchers believed they were able to determine what was going on in the mind. 
• Edward Titchener, a student of Wundt, developed this further by introducing the concept of structuralism. Structuralism attempts to break our experiences down into basic elements to analyze them. Titchener divided experiences into sensations (sights, sounds, tastes), images (thoughts, ideas), and affections (emotions).
• Behaviorism Dominance: From the 1920s to the 1950s, behaviorism (or behavioral psychology ) was the dominant approach to studying behavior. This theory arose out of the criticism that introspection wasn’t scientific enough because the inner workings of the mind couldn’t be observed. By contrast, behaviorism focused on observable behavior. It claims that all behavior can be explained by examining positive reinforcements (rewards) and punishments. Thoughts, memories, and emotions were deemed “unscientific”. 
• Cognitive Revolution: In the 1950s and 60s, researchers returned to studying mental processes. This came about for several reasons. First, while behaviorism does a good job of describing behavior, it’s not so good at explaining it. Also, behaviorism was criticized because it didn’t explain complex cognitive processes and subjective experiences. Another major influencer that sparked the return to cognitive theory was renowned linguist Noam Chomsky. He argued that language acquisition couldn’t be explained only with behaviorist concepts and that much of it is innate rather than learned. 
• Mind as Computer: The development of computer science in the 1960s and 70s contributed to seeing the human mind as an information processing system and comparing it to a computer. This is often referred to as the Computational Theory of Mind (CTM). Just like a computer, the mind has inputs (through the senses), software or algorithms (the mind), hardware and memory (the brain), and outputs (behaviors).
• Cognitive Neuroscience: Starting in the 1980s, the use of brain imaging techniques such as magnetic resonance imaging (MRI) allowed researchers to combine cognitive psychology with neuroscience . This technology allows researchers to observe the brain during cognitive processes. This led to the new field of cognitive neuroscience that explores the relationship of our mental processes with brain activity. 
• Contemporary Subfields: Cognitive psychology continues to evolve and has recently led to several subfields. These include attention, perception, memory, language, decision-making, and problem-solving. We’ll dive into some of these later on.

Cognitive Psychology Theories

• Cognitive Load Theory (CLT): This theory is about the relationship between working memory and long-term memory. It states that working memory has a limited capacity and once that capacity has been reached, we become overloaded and learning suffers. Things that make us feel overloaded include information complexity, irrelevant information that is distracting, and efforting to connect new information to things we already know. This theory has important implications for education and for presenting new information effectively (Bannert, 2002).
• Cognitive Development: Developed by Jean Piaget in 1955, cognitive development theory says that children go through several stages (and sub-stages) as their thinking processes develop. Cognitive development theories attempt to explain the mechanisms driving how and why children’s thinking and perceiving change as they grow and mature. Many preschool and primary school programs are based on this model.
• Information Processing Theory : This theory describes our mind as a computer. It sees the brain as a processor that takes inputs (from senses, attention, and memory) and produces outputs (behaviors) like a computer. 
• Theory of Mind : This is the ability to infer what is going on in someone else’s mind, the ability to understand that someone else has different desires and emotions from yourself. This helps us to understand and predict others’ behavior.
• Dual Process Theory: This theory says that we have two different systems of thought. One is quick, unconscious, intuitive, and based on associations and emotions. The other is slow, thoughtful, conscious , and based on reason (Gronchi & Giovannelli, 2018). This theory explains how we can make decisions based on both fast, instinctive thinking and slower, deliberative reason.  ​

Cognitive Psychology Concepts

• Cognitive Development: Our cognitive abilities develop and change throughout childhood, going through different stages.
• Mental Models or Schemas: This refers to how we create mental frameworks or representations of the world to understand and interact with our environment. They serve as filters through which we perceive and interpret information, influencing our thoughts, actions, and decisions. Mental models are usually subconscious  and automatic. 
• Cognitive Biases: We are all vulnerable to systematic errors in thinking when interpreting information. We tend to oversimplify things, using generalizations and stereotypes, so we can process a lot of information quickly and easily.
• Heuristics: Related to biases, heuristics are “rules of thumb”, shortcuts that allow us to make quick, although sometimes poor decisions.

Cognitive Psychology Approach​

• The experimental approach focuses on behavioral data gained through structured experiments. I’ll describe some experiments next.
• The computational psychology approach uses computer and mathematical models that are designed to mimic human behavior in cognitive tasks.
• Cognitive neuroscience looks at brain measurements and how they relate to thinking and perceiving.

Examples of Cognitive Psychology Research

• False memory formation: A study from 1974 showed that our memory is affected by the way a question is asked. Participants were shown a video of a car accident and then asked questions about what happened, like how fast the cars were going. When asked “How fast were the cars going when they smashed into each other?” they gave consistently higher speed estimates than when another word was used instead of smashed, such as hit, contacted, or collided. Also, when the word “smashed” was used, more people answered “yes” to the question “Was there broken glass?” even though there wasn’t any (Loftus & Palmer, 1974).
• Biases and heuristics: A lot of research has been done on how and why our minds use biases, or stereotypes, and heuristics which are mental shortcuts. Some of the first research was done in 1974 by Tversky and Kahneman. They found that we use mental shortcuts or “rules of thumb” to make decisions easier when information is limited or when situations are complex. The same goes for biases. When we don’t have the time or the information required to make a judgment about someone, we tend to use biases. Both biases and heuristics can lead to wrong conclusions and poor decisions (Tversky & Kahneman, 1974).
• Dual-Task Performance: Have you ever felt like you missed parts of a lecture while taking notes? A study performed in 1994 gave participants two simple tasks to perform at the same time. Something like reading and watching a visual display. Unsurprisingly, performance was worse when doing both tasks as compared to doing each task individually (Pashler, 1994). This has implications for divided attention. (Ahem…texting and driving.)
• Task Switching: Similar to the above, a 2003 study looked at the cognitive processes involved in switching between tasks. Results indicate that our responses are slower and more prone to errors after switching tasks (Monsell, 2003). I definitely feel a delay in my ability to focus right after changing tasks. This has some important implications considering how often we switch between tasks every day. (Popping back and forth between computer work to email to chat to phone to interacting with people around you, etc…).
• The Stroop Effect: This classic study looked at the interference between automatic and controlled, conscious brain processes. Study participants were shown color words that were printed in a color different from the word. For example, the word “red” is printed in blue ink. Participants were instructed to name the color of the ink, rather than reading the word, and reaction times were measured. It’s harder than it sounds! Reaction times were slower and participants were more error-prone (MacLeod, 2015). This is because it’s difficult to “turn off” the unconscious impulse to read the word. You can try out the Stroop experiment here .
• The Incubation Effect: Have you ever had this experience? You’re struggling to figure out a problem, so you take a break and do something completely different, like go for a walk or listen to music. Then you come back to the problem, and the answer just comes to you. This is called the “incubation effect”. Studies show that we are more likely to solve problems when we have this incubation period (Smith & Blankenship, 1989). Researchers believe this is because the unconscious mind continues to make connections and process information when the conscious mind is focused on something else. This suggests that allowing the mind to wander can sometimes lead to unexpected insights.

Cognitive Psychology and Attention

Cognitive psychology and memory, cognitive psychology and perception.

Cognitive Psychology & Neuroscience

Cognitive Psychology Strengths and Weaknesses

• Scientific approach: Cognitive psychology is grounded in the scientific method and uses rigorous research methods to study mental processes. This approach allows for the development of reliable theories and the testing of hypotheses.
• Clinical experiments: Connected to the scientific approach, cognitive psychology uses controlled laboratory experiments which give researchers a high level of control which means that measurements and results are more reliable.
• Practical applications: It has many practical applications, some of which were described above. For example, it has led to improvements in psychotherapy, education, and technology design. Understanding our cognitive processes has helped us learn how to improve memory, problem-solving, and decision-making.
• Effective for treating anxiety: Treating anxiety is one of cognitive psychology’s most widely used practical applications. Anxiety is one of the leading mental health issues today, affecting about 18% of U.S. adults. Cognitive-behavioral therapy has shown to be an effective treatment for many (APA, 2016).
• Too much control? Although the control in a laboratory experiment gives precise results, it may not apply to “real-life” situations where there are many outside variables that affect our thinking and behavior. 
• Reductionism: Researchers tend to reduce complex cognitive processes into small components and study them individually. This may overlook the holistic nature of how the mind works, potentially missing how the different processes connect and work together. The mind is complicated!
• Limited ability to observe: Since mental processes are internal and subjective, researchers are unable to directly observe what is going on in someone’s mind. They rely on self-reports of research participants which can be unreliable (Alahmad, 2020). However, this is getting better with more advanced brain imaging devices.
• Neglects some influences: Cognitive psychology often doesn’t take into account some influences on behavior such as social, cultural, and educational factors (Alahmad, 2020). These factors can also affect how you think and process information.

Video: What is Cognitive Psychology:

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Final Thoughts on Cognitive Psychology​

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• Alahmad, M. (2020). Strengths and weaknesses of cognitive theory. ​ Budapest International Research and Critics Institute-Journal , 3 (3), 1584-1593.
• APA. (2016). Beyond worry: How psychologists help with anxiety disorders . American Psychological Association. 
• American Psychological Association. (2023). Apa Dictionary of Psychology . American Psychological Association. https://dictionary.apa.org/perception
• Baddeley, A. (1988). Cognitive psychology and human memory. Trends in neurosciences , 11 (4), 176-181.
• Bannert, M. (2002). Managing cognitive load—recent trends in cognitive load theory. Learning and instruction , 12 (1), 139-146.
• Bassett, D. S., & Gazzaniga, M. S. (2011). Understanding complexity in the human brain. Trends in cognitive sciences , 15 (5), 200-209.
• Braisby, N., & Gellatly, A. (Eds.). (2012). Cognitive psychology . Oxford University Press.
• Forstmann, B. U., Wagenmakers, E. J., Eichele, T., Brown, S., & Serences, J. T. (2011). Reciprocal relations between cognitive neuroscience and formal cognitive models: opposites attract? . Trends in cognitive sciences , 15 (6), 272-279. ​
• Gaudiano, B. A. (2008). Cognitive-behavioural therapies: achievements and challenges. BMJ Ment Health , 11 (1), 5-7.
• Gronchi, G., & Giovannelli, F. (2018). Dual process theory of thought and default mode network: A possible neural foundation of fast thinking. Frontiers in psychology , 9 , 1237
• Lachter, J., Forster, K. I., & Ruthruff, E. (2004). Forty-five years after Broadbent (1958): still no identification without attention. Psychological review , 111 (4), 880.
• MacLeod, C. M. (2015). The stroop effect. Encyclopedia of color science and technology , 1-6.
• Loftus, E. F., & Palmer, J. C. (1974). Reconstruction of automobile destruction: An example of the interaction between language and memory. Journal of verbal learning and verbal behavior , 13 (5), 585-589.
• Monsell, S. (2003). Task switching. Trends in cognitive sciences , 7 (3), 134-140.
• Pashler, H. (1994). Dual-task interference in simple tasks: data and theory. Psychological bulletin , 116 (2), 220.
• Regehr, G., & Norman, G. R. (1996). Issues in cognitive psychology: implications for professional education. Academic Medicine , 71 (9), 988-1001
• Smith, S. M., & Blankenship, S. E. (1989). Incubation effects. Bulletin of the Psychonomic Society , 27 (4), 311-314.
• Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and Biases. Science , 185 (4157), 1124–1131. https://doi.org/10.1126/science.185.4157.1124  ​
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What Is the Cognitive Psychology Approach? 12 Key Theories

Maintaining focus on the oncoming traffic is paramount, yet I am barely aware of the seagulls flying overhead.

These noisy birds only receive attention when I am safely walking up the other side of the road, their cries reminding me of childhood seaside vacations.

Cognitive psychology focuses on the internal mental processes needed to make sense of the environment and decide on the next appropriate action (Eysenck & Keane, 2015).

This article explores the cognitive psychology approach, its origins, and several theories and models involved in cognition.

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This Article Contains:

What is the cognitive psychology approach, a brief history of cognitive psychology, cognitive psychology vs behaviorism, 12 key theories, concepts, and models, fascinating research experiments, a look at positive cognitive psychology, interesting resources from positivepsychology.com, a take-home message.

The upsurge of research into the mysteries of the human brain and mind has been considerable in recent decades, with recognition of the importance of cognitive process in clinical psychology and social psychology  (Eysenck & Keane, 2015).

As a result, cognitive psychology has profoundly affected the field of psychology and our understanding of what it is to be human.

Perhaps more surprisingly, it has had such an effect without clear boundaries, an integrated set of assumptions and concepts, or a recognizable spokesperson (Gross, 2020).

So, what exactly is the cognitive psychology approach?

Cognitive psychology attempts to understand human cognition by focusing on what appear to be cognitive tasks that require little effort (Goldstein, 2011).

Let’s return to our example of walking down the road. Imagine now that we are also taking a call. We’re now combining several concurrent cognitive tasks:

• Perceiving the environment Distinguishing cars from traffic signals and discerning their direction and speed on the road as well as the people ahead standing, talking, and blocking the sidewalk.
• Paying attention Attending to what our partner is asking us on the phone, above the traffic noise.
• Visualizing Forming a mental image of items in the house, responding to the question, “Where did you leave your car keys?”
• Comprehending and producing language Understanding the real question (“I need to take the car. Where are your keys?”) from what is said and formulating a suitable reply.
• Problem-solving Working out how to get to the next appointment without the car.
• Decision-making Concluding that the timing of one meeting will not work and choosing to push it to another day.

While cognitive psychologists initially focused firmly on an analogy comparing the mind to a computer, their understanding has moved on.

There are currently four approaches, often overlapping and frequently combined, that science uses to understand human cognition (Eysenck & Keane, 2015):

• Cognitive psychology The attempt to “understand human cognition by using behavioral evidence” (Eysenck & Keane, 2015, p. 2).
• Cognitive neuropsychology Understanding ‘normal’ cognition through the study of patients living with a brain injury.
• Cognitive neuroscience Combining evidence from the brain with behavior to form a more complete picture of cognition.
• Computational cognitive science Using computational models to understand and test our understanding of human cognition.

Cognitive psychology plays a massive and essential role in understanding human cognition and is stronger because of its close relationships and interdependencies with other academic disciplines (Eysenck & Keane, 2015).

In 1868, a Dutch physiologist, Franciscus Donders, began to measure reaction time – something we would now see as an experiment in cognitive psychology (Goldstein, 2011).

Donders recognized that mental responses could not be measured directly but could be inferred from behavior. Not long after, Hermann Ebbinghaus began examining the nature and inner workings of human memory using nonsense syllables (Goldstein, 2011).

By the late 1800s, Wilhelm Wundt had set up the first laboratory dedicated to studying the mind scientifically. His approach became known as structuralism . His bold aim was to build a periodic table of the mind , containing all the sensations involved in creating any experience (Goldstein, 2011).

However, the use of analytical introspection to uncover hidden mental processes was gradually dropped when John Watson proposed a new psychological approach that became known as behaviorism (Goldstein, 2011).

Watson rejected the introspective approach and instead focused on observable behavior. His idea of classical conditioning – the connection of a new stimulus with a previously neutral one – was later surpassed by B. F. Skinner’s idea of operant conditioning , which focused on positive reinforcement (Goldstein, 2011).

Both theories sought to understand the relationship between stimulus and response rather than the mind’s inner workings (Goldstein, 2011).

Prompted by a scathing attack by linguist and cognitive scientist Noam Chomsky, by the 1950s behaviorism as the dominant psychological discipline was in decline. The introduction of the digital computer led to the information-processing approach , inspiring psychologists to think of the mind in terms of a sequence of processing stages (Goldstein, 2011).

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Moore (1996) recognized the tensions of the paradigm shift from behaviorism to cognitive psychology.

While research into cognitive psychology, cognitive neuropsychology, cognitive neuroscience , and computational cognitive science is now widely accepted as the driving force behind understanding mental processes (such as memory, perception, problem-solving, and attention), this was not always the case (Gross, 2020).

Moore (1996) highlighted the relationship between behaviorism and the relatively new field of cognitive psychology, and the sometimes mistaken assumptions regarding the nature of the former approach:

• Behaviorism is typically only associated with studying publicly observable behavior. Unlike behaviorism, cognitive psychology is viewed as free of the restrictions of logical positivism, which rely on verification through observation.

Since then, modern cognitive psychology has incorporated findings from many other disciplines, including evolutionary psychology , computer science, artificial intelligence , and neuroscience (Eysenck & Keane, 2015).

• Unlike behaviorism, cognitive psychology is theoretical and explanatory. Behaviorism is often considered merely descriptive, while cognitive psychology is seen as being able to explain what is behind behavior.

Particular ongoing advances in cognitive psychology include perception, language comprehension and production, and problem-solving (Eysenck & Keane, 2015).

• Behaviorism cannot incorporate theoretical terms. While challenged by some behaviorists at the time, it was argued that behaviorism could not incorporate theoretical terms unless related to directly observable behavior.

At the time, cognitive psychologists also argued that it was wrong of behaviorists to interpret mental states in terms of brain states.

Neuroscience advances, such as new imaging techniques like functional MRI, continue to offer fresh insights into the relationship between the brain and mental states (Eysenck & Keane, 2015).

Clearly, the relationship between behaviorism and the developing field of cognitive psychology has been complex. However, cognitive psychology has grown into a school of thought that has led to significant advances in understanding cognition, especially when teamed up with other developments in computing and neuroscience.

This may not have been possible without the shift in the dominant schools of thought in psychology (Gross, 2020; Goldstein, 2011; Eysenck & Keane, 2015).

And while it is beyond the scope of this article to cover the full breadth or depth of the areas of research, we list several of the most important and fascinating specialties and theories below.

It is hardly possible to imagine a world in which attention doesn’t play an essential role in how we interact with the environment, and yet, we rarely give it a thought.

According to cognitive psychology, attention is most active when driven by an individual’s expectations or goals, known as top-down processing . On the other hand, it is more passive when controlled by external stimuli, such as a loud noise, referred to as bottom-up processing (Eysenck & Keane, 2015).

A further distinction exists between focused attention (selective) and divided attention . Research into the former explores how we are able to focus on one item (noise, image, etc.) when there are several. In contrast, the latter looks at how we can maintain attention on two or more stimuli simultaneously.

Donald Broadbent proposed the bottleneck model to explain how we can attend to just one message when several are presented, for example, in dichotic listening experiments, where different auditory stimuli are presented to each ear. Broadbent’s model suggests multiple processing stages, each one progressively restricting the information flow (Goldstein, 2011).

As with all other areas of cognition, perception is far more complicated than we might first imagine. Take, for example, vision. While a great deal of research has “involved presenting a visual stimulus and assessing aspects of its processing,” there is also the time aspect to consider (Eysenck & Keane, 2015, p. 121).

We need to not only perceive objects, but also make sense of their movement and detect changes in the visual environment over time (Eysenck & Keane, 2015).

Research suggests perception, like attention, combines bottom-up and top-down processing. Bottom-up processing involves neurons that fire in response to specific elements of an image – perhaps aspects of a face, nose, eyebrows, jawline, etc. Top-down processing considers how the knowledge someone brings with them affects their perception.

Bottom-down processing helps explain why two people, presented with the same stimuli, experience different perceptions as a result of their expectations and prior knowledge (Goldstein, 2011).

Combining bottom-up and top-down processing also enables the individual to make sense of both static and moving images when limited information is available; we can track a person walking through a crowd or a plane disappearing in and out of clouds (Eysenck & Keane, 2015).

The mirror neuron system is incredibly fascinating and is proving valuable in our attempts to understand biological motion. Observing actions activates similar areas of the brain as performing them. The model appears to explain how we can imitate the actions of another person – crucial to learning (Eysenck & Keane, 2015).

Language comprehension

Whether written or spoken, understanding language involves a high degree of multi-level processing (Eysenck & Keane, 2015).

Comprehension begins with an initial analysis of sentence structure (larger language units require additional processing). Beyond processing syntax (the rules for building and analyzing sentences), analysis of sentence meaning ( semantics ) is necessary to understand if the interpretation should be literal or involve irony, metaphor, or sarcasm (Eysenck & Keane, 2015).

Pragmatics examines intended meaning. For example, shouting, “That’s the doorbell!” is not likely to be a simple observation, but rather a request to answer the door (Eysenck & Keane, 2015).

Several models have been proposed to understand the analysis and comprehension of sentences, known as parsing , including (Eysenck & Keane, 2015):

• Garden-path model This model attempts to explain why some sentences are ambiguous (such as, “The horse raced past the barn fell.”). It suggests they are challenging to comprehend because the analysis is performed on each individual unit of the sentence with little feedback, and correction is inhibited.
• Constraint-based model The interpretations of a sentence may be limited by several constraints, including syntactic, semantic, and general world knowledge.
• Unrestricted race model This model combines the garden-path and constraint-based model, and suggests all sources of information inform syntactic structure. One such interpretation is selected until it is discarded, with good reason, for another.
• Good-enough representation This model proposes that parsing provides a ‘good-enough’ interpretation rather than something detailed, accurate, and complete.

The research and theories above hint at the vast complexity of human cognition and explain why so many models and concepts attempt to answer what happens when it works and, equally important, when it doesn’t.

A level of psychology: the cognitive approach – Atomi

There are many research experiments in cognitive psychology that highlight the successes and failings of human cognition. Each of the following three offers insight into the mental processes behind our thinking and behavior.

Cocktail party phenomenon

Selective attention – or in this case, selective listening – is often exemplified by what has become known as the cocktail party phenomenon  (Eysenck & Keane, 2015).

Even in a busy room and possibly mid-conversation, we can often hear if someone else mentions our name. It seems we can filter out surrounding noise by combining bottom-up and top-down processing to create a “winner takes it all” situation where the processing of one high-value auditory input suppresses the brain activity of all others (Goldstein, 2011).

While people may believe that the speed of hand movement allows magicians to trick us, research suggests the main factor is misdirection (Eysenck & Keane, 2015).

A 2010 study of a trick involving the disappearance of a lighter identified that when the lighter was dropped (to hide it from a later hand-opening finale), it was masked by directing attention from the fixation point – known as covert attention – with surprising effectiveness.

However, subjects were able to identify the drop when their attention was directed to the fixation point – known as overt attention (Kuhn & Findlay, 2010).

In a thought-provoking study exploring freewill, participants were asked to consciously decide whether to move their finger left or right while a functional MRI scanner monitored their prefrontal cortex and parietal cortex (Soon, Brass, Heinze, & Haynes, 2008).

Brain activity predicted the direction of movement a full seven seconds before they consciously became aware of their decision. While follow-up research has challenged some of the findings, it appears that brain activity may come before conscious thinking (Eysenck & Keane, 2015).

Associations have been found between positive emotions, creative thinking, and overall wellbeing, suggesting environmental changes that may benefit staff productivity and innovation in the workplace (Yuan, 2015).

Factors explored include creating climates geared toward creativity, boosting challenge, trust, freedom, risk taking, low conflict, and even the beneficial effects of humor.

Undoubtedly, further innovation will be seen from marrying the two powerful and compelling new fields of positive psychology and cognitive psychology.

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Cognitive psychology is crucial in our search for understanding how we interact with and make sense of a constantly changing and potentially harmful environment.

Not only that, it offers insight into what happens when things go wrong and the likely impact on our wellbeing and ability to cope with life events.

Cognitive psychology’s strength is its willingness to embrace research findings from many other disciplines, combining them with existing psychological theory to create new models of cognition.

The tasks we appear to carry out unconsciously are a great deal more complex than they might first appear. Perception, attention, problem-solving, language comprehension and production, and decision-making often happen without intentional thought and yet have enormous consequences on our lives.

Use this article as a starting point to explore the many and diverse aspects of cognitive psychology. Consider their relationships with associated research fields and reflect on the importance of understanding cognition in helping clients overcome complex events or circumstances.

We hope you enjoyed reading this article. Don’t forget to download our three Positive Psychology Exercises for free .

• Eysenck, M. W., & Keane, M. T. (2015). Cognitive psychology: A student’s handbook . Psychology Press.
• Goldstein, E. B. (2011). Cognitive psychology . Wadsworth, Cengage Learning.
• Gross, R. D. (2020). Psychology: The science of mind and behaviour . Hodder and Stoughton.
• Kuhn, G., & Findlay, J. M. (2010). Misdirection, attention and awareness: Inattentional blindness reveals temporal relationship between eye movements and visual awareness. The Quarterly Journal of Experimental Psychology , 63 (1), 136–146.
• Moore, J. (1996). On the relation between behaviorism and cognitive psychology. Journal of Mind and Behavior , 17 (4), 345–367
• Soon, C. S., Brass, M., Heinze, H., & Haynes, J. (2008). Unconscious determinants of free decisions in the human brain. Nature Neuroscience , 11 (5), 543–545.
• Yuan, L. (2015). The happier one is, the more creative one becomes: An investigation on inspirational positive emotions from both subjective well-being and satisfaction at work. Psychology , 6 , 201–209.

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As a widowed Mother and Grandmother, whom was recently told by an adult child that maybe I should have “cognitive” testing done, I found this article to be very informative and refreshing. Having the ability to read and and learn about cognitive psychology is interesting as their are so many ways our brains are affected from the time we are born until the time we reach each and every stage in life. I have spent time with my grandchildren who are from age 19 months, through 15 years old , and spend time with children who are 35, 34, and 32, and my parents who are 88 and 84. I appreciate your article and your time in writing it. Sincerely,

Cognitive Psychology creates & build human capacity to push physical and mental limits. My concept of cognition in human behavior was judged by the most time I met my lawyer or the doctor. Most of the time while listening a pause, oh I see and it is perpetual transition to see. Cognition emergence is very vital support as we see & perceive. My practices in engineering solution are base on my cognitive sensibilities.You article provokes the same perceptions. Thank you

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7.1 What Is Cognition?

Learning objectives.

By the end of this section, you will be able to:

• Describe cognition
• Distinguish concepts and prototypes
• Explain the difference between natural and artificial concepts
• Describe how schemata are organized and constructed

Imagine all of your thoughts as if they were physical entities, swirling rapidly inside your mind. How is it possible that the brain is able to move from one thought to the next in an organized, orderly fashion? The brain is endlessly perceiving, processing, planning, organizing, and remembering—it is always active. Yet, you don’t notice most of your brain’s activity as you move throughout your daily routine. This is only one facet of the complex processes involved in cognition. Simply put, cognition is thinking, and it encompasses the processes associated with perception, knowledge, problem solving, judgment, language, and memory. Scientists who study cognition are searching for ways to understand how we integrate, organize, and utilize our conscious cognitive experiences without being aware of all of the unconscious work that our brains are doing (for example, Kahneman, 2011).

Upon waking each morning, you begin thinking—contemplating the tasks that you must complete that day. In what order should you run your errands? Should you go to the bank, the cleaners, or the grocery store first? Can you get these things done before you head to class or will they need to wait until school is done? These thoughts are one example of cognition at work. Exceptionally complex, cognition is an essential feature of human consciousness, yet not all aspects of cognition are consciously experienced.

Cognitive psychology is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem solving, in addition to other cognitive processes. Cognitive psychologists strive to determine and measure different types of intelligence, why some people are better at problem solving than others, and how emotional intelligence affects success in the workplace, among countless other topics. They also sometimes focus on how we organize thoughts and information gathered from our environments into meaningful categories of thought, which will be discussed later.

Concepts and Prototypes

The human nervous system is capable of handling endless streams of information. The senses serve as the interface between the mind and the external environment, receiving stimuli and translating it into nervous impulses that are transmitted to the brain. The brain then processes this information and uses the relevant pieces to create thoughts, which can then be expressed through language or stored in memory for future use. To make this process more complex, the brain does not gather information from external environments only. When thoughts are formed, the mind synthesizes information from emotions and memories ( Figure 7.2 ). Emotion and memory are powerful influences on both our thoughts and behaviors.

In order to organize this staggering amount of information, the mind has developed a "file cabinet" of sorts. The different files stored in the file cabinet are called concepts. Concepts are categories or groupings of linguistic information, images, ideas, or memories, such as life experiences. Concepts are, in many ways, big ideas that are generated by observing details, and categorizing and combining these details into cognitive structures. You use concepts to see the relationships among the different elements of your experiences and to keep the information in your mind organized and accessible.

Concepts are informed by our semantic memory (you will learn more about semantic memory in a later chapter) and are present in every aspect of our lives; however, one of the easiest places to notice concepts is inside a classroom, where they are discussed explicitly. When you study United States history, for example, you learn about more than just individual events that have happened in America’s past. You absorb a large quantity of information by listening to and participating in discussions, examining maps, and reading first-hand accounts of people’s lives. Your brain analyzes these details and develops an overall understanding of American history. In the process, your brain gathers details that inform and refine your understanding of related concepts such as war, the judicial system, and voting rights and laws.

Concepts can be complex and abstract, like justice, or more concrete, like types of birds. In psychology, for example, Piaget’s stages of development are abstract concepts. Some concepts, like tolerance, are agreed upon by many people, because they have been used in various ways over many years. Other concepts, like the characteristics of your ideal friend or your family’s birthday traditions, are personal and individualized. In this way, concepts touch every aspect of our lives, from our many daily routines to the guiding principles behind the way governments function.

Another technique used by your brain to organize information is the identification of prototypes for the concepts you have developed. A prototype is the best example or representation of a concept. For example, what comes to your mind when you think of a dog? Most likely your early experiences with dogs will shape what you imagine. If your first pet was a Golden Retriever, there is a good chance that this would be your prototype for the category of dogs.

Natural and Artificial Concepts

In psychology, concepts can be divided into two categories, natural and artificial. Natural concepts are created “naturally” through your experiences and can be developed from either direct or indirect experiences. For example, if you live in Essex Junction, Vermont, you have probably had a lot of direct experience with snow. You’ve watched it fall from the sky, you’ve seen lightly falling snow that barely covers the windshield of your car, and you’ve shoveled out 18 inches of fluffy white snow as you’ve thought, “This is perfect for skiing.” You’ve thrown snowballs at your best friend and gone sledding down the steepest hill in town. In short, you know snow. You know what it looks like, smells like, tastes like, and feels like. If, however, you’ve lived your whole life on the island of Saint Vincent in the Caribbean, you may never actually have seen snow, much less tasted, smelled, or touched it. You know snow from the indirect experience of seeing pictures of falling snow—or from watching films that feature snow as part of the setting. Either way, snow is a natural concept because you can construct an understanding of it through direct observations, experiences with snow, or indirect knowledge (such as from films or books) ( Figure 7.3 ).

An artificial concept , on the other hand, is a concept that is defined by a specific set of characteristics. Various properties of geometric shapes, like squares and triangles, serve as useful examples of artificial concepts. A triangle always has three angles and three sides. A square always has four equal sides and four right angles. Mathematical formulas, like the equation for area (length × width) are artificial concepts defined by specific sets of characteristics that are always the same. Artificial concepts can enhance the understanding of a topic by building on one another. For example, before learning the concept of “area of a square” (and the formula to find it), you must understand what a square is. Once the concept of “area of a square” is understood, an understanding of area for other geometric shapes can be built upon the original understanding of area. The use of artificial concepts to define an idea is crucial to communicating with others and engaging in complex thought. According to Goldstone and Kersten (2003), concepts act as building blocks and can be connected in countless combinations to create complex thoughts.

A schema is a mental construct consisting of a cluster or collection of related concepts (Bartlett, 1932). There are many different types of schemata, and they all have one thing in common: schemata are a method of organizing information that allows the brain to work more efficiently. When a schema is activated, the brain makes immediate assumptions about the person or object being observed.

There are several types of schemata. A role schema makes assumptions about how individuals in certain roles will behave (Callero, 1994). For example, imagine you meet someone who introduces himself as a firefighter. When this happens, your brain automatically activates the “firefighter schema” and begins making assumptions that this person is brave, selfless, and community-oriented. Despite not knowing this person, already you have unknowingly made judgments about them. Schemata also help you fill in gaps in the information you receive from the world around you. While schemata allow for more efficient information processing, there can be problems with schemata, regardless of whether they are accurate: Perhaps this particular firefighter is not brave, they just work as a firefighter to pay the bills while studying to become a children’s librarian.

An event schema , also known as a cognitive script , is a set of behaviors that can feel like a routine. Think about what you do when you walk into an elevator ( Figure 7.4 ). First, the doors open and you wait to let exiting passengers leave the elevator car. Then, you step into the elevator and turn around to face the doors, looking for the correct button to push. You never face the back of the elevator, do you? And when you’re riding in a crowded elevator and you can’t face the front, it feels uncomfortable, doesn’t it? Interestingly, event schemata can vary widely among different cultures and countries. For example, while it is quite common for people to greet one another with a handshake in the United States, in Tibet, you greet someone by sticking your tongue out at them, and in Belize, you bump fists (Cairns Regional Council, n.d.)

Because event schemata are automatic, they can be difficult to change. Imagine that you are driving home from work or school. This event schema involves getting in the car, shutting the door, and buckling your seatbelt before putting the key in the ignition. You might perform this script two or three times each day. As you drive home, you hear your phone’s ring tone. Typically, the event schema that occurs when you hear your phone ringing involves locating the phone and answering it or responding to your latest text message. So without thinking, you reach for your phone, which could be in your pocket, in your bag, or on the passenger seat of the car. This powerful event schema is informed by your pattern of behavior and the pleasurable stimulation that a phone call or text message gives your brain. Because it is a schema, it is extremely challenging for us to stop reaching for the phone, even though we know that we endanger our own lives and the lives of others while we do it (Neyfakh, 2013) ( Figure 7.5 ).

Remember the elevator? It feels almost impossible to walk in and not face the door. Our powerful event schema dictates our behavior in the elevator, and it is no different with our phones. Current research suggests that it is the habit, or event schema, of checking our phones in many different situations that makes refraining from checking them while driving especially difficult (Bayer & Campbell, 2012). Because texting and driving has become a dangerous epidemic in recent years, psychologists are looking at ways to help people interrupt the “phone schema” while driving. Event schemata like these are the reason why many habits are difficult to break once they have been acquired. As we continue to examine thinking, keep in mind how powerful the forces of concepts and schemata are to our understanding of the world.

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1.1: History of Cognitive Psychology

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Early thoughts claimed that knowledge was stored in the brain.

Renaissance and Beyond

Renaissance philosophers of the 17th century generally agreed with Nativists and even tried to show the structure and functions of the brain graphically. But also empiricist philosophers had very important ideas. According to David Hume , the internal representations of knowledge are formed obeying particular rules. These creations and transformations take effort and time. Actually, this is the basis of much current research in Cognitive Psychology. In the 19th Century Wilhelm Wundt and Franciscus Cornelis Donders made the corresponding experiments measuring the reaction time required for a response, of which further interpretation gave rise to Cognitive Psychology 55 years later.

20th Century and the Cognitive Revolution

During the first half of the 20th Century, a radical turn in the investigation of cognition took place. Behaviourists like Burrhus Frederic Skinner claimed that such mental internal operations - such as attention, memory, and thinking – are only hypothetical constructs that cannot be observed or proven. Therefore, Behaviorists asserted, mental constructs are not as important and relevant as the study and experimental analysis of behaviour (directly observable data) in response to some stimulus. According to Watson and Skinner, man could be objectively studied only in this way. The popularity of Behavioralist theory in the psychological world led investigation of mental events and processes to be abandoned for about 50 years.

In the 1950s scientific interest returned again to attention, memory, images, language processing, thinking and consciousness. The “failure” of Behaviourism heralded a new period in the investigation of cognition, called Cognitive Revolution . This was characterized by a revival of already existing theories and the rise of new ideas such as various communication theories. These theories emerged mainly from the previously created information theory, giving rise to experiments in signal detection and attention in order to form a theoretical and practical understanding of communication.

Modern linguists suggested new theories on language and grammar structure, which were correlated with cognitive processes. Chomsky’s Generative Grammar and Universal Grammar theory, proposed language hierarchy, and his critique of Skinner’s “Verbal Behaviour” are all milestones in the history of Cognitive Science. Theories of memory and models of its organization gave rise to models of other cognitive processes. Computer science, especially artificial intelligence, re-examined basic theories of problem solving and the processing and storage of memory, language processing and acquisition.

For clarification: Further discussion on the "behaviorist" history.

Although the above account reflects the most common version of the rise and fall of behaviorism, it is a misrepresentation. In order to better understand the founding of cognitive psychology it must be understood in an accurate historical context. Theoretical disagreements exist in every science. However, these disagreements should be based on an honest interpretation of the opposing view. There is a general tendency to draw a false equivalence between Skinner and Watson. It is true that Watson rejected the role that mental or conscious events played in the behavior of humans. In hindsight this was an error. However, if we examine the historical context of Watson's position we can better understand why he went to such extremes. He, like many young psychologists of the time, was growing frustrated with the lack of practical progress in psychological science. The focus on consciousness was yielding inconsistent, unreliable and conflicting data. Excited by the progress coming from Pavlov's work with elicited responses and looking to the natural sciences for inspiration, Watson rejected the study of observable mental events and also pushed psychology to study stimulus-response relations as a means to better understand human behavior. This new school of psychology, "behaviorism" became very popular. Skinner's school of thought, although inspired by Watson, takes a very different approach to the study of unobservable mental events. Skinner proposed that the distinction between "mind" and "body" brought with it irreconcilable philosophical baggage. He proposed that the events going on "within the skin", previously referred to as mental events, be called private events. This would bring the private experiences of thinking, reasoning, feeling and such, back into the scientific fold of psychology. However, Skinner proposed that these were things we are doing rather than events going on at a theorized mental place. For Skinner, the question was not of a mental world existing or not, it was whether or not we need to appeal to the existence of a mental world in order to explain the things going on inside our heads. Such as the natural sciences ask whether we need to assume the existence of a creator in order to account for phenomena in the natural world. For Skinner, it was an error for psychologists to point to these private events (mental) events as causes of behavior. Instead, he suggested that these too had to be explained through the study of how one evolves as a matter of experience. For example, we could say that a student studies because she "expects" to do better on an exam if she does. To "expect" might sound like an acceptable explanation for the behavior of studying, however, Skinner would ask why she "expects". The answer to this question would yield the true explanation of why the student is studying. To "expect" is to do something, to behave "in our head", and thus must also be explained.

The cognitive psychologist Henry Roediger pointed out that many psychologists erroneously subscribe to the version of psychology presented in the first paragraph. He also pointed to the successful rebuttal against Chomsky's review of Verbal behavior. The evidence for the utility in Skinner's book can be seen in the abundance of actionable data it has generated, therapies unmatched by any modern linguistic account of language. Roediger reminded his readers that in fact, we all measure behavior, some simply choose to make more assumptions about its origins than others. He recalls how, even as a cognitive psychologist, he has been the focus of criticism for not making more assumptions about his data. The law of parsimony tells us that when choosing an explanation for a set of data about observable behavior (the data all psychologists collect), we must be careful not to make assumptions beyond those necessary to explain the data. This is where the main division lies between modern day behavior analysts and cognitive psychologists. It is not in the rejection of our private experiences, it is in how these experiences are studied. Behavior analysts study them in relation to our learning history and the brain correlates of that history. They use this information to design environments that change our private experience by changing our interaction with the world. After all, it is through our interaction with our relative world that our private experiences evolve. It is a far cry from the mechanical stimulus-response psychology of John Watson. Academic honesty requires that we make a good faith effort to understand what we wish to criticize. Henry Roediger pointed out that many psychologists understand a very stereotyped, erroneous version of psychology's history. In doing so they miss the many successful real world applications that Skinner's analysis has generated.

Neuroinformatics, which is based on the natural structure of the human nervous system, tries to build neuronal structures by the idea of artificial neurons. In addition to that, Neuroinformatics is used as a field of evidence for psychological models, for example models for memory. The artificial neuron network “learns” words and behaves like “real” neurons in the brain. If the results of the artificial neuron network are quite similar to the results of real memory experiments, it would support the model. In this way psychological models can be “tested”. Furthermore it would help to build artificial neuron networks, which posses similar skills like the human such as face recognition.

If more about the ways humans process information was understood, it would be much simpler to build artificial structures, which have the same or similar abilities. The area of cognitive development investigation tried to describe how children develop their cognitive abilities from infancy to adolescence. The theories of knowledge representation were first strongly concerned with sensory inputs. Current scientists claim to have evidence that our internal representation of reality is not a one-to-one reproduction of the physical world. It is rather stored in some abstract or neurochemical code. Tolman, Bartlett, Norman and Rumelhart made some experiments on cognitive mapping. Here, the inner knowledge seemed not only to be related to sensory input, but also to be modified by some kind of knowledge network modeled by past experience.

Newer methods, like Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) have given researchers the possibility to measure brain activity and possibly correlate it to mental states and processes. All these new approaches in the study of human cognition and psychology have defined the field of Cognitive Psychology, a very fascinating field which tries to answer what is quite possibly the most interesting question posed since the dawn of reason. There is still a lot to discover and to answer and to ask again, but first we want to make you more familiar with the concept of Cognitive Psychology.

How to Write a Psychology Essay

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

Before you write your essay, it’s important to analyse the task and understand exactly what the essay question is asking. Your lecturer may give you some advice – pay attention to this as it will help you plan your answer.

Next conduct preliminary reading based on your lecture notes. At this stage, it’s not crucial to have a robust understanding of key theories or studies, but you should at least have a general “gist” of the literature.

After reading, plan a response to the task. This plan could be in the form of a mind map, a summary table, or by writing a core statement (which encompasses the entire argument of your essay in just a few sentences).

After writing your plan, conduct supplementary reading, refine your plan, and make it more detailed.

It is tempting to skip these preliminary steps and write the first draft while reading at the same time. However, reading and planning will make the essay writing process easier, quicker, and ensure a higher quality essay is produced.

Components of a Good Essay

Now, let us look at what constitutes a good essay in psychology. There are a number of important features.

• Global Structure – structure the material to allow for a logical sequence of ideas. Each paragraph / statement should follow sensibly from its predecessor. The essay should “flow”. The introduction, main body and conclusion should all be linked.
• Each paragraph should comprise a main theme, which is illustrated and developed through a number of points (supported by evidence).
• Knowledge and Understanding – recognize, recall, and show understanding of a range of scientific material that accurately reflects the main theoretical perspectives.
• Critical Evaluation – arguments should be supported by appropriate evidence and/or theory from the literature. Evidence of independent thinking, insight, and evaluation of the evidence.
• Quality of Written Communication – writing clearly and succinctly with appropriate use of paragraphs, spelling, and grammar. All sources are referenced accurately and in line with APA guidelines.

In the main body of the essay, every paragraph should demonstrate both knowledge and critical evaluation.

There should also be an appropriate balance between these two essay components. Try to aim for about a 60/40 split if possible.

Most students make the mistake of writing too much knowledge and not enough evaluation (which is the difficult bit).

It is best to structure your essay according to key themes. Themes are illustrated and developed through a number of points (supported by evidence).

Choose relevant points only, ones that most reveal the theme or help to make a convincing and interesting argument.

Knowledge and Understanding

Remember that an essay is simply a discussion / argument on paper. Don’t make the mistake of writing all the information you know regarding a particular topic.

You need to be concise, and clearly articulate your argument. A sentence should contain no unnecessary words, a paragraph no unnecessary sentences.

Each paragraph should have a purpose / theme, and make a number of points – which need to be support by high quality evidence. Be clear why each point is is relevant to the argument. It would be useful at the beginning of each paragraph if you explicitly outlined the theme being discussed (.e.g. cognitive development, social development etc.).

Try not to overuse quotations in your essays. It is more appropriate to use original content to demonstrate your understanding.

Psychology is a science so you must support your ideas with evidence (not your own personal opinion). If you are discussing a theory or research study make sure you cite the source of the information.

Note this is not the author of a textbook you have read – but the original source / author(s) of the theory or research study.

For example:

Bowlby (1951) claimed that mothering is almost useless if delayed until after two and a half to three years and, for most children, if delayed till after 12 months, i.e. there is a critical period.

Maslow (1943) stated that people are motivated to achieve certain needs. When one need is fulfilled a person seeks to fullfil the next one, and so on.

As a general rule, make sure there is at least one citation (i.e. name of psychologist and date of publication) in each paragraph.

Remember to answer the essay question. Underline the keywords in the essay title. Don’t make the mistake of simply writing everything you know of a particular topic, be selective. Each paragraph in your essay should contribute to answering the essay question.

Critical Evaluation

In simple terms, this means outlining the strengths and limitations of a theory or research study.

There are many ways you can critically evaluate:

Methodological evaluation of research

Is the study valid / reliable ? Is the sample biased, or can we generalize the findings to other populations? What are the strengths and limitations of the method used and data obtained?

Be careful to ensure that any methodological criticisms are justified and not trite.

Rather than hunting for weaknesses in every study; only highlight limitations that make you doubt the conclusions that the authors have drawn – e.g., where an alternative explanation might be equally likely because something hasn’t been adequately controlled.

Compare or contrast different theories

Outline how the theories are similar and how they differ. This could be two (or more) theories of personality / memory / child development etc. Also try to communicate the value of the theory / study.

Debates or perspectives

Refer to debates such as nature or nurture, reductionism vs. holism, or the perspectives in psychology . For example, would they agree or disagree with a theory or the findings of the study?

What are the ethical issues of the research?

Does a study involve ethical issues such as deception, privacy, psychological or physical harm?

Gender bias

If research is biased towards men or women it does not provide a clear view of the behavior that has been studied. A dominantly male perspective is known as an androcentric bias.

Cultural bias

Is the theory / study ethnocentric? Psychology is predominantly a white, Euro-American enterprise. In some texts, over 90% of studies have US participants, who are predominantly white and middle class.

Does the theory or study being discussed judge other cultures by Western standards?

Animal Research

This raises the issue of whether it’s morally and/or scientifically right to use animals. The main criterion is that benefits must outweigh costs. But benefits are almost always to humans and costs to animals.

Animal research also raises the issue of extrapolation. Can we generalize from studies on animals to humans as their anatomy & physiology is different from humans?

The PEC System

It is very important to elaborate on your evaluation. Don’t just write a shopping list of brief (one or two sentence) evaluation points.

Instead, make sure you expand on your points, remember, quality of evaluation is most important than quantity.

When you are writing an evaluation paragraph, use the PEC system.

• Make your P oint.
• E xplain how and why the point is relevant.
• Discuss the C onsequences / implications of the theory or study. Are they positive or negative?

For Example

• Point: It is argued that psychoanalytic therapy is only of benefit to an articulate, intelligent, affluent minority.
• Explain: Because psychoanalytic therapy involves talking and gaining insight, and is costly and time-consuming, it is argued that it is only of benefit to an articulate, intelligent, affluent minority. Evidence suggests psychoanalytic therapy works best if the client is motivated and has a positive attitude.
• Consequences: A depressed client’s apathy, flat emotional state, and lack of motivation limit the appropriateness of psychoanalytic therapy for depression.

Furthermore, the levels of dependency of depressed clients mean that transference is more likely to develop.

Using Research Studies in your Essays

Research studies can either be knowledge or evaluation.

• If you refer to the procedures and findings of a study, this shows knowledge and understanding.
• If you comment on what the studies shows, and what it supports and challenges about the theory in question, this shows evaluation.

Writing an Introduction

It is often best to write your introduction when you have finished the main body of the essay, so that you have a good understanding of the topic area.

If there is a word count for your essay try to devote 10% of this to your introduction.

Ideally, the introduction should;

Identify the subject of the essay and define the key terms. Highlight the major issues which “lie behind” the question. Let the reader know how you will focus your essay by identifying the main themes to be discussed. “Signpost” the essay’s key argument, (and, if possible, how this argument is structured).

Introductions are very important as first impressions count and they can create a h alo effect in the mind of the lecturer grading your essay. If you start off well then you are more likely to be forgiven for the odd mistake later one.

Writing a Conclusion

So many students either forget to write a conclusion or fail to give it the attention it deserves.

If there is a word count for your essay try to devote 10% of this to your conclusion.

Ideally the conclusion should summarize the key themes / arguments of your essay. State the take home message – don’t sit on the fence, instead weigh up the evidence presented in the essay and make a decision which side of the argument has more support.

Also, you might like to suggest what future research may need to be conducted and why (read the discussion section of journal articles for this).

Don”t include new information / arguments (only information discussed in the main body of the essay).

If you are unsure of what to write read the essay question and answer it in one paragraph.

Points that unite or embrace several themes can be used to great effect as part of your conclusion.

The Importance of Flow

Obviously, what you write is important, but how you communicate your ideas / arguments has a significant influence on your overall grade. Most students may have similar information / content in their essays, but the better students communicate this information concisely and articulately.

When you have finished the first draft of your essay you must check if it “flows”. This is an important feature of quality of communication (along with spelling and grammar).

This means that the paragraphs follow a logical order (like the chapters in a novel). Have a global structure with themes arranged in a way that allows for a logical sequence of ideas. You might want to rearrange (cut and paste) paragraphs to a different position in your essay if they don”t appear to fit in with the essay structure.

To improve the flow of your essay make sure the last sentence of one paragraph links to first sentence of the next paragraph. This will help the essay flow and make it easier to read.

Finally, only repeat citations when it is unclear which study / theory you are discussing. Repeating citations unnecessarily disrupts the flow of an essay.

Referencing

The reference section is the list of all the sources cited in the essay (in alphabetical order). It is not a bibliography (a list of the books you used).

In simple terms every time you cite/refer to a name (and date) of a psychologist you need to reference the original source of the information.

If you have been using textbooks this is easy as the references are usually at the back of the book and you can just copy them down. If you have been using websites, then you may have a problem as they might not provide a reference section for you to copy.

References need to be set out APA style :

Author, A. A. (year). Title of work . Location: Publisher.

Journal Articles

Author, A. A., Author, B. B., & Author, C. C. (year). Article title. Journal Title, volume number (issue number), page numbers

A simple way to write your reference section is use Google scholar . Just type the name and date of the psychologist in the search box and click on the “cite” link.

Next, copy and paste the APA reference into the reference section of your essay.

Once again, remember that references need to be in alphabetical order according to surname.

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APA References Page Formatting and Example

APA Title Page (Cover Page) Format, Example, & Templates

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Lab Report Format: Step-by-Step Guide & Examples

10 Cognitive Psychology Examples (Most Famous Experiments)

Cognitive psychology is the scientific study of mental processes. This includes trying to understand how people perceive the world around them, store and recall memories, acquire and use language, and engage in problem-solving.

Although not the first to study mental processes, Ulric Neisser helped cement the term in the field of psychology in his 1967 book Cognitive Psychology .

He offered an elaborate definition of cognitive psychology, with key points quoted below:

“ The term cognition refers to all processes by which sensory input is transformed, reduced, elaborated, recovered, and used…Giving such a sweeping definition, it is apparent that cognition is involved in everything a human being might possibly do” (p. 4).

In the mid-20 th century, there was significant divide in psychology between behaviorism and cognitive psychologists.

The behaviorists, such as Skinner, argued that only observable phenomena should be studied. Since mental processes could not be observed, they could not be studied scientifically.

Neisser countered, stating that:

“Cognitive processes surely exist, so it can hardly be unscientific to study them” (p. 5).  

Cognitive Psychology Examples (Famous Studies)

1. the forgetting curve and the serial position effect.

The contributions of Hermann Ebbinghaus to cognitive psychology were so significant that his individual studies could consume all 10 examples in this article.

Some believe that his book Über das Gedächtnis (1902) “…records one of the most remarkable research achievements in the history of psychology” (Roediger, 1985, p. 519).

Two of his most influential discoveries on memory include: the forgetting curve and the serial position effect .

To make his research on memory scientific, he created a list of over 2,000 nonsense syllables (e.g., BOK, YAT). Using commonly used vocabulary words would be too heavily associated with meaning, but nonsense syllables had no prior associations.

By conducting testing on himself, he was able to eliminate numerous other variables that would result from using people with varied backgrounds, experiences, and mental acuities.

So, he would present himself with lists of nonsense syllables and then test his memory at various intervals afterward.

This led to the discovery of the forgetting curve : forgetting begins right after the initial presentation of information and continues to degrade from then on.

The serial-position effect is the tendency to remember the first and last items in a list more so than the items in the middle.

2. The Magical Number 7 

One of the most often cited papers in psychology was written by cognitive psychologist George Miller of Harvard University in 1956.

The paper did not describe a series of experiments conducted by Miller himself. Instead, Miller outlines the work of several researchers that point to the magical number 7 as the capacity of short-term memory.

He made the case that this capacity is the same no matter what form the stimuli takes; whether talking about tones or words.

He also suggested that information is organized in “chunks,” not individual bits. A word is just one chunk for a native speaker, but for someone learning the language, the word consists of several bits of information in the form of individual letters.

Therefore, the capacity of the native speaker is 7 words, but for the beginner, it may only be two, or just 7 letters.

Miller concludes the paper by making a point about the number 7 itself:

“And finally, what about the magical number seven? What about the seven wonders of the world, the seven seas, the seven deadly sins, the seven daughters of Atlas in the Pleiades, the seven ages of man, the seven levels of hell, the seven primary colors, the seven notes of the musical scale, and the seven days of the week?” (p. 96).

See Also: Short-Term Memory Examples

3. The Framing Bias 

Tversky and Kahneman (1981) discovered the framing bias , which occurs when a person’s decision is influenced by the way information is presented. 

A typical study involved presenting information to participants, but varying one or two words in how the information was described.

For example:

“Imagine that the U.S. is preparing for the outbreak of an unusual Asian disease, which is expected to kill 600 people. If Program C is adopted 400 people will die. [22 percent] If Program D is adopted there is 1/3 probability that nobody will die, and 2/3 probability that 600 people will die. [78 percent] Which of the two programs would you favor?” (p. 453).

Although both programs lead to the same mortality rate, most research participants preferred Program D.

As the researchers explain, “the certain death of 400 people is less acceptable than the two-in-three chance that 600 will die” (p. 453).

Moreover, the effects were far from trivial:

“They occur when the outcomes concern the loss of human lives as well as in choices about money; they are not restricted to hypothetical questions and are not eliminated by monetary incentives” (p.  457).

4. Schema: Assimilation and Accommodation 

Jean Piaget’s research in the 1950’s and 60’s on cognitive development had a profound impact on our understanding of children. He detailed the way in which children perceive and make sense of the world and identified the stages of that developmental sequence which we still follow today.  

According to Piaget, children develop a schema , usually defined as a mental framework that organizes information about a concept.

As the child grows and experiences the world, everything they encounter will be processed within that schema. This is called assimilation . When the schema is altered or a new schema is developed, it is called accommodation .

He conducted a great deal of his research by observing his own three children and taking excruciatingly detailed notes on their behavior.

During the sensorimotor stage (birth to 2 years old), Piaget highlights a milestone that demonstrates the infant is now exploring their environment with intent.

“…the definitive conquest of the mechanisms of grasping marks the beginning of the complex behavior patterns which we shall call “assimilations through secondary schemata” and which characterize the first forms of deliberate action” (Piaget, 1956, p. 88).

Although this milestone takes place in the sensorimotor stage, it is much more than a sensory experience. It is driven by intent, a purely cognitive construct.

Priming occurs when exposure to a stimulus has an effect on our behavior or how we respond to information presented subsequently. It can occur outside of conscious awareness.  

Priming affects how we process all kinds of information and is a widely used concept in marketing.

Meyer and Schvaneveldt (1971) were among the first to study priming.

They presented research participants with various pairs of associated words (Bread/Butter), unassociated words (Bread/Doctor), or nonwords.

The participants were instructed to indicate “yes” if both words were real words or “no” if one was not a real word.

The results revealed that participants were able to make this decision much faster when the pair of words were associated than when they were unassociated.

Although not conclusive and in need of further research, this pattern indicated that words that have strong connections in memory are activated more easily than words that are less connected.

Research since has identified numerous types of priming, including: perceptual, semantic, associative, affective, and cultural.

6. Semantic Memory Network and Spreading Activation

Further research on priming was conducted by Collins and Loftus (1975). Their studies led to more conclusive evidence that information is stored in a memory network of linked concepts.

When one concept is activated, that activation spreads throughout the network and activates other concepts.

The stronger the connection between concepts, the more likely one will activate the other. Eventually, the activation loses energy and dissipates.

Collins and Loftus provide a thorough explanation of the semantic memory network :

“The more properties two concepts have in common, the more links there are between the two nodes via these properties and the more closely related are the concepts…When a concept is processed (or stimulated), activation spreads out along the paths of the network in a decreasing gradient” (p. 411).

This research led to a more complete understanding of how information is stored and organized in memory. This has helped us understand a wide range of psychological phenomena such as how we form impressions of others and make decisions.

7. The ELM Model of Persuasion

Understanding how people form an attitude has been an area of study in cognitive psychology for more than 50 years.

Researchers Petty and Cacioppo (1986) formulated the Elaboration Likelihood Model (ELM) of persuasion to explain how message factors and personality characteristics affect attitude formation.

The ELM identifies two routes to persuasion: central and peripheral.

The central route to persuasion is activated when the message recipient engages in a critical analysis of the message content. This occurs when the message is about an issue considered important by the recipient.

In this scenario, a person will be persuaded by the quality of arguments in the message.

The central route results

“…from a person’s careful and thoughtful consideration of the true merits of the information presented…” (1986, p. 125).

The peripheral route to persuasion involves very little cognitive processing of the message content. This occurs when the issue is unimportant to the recipient.

In this scenario, a person will be persuaded by the status of the person expressing their opinion.

The peripheral route results from:

“…some simple cue in the persuasion context (e.g., an attractive source) that induces change without necessitating scrutiny of the true merits of the information presented” (p. 125).

Findings from ELM research apply to everything from product advertising, to public health campaigns, to political debate.

Go Deeper: The Six Types of Persuasion

8. The Bobo Doll Study

The Bobo Doll study by Albert Bandura in 1963 may be one of the most famous studies in psychology and a founding study for the social cognitive theory . It had a tremendous impact on society as well.

It took place at a time in the U. S. in which there was great concern and debate over the growing prevalence of violence depicted on television.

In the study, children watched a video of an adult either playing violently or not violently with a Bobo doll.

Afterwards, each child was placed in a room with a Bobo doll. Their behavior was carefully observed by trained raters.

Children that watched the violent video were more aggressive towards the doll than those that watched the non-violent video.

This type of study was among the first demonstrate the powerful effect of television on children’s behavior. It led to decades of research and intense debate throughout society.

9. Bystander Intervention: The First Study

In 1964 in New York City, late at night, a young woman was murdered just steps away from her apartment.

The newspapers reported that nearly 40 residents heard her pleas for help, but that no one actually did anything. That reporting has now been found to have many inaccuracies.

However, the story created a national debate about crime and helping those in need.

This was the impetus for a study conducted by Latané and Darley (1968) on “ the bystander effect .”

The methodology was simple. Over 60 college students at New York University were taken to individual rooms to discuss an issue via an intercom system.

The students knew that several people would be participating in the discussion simultaneously.

One “participant” spoke about their difficulties adjusting to college life and their medical condition which sometimes led to seizures. This was a pre-recorded script and included a part where the “participant” acted as if they were feeling physical distress. They eventually stopped communicating with the other participants.

The results revealed that:

“The number of bystanders that the subject perceived to be present had a major effect on the likelihood with which she would report the emergency. Eighty-five percent of the subjects who thought they alone knew of the victim’s plight reported the seizure before the victim was cut off, only 31% of those who thought four other bystanders were present did so” (p. 379).

This was the beginning of a long program of research that identified the decision-making steps that determine the likelihood of a bystander intervening in an emergency situation.

10. The Car Crash Experiment: Leading Questions

Dr. Elizabeth Loftus and her undergraduate student John Palmer designed a study in 1974 that shook our confidence in eyewitness testimony.

Research participants watched videos that depicted accidents between two cars. Afterward, participants were asked to estimate how fast the two cars were traveling upon impact.  

“How fast were the two cars going when they ______ into each other?”

However, the word in the blank varied. For some participants the word in the blank was “smashed” and for other participants the word was “contacted.”

The results showed that estimates varied depending on the word.

When the word “smashed” was used, estimates were much higher than when the “contacted” was used. 

This was the first in a long line of research conducted on how phrasing can result in leading questions that affect the memory of eyewitnesses.

It has had a tremendous impact on law enforcement interrogation practices, line-up procedures, and the credibility of eyewitness testimony .

Today’s article was about 10 famous studies in cognitive psychology. Ten is actually a low number given how many studies have had substantial impact on the field.

The studies described above include the famous work of Ebbinghaus, who used himself as a test subject. This entire article could have consisted of his work.

Also included above was just one study by Tversky and Kahneman. The two researchers have identified so many heuristics and cognitive biases that only choosing one was just unfair.

Two studies by Loftus were included because they were both groundbreaking: one in memory and the other in eyewitness testimony.

Of course, Bandura’s Bobo Doll study was included because of its fame and impact on public discourse.

The ELM model and the earliest study on bystander intervention were also included. Both have had profound impacts in not just our understanding about the given subjects, but have also had substantial practical applications in various professions and matters in real-life.

Bandura, A. (1977).  Social Learning Theory . Prentice Hall.

Bandura, A., Ross, D., & Ross, S. A. (1963). Imitation of film-mediated aggressive models. The Journal of Abnormal and Social Psychology, 66 (1), 3–11. https://doi.org/10.1037/h0048687

Ebbinghaus, H. (1902). Grundz Üge der Psychologic. Leipzig, Germany: von Veit.

Ebbinghaus, H. (1964). Memory: A contribution to experimental psychology (H. A. Ruger, C. E. Bussenius translators). New York: Dover.

Ebbinghaus, H. (1913). On memory: A contribution to experimental psychology . New York: Teachers College.

Kitchen, P., Kerr, G., Schultz, D., Mccoll, R., & Pals, H. (2014). The elaboration likelihood model: Review, critique and research agenda. European Journal of Marketing, 48 (11/12), 2033-2050. https://doi.org/10.1108/EJM-12-2011-0776

Loftus, E. F., & Palmer, J. C. (1974). Reconstruction of automobile destruction: An example of the interaction between language and memory. Journal of Verbal Learning and Verbal Behavior, 13 (5), 585–589.

Miller, G. A. (1956). The magical number seven plus or minus two: some limits on our capacity for processing information. Psychological Review , 63 (2), 81–97.

Neisser, U. (1967). Cognitive psychology . Englewood Cliffs, NJ: Prentice Hall.

Roediger, H. (1985). Remembering Ebbinghaus. PsycCRITIQUES, 30(7), 519-523.

Petty, R.E. & Cacioppo, J.T. (1986). The Elaboration Likelihood Model of persuasion. Advances in Experimental Social Psychology, 19 , 123-205. Doi: https://doi.org/10.1016/S0065-2601(08)60214-2

Piaget, J. (1956; 1965). The origins of intelligence in children . International Universities Press Inc. New York.

Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice .  Science ,  211 (4481), 453-458.

Dave Cornell (PhD)

Dr. Cornell has worked in education for more than 20 years. His work has involved designing teacher certification for Trinity College in London and in-service training for state governments in the United States. He has trained kindergarten teachers in 8 countries and helped businessmen and women open baby centers and kindergartens in 3 countries.

• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ 25 Positive Punishment Examples
• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ 25 Dissociation Examples (Psychology)
• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ 15 Zone of Proximal Development Examples
• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ Perception Checking: 15 Examples and Definition

Chris Drew (PhD)

This article was peer-reviewed and edited by Chris Drew (PhD). The review process on Helpful Professor involves having a PhD level expert fact check, edit, and contribute to articles. Reviewers ensure all content reflects expert academic consensus and is backed up with reference to academic studies. Dr. Drew has published over 20 academic articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education and holds a PhD in Education from ACU.

• Chris Drew (PhD) #molongui-disabled-link 25 Positive Punishment Examples
• Chris Drew (PhD) #molongui-disabled-link 25 Dissociation Examples (Psychology)
• Chris Drew (PhD) #molongui-disabled-link 15 Zone of Proximal Development Examples
• Chris Drew (PhD) #molongui-disabled-link Perception Checking: 15 Examples and Definition

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The Mind and Brain of Short-Term Memory

The past 10 years have brought near-revolutionary changes in psychological theories about short-term memory, with similarly great advances in the neurosciences. Here, we critically examine the major psychological theories (the “mind”) of short-term memory and how they relate to evidence about underlying brain mechanisms. We focus on three features that must be addressed by any satisfactory theory of short-term memory. First, we examine the evidence for the architecture of short-term memory, with special attention to questions of capacity and how—or whether—short-term memory can be separated from long-term memory. Second, we ask how the components of that architecture enact processes of encoding, maintenance, and retrieval. Third, we describe the debate over the reason about forgetting from short-term memory, whether interference or decay is the cause. We close with a conceptual model tracing the representation of a single item through a short-term memory task, describing the biological mechanisms that might support psychological processes on a moment-by-moment basis as an item is encoded, maintained over a delay with some forgetting, and ultimately retrieved.

INTRODUCTION

Mentally add 324 and 468. Follow the instructions to complete any form for your federal income taxes. Read and comprehend this sentence.

What are the features of the memory system that allows us to complete these and other complex tasks? Consider the opening example. First, you must create a temporary representation in memory for the two numbers. This representation needs to survive for several seconds to complete the task. You must then allocate your attention to different portions of the representation so that you can apply the rules of arithmetic required by the task. By one strategy, you need to focus attention on the “tens” digits (“2” and “6”) and mitigate interference from the other digits (e.g., “3” and “4”) and from partial results of previous operations (e.g., the “12” that results from adding “4” and “8”). While attending to local portions of the problem, you must also keep accessible the parts of the problem that are not in the current focus of attention (e.g., that you now have the units digit “2” as a portion of the final answer). These tasks implicate a short-term memory (STM). In fact, there is hardly a task that can be completed without the involvement of STM, making it a critical component of cognition.

Our review relates the psychological phenomena of STM to their underlying neural mechanisms. The review is motivated by three questions that any adequate account of STM must address:

1. What is its structure?

A proper theory must describe an architecture for short-term storage. Candidate components of this architecture include storage buffers, a moving and varying focus of attention, or traces with differing levels of activation. In all cases, it is essential to provide a mechanism that allows a representation to exist beyond the sensory stimulation that caused it or the process that retrieved the representation from long-term memory (LTM). This architecture should be clear about its psychological constructs. Furthermore, being clear about the neural mechanisms that implement those constructs will aid in development of psychological theory, as we illustrate below.

2. What processes operate on the stored information?

A proper theory must articulate the processes that create and operate on representations. Candidate processes include encoding and maintenance operations, rehearsal, shifts of attention from one part of the representation to another, and retrieval mechanisms. Some of these processes are often classified as executive functions.

3. What causes forgetting?

A complete theory of STM must account for the facts of forgetting. Traditionally, the two leading contending accounts of forgetting have relied on the concepts of decay and interference. We review the behavioral and neurophysiological evidence that has traditionally been brought to the table to distinguish decay and interference accounts, and we suggest a possible mechanism for short-term forgetting.

Most models of STM fall between two extremes: Multistore models view STM and LTM as architecturally separate systems that rely on distinct representations. By contrast, according to unitary-store models, STM and LTM rely largely on the same representations, but differ by ( a ) the level of activation of these representations and ( b ) some of the processes that normally act upon them. We focus on the distinctions drawn by these theories as we examine the evidence concerning the three questions that motivate our review. In this discussion, we assume that a representation in memory consists of a bundle of features that define a memorandum, including the context in which that memorandum was encountered.

WHAT IS THE STRUCTURE OF SHORT-TERM MEMORY?

Multistore models that differentiate short- and long-term memory.

In his Principles of Psychology , William James (1890) articulated the view that short-term (“primary”) memory is qualitatively different from long-term (“secondary”) memory (see also Hebb 1949 ). The most influential successor to this view is the model of STM developed by Baddeley and colleagues (e.g., Baddeley 1986 , 1992 ; Baddeley & Hitch 1974 ; Repov & Baddeley 2006 ). For the years 1980 to 2006, of the 16,154 papers that cited “working memory” in their titles or abstracts, fully 7339 included citations to Alan Baddeley.

According to Baddeley’s model, there are separate buffers for different forms of information. These buffers, in turn, are separate from LTM. A verbal buffer, the phonological loop, is assumed to hold information that can be rehearsed verbally (e.g., letters, digits). A visuospatial sketchpad is assumed to maintain visual information and can be further fractionated into visual/object and spatial stores ( Repov & Baddeley 2006 , Smith et al. 1995 ). An episodic buffer that draws on the other buffers and LTM has been added to account for the retention of multimodal information ( Baddeley 2000 ). In addition to the storage buffers described above, a central executive is proposed to organize the interplay between the various buffers and LTM and is implicated in controlled processing.

In short, the multistore model includes several distinctions: ( a ) STM is distinct from LTM, ( b ) STM can be stratified into different informational buffers based on information type, and ( c ) storage and executive processes are distinguishable. Evidence in support of these claims has relied on behavioral interference studies, neuropsychological studies, and neuroimaging data.

Evidence for the distinction between short- and long-term memory

Studies of brain-injured patients who show a deficit in STM but not LTM or vice versa lead to the implication that STM and LTM are separate systems. 1 Patients with parietal and temporal lobe damage show impaired short-term phonological capabilities but intact LTM( Shallice & Warrington 1970 , Vallar & Papagno 2002 ). Conversely, it is often claimed that patients with medial temporal lobe (MTL) damage demonstrate impaired LTM but preserved STM (e.g., Baddeley & Warrington 1970 , Scoville & Milner 1957 ; we reinterpret these effects below).

Neuroimaging data from healthy subjects have yielded mixed results, however. A meta-analysis comparing regions activated during verbal LTM and STM tasks indicated a great deal of overlap in neural activation for the tasks in the frontal and parietal lobes ( Cabeza et al. 2002 , Cabeza & Nyberg 2000 ). Three studies that directly compared LTM and STM in the same subjects did reveal some regions selective for each memory system ( Braver et al. 2001 , Cabeza et al. 2002 , Talmi et al. 2005 ). Yet, of these studies, only one found that the MTL was uniquely activated for LTM ( Talmi et al. 2005 ). What might account for the discrepancy between the neuropsychological and neuroimaging data?

One possibility is that neuroimaging tasks of STM often use longer retention intervals than those employed for neuropsychological tasks, making the STM tasks more similar to LTM tasks. In fact, several studies have shown that the MTL is important when retention intervals are longer than a few seconds ( Buffalo et al. 1998 , Cabeza et al. 2002 , Holdstock et al. 1995 , Owen et al. 1995 ). Of the studies that compared STM and LTM in the same subjects, only Talmi et al. (2005) used an STM retention interval shorter than five seconds. This study did find, in fact, that the MTL was uniquely recruited at longer retention intervals, providing support for the earlier neuropsychological work dissociating long- and short-term memory. As we elaborate below, however, there are other possible interpretations, especially with regard to the MTL’s role in memory.

Evidence for separate buffers in short-term memory

The idea that STM can be parceled into information-specific buffers first received support from a series of studies of selective interference (e.g., Brooks 1968 , den Heyer & Barrett 1971 ). These studies relied on the logic that if two tasks use the same processing mechanisms, they should show interfering effects on one another if performed concurrently. This work showed a double dissociation: Verbal tasks interfered with verbal STM but not visual STM, and visual tasks interfered with visual STM but not verbal STM, lending support to the idea of separable memory systems (for reviews, see Baddeley 1986 and Baddeley & Hitch 1974 ).

The advent of neuroimaging has allowed researchers to investigate the neural correlates of the reputed separability of STM buffers. Verbal STM has been shown to rely primarily on left inferior frontal and left parietal cortices, spatial STM on right posterior dorsal frontal and right parietal cortices, and object/visual STM on left inferior frontal, left parietal, and left inferior temporal cortices (e.g., Awh et al. 1996 , Jonides et al. 1993 , Smith & Jonides 1997 ; see review by Wager & Smith 2003 ). Verbal STM shows a marked left hemisphere preference, whereas spatial and object STM can be distinguished mainly by a dorsal versus ventral separation in posterior cortices (consistent with Ungerleider & Haxby 1994 ; see Baddeley 2003 for an account of the function of these regions in the service of STM).

The more recently postulated episodic buffer arose from the need to account for interactions between STM buffers and LTM. For example, the number of words recalled in an STM experiment can be greatly increased if the words form a sentence ( Baddeley et al. 1987 ). This “chunking” together of words to increase short-term capacity relies on additional information from LTM that can be used to integrate the words ( Baddeley 2000 ). Thus, there must be some representational space that allows for the integration of information stored in the phonological loop and LTM. This ability to integrate information from STM and LTM is relatively preserved even when one of these memory systems is damaged ( Baddeley & Wilson 2002 , Baddeley et al. 1987 ). These data provide support for an episodic buffer that is separable from other short-term buffers and from LTM ( Baddeley 2000 , Baddeley & Wilson 2002 ). Although neural evidence about the possible localization of this buffer is thin, there is some suggestion that dorsolateral prefrontal cortex plays a role ( Prabhakaran et al. 2000 , Zhang et al. 2004 ).

Evidence for separate storage and executive processes

Baddeley’s multistore model assumes that a collection of processes act upon the information stored in the various buffers. Jointly termed the “central executive,” these processes are assumed to be separate from the storage buffers and have been associated with the frontal lobes.

Both lesion and neuroimaging data support the distinction between storage and executive processes. For example, patients with frontal damage have intact STM under conditions of low distraction ( D’Esposito & Postle 1999 , 2000 ; Malmo 1942 ). However, when distraction is inserted during a delay interval, thereby requiring the need for executive processes to overcome interference, patients with frontal damage show significant memory deficits ( D’Esposito & Postle 1999 , 2000 ). By contrast, patients with left temporo-parietal damage show deficits in phonological storage, regardless of the effects of interference ( Vallar & Baddeley 1984 , Vallar & Papagno 2002 ).

Consistent with these patterns, a meta-analysis of 60 functional neuroimaging studies indicated that increased demand for executive processing recruits dorsolateral frontal cortex and posterior parietal cortex ( Wager & Smith 2003 ). By contrast, storage processes recruit predominately posterior areas in primary and secondary association cortex. These results corroborate the evidence from lesion studies and support the distinction between storage and executive processing.

Unitary-Store Models that Combine Short-Term and Long-Term Memory

The multistore models reviewed above combine assumptions about the distinction between short-term and long-term systems, the decomposition of short-term memory into information-specific buffers, and the separation of systems of storage from executive functions. We now consider unitary models that reject the first assumption concerning distinct systems.

Contesting the idea of separate long-term and short-term systems

The key data supporting separable short-term and long-term systems come from neuropsychology. To review, the critical contrast is between patients who show severely impaired LTM with apparently normal STM (e.g., Cave & Squire 1992 , Scoville & Milner 1957 ) and those who show impaired STM with apparently normal LTM (e.g., Shallice & Warrington 1970 ). However, questions have been raised about whether these neuropsychological studies do, in fact, support the claim that STM and LTM are separable. A central question is the role of the medial temporal lobe. It is well established that the MTL is critical for long-term declarative memory formation and retrieval ( Gabrieli et al. 1997 , Squire 1992 ). However, is the MTL also engaged by STM tasks? Much research with amnesic patients showing preserved STM would suggest not, but Ranganath & Blumenfeld (2005) have summarized evidence showing that MTL is engaged in short-term tasks (see also Ranganath & D’Esposito 2005 and Nichols et al. 2006 ).

In particular, there is growing evidence that a critical function of the MTL is to establish representations that involve novel relations. These relations may be among features or items, or between items and their context. By this view, episodic memory is a special case of such relations (e.g., relating a list of words to the experimental context in which the list was recently presented), and the special role of the MTL concerns its binding capabilities, not the timescale on which it operates. STM that is apparently preserved in amnesic patients may thus reflect a preserved ability to maintain and retrieve information that does not require novel relations or binding, in keeping with their preserved retrieval of remote memories consolidated before the amnesia-inducing lesion.

If this view is correct, then amnesic patients should show deficits in situations that require STM for novel relations, which they do (Hannula et al. 2005, Olson et al. 2006b ). They also show STM deficits for novel materials (e.g., Buffalo et al. 1998 , Holdstock et al. 1995 , Olson et al. 1995, 2006a ). As mentioned above, electrophysiological and neuroimaging studies support the claim that the MTL is active in support of short-term memories (e.g., Miyashita & Chang 1968 , Ranganath & D’Esposito 2001 ). Taken together, the MTL appears to operate in both STM and LTM to create novel representations, including novel bindings of items to context.

Additional evidence for the STM-LTM distinction comes from patients with perisylvian cortical lesions who are often claimed to have selective deficits in STM (e.g., Hanley et al. 1991 , Warrington & Shallice 1969 ). However, these deficits may be substantially perceptual. For example, patients with left perisylvian damage that results in STM deficits also have deficits in phonological processing in general, which suggests a deficit that extends beyond STM per se (e.g., Martin 1993 ).

The architecture of unitary-store models

Our review leads to the conclusion that short- and long-term memory are not architecturally separable systems—at least not in the strong sense of distinct underlying neural systems. Instead, the evidence points to a model in which short-term memories consist of temporary activations of long-term representations. Such unitary models of memory have a long history in cognitive psychology, with early theoretical unification achieved via interference theory ( Postman 1961 , Underwood & Schultz 1960). Empirical support came from demonstrations that memories in both the short and long term suffered from proactive interference (e.g., Keppel & Underwood 1962 ).

Perhaps the first formal proposal that short-term memory consists of activated long-term representations was by Atkinson & Shiffrin (1971 , but also see Hebb 1949) . The idea fell somewhat out of favor during the hegemony of the Baddeley multistore model, although it was given its first detailed computational treatment by Anderson (1983) . It has recently been revived and greatly developed by Cowan (1988 , 1995 , 2000) , McElree (2001) , Oberauer (2002) , Verhaeghen et al. (2004) , Anderson et al. (2004) , and others. The key assumption is the construct of a very limited focus of attention, although as we elaborate below, there are disagreements regarding the scope of the focus.

One shared assumption of these models is that STM consists of temporary activations of LTM representations or of representations of items that were recently perceived. The models differ from one to another regarding specifics, but Cowan’s model (e.g., Cowan 2000 ) is representative. According to this model, there is only one set of representations of familiar material—the representations in LTM. These representations can vary in strength of activation, where that strength varies as a function of such variables as recency and frequency of occurrence. Representations that have increased strength of activation are more available for retrieval in STM experiments, but they must be retrieved nonetheless to participate in cognitive action. In addition, these representations are subject to forgetting over time. A special but limited set of these representations, however, can be within the focus of attention, where being within the focus makes these representations immediately available for cognitive processing. According to this and similar models, then, STM is functionally seen as consisting of LTM representations that are either in the focus of attention or at a heightened level of activation.

These unitary-store models suggest a different interpretation of frontal cortical involvement in STM from multistore models. Early work showing the importance of frontal cortex for STM, particularly that of Fuster and Goldman-Rakic and colleagues, was first seen as support for multistore models (e.g., Funahashi et al. 1989 , Fuster 1973 , Jacobsen 1936 , Wilson et al. 1993 ). For example, single-unit activity in dorsolateral prefrontal cortex regions (principal sulcus, inferior convexity) that was selectively responsive to memoranda during the delay interval was interpreted as evidence that these regions were the storage sites for STM. However, the sustained activation of frontal cortex during the delay period does not necessarily mean that this region is a site of STM storage. Many other regions of neo-cortex also show activation that outlasts the physical presence of a stimulus and provides a possible neural basis for STM representations (see Postle 2006 ). Furthermore, increasing evidence suggests that frontal activations reflect the operation of executive processes [including those needed to keep the representations in the focus of attention; see reviews by Postle (2006) , Ranganath & D’Esposito (2005) , Reuter-Lorenz & Jonides (2007) , and Ruchkin et al. (2003) ]. Modeling work and lesion data provide further support for the idea that the representations used in both STM and LTM are stored in those regions of cortex that are involved in initial perception and encoding, and that frontal activations reflect processes involved in selecting this information for the focus of attention and keeping it there ( Damasio 1989 , McClelland et al. 1995 ).

The principle of posterior storage also allows some degree of reconciliation between multi- and unitary-store models. Posterior regions are clearly differentiated by information type (e.g., auditory, visual, spatial), which could support the information-specific buffers postulated by multistore models. Unitary-store models focus on central capacity limits, irrespective of modality, but they do allow for separate resources ( Cowan 2000 ) or feature components ( Lange & Oberauer 2005 , Oberauer & Kliegl 2006 ) that occur at lower levels of perception and representation. Multi- and unitary-store models thus both converge on the idea of modality-specific representations (or components of those representations) supported by distinct posterior neural systems.

Controversies over Capacity

Regardless of whether one subscribes to multi- or unitary-store models, the issue of how much information is stored in STM has long been a prominent one ( Miller 1956 ). Multistore models explain capacity estimates largely as interplay between the speed with which information can be rehearsed and the speed with which information is forgotten ( Baddeley 1986 , 1992 ; Repov & Baddeley 2006 ). Several studies have measured this limit by demonstrating that approximately two seconds worth of verbal information can be re-circulated successfully (e.g., Baddeley et al. 1975 ).

Unitary-store models describe capacity as limited by the number of items that can be activated in LTM, which can be thought of as the bandwidth of attention. However, these models differ on what that number or bandwidth might be. Cowan (2000) suggested a limit of approximately four items, based on performance discontinuities such as errorless performance in immediate recall when the number of items is less than four, and sharp increases in errors for larger numbers. (By this view, the classic “seven plus or minus two” is an overestimate because it is based on studies that allowed participants to engage in processes of rehearsal and chunking, and reflected contributions of both the focus and LTM; see also Waugh & Norman 1965 .) At the other extreme are experimental paradigms suggesting that the focus of attention consists of a single item ( Garavan 1998 , McElree 2001 , Verhaeghen & Basak 2007 ). We briefly consider some of the central issues behind current controversies concerning capacity estimates.

Behavioral and neural evidence for the magic number 4

Cowan (2000) has reviewed an impressive array of studies leading to his conclusion that the capacity limit is four items, plus or minus one (see his Table 1). Early behavioral evidence came from studies showing sharp drop-offs in performance at three or four items on short-term retrieval tasks (e.g., Sperling 1960 ). These experiments were vulnerable to the criticism that this limit might reflect output interference occurring during retrieval rather than an actual limit on capacity. However, additional evidence comes from change-detection and other tasks that do not require the serial recall of individual items. For example, Luck & Vogel (1997) presented subjects with 1 to 12 colored squares in an array. After a blank interval of nearly a second, another array of squares was presented, in which one square may have changed color. Subjects were to respond whether the arrays were identical. These experiments and others that avoid the confound of output-interference (e.g., Pashler 1988 ) likewise have yielded capacity estimates of approximately four items.

Electrophysiological and neuroimaging studies also support the idea of a four-item capacity limit. The first such report was by Vogel & Machizawa (2004) , who recorded event-related potentials (ERPs) from subjects as they performed a visual change-detection task. ERP recording shortly after the onset of the retention interval in this task indicated a negative-going wave over parietal and occipital sites that persisted for the duration of the retention interval and was sensitive to the number of items held in memory. Importantly, this signal plateaued when array size reached between three and four items. The amplitude of this activity was strongly correlated with estimates of each subject’s memory capacity and was less pronounced on incorrect than correct trials, indicating that it was causally related to performance. Subsequent functional magnetic resonance imaging (fMRI) studies have observed similar load- and accuracy-dependent activations, especially in intraparietal and intraoccipital sulci ( Todd & Marois 2004 , 2005 ). These regions have been implicated by others (e.g., Yantis & Serences 2003 ) in the control of attentional allocation, so it seems plausible that one rate-limiting step in STM capacity has to do with the allocation of attention ( Cowan 2000 ; McElree 1998 , 2001 ; Oberauer 2002 ).

Evidence for more severe limits on focus capacity

Another set of researchers agree there is a fixed capacity, but by measuring a combination of response time and accuracy, they contend that the focus of attention is limited to just one item (e.g., Garavan 1998 , McElree 2001 , Verhaeghen & Basak 2007 ). For example, Garavan (1998) required subjects to keep two running counts in STM, one for triangles and one for squares—as shape stimuli appeared one after another in random order. Subjects controlled their own presentation rate, which allowed Garavan to measure the time spent processing each figure before moving on. He found that responses to a figure of one category (e.g., a triangle) that followed a figure from the other category (e.g., a square) were fully 500 milliseconds longer than responses to the second of two figures from the same category (e.g., a triangle followed by another triangle). These findings suggested that attention can be focused on only one internal counter in STM at a time. Switching attention from one counter to another incurred a substantial cost in time. Using a speed-accuracy tradeoff procedure, McElree (1998) came to the same conclusion that the focus of attention contained just one item. He found that the retrieval speed for the last item in a list was substantially faster than for any other item in the list, and that other items were retrieved at comparable rates to each other even though the accuracy of retrieval for these other items varied.

Oberauer (2002) suggested a compromise solution to the “one versus four” debate. In his model, up to four items can be directly accessible, but only one of these items can be in the focus of attention. This model is similar to that of Cowan (2000) , but adds the assumption that an important method of accessing short-term memories is to focus attention on one item, depending on task demands. Thus, in tasks that serially demand attention on several items (such as those of Garavan 1998 or McElree 2001 ), the mechanism that accomplishes this involves changes in the focus of attention among temporarily activated representations in LTM.

Alternatives to capacity limits based on number of items

Attempting to answer the question of how many items may be held in the focus implicitly assumes that items are the appropriate unit for expressing capacity limits. Some reject this basic assumption. For example, Wilken & Ma (2004) demonstrated that a signal-detection account of STM, in which STM capacity is primarily constrained by noise, better fit behavioral data than an item-based fixed-capacity model. Recent data from change-detection tasks suggest that object complexity ( Eng et al. 2005 ) and similarity ( Awh et al. 2007 ) play an important role in determining capacity. Xu & Chun (2006) offer neuroimaging evidence that may reconcile the item-based and complexity accounts: In a change-detection task, they found that activation of inferior intra-parietal sulcus tracked a capacity limit of four, but nearby regions were sensitive to the complexity of the memoranda, as were the behavioral results.

Other researchers disagree with fixed item-based limits because they have demonstrated that the limit is mutable. Practice may improve subjects’ ability to use processes such as chunking to allow greater functional capacities ( McElree 1998 , Verhaeghen et al. 2004 ; but see Oberauer 2006 ). However, this type of flexibility appears to alter the amount of information that can be compacted into a single representation rather than the total number of representations that can be held in STM ( Miller 1956 ). The data of Verhaegen et al. (2004; see Figure 5 of that paper) suggest that the latter number still approximates four, consistent with Cowan’s claims.

Building on these findings, we suggest a new view of capacity. The fundamental idea that attention can be allocated to one piece of information in memory is correct, but the definition of what that one piece is needs to be clarified. It cannot be that just one item is in the focus of attention because if that were so, hardly any computation would be possible. How could one add 3+4, for example, if at any one time, attention could be allocated only to the “3” or the “4” or the “+” operation? We propose that attention focuses on what is bound together into a single “functional context,” whether that context is defined by time, space, some other stimulus characteristic such as semantic or visual similarity or momentary task relevance. By this account, attention can be placed on the whole problem “3+4,” allowing relevant computations to be made. Complexity comes into play by limiting the number of subcomponents that can be bound into one functional context.

What are we to conclude from the data concerning the structure of STM? We favor the implication that the representational bases for perception, STM, and LTM are identical. That is, the same neural representations initially activated during the encoding of a piece of information show sustained activation during STM (or retrieval from LTM into STM; Wheeler et al. 2000 ) and are the repository of long-term representations. Because regions of neocortex represent different sorts of information (e.g., verbal, spatial), it is reasonable to expect that STM will have an organization by type of material as well. Functionally, memory in the short term seems to consist of items in the focus of attention along with recently attended representations in LTM. These items in the focus of attention number no more than four, and they may be limited to just a single representation (consisting of items bound within a functional context).

We turn below to processes that operate on these representations.

WHAT PROCESSES OPERATE ON THE STORED INFORMATION?

Theoretical debate about the nature of STM has been dominated by discussion of structure and capacity, but the issue of process is also important. Verbal rehearsal is perhaps most intuitively associated with STM and plays a key role in the classic model ( Baddeley 1986 ). However, as we discuss below, rehearsal most likely reflects a complex strategy rather than a primitive STM process. Modern approaches offer a large set of candidate processes, including encoding and maintenance ( Ranganath et al. 2004 ), attention shifts ( Cowan 2000 ), spatial rehearsal ( Awh & Jonides 2001 ), updating (Oberauer 2005), overwriting ( Neath & Nairne 1995 ), cue-based parallel retrieval ( McElree 2001 ), and interference-resolution ( Jonides & Nee 2006 ).

Rather than navigating this complex and growing list, we take as our cornerstone the concept of a limited focus of attention. The central point of agreement for the unitary-store models discussed above is that there is a distinguishable focus of attention in which representations are directly accessible and available for cognitive action. Therefore, it is critical that all models must identify the processes that govern the transition of memory representations into and out of this focused state.

The Three Core Processes of Short-Term Memory: Encoding, Maintenance, and Retrieval

If one adopts the view that a limited focus of attention is a key feature of short-term storage, then understanding processing related to this limited focus amounts to understanding three basic types of cognitive events 2 : ( a ) encoding processes that govern the transformation from perceptual representations into the cognitive/attentional focus, ( b ) maintenance processes that keep information in the focus (and protect it from interference or decay), and ( c ) retrieval processes that bring information from the past back into the cognitive focus (possibly reactivating perceptual representations).

Encoding of items into the focus

Encoding processes are the traditional domain of theories of perception and are not treated explicitly in any of the current major accounts of STM. Here we outline three implicit assumptions about encoding processes made in most accounts of STM, and we assess their empirical and theoretical support.

First, the cognitive focus is assumed to have immediate access to perceptual processing— that is, the focus may include contents from the immediate present as well as contents retrieved from the immediate past. In Cowan’s (2000) review of evidence in favor of the number four in capacity estimates, several of the experimental paradigms involve focused representations of objects in the immediate perceptual present or objects presented less than a second ago. These include visual tracking experiments ( Pylyshyn et al. 1994 ), enumeration ( Trick & Pylyshyn 1993 ), and whole report of spatial arrays and spatiotemporal arrays ( Darwin et al. 1972 , Sperling 1960 ). Similarly, in McElree’s (2006) and Garavan’s (1998) experiments, each incoming item in the stream of material (words or letters or objects) is assumed to be represented momentarily in the focus.

Second, all of the current theories assume that perceptual encoding into the focus of attention results in a displacement of other items from the focus. For example, in McElree’s single-item focus model, each incoming item not only has its turn in the focus, but it also replaces the previous item. On the one hand, the work reviewed above regarding performance discontinuities after the putative limit of STM capacity has been reached appears to support the idea of whole-item displacement. On the other hand, as also described above, this limit may be susceptible to factors such as practice and stimulus complexity. An alternative to whole-item displacement as the basis for interference is a graded similarity-based interference, in which new items entering the focus may partially overwrite features of the old items or compete with old items to include those featural components in their representations as a function of their similarity. At some level, graded interference is clearly at work in STM, as Nairne (2002) and others have demonstrated (we review this evidence in more detail below). But the issue at hand is whether the focus is subject to such graded interference, and if such interference is the process by which encoding (or retrieving) items into the focus displaces prior items. Although there does not appear to be evidence that bears directly on this issue (the required experiments would involve manipulations of similarity in just the kinds of paradigms that Cowan, McElree, Oberauer, and others have used to provide evidence for the limited focus), the performance discontinuities strongly suggest that something like displacement is at work.

Third, all of the accounts assume that perceptual encoding does not have obligatory access to the focus. Instead, encoding into the focus is modulated by attention. This follows rather directly from the assumptions about the severe limits on focus capacity: There must be some controlled way of directing which aspects of the perceptual present, as well as the cognitive past, enter into the focused state. Stated negatively, there must be some way of preventing aspects of the perceptual present from automatically entering into the focused state. Postle (2006) recently found that increased activity in dorsolateral prefrontal cortex during the presentation of distraction during a retention interval was accompanied by a selective decrease in inferior temporal cortical activity. This pattern suggests that prefrontal regions selectively modulated posterior perceptual areas to prevent incoming sensory input from disrupting the trace of the task-relevant memorandum.

In summary, current approaches to STM have an obligation to account for how controlled processes bring relevant aspects of perception into cognitive focus and leave others out. It is by no means certain that existing STM models and existing models of perceptual attention are entirely compatible on this issue, and this is a matter of continued lively debate ( Milner 2001 , Schubert & Frensch 2001 , Woodman et al. 2001 ).

Maintenance of items in the focus

Once an item is in the focus of attention, what keeps it there? If the item is in the perceptual present, the answer is clear: attention-modulated, perceptual encoding. The more pressing question is: What keeps something in the cognitive focus when it is not currently perceived? For many neuroscientists, this is the central question of STM—how information is held in mind for the purpose of future action after the perceptual input is gone. There is now considerable evidence from primate models and from imaging studies on humans for a process of active maintenance that keeps representations alive and protects them from irrelevant incoming stimuli or intruding thoughts (e.g., Postle 2006 ).

We argue that this process of maintenance is not the same as rehearsal. Indeed, the number of items that can be maintained without rehearsal forms the basis of Cowan’s (2000) model. Under this view, rehearsal is not a basic process but rather is a strategy for accomplishing the functional demands for sustaining memories in the short term—a strategy composed of a series of retrievals and re-encodings. We consider rehearsal in more detail below, but we consider here the behavioral and neuroimaging evidence for maintenance processes.

There is now considerable evidence from both primate models and human electroencephalography and fMRI studies for a set of prefrontal-posterior circuits underlying active maintenance. Perhaps the most striking is the classic evidence from single-cell recordings showing that some neurons in prefrontal cortex fire selectively during the delay period in delayed-match-to-sample tasks (e.g., Funahashi et al. 1989 , Fuster 1973 ). As mentioned above, early interpretations of these frontal activations linked them directly to STM representations ( Goldman-Rakic 1987 ), but more recent theories suggest they are part of a frontal-posterior STM circuit that maintains representations in posterior areas ( Pasternak & Greenlee 2005 , Ranganath 2006 , Ruchkin et al. 2003 ). Furthermore, as described above, maintenance operations may modulate perceptual encoding to prevent incoming perceptual stimuli from disrupting the focused representation in posterior cortex ( Postle 2006 ). Several computational neural-network models of circuits for maintenance hypothesize that prefrontal cortical circuits support attractors, self-sustaining patterns observed in certain classes of recurrent networks ( Hopfield 1982 , Rougier et al. 2005 , Polk et al. 2002 ). A major challenge is to develop computational models that are able to engage in active maintenance of representations in posterior cortex while simultaneously processing, to some degree, incoming perceptual material (see Renart et al. 1999 for a related attempt).

Retrieval of items into the focus

Many of the major existing STM architectures are silent on the issue of retrieval. However, all models that assume a limited focus also assume that there is some means by which items outside that focus (either in a dormant long-term store or in some highly activated portion of LTM) are brought into the focus by switching the attentional focus onto those items. Following Sternberg (1966) , McElree (2006) , and others, we label this process “retrieval.” Despite this label, it is important to keep in mind that the associated spatial metaphor of an item moving from one location to another is misleading given our assumption about the common neural representations underlying STM and LTM.

There is now considerable evidence, mostly from mathematical models of behavioral data, that STM retrieval of item information is a rapid, parallel, content-addressable process. The current emphasis on parallel search processes is quite different from the earliest models of STM retrieval, which postulated a serial scanning process (i.e., Sternberg 1966 ; see McElree 2006 for a recent review and critique). Serial-scanning models fell out of favor because of empirical and modeling work showing that parallel processes provide a better account of the reaction time distributions in STM tasks (e.g., Hockley 1984 ). For example, McElree has created a variation on the Sternberg recognition probe task that provides direct support for parallel, rather than serial, retrieval. In the standard version of the task, participants are presented with a memory set consisting of a rapid sequence of verbal items (e.g., letters or digits), followed by a probe item. The task is to identify whether the probe was a member of the memory set. McElree & Dosher’s (1989) innovation was to manipulate the deadline for responding. The time course of retrieval (accuracy as a function of response deadline) can be separately plotted for each position within the presentation sequence, allowing independent assessments of accessibility (how fast an item can be retrieved) and availability (asymptotic accuracy) as a function of set size and serial position. Many experiments yield a uniform rate of access for all items except for the most recent item, which is accessed more quickly. The uniformity of access rate is evidence for parallel access, and the distinction between the most recent item and the other items is evidence for a distinguished focus of attention.

Neural Mechanisms of Short- and Long-Term Memory Retrieval

The cue-based retrieval processes described above for STM are very similar to those posited for LTM (e.g., Anderson et al. 2004 , Gillund & Shiffrin 1984 , Murdock 1982 ). As a result, retrieval failures resulting from similarity-based interference and cue overlap are ubiquitous in both STM and LTM. Both classic studies of recall from STM (e.g., Keppel & Underwood 1962 ) and more recent studies of interference in probe-recognition tasks (e.g., Jonides & Nee 2006 , McElree & Dosher 1989 , Monsell 1978 ) support the idea that interference plays a major role in forgetting over short retention intervals as well as long ones (see below). These common effects would not be expected if STM retrieval were a different process restricted to operate over a limited buffer, but they are consistent with the notion that short-term and long-term retrieval are mediated by the same cue-based mechanisms.

The heavy overlap in the neural substrates for short-term and long-term retrieval provides additional support for the idea that retrieval processes are largely the same over different retention intervals. A network of medial temporal regions, lateral prefrontal regions, and anterior prefrontal regions has been extensively studied and shown to be active in long-term retrieval tasks (e.g., Buckner et al. 1998 , Cabeza & Nyberg 2000 , Fletcher & Henson 2001 ). We reviewed above the evidence for MTL involvement in both short- and long-term memory tasks that require novel representations (see section titled “Contesting the Idea of Separate Long-Term and Short-Term Systems”). Here, we examine whether the role of frontal cortex is the same for both short- and long-term retrieval.

The conclusion derived from neuroimaging studies of various different STM procedures is that this frontal role is the same in short-term and long-term retrieval. For example, several event-related fMRI studies of the retrieval stage of the probe-recognition task found increased activation in lateral prefrontal cortex similar to the activations seen in studies of LTM retrieval (e.g., D’Esposito et al. 1999 , D’Esposito & Postle 2000 , Manoach et al. 2003 ). Badre & Wagner (2005) also found anterior prefrontal activations that overlapped with regions implicated in episodic recollection. The relatively long retention intervals often used in event-related fMRI studies leaves them open to the criticism that by the time of the probe, the focus of attention has shifted elsewhere, causing the need to retrieve information from LTM (more on this discussion below). However, a meta-analysis of studies that involved bringing very recently presented items to the focus of attention likewise found specific involvement of lateral and anterior prefrontal cortex ( Johnson et al. 2005 ). These regions appear to be involved in retrieval, regardless of timescale.

The same conclusion may be drawn from recent imaging studies that have directly compared long- and short-term retrieval tasks using within-subjects designs ( Cabeza et al. 2002 , Ranganath et al. 2003 , Talmi et al. 2005 ). Ranganath et al. (2003) found the same bilateral ventrolateral and dorsolateral prefrontal regions engaged in both short- and long-term tasks. In some cases, STM and LTM tasks involve the same regions but differ in the relative amount of activation shown within those regions. For example, Cabeza et al. (2002) reported similar engagement of medial temporal regions in both types of task, but greater anterior and ventrolateral activation in the long-term episodic tasks. Talmi et al. (2005) reported greater activation in both medial temporal and lateral frontal cortices for recognition probes of items presented early in a 12-item list (presumably necessitating retrieval from LTM) versus items presented later in the list (presumably necessitating retrieval from STM). One possible reason for this discrepancy is that recognition for late-list items did not require retrieval because these items were still in the focus of attention. This account is plausible since late-list items were drawn either from the last-presented or second-to-last presented item and preceded the probe by less than two seconds.

In summary, the bulk of the neuroimaging evidence points to the conclusion that the activation of frontal and medial temporal regions depends on whether the information is currently in or out of focus, not whether the task nominally tests STM or LTM. Similar reactivation processes occur during retrieval from LTM and from STM when the active maintenance has been interrupted (see Sakai 2003 for a more extensive review).

The Relationship of Short-Term Memory Processes to Rehearsal

Notably, our account of core STM processes excludes rehearsal. How does rehearsal fit in? We argue that rehearsal is simply a controlled sequence of retrievals and re-encodings of items into the focus of attention ( Baddeley 1986 , Cowan 1995 ). The theoretical force of this assumption can be appreciated by examining the predictions it makes when coupled with our other assumptions about the structures and processes of the underlying STM architecture. Below we outline these predictions and the behavioral, developmental, neuroimaging, and computational work that support this view.

Rehearsal as retrieval into the focus

When coupled with the idea of a single-item focus, the assumption that rehearsal is a sequence of retrievals into the focus of attention makes a very clear prediction: A just-rehearsed item should display the same retrieval dynamics as a just-perceived item. McElree (2006) directly tested this prediction using a version of his response-deadline recognition task, in which subjects were given a retention interval between presentation of the list and the probe rather than presented with the probe immediately after the list. Subjects were explicitly instructed to rehearse the list during this interval and were trained to do so at a particular rate. By controlling the rate, it was possible to know when each item was rehearsed and hence re-established in the focus. The results were compelling: When an item was predicted to be in focus because it had just been rehearsed, it showed the same fast retrieval dynamics as an item that had just been perceived. In short, the speed-accuracy tradeoff functions showed the familiar in-focus/out-of-focus dichotomy of the standard paradigm, but the dichotomy was established for internally controlled rehearsal as well as externally controlled perception.

Rehearsal as strategic retrieval

Rehearsal is often implicitly assumed as a component of active maintenance, but formal theoretical considerations of STM typically take the opposite view. For example, Cowan (2000) provides evidence that although first-grade children do not use verbal rehearsal strategies, they nevertheless have measurable focus capacities. In fact, Cowan (2000) uses this evidence to argue that the performance of very young children is revealing of the fundamental capacity limits of the focus of attention because it is not confounded with rehearsal.

If rehearsal is the controlled composition of more primitive STM processes, then rehearsal should activate the same brain circuits as the primitive processes, possibly along with additional (frontal) circuits associated with their control. In other words, there should be overlap of rehearsal with brain areas sub-serving retrieval and initial perceptual encoding. Likewise, there should be control areas distinct from those of the primitive processes.

Both predictions receive support from neuroimaging studies. The first prediction is broadly confirmed: There is now considerable evidence for the reactivation of areas associated with initial perceptual encoding in tasks that require rehearsal (see Jonides et al. 2005 for a recent review; note also that evidence exists for reactivation in LTM retrieval: Wheeler 2000 , 2006 ).

The second prediction—that rehearsal engages additional control areas beyond those participating in maintenance, encoding, and retrieval—receives support from two effects. One is that verbal rehearsal engages a set of frontal structures associated with articulation and its planning: supplementary motor, premotor, inferior frontal, and posterior parietal areas (e.g., Chein & Fiez 2001, Jonides et al. 1998 , Smith & Jonides 1999 ). The other is that spatial rehearsal engages attentionally mediated occipital regions, suggesting rehearsal processes that include retrieval of spatial information ( Awh et al. 1998 , 1999 , 2001 ).

Computational modeling relevant to strategic retrieval

Finally, prominent symbolic and connectionist computational models of verbal STM tasks are based on architectures that do not include rehearsal as a primitive process, but rather assume it as a strategic composition of other processes operating over a limited focus. The Burgess & Hitch (2005 , 2006) connectionist model, the Executive-Process/Interactive Control (EPIC) symbolic model ( Meyer and Kieras 1997 ), and the Atomic Components of Thought (ACT-R) hybrid model ( Anderson & Matessa 1997 ) all assume that rehearsal in verbal STM consists of a controlled sequence of retrievals of items into a focused state. They all assume different underlying mechanisms for the focus (the Burgess & Hitch model has a winner-take-all network; ACT-R has an architectural buffer with a capacity of one chunk; EPIC has a special auditory store), but all assume strategic use of this focus to accomplish rehearsal. These models jointly represent the most successful attempts to account for a range of detailed empirical phenomena traditionally associated with rehearsal, especially in verbal serial recall tasks. Their success therefore provides further support for the plausibility of a compositional view of rehearsal.

WHY DO WE FORGET?

Forgetting in STM is a vexing problem: What accounts for failures to retrieve something encoded just seconds ago? There are two major explanations for forgetting, often placed in opposition: time-based decay and similarity-based interference. Below, we describe some of the major findings in the literature related to each of these explanations, and we suggest that they may ultimately result from the same underlying principles.

Decay Theories: Intuitive but Problematic

The central claim of decay theory is that as time passes, information in memory erodes, and so it is less available for later retrieval. This explanation has strong intuitive appeal. However, over the years there have been sharp critiques of decay, questioning whether it plays any role at all (for recent examples, see Lewandowsky et al. 2004 and the review in this journal by Nairne 2002 ).

Decay explanations are controversial for two reasons: First, experiments attempting to demonstrate decay can seldom eliminate alternative explanations. For example, Keppel & Underwood (1962) demonstrated that forgetting in the classic Brown-Peterson paradigm (designed to measure time-based decay) was due largely, if not exclusively, to proactive interference from prior trials. Second, without an explanation of how decay occurs, it is difficult to see decay theories as more than a restatement of the problem. Some functional arguments have been made for the usefulness of the notion of memory decay—that decaying activations adaptively mirror the likelihood that items will need to be retrieved ( Anderson & Schooler 1991 ), or that decay is functionally necessary to reduce interference ( Altmann & Gray 2002 ). Nevertheless, McGeoch’s famous (1932) criticism of decay theories still holds merit: Rust does not occur because of time itself, but rather from oxidation processes that occur with time. Decay theories must explain the processes by which decay could occur, i.e., they must identify the oxidation process in STM.

Retention-interval confounds: controlling for rehearsal and retroactive interference

The main problem in testing decay theories is controlling for what occurs during the retention interval. Many experiments include an attention-demanding task to prevent participants from using rehearsal that would presumably circumvent decay. However, a careful analysis of these studies by Roediger et al. (1977) makes one wonder whether the use of a secondary task is appropriate to prevent rehearsal at all. They compared conditions in which a retention interval was filled by nothing, by a relatively easy task, or by a relatively difficult one. Both conditions with a filled interval led to worse memory performance, but the difficulty of the intervening task had no effect. Roediger et al. (1977) concluded that the primary memory task and the interpolated task, although demanding, used different processing pools of resources, and hence the interpolated tasks may not have been effective in preventing rehearsal. So, they argued, this sort of secondary-task technique may not prevent rehearsal and may not allow for a convincing test of a decay hypothesis.

Another problem with tasks that fill the retention interval is that they require subjects to use STM (consider counting backward, as in the Brown-Peterson paradigm). This could lead to active displacement of items from the focus according to views (e.g., McElree 2001 ) that posit such displacement as a mechanism of STM forgetting, or increase the noise according to interference-based explanations (see discussion below in What Happens Neurally During the Delay?). By either account, the problem with retention-interval tasks is that they are questionable ways to prevent rehearsal of the to-be-remembered information, and they introduce new, distracting information that may engage STM. This double-edged sword makes it difficult to tie retention-interval manipulations directly to decay.

Attempts to address the confounding factors

A potential way out of the rehearsal conundrum is to use stimuli that are not easily converted to verbal codes and that therefore may be difficult to rehearse. For example, Harris (1952) used tones that differed so subtly in pitch that they would be difficult to name by subjects without perfect pitch. On each trial, participants were first presented with a to-be-remembered tone, followed by a retention interval of 0.1 to 25 seconds, and finally a probe tone. The accuracy of deciding whether the initial and probe tones were the same declined with longer retention intervals, consistent with the predictions of decay theory.

Using another technique, McKone (1995 , 1998) reduced the probability of rehearsal or other explicit-memory strategies by using an implicit task. Words and nonwords were repeated in a lexical-decision task, with the measure of memory being faster performance on repeated trials than on novel ones (priming). To disentangle the effects of decay and interference, McKone varied the time between repetitions (the decay-related variable) while holding the number of items between repetitions (the interference-related variable) constant, and vice versa. She found that greater time between repetitions reduced priming even after accounting for the effects of intervening items, consistent with decay theory. However, interference and decay effects seemed to interact and to be especially important for nonwords.

Procedures such as those used by Harris (1952) and McKone (1995 , 1998) do not have the problems associated with retention-interval tasks. They are, however, potentially vulnerable to the criticism of Keppel & Underwood (1962) regarding interference from prior trials within the task, although McKone’s experiments address this issue to some degree. Another potential problem is that these participants’ brains and minds are not inactive during the retention interval ( Raichle et al. 2001 ). There is increasing evidence that the processes ongoing during nominal “resting states” are related to memory, including STM ( Hampson et al. 2006 ). Spontaneous retrieval by participants during the retention interval could interfere with memory for the experimental items. So, although experiments that reduce the influence of rehearsal provide some of the best evidence of decay, they are not definitive.

What happens neurally during the delay?

Neural findings of delay-period activity have also been used to support the idea of decay. For example, at the single-cell level, Fuster (1995) found that in monkeys performing a delayed-response task, delay-period activity in inferotemporal cortex steadily declined over 18 seconds (see also Pasternak & Greenlee 2005 ). At a molar level, human neuroimaging studies often show delay-period activity in prefrontal and posterior regions, and this activity is often thought to support maintenance or storage (see review by Smith & Jonides 1999 ). As reviewed above, it is likely that the posterior regions support storage and that frontal regions support processes related to interference-resolution, control, attention, response preparation, motivation, and reward.

Consistent with the suggestive primate data, Jha & McCarthy (2000) found a general decline in activation in posterior regions over a delay period, which suggests some neural evidence for decay. However, this decline in activation was not obviously related to performance, which suggests two (not mutually exclusive) possibilities: ( a ) the decline in activation was not representative of decay, so it did not correlate with performance, or ( b ) these regions might not have been storage regions (but see Todd & Marois 2004 and Xu & Chun 2006 for evidence more supportive of load sensitivity in posterior regions).

The idea that neural activity decays also faces a serious challenge in the classic results of Malmo (1942) , who found that a monkey with frontal lesions was able to perform a delayed response task extremely well (97% correct) if visual stimulation and motor movement (and therefore associated interference) were restricted during a 10-second delay. By contrast, in unrestricted conditions, performance was as low as 25% correct (see also Postle & D’Esposito 1999 ). In summary, evidence for time-based declines in neural activity that would naturally be thought to be part of a decay process is at best mixed.

Is there a mechanism for decay?

Although there are data supporting the existence of decay, much of these data are subject to alternative, interference-based explanations. However, as Crowder (1976) noted, “Good ideas die hard.” At least a few key empirical results ( Harris 1952 ; McKone 1995 , 1998) do seem to implicate some kind of time-dependent decay. If one assumes that decay happens, how might it occur?

One possibility—perhaps most compatible with results like those of Malmo (1942) —is that what changes over time is not the integrity of the representation itself, but the likelihood that attention will be attracted away from it. As more time passes, the likelihood increases that attention will be attracted away from the target and toward external stimuli or other memories, and it will be more difficult to return to the target representation. This explanation seems compatible with the focus-of-attention views of STM that we have reviewed. By this explanation, capacity limits are a function of attention limits rather than a special property of STM per se.

Another explanation, perhaps complementary to the first, relies on stochastic variability in the neuronal firing patterns that make up the target representation. The temporal synchronization of neuronal activity is an important part of the representation (e.g., Deiber et al. 2007 , Jensen 2006 , Lisman & Idiart 1995 ). As time passes, variability in the firing rates of individual neurons may cause them to fall increasingly out of synchrony unless they are reset (e.g., by rehearsal). As the neurons fall out of synchrony, by this hypothesis, the firing pattern that makes up the representation becomes increasingly difficult to discriminate from surrounding noise [see Lustig et al. (2005) for an example that integrates neural findings with computational ( Frank et al. 2001 ) and behaviorally based ( Brown et al. 2000 ) models of STM].

Interference Theories: Comprehensive but Complex

Interference effects play several roles in memory theory: First, they are the dominant explanation of forgetting. Second, some have suggested that STM capacity and its variation among individuals are largely determined by the ability to overcome interference (e.g., Hasher & Zacks 1988 , Unsworth & Engle 2007 ). Finally, differential interference effects in STM and LTM have been used to justify the idea that they are separate systems, and common interference effects have been used to justify the idea that they are a unitary system.

Interference theory has the opposite problem of decay: It is comprehensive but complex ( Crowder 1976 ). The basic principles are straightforward. Items in memory compete, with the amount of interference determined by the similarity, number, and strength of the competitors. The complexity stems from the fact that interference may occur at multiple stages (encoding, retrieval, and possibly storage) and at multiple levels (the representation itself or its association with a cue or a response). Interference from the past (proactive interference; PI) may affect both the encoding and the retrieval of new items, and it often increases over time. By contrast, interference from new items onto older memories (retroactive interference; RI) frequently decreases over time and may not be as reliant on similarity (see discussion by Wixted 2004 ).

Below, we review some of the major findings with regard to interference in STM, including a discussion of its weaknesses in explaining short-term forgetting. We then present a conceptual model of STM that attempts to address these weaknesses and the questions regarding structure, process, and forgetting raised throughout this review.

Interference Effects in Short-Term Memory

Selection-based interference effects.

The Brown-Peterson task, originally conceived to test decay theory, became a workhorse for testing similarity-based interference as well. In the “release-from-PI” version ( Wickens 1970 ), short lists of categorized words are used as memoranda. Participants learn one three-item list on each trial, perform some other task during the retention interval, and then attempt to recall the list. For the first three trials, all lists consist of words from the same category (e.g., flowers). The typical PI effects occur: Recall declines over subsequent trials. The critical manipulation occurs at the final list. If it is from a different category (e.g., sports), recall is much higher than if it is from the same category as preceding trials. In some cases, performance on this set-shift or release from-PI trial is nearly as high as on the very first trial.

The release-from-PI effect was originally interpreted as an encoding effect. Even very subtle shifts (e.g., from “flowers” to “wild-flowers”) produce the effect if participants are warned about the shift before the words are presented (see Wickens 1970 for an explanation). However, Gardiner et al. (1972) showed that release also occurs if the shift-cue is presented only at the time of the retrieval test—i.e., after the list has been encoded. They suggested that cues at retrieval could reduce PI by differentiating items from the most recent list, thus aiding their selection.

Selection processes remain an important topic in interference research. Functional neuroimaging studies consistently identify a region in left inferior frontal gyrus (LIFG) as active during interference resolution, at least for verbal materials (see a review by Jonides & Nee 2006 ). This region appears to be generally important for selection among competing alternatives, e.g., in semantic memory as well as in STM ( Thompson-Schill et al. 1997 ). In STM, LIFG is most prominent during the test phase of interference trials, and its activation during this phase often correlates with behavioral measures of interference resolution ( D’Esposito et al. 1999 , Jonides et al. 1998 , Reuter-Lorenz et al. 2000 , Thompson-Schill et al. 2002 ). These findings attest to the importance of processes for resolving retrieval interference. The commonality of the neural substrate for interference resolution across short-term and long-term tasks provides yet further support for the hypothesis of shared retrieval processes for the two types of memory.

Interference effects occur at multiple levels, and it is important to distinguish between interference at the level of representations and interference at the level of responses. The LIFG effects described above appear to be familiarity based and to occur at the level of representations. Items on a current trial must be distinguished and selected from among items on previous trials that are familiar because of prior exposure but are currently incorrect. A separate contribution occurs at the level of responses: An item associated with a positive response on a prior trial may now be associated with a negative response, or vice versa. This response-based conflict can be separated from the familiarity-based conflict, and its resolution appears to rely more on the anterior cingulate ( Nelson et al. 2003 ).

Other mechanisms for interference effects?

Despite the early work of Keppel & Underwood (1962) , most studies examining encoding in STM have focused on RI: how new information disrupts previous memories. Early theorists described this disruption in terms of displacement of entire items from STM, perhaps by disrupting consolidation (e.g., Waugh & Norman 1965 ). However, rapid serial visual presentation studies suggest that this type of consolidation is complete within a very short time—approximately 500 milliseconds, and in some situations as short as 50 milliseconds ( Vogel et al. 2006 ).

What about interference effects beyond this time window? As reviewed above, most current focus-based models implicitly assume something like whole-item displacement is at work, but these models may need to be elaborated to account for retroactive similarity-based interference, such as the phonological interference effects reviewed by Nairne (2002) . The models of Nairne (2002) and Oberauer (2006) suggest a direction for such an elaboration. Rather than a competition at the item level for a single-focus resource, these models posit a lower-level similarity-based competition for “feature units.” By this idea, items in STM are represented as bundles of features (e.g., color, shape, spatial location, temporal location). Representations of these features in turn are distributed over multiple units. The more two items overlap, the more they compete for these feature units, resulting in greater interference. This proposed mechanism fits well with the idea that working memory reflects the heightened activation of representations that are distributed throughout sensory, semantic, and motor cortex ( Postle 2006 ), and that similarity-based interference constrains the capacity due to focusing (see above; Awh et al. 2007 ). Hence, rather than whole-item displacement, specific feature competition may underlie the majority of encoding-stage RI.

Interference-based decay?

Above, we proposed a mechanism for decay based on the idea that stochastic variability causes the neurons making up a representation to fall out of synchrony (become less coherent in their firing patterns). Using the terminology of Nairne (2002) and Oberauer (2006) , the feature units become less tightly bound. Importantly, feature units that are not part of a representation also show some random activity due to their own stochastic variability, creating a noise distribution. Over time, there is an increasing likelihood that the feature units making up the to-be-remembered item’s representation will overlap with those of the noise distribution, making them increasingly difficult to distinguish. This increasing overlap with the noise distribution and loss of feature binding could lead to the smooth forgetting functions often interpreted as evidence for decay.

Such a mechanism for decay has interesting implications. It may explain why PI effects interact with retention interval. Prior trials with similar items would structure the noise distribution so that it is no longer random but rather is biased to share components with the representation of the to-be remembered item (target). Representations of prior, now-irrelevant items might compete with the current target’s representation for control of shared feature units, increasing the likelihood (rate) at which these units fall out of synchrony.

Prior similar items may also dampen the fidelity of the target representation to begin with, weakening their initial binding and thus causing these items to fall out of synchrony more quickly. In addition, poorly learned items might have fewer differentiating feature units, and these units may be less tightly bound and therefore more vulnerable to falling out of synchrony. This could explain why Keppel & Underwood (1962) found that poorly learned items resulted in retention interval effects even on the first trial. It may also underlie the greater decay effects that McKone (1995 , 1998) found for nonwords than for words, if one assumes that non-words have fewer meaning-based units and connections.

A SUMMARY OF PRINCIPLES AND AN ILLUSTRATION OF SHORT-TERM MEMORY AT WORK

Here we summarize the principles of STM that seem best supported by the behavioral and neural evidence. Building on these principles, we offer a hypothetical sketch of the processes and neural structures that are engaged by a canonical STM task, the probe recognition task with distracting material.

Principles of Short-Term Memory

We have motivated our review by questions of structure, process, and forgetting. Rather than organize our summary this way, we wish to return here to the title of our review and consider what psychological and neural mechanisms seem best defended by empirical work. In that we have provided details about each of these issues in our main discussion, we summarize them here as bullet points. Taken together, they provide answers to our questions about structure, process, and forgetting.

The mind of short-term memory

Representations in memory are composed of bundles of features for stored information, including features representing the context in which that information was encountered.

• ■ Representations in memory vary in activation, with a dormant state characterizing long-term memories, and varying states of activation due to recent perceptions or retrievals of those representations.
• ■ There is a focus of attention in which a bound collection of information may be held in a state that makes it immediately available for cognitive action. Attention may be focused on only a single chunk of information at a time, where a chunk is defined as a set of items that are bound by a common functional context.
• ■ Items may enter the focus of attention via perceptual encoding or via cue-based retrieval from LTM.
• ■ Items are maintained in the focus via a controlled process of maintenance, with rehearsal being a case of controlled sequential allocation of attentional focus.
• ■ Forgetting occurs when items leave the focus of attention and must compete with other items to regain the focus (interference), or when the fidelity of the representation declines over time due to stochastic processes (decay).

The brain of short-term memory

Items in the focus of attention are represented by patterns of heightened, synchronized firing of neurons in primary and secondary association cortex.

• ■ The sensorimotor features of items in the focus of attention or those in a heightened state of activation are the same as those activated by perception or action. Information within a representation is associated with the cortical region that houses it (e.g., verbal, spatial, motor). In short, item representations are stored where they are processed.
• ■ Medial temporal structures are important for binding items to their context for both the short- and long-term and for retrieving items whose context is no longer in the focus of attention or not yet fully consolidated in the neocortex.
• ■ The capacity to focus attention is constrained by parietal and frontal mechanisms that modulate processing as well as by increased noise in the neural patterns arising from similarity-based interference or from stochastic variability in firing.
• ■ Frontal structures support controlled processes of retrieval and interference resolution.
• ■ Placing an item into the focus of attention from LTM involves reactivating the representation that is encoded in patterns of neural connection weights.
• ■ Decay arises from the inherent variability of the neural firing of feature bundles that build a representation: The likelihood that the firing of multiple features will fall out of synchrony increases with time due to stochastic variability.

A Sketch of Short-Term Memory at Work

The theoretical principles outlined above summarize our knowledge of the psychological and neural bases of STM, but further insight can be gained by attempting to see how these mechanisms might work together, moment-by-moment, to accomplish the demands of simple tasks. We believe that working through an illustration will not only help to clarify the nature of the proposed mechanisms, but it may also lead to a picture of STM that is more detailed in its bridging of neural process and psychological function.

Toward these ends, we present here a specific implementation of the principles that allows us to give a description of the mechanisms that might be engaged at each point in a simple visual STM task. This exercise leads us to a view of STM that is heavily grounded in concepts of neural activation and plasticity. More specifically, we complement the assumptions about cognitive and brain function above with simple hypotheses about the relative supporting roles of neuronal firing and plasticity (described below). Although somewhat speculative in nature, this description is consistent with the summary principles, and it grounds the approach more completely in a plausible neural model. In particular, it has the virtue of providing an unbroken chain of biological mechanisms that supports the encoding of short-term memories over time.

Figure 1 traces the representation of one item in memory over the course of a few seconds in our hypothetical task. The cognitive events are demarcated at the top of the figure, and the task events at the bottom. In the hypothetical task, the subject must keep track of three visual items (such as novel shapes). The first item is presented for 700 milliseconds, followed by a delay of 2 seconds. The second stimulus then appears, followed by a delay of a few seconds, then the third stimulus, and another delay. Finally, the probe appears, and contact must be made with the memory for the first item. The assumption is that subjects will engage in a strategy of actively maintaining each item during the delay periods.

The processing and neural representation of one item in memory over the course of a few seconds in a hypothetical short-term memory task, assuming a simple single-item focus architecture. The cognitive events are demarcated at the top; the task events, at the bottom. The colored layers depict the extent to which different brain areas contribute to the representation of the item over time, at distinct functional stages of short-term memory processing. The colored layers also distinguish two basic types of neural representation: Solid layers depict memory supported by a coherent pattern of active neural firing, and hashed layers depict memory supported by changes in synaptic patterns. The example task requires processing and remembering three visual items; the figure traces the representation of the first item only. In this task, the three items are sequentially presented, and each is followed by a delay period. After the delay following the third item, a probe appears that requires retrieval of the first item. See the text for details corresponding to the numbered steps in the figure.

Before walking through the timeline in Figure 1 , let us take a high-level view. At any given time point, a vertical slice through the figure is intended to convey two key aspects of the neural basis of the memory. The first is the extent to which multiple cortical areas contribute to the representation of the item, as indicated by the colored layers corresponding to different cortical areas. The dynamic nature of the relative sizes of the layers captures several of our theoretical assumptions concerning the evolving contribution of those different areas at different functional stages of STM. The second key aspect is the distinction between memory supported by a coherent pattern of active neural firing (captured in solid layers) and memory supported by synaptic plasticity (captured in the hashed layers) ( Fuster 2003 , Grossberg 2003 , Rolls 2000 ). The simple hypothesis represented here is that perceptual encoding and active-focus maintenance are supported by neuronal firing, and memory of items outside the focus is supported by short-term synaptic plasticity ( Zucker & Regehr 2002 ). 3

We now follow the time course of the neural representation of the first item (in the order indicated by the numbers in the figure). ( 1 ) The stimulus is presented and rapidly triggers a coherent pattern of activity in posterior perceptual regions, representing both low-level visual features of the item content and its abstract identification in higher-level regions. ( 2 ) There is also a rapid onset of the representation of item-context binding (temporal context in our example) supported by the medial-temporal lobes (see section titled “Contesting the Idea of Separate Long-Term and Short-Term Systems”) ( Ranganath & Blumenfeld 2005 ). ( 3 ) Over the first few hundred milliseconds, this pattern increases in quality, yielding speed-accuracy tradeoffs in perceptual identification. ( 4 ) Concurrent with the active firing driven by the stimulus, very short-term synaptic plasticity across cortical areas begins to encode the item’s features and its binding to context. Zucker & Regehr (2002) identify at least three distinct plasticity mechanisms that begin to operate on this time scale (tens of milliseconds) and that together are sufficient to produce memories lasting several seconds. (For the use of this mechanism in a prominent neural network model of STM, see Burgess & Hitch 1999 , 2005 , 2006 .) ( 5 ) At the offset of the stimulus, the active firing pattern decays very rapidly (consistent with identified mechanisms of rapid decay in short-term potentiation; Zucker & Regehr 2002 ), but ( 6 ) active maintenance, mediated by increased activity in frontal and parietal systems, maintains the firing pattern during the delay period (see sections titled “The Architecture of Unitary-Store Models” and “Maintenance of Items in the Focus”) ( Pasternak & Greenlee 2005 , Ranganath 2006 , Ruchkin et al. 2003 ). This active delay firing includes sustained contribution of MTL to item-context binding (see section titled “Contesting the Idea of Separate Long-Term and Short-Term Systems”). Significant reduction in coherence of the firing pattern may occur as a result of stochastic drift as outlined above (in sections titled “What Happens Neurally During the Delay?” and “Interference-Based Decay?”), possibly leading to a kind of short-term decay during maintenance (see section titled “What Happens Neurally During the Delay?”) ( Fuster 1995 , Pasternak & Greenlee 2005 ). ( 7 ) The active maintenance involves the reuse of posterior perceptual regions in the service of the task demands on STM. This reuse includes even early perceptual areas, but we show here a drop in the contribution of primary perceptual regions to maintenance in order to indicate a relatively greater effect of top-down control on the later high-level regions ( Postle 2006 , Ranganath 2006 ). ( 8 ) During this delay period of active maintenance, short-term potentiation continues to lay down a trace of the item and its binding to context via connection weights both within and across cortical regions. The overall efficacy of this memory encoding is the result of the interaction of the possibly decaying active firing pattern with the multiple plasticity mechanisms and their individual facilitation and depression profiles ( Zucker & Regehr 2002 ).

( 9 ) At the end of the delay period and the onset of the second stimulus, the focus rapidly shifts to the new stimulus, and the active firing of the neural pattern of the target stimulus ceases. ( 10 ) The memory of the item is now carried completely by the changed synaptic weights, but this change is partially disrupted by the incoming item and its engagement of a similar set of neural activity patterns. Cognitively, this disruption yields similarity-based retroactive interference (see “Other Mechanisms for Interference Effects?”) ( Nairne 2002 ). ( 11 ) Even in the absence of interference, a variety of biochemical processes give rise to the decay of short-term neural change and therefore the gradual loss of the memory trace over time. This pattern of interference and decay continues during processing of both the second and third stimulus. The probe triggers a rapid memory retrieval of the target item ( 12 ), mediated in part by strategic frontal control (see “Neural Mechanisms of Short- and Long-Term Memory Retrieval”) ( Cabeza et al. 2002 , Ranganath et al. 2004 ). This rapid retrieval corresponds to the reinstantiation of the target item’s firing pattern in both posterior perceptual areas ( 13 ) and medial-temporal regions, the latter supporting the contextual binding. A plausible neural mechanism for the recovery of this activity pattern at retrieval is the emergent pattern-completion property of attractor networks ( Hopfield 1982 ). Attractor networks depend on memories encoded in a pattern of connection weights, whose formation and dynamics we have sketched above in terms of short-term synaptic plasticity. Such networks also naturally give rise to the kind of similarity-based proactive interference clearly evident in STM retrieval (see “Selection-Based Interference Effects”) ( Jonides & Nee 2006 , Keppel & Underwood 1962 ).

We have intentionally left underspecified a precise quantitative interpretation of the y -axis in Figure 1 . Psychologically, it perhaps corresponds to a combination of availability (largely driven by the dichotomous nature of the focus state) and accessibility (driven by a combination of both firing and plasticity). Neurally, it perhaps corresponds to some measure of both firing amplitude and coherence and potential firing amplitude and coherence.

We are clearly a long way from generating something like the plot in Figure 1 from neuroimaging data on actual tasks—though plots of event-related potentials in STM tasks give us an idea of what these data may look like ( Ruchkin et al. 2003 ). There no doubt is more missing from Figure 1 than is included (e.g., the role of subcortical structures such as the basal ganglia in the frontal/parietal mediated control, or the reciprocal cortical-thalamic circuits that shape the nature of the neocortical patterns).We nevertheless believe that the time course sketched in Figure 1 is useful for making clear many of the central properties that characterize the psychological and neural theory of human STM outlined above: ( a ) STM engages essentially all cortical areas—including medial temporal lobes—and does so from the earliest moments, though it engages these areas differentially at different functional stages. ( b ) STM reuses the same posterior cortical areas and representations that subserve perception, and active maintenance of these representations depends on these posterior areas receiving input from frontal-parietal circuits. ( c ) Focused items are distinguished both functionally and neurally by active firing patterns, and nonfocused memories depend on synaptic potentiation and thereby suffer from decay and retroactive interference. ( d ) Nonfocused memories are reinstantiated into active firing states via an associative retrieval process subject to proactive interference from similarly encoded patterns.

Postscript: Revisiting Complex Cognition

A major goal of this review has been to bring together psychological theorizing (the mind) and neuroscientific evidence (the brain) of STM. However, any celebration of this union is premature until we address this question: Can our account explain how the mind and brain accomplish the everyday tasks (e.g., completing a tax form) that opened this review? The recognition probe task used in our example and the other procedures discussed throughout the main text are considerably simpler than those everyday tasks. Is it plausible to believe that the system outlined here, particularly in light of its severely limited capacity, could support human cognition in the wild?

It is sobering to note that Broadbent (1993) and Newell (1973 , 1990) asked this question nearly two decades ago, and at that time they were considering models of STM with even larger capacities than the one advocated here. Even so, both observed that none of the extant computational models of complex cognitive tasks (e.g., the Newell & Simon 1972 models of problem solving) used contemporary psychological theories of STM. Instead, the complex-cognition models assumed much larger (in some cases, effectively unlimited) working memories. The functional viability of the STM theories of that time was thus never clearly demonstrated. Since then, estimates of STM capacity have only grown smaller, so the question, it would seem, has grown correspondingly more pressing.

Fortunately, cognitive modeling and cognitive theory have also developed over that time, and in ways that would have pleased both Broadbent and Newell. Importantly, many computational cognitive architectures now make assumptions about STM capacity that are congruent with the STM models discussed in this review. The most prominent example is ACT-R, a descendent of the early Newell production-system models. ACT-R continues to serve as the basis of computational models of problem solving (e.g., Anderson & Douglass 2001 ), sentence processing ( Lewis & Vasishth 2005 , Lewis et al. 2006 ), and complex interactive tasks ( Anderson et al. 2004 ). However, the current version of ACT-R has a focus-based structure with an effective capacity limit of four or fewer items ( Anderson et al. 2004 ).

Another important theoretical development is the long-term working memory approach of Ericsson & Kintsch (1995) . This approach describes how LTM, using the kind of fast-encoding and cue-based associative retrieval processes assumed here, can support a variety of complex cognitive tasks ranging from discourse comprehension to specialized expert performance. In both the modern approaches to computational architecture and long-term working memory, the power of cognition resides not in capacious short-term buffers but rather in the effective use of an associative LTM. A sharply limited focus of attention does not, after all, seem to pose insurmountable functional problems.

In summary, this review describes the still-developing convergence of computational models of complex cognition, neural network models of simple memory tasks, modern psychological studies of STM, and neural studies of memory in both humans and primates. The points of contact among these different methods of studying STM have multiplied over the past several years. As we have pointed out, significant and exciting challenges in furthering this integration lie ahead.

1 Another line of neural evidence about the separability of short- and long-term memory comes from electrophysiological studies of animals engaged in short-term memory tasks. We review this evidence and its interpretation in The Architecture of Unitary-Store Models section.

2 This carving up of STM processes is also consistent with recent approaches to individual differences in working memory, which characterize individual variation not in terms of variation in buffer capacity, but rather in variation in maintenance and retrieval processes ( Unsworth & Engle 2007 ).

3 The alternative to this strong claim is that memory items outside the focus might also be supported by residual active firing. The empirical results reviewed above indicating load-dependent posterior activation might lend support to this alternative if one assumes that the memory load in those experiments was not entirely held in the focus, and that these activations exclusively index firing associated with the memory load itself.

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Cognitive Development Essay

Cognitive development is concerned with how thinking processes flow from childhood through adolescence to adulthood by involving mental processes such as remembrance, problem solving, and decision-making. It therefore focuses on how people perceive, think, and evaluate their world by invoking the integration of genetic and learned factors.

Hence, cognitive development mainly concentrates on “areas of information processing, intelligence, reasoning, language development, and memory” (Kendler, 1995, p.164). In essence, cognitive development theory reveals how people think and how thinking changes over time.

The basic premises of cognitive development theory

The premises of cognitive development theory largely allow future investigation to amplify, specify, and modify them according to data trends. These premises frame the theory in a way that it addresses the structure, working, and progress of the system that governs discrimination learning.

Primarily, the theory is based on observable behaviors and indirectly defined theoretical constructs. These constructs assume that psychological and neurological theorizing about cognitive development will gradually coalesce (Kendler, 1995). The premises take form of two different approaches that have been developed over the years.

The first approach postulates that thinking is a universal sequence of stages, while the second approach postulates that people process information in a similar manner computers do (Kail & Cavanaugh, 2008, p.13). One of the best-known examples of the first approach is Piaget’s theory of development that explains how children construct their knowledge, and how the format of their knowledge changes over time.

The second approach is exemplified by Information processing theory that focuses on how computers work to explain thinking and its development through childhood and adolescence.

The cognitive development theory has application in various areas such as works of Aaron Beck and Albert Ellis with the Beck Depression Inventory (BDI) and the Beck Anxiety Inventory (BAI), both being very popular quick assessments of an individual’s functioning (Kail & Cavanaugh, 2008).

Discussion of Piaget Theory and Vygotsky Theory on Intelligence Development

The next part of this paper will be a discussion of the works of Piaget and Vygotsky, including comparison and contrast of their views on various aspects of cognitive development theory.

Jean Piaget was one of the most influential developmental psychologists of the 20 th century, who believed that children naturally make sense of their world.

Lev Vygotsky, a Russian psychologist, was one of the first theorists to emphasize that children’s thinking develops through influence of the socio-cultural context in which children grow up rather than developing in a void. Piaget observed children’s past and potential interaction with their environment as being determined by their schemas, which are modified by the processes of assimilation and accommodation.

According to Kail & Cavanaugh (2008), assimilation may be described as a process that allows a child to add “new information by incorporating it into an existing schema.” For Piaget, enhancing a balance or truce between assimilation and accommodation in the schemas definitely leads to cognitive development.

This unlike Vygotsky, whose view is that cognitive growth occurs in a socio-cultural context that influences the form it takes, for instance, a child’s most remarkable cognitive skills are shaped by social interactions with parents, teachers, and other competent partners (Shaffer & Kipp, 2009).

Thus, cognitive development is more of an apprenticeship in which children develop through working with skilled adult assistants. Both Piaget and Vygotsky held the view that children’s thinking becomes more complex as they develop, highlighting that this change is influenced by the more complex knowledge that children construct from the more complex thinking.

Stages of development in both theories

Both theorists explain cognitive development in four distinct stages, but each of them explains these stages in different aspects and perspectives. According to Piaget, cognitive development takes place in “four distinct, universal stages, each characterized by increasingly sophisticated and abstract levels of thought” (Kendler, 1995).

These stages include sensorimotor stage (infancy) that begins from birth to 2 years and is characterized infant’s knowledge being demonstrated in six sub-stages through sensory and motor skills. The second stage is pre-operational stage (2 to 6 years) during which a child learns how to use symbols such as words and numbers to represent various aspects of the world but relates to the world only through his or her perspective.

Additionally, “concrete operational stage is characterized by seven types of conservation,” with “intelligence being demonstrated through logical and systematical manipulation of symbols related to concrete objects” (Kail & Cavanaugh, 2008).

In this third stage, operational thinking develops while the egocentric thinking diminishes. Lastly, formal operational stage, which occurs in late stages of human development or old age, involves “logical use of symbols related to abstract concepts” signifying a more complex and mature way of thinking (Kail & Cavanaugh, 2008).

A departure from Piaget, Vygotsky proposed that we should evaluate development from perspective of four interrelated levels in interaction with children’s environment. These stages include ontogenetic development, which refers to development of the individual over his or her lifetime.

Secondly, Microgenetic development refers to changes that occur over brief periods such as minutes, a few days, or seconds. In addition, Phylogenetic development refers to changes over evolutionally time. Lastly, sociohistorical development refers to changes that have occurred in one’s culture and the values, norms, and technology, such as a history has generated (Shaffer & Kipp, 2009).

Classroom Application of Both Theorists’ Views

Both theorists’ views can find classroom application in trying to explain educational process. For Piaget, children learn because naturally, all children want to understand their world. According to Piaget, early children’s life up to adolescence stage presents them with an urge to explore and try to “understand the workings of both the physical and the social world” (Kail & Cavanaugh, 2008).

Whereas, Vygotsky would explain education as being shaped by cultural transmission, since the fundamental aim of all societies is to impart on their children, the basic cultural values, and skills. For example, most parents in western nations want their children to do well in their studies and obtain a college degree, as this may lead to a good job.

However, parents in African countries such as Mali want their children to learn activities such as farming, herding animals, hunting, and gathering of food, as these skills may enhance their survival in their environment. Thus, each culture provides its children with tools of intellectual adaptation that permit them to use their basic mental functions more adaptively (Shaffer & Kipp, 2009).

Piaget theory would be limited in explaining academic excellence, since it views education as a natural process, while Vygotsky would explains that as a product of cultural environment that influences a student to excel. Educationally, Piaget provided an accurate overview of how children of different ages think and asked crucial questions that drew literally, thousands of scholars to the study of cognitive development.

According to Vygotsky, children are active participants in their education, with teachers in Vygotsky’s classroom favoring a guided participation, in which they structure learning activity, as well as guiding, monitoring, and promoting cooperative learning process.

Piaget’s theory would be limited in explaining academic excellence, since it views education as a natural process, while Vygotsky would explain that as a product of cultural environment that influences a student to excel.

Educationally, Piaget provided an accurate overview of how children of different ages think, and asked crucial questions that drew literally, thousands of scholars to the study of cognitive development. In essence, these theories laid grounds for other developmental theorists to further their views or critique them, leading to other cognitive development theories.

Kail, R.V. & Cavanaugh, J.C. (2008). Human Development: A Life-Span View . OH: Cengage Learning.

Kendler, T.S. (1995). Levels of cognitive development. NJ: Routledge.

Shaffer, D.R. & Kipp, K. (2009). Developmental Psychology: Childhood and Adolescence. Eighth edition. OH: Cengage Learning.

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50+ Research Topics for Psychology Papers

How to Find Psychology Research Topics for Your Student Paper

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Are you searching for a great topic for your psychology paper ? Sometimes it seems like coming up with topics of psychology research is more challenging than the actual research and writing. Fortunately, there are plenty of great places to find inspiration and the following list contains just a few ideas to help get you started.

Finding a solid topic is one of the most important steps when writing any type of paper. It can be particularly important when you are writing a psychology research paper or essay. Psychology is such a broad topic, so you want to find a topic that allows you to adequately cover the subject without becoming overwhelmed with information.

I can always tell when a student really cares about the topic they chose; it comes through in the writing. My advice is to choose a topic that genuinely interests you, so you’ll be more motivated to do thorough research.

In some cases, such as in a general psychology class, you might have the option to select any topic from within psychology's broad reach. Other instances, such as in an  abnormal psychology  course, might require you to write your paper on a specific subject such as a psychological disorder.

As you begin your search for a topic for your psychology paper, it is first important to consider the guidelines established by your instructor.

Research Topics Within Specific Branches of Psychology

The key to selecting a good topic for your psychology paper is to select something that is narrow enough to allow you to really focus on the subject, but not so narrow that it is difficult to find sources or information to write about.

One approach is to narrow your focus down to a subject within a specific branch of psychology. For example, you might start by deciding that you want to write a paper on some sort of social psychology topic. Next, you might narrow your focus down to how persuasion can be used to influence behavior .

Other social psychology topics you might consider include:

• Prejudice and discrimination (i.e., homophobia, sexism, racism)
• Social cognition
• Person perception
• Social control and cults
• Persuasion, propaganda, and marketing
• Attraction, romance, and love
• Nonverbal communication
• Prosocial behavior

Psychology Research Topics Involving a Disorder or Type of Therapy

Exploring a psychological disorder or a specific treatment modality can also be a good topic for a psychology paper. Some potential abnormal psychology topics include specific psychological disorders or particular treatment modalities, including:

• Eating disorders
• Borderline personality disorder
• Seasonal affective disorder
• Schizophrenia
• Antisocial personality disorder
• Profile a  type of therapy  (i.e., cognitive-behavioral therapy, group therapy, psychoanalytic therapy)

Topics of Psychology Research Related to Human Cognition

Some of the possible topics you might explore in this area include thinking, language, intelligence, and decision-making. Other ideas might include:

• False memories
• Speech disorders
• Problem-solving

Topics of Psychology Research Related to Human Development

In this area, you might opt to focus on issues pertinent to  early childhood  such as language development, social learning, or childhood attachment or you might instead opt to concentrate on issues that affect older adults such as dementia or Alzheimer's disease.

Some other topics you might consider include:

• Language acquisition
• Media violence and children
• Learning disabilities
• Gender roles
• Child abuse
• Prenatal development
• Parenting styles
• Aspects of the aging process

Do a Critique of Publications Involving Psychology Research Topics

One option is to consider writing a critique paper of a published psychology book or academic journal article. For example, you might write a critical analysis of Sigmund Freud's Interpretation of Dreams or you might evaluate a more recent book such as Philip Zimbardo's  The Lucifer Effect: Understanding How Good People Turn Evil .

Professional and academic journals are also great places to find materials for a critique paper. Browse through the collection at your university library to find titles devoted to the subject that you are most interested in, then look through recent articles until you find one that grabs your attention.

Topics of Psychology Research Related to Famous Experiments

There have been many fascinating and groundbreaking experiments throughout the history of psychology, providing ample material for students looking for an interesting term paper topic. In your paper, you might choose to summarize the experiment, analyze the ethics of the research, or evaluate the implications of the study. Possible experiments that you might consider include:

• The Milgram Obedience Experiment
• The Stanford Prison Experiment
• The Little Albert Experiment
• Pavlov's Conditioning Experiments
• The Asch Conformity Experiment
• Harlow's Rhesus Monkey Experiments

Topics of Psychology Research About Historical Figures

One of the simplest ways to find a great topic is to choose an interesting person in the  history of psychology  and write a paper about them. Your paper might focus on many different elements of the individual's life, such as their biography, professional history, theories, or influence on psychology.

While this type of paper may be historical in nature, there is no need for this assignment to be dry or boring. Psychology is full of fascinating figures rife with intriguing stories and anecdotes. Consider such famous individuals as Sigmund Freud, B.F. Skinner, Harry Harlow, or one of the many other  eminent psychologists .

Psychology Research Topics About a Specific Career

​Another possible topic, depending on the course in which you are enrolled, is to write about specific career paths within the  field of psychology . This type of paper is especially appropriate if you are exploring different subtopics or considering which area interests you the most.

In your paper, you might opt to explore the typical duties of a psychologist, how much people working in these fields typically earn, and the different employment options that are available.

Topics of Psychology Research Involving Case Studies

One potentially interesting idea is to write a  psychology case study  of a particular individual or group of people. In this type of paper, you will provide an in-depth analysis of your subject, including a thorough biography.

Generally, you will also assess the person, often using a major psychological theory such as  Piaget's stages of cognitive development  or  Erikson's eight-stage theory of human development . It is also important to note that your paper doesn't necessarily have to be about someone you know personally.

In fact, many professors encourage students to write case studies on historical figures or fictional characters from books, television programs, or films.

Psychology Research Topics Involving Literature Reviews

Another possibility that would work well for a number of psychology courses is to do a literature review of a specific topic within psychology. A literature review involves finding a variety of sources on a particular subject, then summarizing and reporting on what these sources have to say about the topic.

Literature reviews are generally found in the  introduction  of journal articles and other  psychology papers , but this type of analysis also works well for a full-scale psychology term paper.

Topics of Psychology Research Based on Your Own Study or Experiment

Many psychology courses require students to design an actual psychological study or perform some type of experiment. In some cases, students simply devise the study and then imagine the possible results that might occur. In other situations, you may actually have the opportunity to collect data, analyze your findings, and write up your results.

Finding a topic for your study can be difficult, but there are plenty of great ways to come up with intriguing ideas. Start by considering your own interests as well as subjects you have studied in the past.

Online sources, newspaper articles, books , journal articles, and even your own class textbook are all great places to start searching for topics for your experiments and psychology term papers. Before you begin, learn more about  how to conduct a psychology experiment .

What This Means For You

After looking at this brief list of possible topics for psychology papers, it is easy to see that psychology is a very broad and diverse subject. While this variety makes it possible to find a topic that really catches your interest, it can sometimes make it very difficult for some students to select a good topic.

If you are still stumped by your assignment, ask your instructor for suggestions and consider a few from this list for inspiration.

• Hockenbury, SE & Nolan, SA. Psychology. New York: Worth Publishers; 2014.
• Santrock, JW. A Topical Approach to Lifespan Development. New York: McGraw-Hill Education; 2016.

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Cognitive Psychology: Questions and Response, Essay Example

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You are free to use it as an inspiration or a source for your own work.

• How would you define intelligence?

Intelligence is the measure of one’s capacity to think in manner that is a accepted as proper and comprehensive. In the field of cognitive psychology, intelligence is noted as the process by which one thinks and responds to the different situations that occur in his life (Sternberg, et al, 45). Overall, intelligence is understood as the capacity of one to the abstract thought, the capacity of understanding, the self-awareness and the process of comprehension that one’s brain could infer in relation to how he is able to respond to the world around him.

• Is intelligence the single best predictor of success? Why or why not?

No. It is understood that even though intelligence is an element of thinking that provides the best source of indication on whether or not a person is able to create proper decisions (Piaget, 134), there are still other elements such as environmental intensities that define what a person thinks about which could not be controlled by intelligence fully.

How one utilizes his intelligence in relation to other elements such as personal instinct and environmental motivation accounts for the proper prediction of one’s success in life. True, one cannot succeed unless he is able to direct all these elements together for the best results of his being.

• Are there multiple types of intelligence or just one unifying type of intelligence?

There are different types or forms of intelligence. At one point, abstract thinking is most often than not direct yet unlimited. Abstract as it is, it is most often than not understood to be creative and free in form. Another form of intelligence is dependent on emotional knowledge where one utilizes his full emotional capacity to understand matters and respond to particular situations in life (Piaget, 135). Another form of intelligence is that of artificial intelligence which is most likely found on machines developed under full command of computerized functions.

• Apart from your intellectual abilities, identify the skills and/or abilities that aid you the most as you move through school, work, and life. Explain.

There are several instances with my instincts help me so much in completing my tasks. Apart from upfront intelligence, it could be understood that somehow, my instinctive response to matters as they happen affect my final decisions so much hence also having a great impact on how the said decisions turn out to be for the best on my part as a student and as an individual hoping for the best that I could accomplish. My natural instinct on matters developed through time and experience allows me to utilize my intelligence accordingly as I tend to complete my tasks and the responsibilities (Demetriou, 179) I am expected to accomplish both in school and in life.

Through the collaborative use of these elements, I see that my utilization and application of proper intelligence has become more effective in defining my personality and how my life is directed through the decisions I make every day.

Sternberg RJ; Salter W (1982). Handbook of human intelligence . Cambridge, UK: Cambridge University Press.

Piaget, J. (1953). The origin of intelligence in the child . New Fetter Lane, New York: Routledge & Kegan Paul.

Demetriou, A. (1998). Cognitive development. In A. Demetriou, W. Doise, K.F.M. van Lieshout (Eds.), Life-span developmental psychology (pp. 179-269). London: Wiley.

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Exam Question Bank: Paper 1: Cognitive Approach

Travis Dixon April 18, 2019 Assessment (IB) , Cognitive Psychology , Revision and Exam Preparation

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Disclaimer : These questions are not IB “official” questions and are written with our best guess as to what the probable exam questions may look like. Therefore, not every  possible question is covered.

READ MORE  IB Psychology Exam Question Banks

• Paper 1: Biological approach ( Link)
• Paper 1: Sociocultural approach ( Link )
• Paper 1: HL Ext Bio Animal Studies ( Link )
• Paper 1: HL Ext Cog Technology & Cognition ( Link )
• Paper 1: HL Ext Soc/cult Globalization ( Link )
• Paper 2: Human Relationships ( Link )
• Paper 2: Abnormal Psychology ( Link )

Cognitive Approach

The following table is taken from “IB Psychology: A Revision Guide” ( Link ).

The exam questions will be based on the topic and content headings as shown above (Note: terms in italics will only be asked from May 2020 onwards).

Exam Questions

Research methods & ethical considerations.

Questions about research methods and ethics will be based on the three “topics” for the cognitive approach (cognitive processes, the reliability of cognitive processes and emotion and cognition).

Research Methods

Short answer questions.

• Outline one research method used to study cognitive processes.
• Describe the use of one research method used to study cognitive processes.
• Explain how and why one research method is used to study the reliability of one cognitive process.
•   Explain the use of one research method used in the cognitive approach to understanding human behaviour.

Essay Questions

• Discuss one research method used to study cognitive processes.
• Evaluate one or more research methods used to study cognitive processes.
• Evaluate the use of one research method used to study the reliability of cognitive processes.
• Evaluate how and why one research method is used to study the effects of emotion on cognition.
• Discuss the use of one or more research methods used in the cognitive approach to understanding human behaviour.

Ethical Considerations

• Outline one ethical consideration related to studies on cognitive processes.
• Explain one ethical consideration relevant to studies on the effects of emotion on cognition.
• Explain one ethical consideration relevant to one study on the reliability of cognitive processes.
• Outline one ethical consideration related to studies in the cognitive approach to understanding human behaviour.
• Discuss one ethical consideration relevant to studies on cognitive processes.
• Discuss one ethical consideration relevant to one study on the reliability of cognitive processes.
• Discuss ethical considerations relevant to research on the effects of emotion on cognition.
• Discuss one or more ethical considerations relevant to research on cognitive processes.
• Discuss one or more ethical considerations related to research in the cognitive approach to understanding human behaviour.

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Paper One has two sections – A and B. In Section A you have three compulsory short answer questions, one from each approach (biological, cognitive and sociocultural). In Section B, you have three exam questions, also one from each approach and you answer only  one. This means you should prep all core approach topics for SAQs and you can choose one approach for essays.

• For short answer questions, because you can use the command terms interchangeably (outline, describe, explain) their selection for the above questions has been random.
• The italicized terms above (e.g. cognitive schema) are the SAQ additional terms. It’s often difficult to predict how these will be phrased in IB exam questions.

Disclaimer : These questions are not IB “official” questions and are written with our best guess as to what the  probable  exam questions may look like. Therefore, not  every   possible  question is covered.

Travis Dixon is an IB Psychology teacher, author, workshop leader, examiner and IA moderator.

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37 Short Answer/Essay Questions

Try these AFTER you have thoroughly studied the chapter.  You should not have to look back at the text to answer them (only to check your answer!).  Remember, the point is NOT to memorize parts of the textbook but rather to understand the material and describe it in your OWN WORDS.

If you are going to write more than a couple of paragraphs, think about the structure of your answer

• What is the difference between longitudinal designs and cross-sectional designs? Describe some of the pros and cons of each approach.
• Briefly describe Piaget’s four stages of cognitive development.
• Describe the four parenting styles described in the text and illustrate each of them with an example.
• What cognitive changes typically occur during late adulthood?

Introduction to Psychology Study Guide Copyright © 2021 by Sarah Murray is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

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