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Related Concept Videos

Working Memory01:24

Working Memory

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Working memory refers to a combination of components, including short-term memory and attention, that allow an individual to hold information temporarily as we perform cognitive tasks. It is an essential cognitive function that enables the execution of complex tasks such as problem-solving, comprehension, and reasoning. Unlike short-term memory, which simply involves the storage of information for a brief period, working memory involves the active manipulation and processing of this...
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Encoding01:19

Encoding

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Information enters the brain through encoding, which is the input of information into the memory system. Once sensory information is received from the environment, the brain labels or codes it. The information is then organized with similar information and connected to existing concepts. Encoding occurs through automatic processing and effortful processing.
Automatic processing involves the encoding of details like time, space, frequency, and the meaning of words, usually done without conscious...
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Chunking and Rehearsal in Sensory Memory01:22

Chunking and Rehearsal in Sensory Memory

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Improving short-term memory can be achieved through techniques like chunking and rehearsal. Chunking involves organizing information into larger, more manageable units. This technique is particularly useful for information that exceeds the typical memory span of between five and nine items. For instance, logging into an online account with a password like "ta89vq0179gz" involves grouping letters and numbers into three chunks—ta89, vq01, and 79gz. It makes large amounts of...
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Storage01:23

Storage

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A schema is a mental framework that helps individuals organize and interpret information. Schemata, formed from previous experiences, influence how we process new information: how we encode it, the inferences we make, and how we retrieve it. For instance, a schema for what a typical classroom looks like might include desks, a teacher's desk, a whiteboard, and students in such an environment. This expectation helps us quickly understand and navigate new classrooms without needing to analyze...
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Information Processing Approach01:30

Information Processing Approach

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The information-processing theory of cognitive development centers on fundamental mental processes, including attention, memory, and problem-solving skills. Researchers in this field examine how cognitive abilities, such as working memory, evolve and influence children's overall development. Studies indicate that children with stronger working memory tend to excel in reading comprehension, math, and problem-solving compared to peers with less efficient memory skills. Low working memory is...
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Chunking01:12

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Chunking is a powerful cognitive technique that improves short-term memory retention by organizing information into smaller, more manageable units. The brain, limited by working memory capacity, can more easily process and store information when it is divided into "chunks" rather than presented as discrete, unrelated elements. Chunking is especially useful when dealing with large amounts of information, such as numerical sequences, words, or complex ideas.
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Updated: Jun 29, 2025

Assessing Working Memory in Children: The Comprehensive Assessment Battery for Children – Working Memory (CABC-WM)
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The computational foundations of dynamic coding in working memory.

Jake P Stroud1, John Duncan2, Máté Lengyel3

  • 1Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge, UK.

Trends in Cognitive Sciences
|April 5, 2024
PubMed
Summary
This summary is machine-generated.

Working memory maintenance may rely on dynamic neural coding, not just stable activity. Task-optimized models naturally show these dynamics, suggesting dynamic coding is key to cognitive function.

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Area of Science:

  • Cognitive Neuroscience
  • Computational Neuroscience

Background:

  • Working memory (WM) is crucial for cognition.
  • Traditionally, WM maintenance was linked to stable neural activity patterns.

Purpose of the Study:

  • To investigate the role of stable versus dynamic neural coding in working memory.
  • To explain why task-optimized models exhibit dynamic coding, unlike classical models.

Main Methods:

  • Analysis of neural data.
  • Examination of classical and task-optimized neural network models.

Main Results:

  • Neural activity during WM maintenance shows dynamic variations before stabilization.
  • Task-optimized models naturally exhibit dynamic coding, offering a theoretical explanation.
  • Classical models do not inherently display dynamic coding.

Conclusions:

  • Dynamic coding is a fundamental computational feature of working memory maintenance.
  • Revising the understanding of WM to incorporate dynamic neural processes is necessary.