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Related Concept Videos

Working Memory01:24

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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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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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Memory is one of the most vital higher mental functions of the brain. Memory is closely related to learning because it enables us to retain information and experiences from our past to use them in our present life. It also helps us to remember facts, events, and skills, such as riding a bike or swimming. There are two types of memory — declarative memory, which involves memorizing facts or events, and procedural memory, which enables us to remember how to do something like writing or...
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Elaborative Rehearsals01:07

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Elaborative rehearsal is a crucial cognitive strategy that strengthens information encoding in long-term memory by making meaningful connections between new data and pre-existing knowledge. This approach contrasts with maintenance rehearsal, which involves simple repetition without delving into the significance of the information. While maintenance rehearsal might temporarily keep information active in short-term memory, it is less effective for long-term retention.
The effectiveness of...
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Implicit Memories01:24

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Implicit memories, also known as non-declarative memories, are long-term memories that function outside of conscious awareness. These memories influence behavior and skills without explicit knowledge. This type of memory is evident in tasks like playing tennis, snowboarding, and texting. Implicit memory has three subsystems: procedural memory, conditioning, and priming. This type of memory is essential in various activities, from everyday tasks to specialized skills.
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Long-Term Memory01:18

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Long-term memory is a relatively permanent type of memory, capable of storing vast amounts of information over extended periods. Its storage capacity is generally considered unlimited.
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Related Experiment Video

Updated: Jun 7, 2025

The Double-H Maze: A Robust Behavioral Test for Learning and Memory in Rodents
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Working memory as a representational template for reinforcement learning.

Kengo Shibata1, Verena Klar2, Sean J Fallon3

  • 1Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Level 6, West Wing, Oxford, OX3 9DU, UK. kengo.shibata@ndcn.ox.ac.uk.

Scientific Reports
|November 12, 2024
PubMed
Summary
This summary is machine-generated.

Working memory (WM) and reinforcement learning (RL) interact to shape decisions. How we remember information, as features or objects, impacts learning and strategy, revealing cognitive cooperation.

Keywords:
Feature-based representationsObject-based representationsReinforcement learningRepresentational templatesWorking memory

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Area of Science:

  • Cognitive Neuroscience
  • Decision-Making Science

Background:

  • Working memory (WM) and reinforcement learning (RL) are crucial for decision-making.
  • The interaction between WM and RL and its impact on behavior is not fully understood.

Purpose of the Study:

  • To investigate if the format of visual stimuli in WM influences reinforcement learning.
  • To determine if feature-based or object-based WM representations affect RL.

Main Methods:

  • Participants engaged in a learning task with probabilistic rewards.
  • Stimulus-action associations were learned while retaining stimuli in WM.
  • WM representation format (feature-based vs. object-based) was manipulated across blocks.

Main Results:

  • Incentivizing a feature-based WM representation enhanced feature-based learning.
  • An improved choice strategy was observed when WM encouraged feature-based representations.
  • This suggests WM representations are actively utilized by RL.

Conclusions:

  • Working memory plays a role in reinforcement learning by providing internal representations.
  • The format of WM representations can modulate learning and decision-making strategies.
  • This work provides a framework for understanding the cooperation between WM and RL.