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Context-dependent persistency as a coding mechanism for robust and widely distributed value coding.

Ryoma Hattori1, Takaki Komiyama1

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Summary
This summary is machine-generated.

Persistent neural coding in the brain, particularly in the retrosplenial cortex, helps represent decision-making values. This finding, observed in mice and artificial networks, aids reliable signal distribution.

Keywords:
context dependentdeep learninghistory codingmachine learningmanifoldpersistent codingrecurrent neural networkreinforcement learningretrosplenial cortexvalue-based decision making

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Reinforcement Learning

Background:

  • Neural information processing relies on diverse coding properties, including temporal persistence.
  • Understanding how the brain maintains and distributes task-related information is crucial for cognitive function.

Purpose of the Study:

  • To investigate the role and characteristics of persistent neural coding in value-based decision-making.
  • To explore how persistency contributes to the representation and distribution of value information across brain areas.

Main Methods:

  • Electrophysiological recordings in mice performing decision-making tasks.
  • Analysis of neural population activity and neuronal manifold dynamics.
  • Training and analysis of artificial neural networks performing reinforcement learning.

Main Results:

  • Coding persistency for action history and value varied across brain regions, learning stages, and task contexts.
  • Highest persistency was observed in the retrosplenial cortex of expert mice during value-based decisions.
  • Persistent coding was also replicated in artificial networks trained on reinforcement learning tasks.
  • Persistency enabled temporally untangled value representations and facilitated robust value retrieval by downstream networks.

Conclusions:

  • Context-dependent, untangled neural persistency is key for reliable signal coding and brain-wide information distribution.
  • Persistent coding aids in maintaining and distributing value representations essential for complex decision-making.
  • Findings suggest a generalizable mechanism for information processing applicable to both biological and artificial systems.