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Updated: Sep 12, 2025

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Cognitive processes are disentangled at cortex-wide scales.

Renan M Costa1, Jiaqi Keith Luo1, Peter S Salvino1

  • 1Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago IL USA.

Biorxiv : the Preprint Server for Biology
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Summary
This summary is machine-generated.

Researchers found that distinct cognitive processes in the brain are disentangled across the cortex. This organization supports accurate decision-making, but breaks down during errors.

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Computational Neuroscience

Background:

  • Decision-making relies on multiple cognitive processes.
  • These processes are distributed across the cortex but implemented via orthogonal population-activity patterns within regions.
  • The integration of local neural geometries across the cortex remains unclear.

Purpose of the Study:

  • To investigate how cortex-wide neural dynamics support distinct cognitive processes during decision-making.
  • To determine the geometric organization of neural activity representing sensory evidence accumulation, short-term memory, and choice.

Main Methods:

  • Developed a virtual-navigation task for mice to dissociate evidence accumulation, memory, and choice.
  • Utilized cortex-wide widefield calcium (Ca2+) imaging.
  • Applied dimensionality reduction and decoding models to analyze neural population activity.

Main Results:

  • Observed distributed but near-orthogonal coding subspaces for distinct cognitive processes (evidence accumulation, memory, choice).
  • This neural geometry disintegrates during erroneous choices.
  • The memory subspace, but not others, aligned with a spontaneous activity-timescale hierarchy, suggesting co-option of intrinsic circuit properties.

Conclusions:

  • Cortex-wide neural dynamics supporting distinct cognitive processes are disentangled.
  • This disentanglement is crucial for accurate decision-making and breaks down during errors.
  • The memory subspace's alignment with intrinsic circuit properties suggests a mechanism for its integration into decision computations.