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This review aims to understand how context-dependent decisions are made through population coding in neural circuits.

Population codes for context-dependent decision-making

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Review reveals how population coding mechanisms guide decision-making flexibility by integrating sensory and contextual information.

This review aims to understand how context-dependent decisions are made through population coding in neural circuits.
Review of recent advances in large-scale neural recordings
Analysis of nonlinear mixed selectivity and task-dependent population geometry
Examination of structured correlations in neural populations
Nonlinear mixed selectivity increases representational dimensionality, enhancing task variable combinations
Learning alters population geometry to balance flexibility and generalization
Structured correlations improve context-dependent information transmission to downstream circuits

Kira et al. (2026) studied this question.

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