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Neural circuit models for evidence accumulation through choice-selective sequences.

Lindsey S Brown, Jounhong Ryan Cho, Scott S Bolkan

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|January 18, 2024

Summary

New models suggest brain circuits use sequential neural firing, not just persistent rates, to accumulate evidence for decisions. This finding offers insights into neural computations underlying choice behavior.

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Area of Science:

Neuroscience
Computational Neuroscience
Cognitive Neuroscience

Background:

Traditional models posit persistent neural firing for evidence accumulation in decision-making.
Recent rodent studies reveal sequential neural activity patterns correlated with spatial or temporal factors during decisions.

Purpose of the Study:

To propose and test novel circuit models for sequential evidence accumulation in neural decision-making.
To investigate how neural populations encode and transfer evidence across different brain regions.

Main Methods:

Development of two circuit models: competing neuronal chains and activity "bump" network location.
Analysis of neural recordings from four brain regions during a decision-making task.
Comparison of observed neural tuning curves with model predictions for evidence accumulation.

Main Results:

Different brain regions exhibited neural tuning curves consistent with distinct evidence accumulation models.
Evidence encoding was observed to transfer between neuronal populations representing different temporal or spatial contexts.

Conclusions:

Sequential firing patterns and network location shifts are plausible mechanisms for evidence accumulation.
These findings provide mechanistic models and potential neural substrates for graded information processing in the brain.