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A Sparse Probabilistic Code Underlies the Limits of Behavioral Discrimination.

Balaji Sriram^1,2, Lillian Li¹, Alberto Cruz-Martín^3,4,5

¹Division of Biology, University of California San Diego, La Jolla, CA 92093, USA.

Cerebral Cortex (New York, N.Y. : 1991)

|August 13, 2019

Summary

This summary is machine-generated.

Mice perceive visual stimuli rapidly by integrating information from many unreliable neurons. This neural integration allows the visual cortex to generate accurate perception even with sparse, probabilistic single-unit responses.

Keywords:

2AFC electrophysiology mouse behavior orientation discrimination population coding

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Area of Science:

Neuroscience
Computational Neuroscience
Visual Perception

Background:

Perception relies on cortical processing at behaviorally relevant timescales.
Mice exhibit rapid visual stimulus integration (<100 ms) for orientation discrimination.

Purpose of the Study:

Characterize cortical activity underlying rapid visual perception.
Investigate how the brain achieves reliable perception from unreliable neural signals.

Main Methods:

Measured single-unit responses in mouse visual cortex.
Utilized a linear decoding model to assess information integration.
Analyzed neural activity at timescales relevant to behavioral performance.

Main Results:

Stimuli near perception threshold evoke sparse, unreliable neuronal responses.
Individual neurons do not reliably encode stimulus orientation.
Integrating information across 50-100 neurons sufficiently explains behavioral performance.

Conclusions:

The visual system integrates probabilistic information from unreliable single neurons.
Neural integration is crucial for generating reliable perception at the limits of detection.
Cortical computation balances sparse coding with efficient information pooling.