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Can Serial Dependencies in Choices and Neural Activity Explain Choice Probabilities?

Jan-Matthis Lueckmann¹, Jakob H Macke^1,2, Hendrikje Nienborg³

¹Research Center Caesar, An associate of the Max-Planck Society, 53175 Bonn, Germany.

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience

|February 15, 2018

Summary

This summary is machine-generated.

Choice probabilities in sensory neurons and serial dependencies in choices are separate processes. Temporal correlations in neural activity and behavior do not explain choice probabilities, constraining computational models.

Keywords:

V2 choice probability macaque perceptual decision-making sequential dependence

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Area of Science:

Neuroscience
Computational Neuroscience
Systems Neuroscience

Background:

Sensory neuron activity covaries with perceptual choice (choice probability).
Previous choices influence current decisions (serial dependence).
Neuronal activity exhibits long-timescale temporal correlations.

Purpose of the Study:

Investigate the link between choice probabilities, serial dependence, and temporal correlations in neural activity.
Determine if temporal correlations explain choice probabilities.

Main Methods:

Generalized linear models to analyze simultaneous behavioral and V2 neural activity in macaques.
Semipartial correlation analysis to remove history effects.

Main Results:

Both decisions and neural activity showed temporal correlations.
Choice probabilities remained largely unchanged after removing history effects.
Serial dependencies in choices and neural activity appear to be separate processes.

Conclusions:

Serial dependencies in choices and neural activity do not explain choice probabilities.
These processes are predominantly separate but parallel, coupled by trial-by-trial covariations.
Findings constrain computational models of perceptual decision-making with feedback signals.