Sensory uncertainty decoded from visual cortex predicts behavior

Ruben S. Van Bergen; Wei Ji Ma; Michael S. Pratte; Janneke F M Jehee

doi:10.1038/nn.4150

Sensory uncertainty decoded from visual cortex predicts behavior

Ruben S. Van Bergen, Wei Ji Ma, Michael S. Pratte, Janneke F M Jehee

Research output: Contribution to journal › Article › peer-review

Abstract

Bayesian theories of neural coding propose that sensory uncertainty is represented by a probability distribution encoded in neural population activity, but direct neural evidence supporting this hypothesis is currently lacking. Using fMRI in combination with a generative model-based analysis, we found that probability distributions reflecting sensory uncertainty could reliably be estimated from human visual cortex and, moreover, that observers appeared to use knowledge of this uncertainty in their perceptual decisions.

Original language	English (US)
Pages (from-to)	1728-1730
Number of pages	3
Journal	Nature Neuroscience
Volume	18
Issue number	12
DOIs	https://doi.org/10.1038/nn.4150
State	Published - Nov 25 2015

ASJC Scopus subject areas

General Neuroscience

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10.1038/nn.4150

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title = "Sensory uncertainty decoded from visual cortex predicts behavior",

abstract = "Bayesian theories of neural coding propose that sensory uncertainty is represented by a probability distribution encoded in neural population activity, but direct neural evidence supporting this hypothesis is currently lacking. Using fMRI in combination with a generative model-based analysis, we found that probability distributions reflecting sensory uncertainty could reliably be estimated from human visual cortex and, moreover, that observers appeared to use knowledge of this uncertainty in their perceptual decisions.",

author = "{Van Bergen}, {Ruben S.} and {Ji Ma}, Wei and Pratte, {Michael S.} and Jehee, {Janneke F M}",

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AB - Bayesian theories of neural coding propose that sensory uncertainty is represented by a probability distribution encoded in neural population activity, but direct neural evidence supporting this hypothesis is currently lacking. Using fMRI in combination with a generative model-based analysis, we found that probability distributions reflecting sensory uncertainty could reliably be estimated from human visual cortex and, moreover, that observers appeared to use knowledge of this uncertainty in their perceptual decisions.

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Sensory uncertainty decoded from visual cortex predicts behavior

Abstract

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