Revealing nonlinear neural decoding by analyzing choices

Sensory data about most natural task-relevant variables are entangled with task-irrelevant nuisance variables. Here, the authors present a theoretical framework for quantifying how the brain uses or decodes its nonlinear information which indicates near-optimal nonlinear decoding.

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Bibliographic Details
Main Authors: Qianli Yang, Edgar Walker, R. James Cotton, Andreas S. Tolias, Xaq Pitkow
Format: article
Language:EN
Published: Nature Portfolio 2021
Subjects:
Q
Online Access:https://doaj.org/article/8a6c8800814c4391be68ee95e74e47af
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