The Geometry of Information Coding in Correlated Neural Populations

Neurons in the brain represent information in their collective activity. The fidelity of this neural population code depends on whether and how variability in the response of one neuron is shared with other neurons. Two decades of studies have investigated the influence of these noise correlations o...

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Published inAnnual review of neuroscience Vol. 44; no. 1; pp. 403 - 424
Main Authors Azeredo da Silveira, Rava, Rieke, Fred
Format Journal Article
LanguageEnglish
Published United States Annual Reviews 08.07.2021
Annual Reviews, Inc
Subjects
correlations
Life Sciences
Neural coding
neural computation
Neurons and Cognition
Noise
Ultrastructure
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Summary:Neurons in the brain represent information in their collective activity. The fidelity of this neural population code depends on whether and how variability in the response of one neuron is shared with other neurons. Two decades of studies have investigated the influence of these noise correlations on the properties of neural coding. We provide an overview of the theoretical developments on the topic. Using simple, qualitative, and general arguments, we discuss, categorize, and relate the various published results. We emphasize the relevance of the fine structure of noise correlation, and we present a new approach to the issue. Throughout this review, we emphasize a geometrical picture of how noise correlations impact the neural code.
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ISSN:0147-006X
1545-4126
0147-006X
DOI:10.1146/annurev-neuro-120320-082744