Work

Common Input Explains Higher-Order Correlations and Entropy in a Simple Model of Neural Population Activity

Year: 2011

Type: article

Abstract: Simultaneously recorded neurons exhibit correlations whose underlying causes are not known. Here, we use a population of threshold neurons receiving correlated inputs to model neural population recordings. We show analytically that small changes in second-order correlations can lead to large changes in higher-order redundancies, and that the resulting interactions have a strong impact on the entropy, sparsity, and statistical heat capacity of the population. Our findings for this simple model may explain some surprising effects recently observed in neural population recordings.

Source: Physical Review Letters

DOI: 10.1103/physrevlett.106.208102

Authors: Jakob H. Macke, Manfred Opper, Matthias Bethge

Institutions: Gatsby Computational Neuroscience Unit, University College London, University of Tübingen, Technische Universität Berlin, Max Planck Society, Max Planck Institute for Biological Cybernetics, Bernstein Center for Computational Neuroscience Tübingen

Language: English

Topic: Neural dynamics and brain function

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: green

OpenAlex ID: W2070892134

FWCI: 5.571

Cites: 15

Cited by: 98

Related to: 10