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Nat Neurosci. 2014 Jun;17(6):851-7. doi: 10.1038/nn.3707. Epub 2014 Apr 20.

Population code in mouse V1 facilitates readout of natural scenes through increased sparseness.

Author information

1
Department of Neuroscience, Baylor College of Medicine, Houston, Texas, USA.
2
1] Department of Neuroscience, Baylor College of Medicine, Houston, Texas, USA. [2] Bernstein Center for Computational Neuroscience, Tübingen, Germany. [3] Werner-Reichardt-Center for Integrative Neuroscience and Institute for Theoretical Physics, University of Tübingen, Germany.
3
1] Department of Neuroscience, Baylor College of Medicine, Houston, Texas, USA. [2] Bernstein Center for Computational Neuroscience, Tübingen, Germany. [3] Werner-Reichardt-Center for Integrative Neuroscience and Institute for Theoretical Physics, University of Tübingen, Germany. [4] Max Planck Institute for Biological Cybernetics, Tübingen, Germany.
4
1] Bernstein Center for Computational Neuroscience, Tübingen, Germany. [2] Institute for Neurobiology, Department for Neuroethology, University of Tübingen, Germany.
5
1] Department of Neuroscience, Baylor College of Medicine, Houston, Texas, USA. [2] Department of Bioengineering, Rice University, Houston, Texas, USA.
6
1] Bernstein Center for Computational Neuroscience, Tübingen, Germany. [2] Werner-Reichardt-Center for Integrative Neuroscience and Institute for Theoretical Physics, University of Tübingen, Germany. [3] Max Planck Institute for Biological Cybernetics, Tübingen, Germany.
7
1] Department of Neuroscience, Baylor College of Medicine, Houston, Texas, USA. [2] Bernstein Center for Computational Neuroscience, Tübingen, Germany. [3] Department of Computational and Applied Mathematics, Rice University, Houston, Texas, USA.

Abstract

Neural codes are believed to have adapted to the statistical properties of the natural environment. However, the principles that govern the organization of ensemble activity in the visual cortex during natural visual input are unknown. We recorded populations of up to 500 neurons in the mouse primary visual cortex and characterized the structure of their activity, comparing responses to natural movies with those to control stimuli. We found that higher order correlations in natural scenes induced a sparser code, in which information is encoded by reliable activation of a smaller set of neurons and can be read out more easily. This computationally advantageous encoding for natural scenes was state-dependent and apparent only in anesthetized and active awake animals, but not during quiet wakefulness. Our results argue for a functional benefit of sparsification that could be a general principle governing the structure of the population activity throughout cortical microcircuits.

PMID:
24747577
PMCID:
PMC4106281
DOI:
10.1038/nn.3707
[Indexed for MEDLINE]
Free PMC Article

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