Neural correlates of sparse coding and dimensionality reduction
Abstract
Supported by recent computational studies, there is increasing evidence that a wide range of neuronal responses can be understood as an emergent property of nonnegative sparse coding (NSC), an efficient population coding scheme based on dimensionality reduction and sparsity constraints. We review evidence that NSC might be employed by sensory areas to efficiently encode external stimulus spaces, by some associative areas to conjunctively represent multiple behaviorally relevant variables, and possibly by the basal ganglia to coordinate movement. In addition, NSC might provide a useful theoretical framework under which to understand the often complex and nonintuitive response properties of neurons in other brain areas. Although NSC might not apply to all brain areas (for example, motor or executive function areas) the success of NSC-based models, especially in sensory areas, warrants further investigation for neural correlates in other regions.
- Authors:
-
[1];
- Univ. of California, Irvine, CA (United States); Univ. of Washington, Seattle, WA (United States)
- Univ. of California, Irvine, CA (United States)
- Univ. of California, Irvine, CA (United States); Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Publication Date:
- Research Org.:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Org.:
- USDOE National Nuclear Security Administration (NNSA); National Science Foundation (NSF); Washington Research Foundation Funds for Innovation in Neuroengineering and Data-Intensive Discovery; Defense Advanced Research Projects Agency (DARPA); Air Force Research Laboratory (AFRL); Sandia National Laboratories
- OSTI Identifier:
- 1627259
- Grant/Contract Number:
- NA0003525; IIS-1302125; FA8750-18-C-0103
- Resource Type:
- Accepted Manuscript
- Journal Name:
- PLoS Computational Biology (Online)
- Additional Journal Information:
- Journal Name: PLoS Computational Biology (Online); Journal Volume: 15; Journal Issue: 6; Journal ID: ISSN 1553-7358
- Publisher:
- Public Library of Science
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES; Biochemistry & Molecular Biology; Mathematical & Computational Biology
Citation Formats
Beyeler, Michael, Rounds, Emily L., Carlson, Kristofor D., Dutt, Nikil, and Krichmar, Jeffrey L. Neural correlates of sparse coding and dimensionality reduction. United States: N. p., 2019.
Web. doi:10.1371/journal.pcbi.1006908.
Beyeler, Michael, Rounds, Emily L., Carlson, Kristofor D., Dutt, Nikil, & Krichmar, Jeffrey L. Neural correlates of sparse coding and dimensionality reduction. United States. https://doi.org/10.1371/journal.pcbi.1006908
Beyeler, Michael, Rounds, Emily L., Carlson, Kristofor D., Dutt, Nikil, and Krichmar, Jeffrey L. Thu .
"Neural correlates of sparse coding and dimensionality reduction". United States. https://doi.org/10.1371/journal.pcbi.1006908. https://www.osti.gov/servlets/purl/1627259.
@article{osti_1627259,
title = {Neural correlates of sparse coding and dimensionality reduction},
author = {Beyeler, Michael and Rounds, Emily L. and Carlson, Kristofor D. and Dutt, Nikil and Krichmar, Jeffrey L.},
abstractNote = {Supported by recent computational studies, there is increasing evidence that a wide range of neuronal responses can be understood as an emergent property of nonnegative sparse coding (NSC), an efficient population coding scheme based on dimensionality reduction and sparsity constraints. We review evidence that NSC might be employed by sensory areas to efficiently encode external stimulus spaces, by some associative areas to conjunctively represent multiple behaviorally relevant variables, and possibly by the basal ganglia to coordinate movement. In addition, NSC might provide a useful theoretical framework under which to understand the often complex and nonintuitive response properties of neurons in other brain areas. Although NSC might not apply to all brain areas (for example, motor or executive function areas) the success of NSC-based models, especially in sensory areas, warrants further investigation for neural correlates in other regions.},
doi = {10.1371/journal.pcbi.1006908},
journal = {PLoS Computational Biology (Online)},
number = 6,
volume = 15,
place = {United States},
year = {2019},
month = {6}
}
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