Optimal Information Storage in Noisy Synapses under Resource Constraints

Varshney, L. R., Sjöström, P. J., Chklovskii, D. B. (2006) Optimal Information Storage in Noisy Synapses under Resource Constraints. Neuron, 52 (3). pp. 409-423. ISSN 08966273

URL: https://www.ncbi.nlm.nih.gov/pubmed/17088208
DOI: 10.1016/j.neuron.2006.10.017

Abstract

Experimental investigations have revealed that synapses possess interesting and, in some cases, unexpected properties. We propose a theoretical framework that accounts for three of these properties: typical central synapses are noisy, the distribution of synaptic weights among central synapses is wide, and synaptic connectivity between neurons is sparse. We also comment on the possibility that synaptic weights may vary in discrete steps. Our approach is based on maximizing information storage capacity of neural tissue under resource constraints. Based on previous experimental and theoretical work, we use volume as a limited resource and utilize the empirical relationship between volume and synaptic weight. Solutions of our constrained optimization problems are not only consistent with existing experimental measurements but also make nontrivial predictions. © 2006 Elsevier Inc. All rights reserved.

Item Type: Paper
Subjects: bioinformatics > genomics and proteomics > analysis and processing
organs, tissues, organelles, cell types and functions > sub-cellular tissues: types and functions
organs, tissues, organelles, cell types and functions > sub-cellular tissues: types and functions > synapse
CSHL Authors:
Communities: CSHL labs > Chklovskii lab
Depositing User: CSHL Librarian
Date: 2006
Date Deposited: 06 Dec 2011 19:17
Last Modified: 27 Apr 2018 19:40
Related URLs:
URI: https://repository.cshl.edu/id/eprint/22922

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