How to find decision makers in neural networks

Koulakov, A. A., Rinberg, D. A., Tsigankov, D. N. (2005) How to find decision makers in neural networks. Biological Cybernetics, 94 (1). pp. 86-88. ISSN 03401200

URL: http://www.ncbi.nlm.nih.gov/pubmed/16273385
DOI: 10.1007/s00422-005-0044-6

Abstract

Nervous systems often face the problem of classifying stimuli and making decisions based on these classifications. The neurons involved in these tasks can be characterized as sensory or motor, according to their correlation with sensory stimulus or motor response. In this study we define a third class of neurons responsible for making perceptual decisions. Our mathematical formalism enables the weighting of neuronal units according to their contribution to decision making, thus narrowing the field for more detailed studies of underlying mechanisms. We develop two definitions of a contribution to decision making. The first definition states that decision making activity can be found at the points of emergence for behavioral correlations in the system. The second definition involves the study of propagation of noise in the network. The latter definition is shown to be equivalent to the first one in the cases when they can be compared. Our results suggest a new approach to analyzing decision making networks.

Item Type: Paper
Subjects: bioinformatics > genomics and proteomics > Mapping and Rendering
bioinformatics > computational biology
organs, tissues, organelles, cell types and functions > cell types and functions > cell types > neurons
organs, tissues, organelles, cell types and functions > cell types and functions > cell types > neurons
organs, tissues, organelles, cell types and functions > cell types and functions > cell types > neurons
CSHL Authors:
Communities: CSHL labs > Koulakov lab
Depositing User: CSHL Librarian
Date Deposited: 13 Dec 2011 17:06
Last Modified: 01 Mar 2013 20:06
Related URLs:
URI: http://repository.cshl.edu/id/eprint/22846

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