A network that performs brute-force conversion of a temporal sequence to a spatial pattern: relevance to odor recognition

Sanders, H., Kolterman, B. E., Shusterman, R., Rinberg, D., Koulakov, A., Lisman, J. (2014) A network that performs brute-force conversion of a temporal sequence to a spatial pattern: relevance to odor recognition. Frontiers in Computational Neuroscience, 8. Article no.108. ISSN 1662-5188

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URL: http://www.ncbi.nlm.nih.gov/pubmed/25278870
DOI: 10.3389/fncom.2014.00108

Abstract

A classic problem in neuroscience is how temporal sequences (TSs) can be recognized. This problem is exemplified in the olfactory system, where an odor is defined by the TS of olfactory bulb (OB) output that occurs during a sniff. This sequence is discrete because the output is subdivided by gamma frequency oscillations. Here we propose a new class of "brute-force" solutions to recognition of discrete sequences. We demonstrate a network architecture in which there are a small number of modules, each of which provides a persistent snapshot of what occurs in a different gamma cycle. The collection of these snapshots forms a spatial pattern (SP) that can be recognized by standard attractor-based network mechanisms. We will discuss the implications of this strategy for recognizing odor-specific sequences generated by the OB.

Item Type: Paper
Subjects: bioinformatics > genomics and proteomics > genetics & nucleic acid processing > protein structure, function, modification > protein types > NMDA receptor
organs, tissues, organelles, cell types and functions > tissues types and functions > neural networks
organism description > animal behavior > olfactory
organs, tissues, organelles, cell types and functions > tissues types and functions > olfactory bulb
CSHL Authors:
Communities: CSHL labs > Koulakov lab
Depositing User: Matt Covey
Date Deposited: 09 Oct 2014 16:19
Last Modified: 03 Nov 2017 19:23
PMCID: PMC4166365
Related URLs:
URI: http://repository.cshl.edu/id/eprint/30837

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