Sanders, H., Kolterman, B. E., Shusterman, R., Rinberg, D., Koulakov, A., Lisman, J. (September 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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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 |
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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: | 17 September 2014 |
Date Deposited: | 09 Oct 2014 16:19 |
Last Modified: | 03 Nov 2017 19:23 |
PMCID: | PMC4166365 |
Related URLs: | |
URI: | https://repository.cshl.edu/id/eprint/30837 |
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