期刊
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE
卷 8, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fncom.2014.00108
关键词
bistability; olfactory bulb; temporal sequence decoding; olfaction; receptors; N-methyl-D-aspartate
资金
- NSF Collaborative Research in Computational Neuroscience [1R01DA027807-01]
- NSF IGERT [DGE-1068620]
- Howard Hughes Medical Institute
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.
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