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.
journal_name
Front Comput Neuroscijournal_title
Frontiers in computational neuroscienceauthors
Sanders H,Kolterman BE,Shusterman R,Rinberg D,Koulakov A,Lisman Jdoi
10.3389/fncom.2014.00108subject
Has Abstractpub_date
2014-09-17 00:00:00pages
108issn
1662-5188journal_volume
8pub_type
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