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Front Comput Neurosci. 2014 Sep 17;8:108. doi: 10.3389/fncom.2014.00108. eCollection 2014.

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

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Department of Biology, Volen Center for Complex Systems, Brandeis University Waltham, MA, USA.
Cold Spring Harbor Laboratory Cold Spring Harbor, NY, USA.
Sagol Department of Neuroscience, University of Haifa Haifa, Israel ; HHMI Janelia Farm Ashburn, VA, USA.
HHMI Janelia Farm Ashburn, VA, USA ; Department of Neuroscience and Physiology, New York University Medical Center New York, NY, USA.


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.


N-methyl-D-aspartate; bistability; olfaction; olfactory bulb; receptors; temporal sequence decoding

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