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Journal of Computational Neuroscience

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01-12-2009

A large-scale model of the locust antennal lobe

Authors: Mainak Patel, Aaditya V. Rangan, David Cai

Published in: Journal of Computational Neuroscience | Issue 3/2009

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Abstract

The antennal lobe (AL) is the primary structure within the locust’s brain that receives information from olfactory receptor neurons (ORNs) within the antennae. Different odors activate distinct subsets of ORNs, implying that neuronal signals at the level of the antennae encode odors combinatorially. Within the AL, however, different odors produce signals with long-lasting dynamic transients carried by overlapping neural ensembles, suggesting a more complex coding scheme. In this work we use a large-scale point neuron model of the locust AL to investigate this shift in stimulus encoding and potential consequences for odor discrimination. Consistent with experiment, our model produces stimulus-sensitive, dynamically evolving populations of active AL neurons. Our model relies critically on the persistence time-scale associated with ORN input to the AL, sparse connectivity among projection neurons, and a synaptic slow inhibitory mechanism. Collectively, these architectural features can generate network odor representations of considerably higher dimension than would be generated by a direct feed-forward representation of stimulus space.

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Title: A large-scale model of the locust antennal lobe
Authors: Mainak Patel
Aaditya V. Rangan
David Cai
Publication date: 01-12-2009
Publisher: Springer US
Published in: Journal of Computational Neuroscience / Issue 3/2009
Print ISSN: 0929-5313
Electronic ISSN: 1573-6873
DOI: https://doi.org/10.1007/s10827-009-0169-z

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