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Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/10113

Title: Stimulus and network dynamics collide in a ratiometric model of the antennal lobe macroglomerular complex.
Authors: Chong, Kwok Ying
Capurro, Alberto
Karout, Salah
Pearce, Timothy Charles
Issue Date: 10-Jan-2012
Publisher: Public Library of Science (PLoS)
Citation: PLoS One, 2012, 7 (1), pp. e29602.
Abstract: Time is considered to be an important encoding dimension in olfaction, as neural populations generate odour-specific spatiotemporal responses to constant stimuli. However, during pheromone mediated anemotactic search insects must discriminate specific ratios of blend components from rapidly time varying input. The dynamics intrinsic to olfactory processing and those of naturalistic stimuli can therefore potentially collide, thereby confounding ratiometric information. In this paper we use a computational model of the macroglomerular complex of the insect antennal lobe to study the impact on ratiometric information of this potential collision between network and stimulus dynamics. We show that the model exhibits two different dynamical regimes depending upon the connectivity pattern between inhibitory interneurons (that we refer to as fixed point attractor and limit cycle attractor), which both generate ratio-specific trajectories in the projection neuron output population that are reminiscent of temporal patterning and periodic hyperpolarisation observed in olfactory antennal lobe neurons. We compare the performance of the two corresponding population codes for reporting ratiometric blend information to higher centres of the insect brain. Our key finding is that whilst the dynamically rich limit cycle attractor spatiotemporal code is faster and more efficient in transmitting blend information under certain conditions it is also more prone to interference between network and stimulus dynamics, thus degrading ratiometric information under naturalistic input conditions. Our results suggest that rich intrinsically generated network dynamics can provide a powerful means of encoding multidimensional stimuli with high accuracy and efficiency, but only when isolated from stimulus dynamics. This interference between temporal dynamics of the stimulus and temporal patterns of neural activity constitutes a real challenge that must be successfully solved by the nervous system when faced with naturalistic input.
DOI Link: 10.1371/journal.pone.0029602
eISSN: 1932-6203
Links: http://www.plosone.org/home.action
http://hdl.handle.net/2381/10113
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: © 2012 Chong et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Appears in Collections:Published Articles, Dept. of Engineering

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