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Title: Non-linear blend coding in the moth antennal lobe emerges from random glomerular networks
Authors: Capurro, Alberto
Baroni, Fabiano
Olsson, Shannon B.
Kuebler, Linda S.
Karout, Salah
Hansson, Bill S.
Pearce, Timothy C.
First Published: 19-Apr-2012
Publisher: Frontiers Research Foundation
Citation: Frontiers in Neuroengineering, 2012, 5, article 6.
Abstract: Neural responses to odor blends often exhibit non-linear interactions to blend components. The first olfactory processing center in insects, the antennal lobe (AL), exhibits a complex network connectivity. We attempt to determine if non-linear blend interactions can arise purely as a function of the AL network connectivity itself, without necessitating additional factors such as competitive ligand binding at the periphery or intrinsic cellular properties. To assess this, we compared blend interactions among responses from single neurons recorded intracellularly in the AL of the moth Manduca sexta with those generated using a population-based computational model constructed from the morphologically based connectivity pattern of projection neurons (PNs) and local interneurons (LNs) with randomized connection probabilities from which we excluded detailed intrinsic neuronal properties. The model accurately predicted most of the proportions of blend interaction types observed in the physiological data. Our simulations also indicate that input from LNs is important in establishing both the type of blend interaction and the nature of the neuronal response (excitation or inhibition) exhibited by AL neurons. For LNs, the only input that significantly impacted the blend interaction type was received from other LNs, while for PNs the input from olfactory sensory neurons and other PNs contributed agonistically with the LN input to shape the AL output. Our results demonstrate that non-linear blend interactions can be a natural consequence of AL connectivity, and highlight the importance of lateral inhibition as a key feature of blend coding to be addressed in future experimental and computational studies.
DOI Link: 10.3389/fneng.2012.00006
ISSN: 1662-6443
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright: © 2012 Capurro, Baroni, Olsson, Kuebler, Karout, Hansson and Pearce. This is an open-access article distributed under the terms of the Creative Commons Attribution Non Commercial License, which permits non-commercial use, distribution, and reproduction in other forums, provided the original authors and source are credited.
Appears in Collections:Published Articles, Dept. of Engineering

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