Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/82718
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Type: Conference paper
Title: Can a competitive neural network explain selective attention in insect target tracking neurons?
Author: Shoemaker, P.
Wiederman, S.
O'Carroll, D.
Citation: 2013 6th International IEEE/EMBS Conference on Neural Engineering (NER), San Diego, California, 6 - 8 November, 2013: pp.903-906
Publisher: IEEE
Publisher Place: USA
Issue Date: 2013
Series/Report no.: International IEEE EMBS Conference on Neural Engineering
ISBN: 9781467319690
ISSN: 1948-3546
1948-3554
Conference Name: International IEEE/EMBS Conference on Neural Engineering (6th : 2013 : San Diego, U.S.A.)
Statement of
Responsibility: 
Patrick A. Shoemaker, Steven D. Wiederman, and David C. O’Carroll
Abstract: Small target motion detecting (STMD) neurons in the dragonfly brain are neural correlates of a highly-specialized and ethologically-significant feature detection function, and the recent discovery of selective attention in STMDs has clear implications for the ability of dragonflies to track and pursue one target from among several. We used a biophysically-plausible neural network model, based on competitive units fed by NMDA-type synaptic inputs and including lateral feedback inhibition, to model these attentional effects in numerical simulations. With appropriate forward gain, the model displays a winner-takes-all behavior that partially captures the selective attention documented in electrophysiological recordings from STMDs. It cannot, however, explain the full range of results that have now been observed in wide-field STMDs, in particular a bias toward attention to targets dependent on their traversal of continuous trajectories.
Rights: ©2013 IEEE
RMID: 0020135430
DOI: 10.1109/NER.2013.6696081
Appears in Collections:Medical Sciences publications

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