Spike-timing-based computation in sound localization

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Title: Spike-timing-based computation in sound localization
Author(s): Goodman, DF
Brette, R
Item Type: Journal Article
Abstract: Spike timing is precise in the auditory system and it has been argued that it conveys information about auditory stimuli, in particular about the location of a sound source. However, beyond simple time differences, the way in which neurons might extract this information is unclear and the potential computational advantages are unknown. The computational difficulty of this task for an animal is to locate the source of an unexpected sound from two monaural signals that are highly dependent on the unknown source signal. In neuron models consisting of spectro-temporal filtering and spiking nonlinearity, we found that the binaural structure induced by spatialized sounds is mapped to synchrony patterns that depend on source location rather than on source signal. Location-specific synchrony patterns would then result in the activation of location-specific assemblies of postsynaptic neurons. We designed a spiking neuron model which exploited this principle to locate a variety of sound sources in a virtual acoustic environment using measured human head-related transfer functions. The model was able to accurately estimate the location of previously unknown sounds in both azimuth and elevation (including front/back discrimination) in a known acoustic environment. We found that multiple representations of different acoustic environments could coexist as sets of overlapping neural assemblies which could be associated with spatial locations by Hebbian learning. The model demonstrates the computational relevance of relative spike timing to extract spatial information about sources independently of the source signal.
Publication Date: 11-Nov-2010
Date of Acceptance: 8-Oct-2010
URI: http://hdl.handle.net/10044/1/40629
DOI: http://dx.doi.org/10.1371/journal.pcbi.1000993
ISSN: 1553-734X
Publisher: Public Library of Science
Journal / Book Title: PLOS Computational Biology
Volume: 6
Issue: 11
Copyright Statement: © 2010 Goodman, Brette. 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.
Keywords: Action Potentials
Artificial Intelligence
Cochlea
Computational Biology
Computer Simulation
Evoked Potentials, Auditory
Hair Cells, Auditory
Humans
Models, Neurological
Neuronal Plasticity
Pyramidal Cells
Sound Localization
Synapses
Pyramidal Cells
Synapses
Cochlea
Humans
Sound Localization
Computational Biology
Evoked Potentials, Auditory
Action Potentials
Neuronal Plasticity
Models, Neurological
Artificial Intelligence
Computer Simulation
Hair Cells, Auditory
Bioinformatics
06 Biological Sciences
08 Information And Computing Sciences
01 Mathematical Sciences
Publication Status: Published
Article Number: e1000993
Appears in Collections:Faculty of Engineering
Electrical and Electronic Engineering



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