Decoding Sound Source Location and Separation Using Neural Population Activity Patterns

The strategies by which the central nervous system decodes the properties of sensory stimuli, such as sound source location, from the responses of a population of neurons are a matter of debate. We show, using the average firing rates of neurons in the inferior colliculus (IC) of awake rabbits, that...

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Main Authors: Day, Mitchell L., Delgutte, Bertrand
Other Authors: Massachusetts Institute of Technology. Research Laboratory of Electronics
Format: Article
Language:en_US
Published: Society for Neuroscience 2014
Online Access:http://hdl.handle.net/1721.1/89135
https://orcid.org/0000-0003-1349-9608
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author Day, Mitchell L.
Delgutte, Bertrand
author2 Massachusetts Institute of Technology. Research Laboratory of Electronics
author_facet Massachusetts Institute of Technology. Research Laboratory of Electronics
Day, Mitchell L.
Delgutte, Bertrand
author_sort Day, Mitchell L.
collection MIT
description The strategies by which the central nervous system decodes the properties of sensory stimuli, such as sound source location, from the responses of a population of neurons are a matter of debate. We show, using the average firing rates of neurons in the inferior colliculus (IC) of awake rabbits, that prevailing decoding models of sound localization (summed population activity and the population vector) fail to localize sources accurately due to heterogeneity in azimuth tuning across the population. In contrast, a maximum-likelihood decoder operating on the pattern of activity across the population of neurons in one IC accurately localized sound sources in the contralateral hemifield, consistent with lesion studies, and did so with a precision consistent with rabbit psychophysical performance. The pattern decoder also predicts behavior in response to incongruent localization cues consistent with the long-standing “duplex” theory of sound localization. We further show that the pattern decoder accurately distinguishes two concurrent, spatially separated sources from a single source, consistent with human behavior. Decoder detection of small amounts of source separation directly in front is due to neural sensitivity to the interaural decorrelation of sound, at both low and high frequencies. The distinct patterns of IC activity between single and separated sound sources thereby provide a neural correlate for the ability to segregate and localize sources in everyday, multisource environments.
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spelling mit-1721.1/891352022-09-30T15:30:40Z Decoding Sound Source Location and Separation Using Neural Population Activity Patterns Day, Mitchell L. Delgutte, Bertrand Massachusetts Institute of Technology. Research Laboratory of Electronics Delgutte, Bertrand The strategies by which the central nervous system decodes the properties of sensory stimuli, such as sound source location, from the responses of a population of neurons are a matter of debate. We show, using the average firing rates of neurons in the inferior colliculus (IC) of awake rabbits, that prevailing decoding models of sound localization (summed population activity and the population vector) fail to localize sources accurately due to heterogeneity in azimuth tuning across the population. In contrast, a maximum-likelihood decoder operating on the pattern of activity across the population of neurons in one IC accurately localized sound sources in the contralateral hemifield, consistent with lesion studies, and did so with a precision consistent with rabbit psychophysical performance. The pattern decoder also predicts behavior in response to incongruent localization cues consistent with the long-standing “duplex” theory of sound localization. We further show that the pattern decoder accurately distinguishes two concurrent, spatially separated sources from a single source, consistent with human behavior. Decoder detection of small amounts of source separation directly in front is due to neural sensitivity to the interaural decorrelation of sound, at both low and high frequencies. The distinct patterns of IC activity between single and separated sound sources thereby provide a neural correlate for the ability to segregate and localize sources in everyday, multisource environments. National Institute on Deafness and Other Communication Disorders (U.S.) (Grant R01 DC002258) National Institute on Deafness and Other Communication Disorders (U.S.) (Grant P30 DC005209) 2014-09-02T17:49:20Z 2014-09-02T17:49:20Z 2013-10 2013-07 Article http://purl.org/eprint/type/JournalArticle 0270-6474 1529-2401 http://hdl.handle.net/1721.1/89135 Day, M. L., and B. Delgutte. “Decoding Sound Source Location and Separation Using Neural Population Activity Patterns.” Journal of Neuroscience 33, no. 40 (October 2, 2013): 15837–15847. https://orcid.org/0000-0003-1349-9608 en_US http://dx.doi.org/10.1523/jneurosci.2034-13.2013 Journal of Neuroscience Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf Society for Neuroscience Society for Neuroscience
spellingShingle Day, Mitchell L.
Delgutte, Bertrand
Decoding Sound Source Location and Separation Using Neural Population Activity Patterns
title Decoding Sound Source Location and Separation Using Neural Population Activity Patterns
title_full Decoding Sound Source Location and Separation Using Neural Population Activity Patterns
title_fullStr Decoding Sound Source Location and Separation Using Neural Population Activity Patterns
title_full_unstemmed Decoding Sound Source Location and Separation Using Neural Population Activity Patterns
title_short Decoding Sound Source Location and Separation Using Neural Population Activity Patterns
title_sort decoding sound source location and separation using neural population activity patterns
url http://hdl.handle.net/1721.1/89135
https://orcid.org/0000-0003-1349-9608
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