<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-20T18:43:58Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/16700" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/16700</identifier><datestamp>2022-01-13T07:53:45Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131022</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Bertrand Delgutte.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Lane, Courtney C., 1974-</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Harvard University--MIT Division of Health Sciences and Technology.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Harvard University--MIT Division of Health Sciences and Technology</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2005-05-17T14:58:54Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2005-05-17T14:58:54Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2003</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2004</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/16700</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">57509641</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, February 2004.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (p. 138-142).</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">This electronic version was submitted by the student author.  The certified thesis is available in the Institute Archives and Special Collections.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">Normal-hearing listeners have a remarkable ability to hear in noisy environments, while hearing-impaired listeners and automatic speech-recognition systems often have difficulty in noise. With the ultimate goal of improving hearing aids and speech-recognition systems, we study the neural mechanisms involved in one aspect of noisy-environment listening, "spatial release from masking," which is the observation that a signal is more easily detected when its source is spatially separated from a masking-noise source. We use neurophysiology, computational modeling, and psychoacoustics to investigate the neural mechanisms of spatial release from masking, and we focus on low frequencies, which are important for speech recognition and are often spared in hearing-impaired listeners. Previous studies suggest that at low frequencies, listeners use interaural time differences (ITDs) to improve signal detection when signals and maskers are spatially separated in azimuth. To determine how individual neurons respond to spatially separated signals and maskers, we record in anesthetized cats from low-frequency, ITD-sensitive neurons in the inferior colliculus (IC), a major center of converging auditory pathways in the midbrain. We develop a computational model of the neuron responses, which incorporates both interaural cross-correlation (as used in existing binaural models) and amplitude-modulation sensitivity. The need for modulation sensitivity to predict the neural responses indicates that binaural and temporal processing are interacting in signal detection, rather than acting independently as is often assumed. This modification is especially important because most natural sounds, including speech, have pronounced envelope fluctuations that</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">(cont.) previous models of binaural detection have not utilized. To relate these neurophysiological results to human behavioral thresholds, we define population thresholds based on the most sensitive neurons in the population. The neural population thresholds are similar to human behavioral thresholds, indicating that low-frequency, ITD-sensitive neurons in the IC may be necessary for low-frequency spatial release from masking in humans. Both interaural correlation and modulation sensitivity seem to be required for the model population thresholds to predict human behavioral thresholds. Overall, our findings suggest that considering the auditory system's modulation sensitivity and interaural cross-correlation in the design of hearing aids and speech-recognition systems may improve these devices' performance in noise.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Courtney C. Lane.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">Ph.D.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">142 p.</dim:field>
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   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Harvard University--MIT Division of Health Sciences and Technology.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Signal detection in the auditory midbrain : neural correlated and mechanisms of spatial release from masking</dim:field>
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   	&lt;Title>Signal detection in the auditory midbrain : neural correlated and mechanisms of spatial release from masking&lt;/Title>
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   	&lt;PublicationDate>2004&lt;/PublicationDate&gt;
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        	&lt;DisplayName>Lane, Courtney C., 1974-&lt;/DisplayName>
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   	&lt;Abstract>Normal-hearing listeners have a remarkable ability to hear in noisy environments, while hearing-impaired listeners and automatic speech-recognition systems often have difficulty in noise. With the ultimate goal of improving hearing aids and speech-recognition systems, we study the neural mechanisms involved in one aspect of noisy-environment listening, &amp;quot;spatial release from masking,&amp;quot; which is the observation that a signal is more easily detected when its source is spatially separated from a masking-noise source. We use neurophysiology, computational modeling, and psychoacoustics to investigate the neural mechanisms of spatial release from masking, and we focus on low frequencies, which are important for speech recognition and are often spared in hearing-impaired listeners. Previous studies suggest that at low frequencies, listeners use interaural time differences (ITDs) to improve signal detection when signals and maskers are spatially separated in azimuth. To determine how individual neurons respond to spatially separated signals and maskers, we record in anesthetized cats from low-frequency, ITD-sensitive neurons in the inferior colliculus (IC), a major center of converging auditory pathways in the midbrain. We develop a computational model of the neuron responses, which incorporates both interaural cross-correlation (as used in existing binaural models) and amplitude-modulation sensitivity. The need for modulation sensitivity to predict the neural responses indicates that binaural and temporal processing are interacting in signal detection, rather than acting independently as is often assumed. This modification is especially important because most natural sounds, including speech, have pronounced envelope fluctuations that&lt;/Abstract>
   	&lt;Abstract>(cont.) previous models of binaural detection have not utilized. To relate these neurophysiological results to human behavioral thresholds, we define population thresholds based on the most sensitive neurons in the population. The neural population thresholds are similar to human behavioral thresholds, indicating that low-frequency, ITD-sensitive neurons in the IC may be necessary for low-frequency spatial release from masking in humans. Both interaural correlation and modulation sensitivity seem to be required for the model population thresholds to predict human behavioral thresholds. Overall, our findings suggest that considering the auditory system&amp;apos;s modulation sensitivity and interaural cross-correlation in the design of hearing aids and speech-recognition systems may improve these devices&amp;apos; performance in noise.&lt;/Abstract>
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