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Response properties of neighboring neurons in the auditory midbrain

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dc.contributor.advisor Bertrand Delgutte. en_US
dc.contributor.author Seshagiri, Chandran V. (Chandran Venkatraman) en_US
dc.contributor.other Harvard University--MIT Division of Health Sciences and Technology. en_US
dc.date.accessioned 2008-01-10T17:25:12Z
dc.date.available 2008-01-10T17:25:12Z
dc.date.copyright 2006 en_US
dc.date.issued 2006 en_US
dc.identifier.uri http://dspace.mit.edu/handle/1721.1/35512 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/35512
dc.description Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2006. en_US
dc.description Includes bibliographical references (p. 171-175). en_US
dc.description.abstract The inferior colliculus, the primary nucleus in the mammalian auditory midbrain, occupies a central position in the ascending auditory pathway. Nearly all ascending neural pathways converge and synapse in the central nucleus of the inferior colliculus (ICC). Further, the anatomical arrangement of axons and neurons in the ICC suggests the existence of functional regions which may play a role in organizing different types of physiological information. To investigate this organization, we characterized the response properties of neighboring neurons in the ICC. To record reliably from neighboring neurons, we adopted a relatively new electrophysiological technique, tetrode recordings. Tetrodes have four closely spaced recording sites (<20[mu]m) which record multi-unit activity from a small number of neighboring neurons. The recorded signals contain action potentials originating from more than one neuron. Based on action potential wave shape differences across the four channels, we can reconstruct the contributions of individual neurons. Applying tetrode recordings to the ICC of anesthetized cats, we successfully reconstructed individual spike trains for 190 neurons at 52 recording sites. en_US
dc.description.abstract (cont.) To quantify the advantage of tetrodes, we compared our multi-channel recording results with waveform sorting from single-channel electrode recordings. At best, only 32% of the single-units from tetrode sorting were correctly identified using single-channel recordings. We used tetrode to characterize pure tone responses of neighboring neurons in the ICC in terms of frequency selectivity, level dependence, temporal discharge patterns, and sensitivity to interaural time differences. We find similarities in best frequency and pure-tone threshold among neighboring neurons; however, we find large disparities in bandwidth, level dependence, temporal discharge patterns, and sensitivity to interaural time differences. These results suggest that neighboring neurons in ICC can greatly differ in membrane properties and/or their patterns of synaptic input from different brainstem nuclei and tonotopic regions. Using tetrode recordings, we investigated how well multi-unit responses represent the response properties of the contributing single-unit responses. en_US
dc.description.abstract (cont.) We find that multi-unit responses represent single-unit best frequency, pure-tone threshold and level dependence well, and they represent single-unit bandwidth and interaural phase sensitivity poorly. These results suggest caution must be used not to infer single-unit responses from multi-unit recordings. en_US
dc.description.statementofresponsibility by Chandran V. Seshagiri. en_US
dc.format.extent 175 p. en_US
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights 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. en_US
dc.rights.uri http://dspace.mit.edu/handle/1721.1/35512 en_US
dc.rights.uri http://dspace.mit.edu/handle/1721.1/7582
dc.subject Harvard University--MIT Division of Health Sciences and Technology. en_US
dc.title Response properties of neighboring neurons in the auditory midbrain en_US
dc.type Thesis en_US
dc.description.degree Ph.D. en_US
dc.contributor.department Harvard University--MIT Division of Health Sciences and Technology. en_US
dc.identifier.oclc 71822278 en_US


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