{"id":{"repo_id":"rice","oai_identifier":"oai:repository.rice.edu:1911/104316"},"canonical_url":"https://search.dev.ndltd.org/etd/rice/oai:repository.rice.edu:1911/104316","repository":{"repo_id":"rice","name":"Rice University","base_url":"https://repository.rice.edu/server/oai/request"},"display":{"title":"Point process models for discharge patterns of single units in the lateral superior olive of the cat","abstract":"Discharge patterns from the Lateral Superior Olive of the cat are analyzed using point process methods. An intensity description is developed for responses to continuous tone and tone burst stimuli. The statistics of each process are described using the intervals between events in the response. We find that a first order Markovian model is sufficient to describe the observed serial dependence of the inter-spike intervals. In our model, the duration of the absolute dead time of one interval is inversely related to the duration of the previous interval. Superposition of renewal processes with a dead time implemented is shown to lack the necessary serial dependence which would qualify it as a potential model for LSO discharge patterns. Using our model, the early, non-stationary portion of tone burst responses is predicted based on the statistics of the later, stationary portion.","abstract_html":"Discharge patterns from the Lateral Superior Olive of the cat are analyzed using point process methods. An intensity description is developed for responses to continuous tone and tone burst stimuli. The statistics of each process are described using the intervals between events in the response. We find that a first order Markovian model is sufficient to describe the observed serial dependence of the inter-spike intervals. In our model, the duration of the absolute dead time of one interval is inversely related to the duration of the previous interval. Superposition of renewal processes with a dead time implemented is shown to lack the necessary serial dependence which would qualify it as a potential model for LSO discharge patterns. Using our model, the early, non-stationary portion of tone burst responses is predicted based on the statistics of the later, stationary portion.","abstract_has_math":false,"creators":["Linebarger, Darel Allen"],"institution":"Rice University","degree_name":"Master of Science","degree_level":"Masters","degree_discipline":"Engineering","degree_department":null,"school":null,"contributors":[],"advisors":["Johnson, Don H."],"committee_chairs":[],"committee_members":["Clark, John W.","Pfeiffer, Paul E."],"year":1985,"date_issued":"1985","date_published":"1985","updated_at":"2026-07-24T04:10:19Z","subjects":[],"languages":["eng"],"rights":["Copyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/1911/104316","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Johnson, Don H."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Clark, John W.","Pfeiffer, Paul E."]},{"key":"dc:creator","label":"Author","values":["Linebarger, Darel Allen"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2018-12-18T21:20:52Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2018-12-18T21:20:52Z"]},{"key":"dc:date.issued","label":"Date","values":["1985"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Rice University"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright is held by the author, unless otherwise indicated. 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In our model, the duration of the absolute dead time of one interval is inversely related to the duration of the previous interval. Superposition of renewal processes with a dead time implemented is shown to lack the necessary serial dependence which would qualify it as a potential model for LSO discharge patterns. Using our model, the early, non-stationary portion of tone burst responses is predicted based on the statistics of the later, stationary portion."]},{"key":"dc:title","label":"Title","values":["Point process models for discharge patterns of single units in the lateral superior olive of the cat"]}]}],"canonical_facts":{"dc:contributor.advisor":["Johnson, Don H."],"dc:contributor.committeemember":["Clark, John W.","Pfeiffer, Paul E."],"dc:creator":["Linebarger, Darel Allen"],"dc:date.accessioned":["2018-12-18T21:20:52Z"],"dc:date.available":["2018-12-18T21:20:52Z"],"dc:date.issued":["1985"],"dc:description.abstract":["Discharge patterns from the Lateral Superior Olive of the cat are analyzed using point process methods. An intensity description is developed for responses to continuous tone and tone burst stimuli. The statistics of each process are described using the intervals between events in the response. We find that a first order Markovian model is sufficient to describe the observed serial dependence of the inter-spike intervals. In our model, the duration of the absolute dead time of one interval is inversely related to the duration of the previous interval. Superposition of renewal processes with a dead time implemented is shown to lack the necessary serial dependence which would qualify it as a potential model for LSO discharge patterns. Using our model, the early, non-stationary portion of tone burst responses is predicted based on the statistics of the later, stationary portion."],"dc:identifier.uri":["https://hdl.handle.net/1911/104316"],"dc:language.iso":["eng"],"dc:rights":["Copyright is held by the author, unless otherwise indicated. 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