Epilepsy is one of the most common neurological diseases, affecting up to 1% of the world population. Epilepsy remains poorly understood and there are currently no medications to cure it. Patients with epilepsy have both seizures as well as another type of abnormal activity between seizures, known as interictal spikes. Interictal spikes have thus far been poorly researched, yet growing evidence supports an important role for them in epilepsy. In this project, we first show the high variability between reviewers in marking interictal spikes on intracranial EEG, and then develop and test an automated detection method to solve this problem. Next, we use this automated detection algorithm to identify spikes on intracranial EEG in both tumor and non-tumor patients in order to determine the best spiking parameters to identify the seizure onset zone in each group. We then develop and characterize an animal model of chronic, neocortical interictal spiking to test our observations previously made in human epilepsy and to have a molecularly-accurate model on which to test new therapeutics. Finally, we show that interictal spikes are associated with behavioral changes in this animal model and that a targeted inhibitor can both prevent the development of a spiking focus and normalize behavior.
","abstract_html":"<p>Epilepsy is one of the most common neurological diseases, affecting up to 1% of the world population. Epilepsy remains poorly understood and there are currently no medications to cure it. Patients with epilepsy have both seizures as well as another type of abnormal activity between seizures, known as interictal spikes. Interictal spikes have thus far been poorly researched, yet growing evidence supports an important role for them in epilepsy. In this project, we first show the high variability between reviewers in marking interictal spikes on intracranial EEG, and then develop and test an automated detection method to solve this problem. Next, we use this automated detection algorithm to identify spikes on intracranial EEG in both tumor and non-tumor patients in order to determine the best spiking parameters to identify the seizure onset zone in each group. We then develop and characterize an animal model of chronic, neocortical interictal spiking to test our observations previously made in human epilepsy and to have a molecularly-accurate model on which to test new therapeutics. Finally, we show that interictal spikes are associated with behavioral changes in this animal model and that a targeted inhibitor can both prevent the development of a spiking focus and normalize behavior.</p>","abstract_has_math":false,"creators":["Barkmeier, Daniel Tice"],"institution":null,"degree_name":"Ph.D.","degree_level":"Open Access Dissertation","degree_discipline":"Molecular Biology and Genetics","degree_department":null,"school":null,"contributors":["Jeffrey A. Loeb"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2010,"date_issued":"2010-01-01T08:00:00Z","date_published":"2010-01-01T08:00:00Z","updated_at":"2026-07-24T05:58:35Z","subjects":["animal model","behavior","epilepsy","interictal","Molecular Biology","Neurosciences","Zoology"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.wayne.edu/oa_dissertations/3","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Jeffrey A. Loeb"]},{"key":"dc:creator","label":"Author","values":["Barkmeier, Daniel Tice"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2010-09-23T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Molecular Biology and Genetics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Open Access Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["animal model","behavior","epilepsy","interictal","Molecular Biology","Neurosciences","Zoology"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.wayne.edu/oa_dissertations/3"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Epilepsy is one of the most common neurological diseases, affecting up to 1% of the world population. Epilepsy remains poorly understood and there are currently no medications to cure it. Patients with epilepsy have both seizures as well as another type of abnormal activity between seizures, known as interictal spikes. Interictal spikes have thus far been poorly researched, yet growing evidence supports an important role for them in epilepsy. In this project, we first show the high variability between reviewers in marking interictal spikes on intracranial EEG, and then develop and test an automated detection method to solve this problem. Next, we use this automated detection algorithm to identify spikes on intracranial EEG in both tumor and non-tumor patients in order to determine the best spiking parameters to identify the seizure onset zone in each group. We then develop and characterize an animal model of chronic, neocortical interictal spiking to test our observations previously made in human epilepsy and to have a molecularly-accurate model on which to test new therapeutics. Finally, we show that interictal spikes are associated with behavioral changes in this animal model and that a targeted inhibitor can both prevent the development of a spiking focus and normalize behavior.
"]},{"key":"dc:title","label":"Title","values":["The Interictal State In Epilepsy And Behavior"]}]}],"canonical_facts":{"dc:contributor":["Jeffrey A. Loeb"],"dc:creator":["Barkmeier, Daniel Tice"],"dc:date.available":["2010-09-23T07:00:00Z"],"dc:description.abstract":["Epilepsy is one of the most common neurological diseases, affecting up to 1% of the world population. Epilepsy remains poorly understood and there are currently no medications to cure it. Patients with epilepsy have both seizures as well as another type of abnormal activity between seizures, known as interictal spikes. Interictal spikes have thus far been poorly researched, yet growing evidence supports an important role for them in epilepsy. In this project, we first show the high variability between reviewers in marking interictal spikes on intracranial EEG, and then develop and test an automated detection method to solve this problem. Next, we use this automated detection algorithm to identify spikes on intracranial EEG in both tumor and non-tumor patients in order to determine the best spiking parameters to identify the seizure onset zone in each group. We then develop and characterize an animal model of chronic, neocortical interictal spiking to test our observations previously made in human epilepsy and to have a molecularly-accurate model on which to test new therapeutics. Finally, we show that interictal spikes are associated with behavioral changes in this animal model and that a targeted inhibitor can both prevent the development of a spiking focus and normalize behavior.
"],"dc:identifier":["https://digitalcommons.wayne.edu/oa_dissertations/3"],"dc:subject":["animal model","behavior","epilepsy","interictal","Molecular Biology","Neurosciences","Zoology"],"dc:title":["The Interictal State In Epilepsy And Behavior"],"thesis:degree_discipline":["Molecular Biology and Genetics"],"thesis:degree_level":["Open Access Dissertation"],"thesis:degree_name":["Ph.D."]},"updated_at":"2026-07-24T05:58:35Z"}