{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/121459"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/121459","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"A biophysical conductance-based model of neural spike timing and interspike interval correlations","abstract":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-12-04 without embargo terms","abstract_html":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-12-04 without embargo terms","abstract_has_math":false,"creators":["Asilador, Alexander"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Neuroscience","degree_department":null,"school":null,"contributors":["Ratnam, Rama","Jones, Douglas L","Llano, Daniel A","Auerbach, Benjamin D"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-08","date_published":"2023-08","updated_at":"2026-07-22T22:24:57Z","subjects":["Biophysical Model","Neural Coding","Sensory Neurons","Temporal Coding"],"languages":["en","eng"],"rights":["Copyright 2023 Alexander Asilador"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/121459","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Ratnam, Rama","Jones, Douglas L","Llano, Daniel A","Auerbach, Benjamin D"]},{"key":"dc:creator","label":"Author","values":["Asilador, Alexander"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2023-08","2023-07-12"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Neuroscience"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Biophysical Model","Neural Coding","Sensory Neurons","Temporal Coding"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2023 Alexander Asilador"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/121459"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-12-04 without embargo terms","The student, Alexander Asilador, accepted the attached license on 2023-07-05 at 17:23.","The student, Alexander Asilador, submitted this Dissertation for approval on 2023-07-05 at 17:37.","This Dissertation was approved for publication on 2023-07-12 at 07:11.","DSpace SAF Submission Ingestion Package generated from Vireo submission #19522 on 2023-12-04 at 17:00:44","Neurons encode information in the form of spike times. It is argued that the timing between spikes (i.e., spike-timing) encodes the stimulus input. Spike threshold adaptation is speculated to be the major driving force behind a spike-timing code. Efforts to understand the neuron channels that drive an adaptive threshold have relied on purely mathematical models. Such models have had great success at predicting spike times, but do not have a strong basis in biophysics or what is known about neural channels to predict spike timing. State-of-the-art biophysical models, however, suffer at the cost of model interpretability and spike-timing accuracy. We investigate spike threshold adaptation with a biophysical, Hodgkin-Huxley type model in a reduced fashion, with consideration to voltage-gated ion channels present only the axonal hillock, and fit spike timing that outperforms the best phenomenological model. We then evaluate the presence and effect of spike-threshold adaptation by estimating the current-voltage interaction and determine that the Kv7/KCNQ ion channel is likely the major ion channel responsible for an adaptive threshold in rodent pyramidal cells in-vitro. These findings are an alternative approach to previous research investigating outward potassium channels, and partially agree with previous research. We next develop a stochastic extension of the model with consideration of other stochastic models to produce stochastic spike timing and behavior observed in experimental data. We find that a stochastic Kv7/KCNQ ion channel with correlated spike-to-spike noise is able to reproduce neuron variability in experimental data and is consistent with the theoretical parameters derived from a stochastic dynamic threshold model."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["A biophysical conductance-based model of neural spike timing and interspike interval correlations"]}]}],"canonical_facts":{"dc:contributor":["Ratnam, Rama","Jones, Douglas L","Llano, Daniel A","Auerbach, Benjamin D"],"dc:creator":["Asilador, Alexander"],"dc:date":["2023-08","2023-07-12"],"dc:description":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-12-04 without embargo terms","The student, Alexander Asilador, accepted the attached license on 2023-07-05 at 17:23.","The student, Alexander Asilador, submitted this Dissertation for approval on 2023-07-05 at 17:37.","This Dissertation was approved for publication on 2023-07-12 at 07:11.","DSpace SAF Submission Ingestion Package generated from Vireo submission #19522 on 2023-12-04 at 17:00:44","Neurons encode information in the form of spike times. It is argued that the timing between spikes (i.e., spike-timing) encodes the stimulus input. Spike threshold adaptation is speculated to be the major driving force behind a spike-timing code. Efforts to understand the neuron channels that drive an adaptive threshold have relied on purely mathematical models. Such models have had great success at predicting spike times, but do not have a strong basis in biophysics or what is known about neural channels to predict spike timing. State-of-the-art biophysical models, however, suffer at the cost of model interpretability and spike-timing accuracy. We investigate spike threshold adaptation with a biophysical, Hodgkin-Huxley type model in a reduced fashion, with consideration to voltage-gated ion channels present only the axonal hillock, and fit spike timing that outperforms the best phenomenological model. We then evaluate the presence and effect of spike-threshold adaptation by estimating the current-voltage interaction and determine that the Kv7/KCNQ ion channel is likely the major ion channel responsible for an adaptive threshold in rodent pyramidal cells in-vitro. These findings are an alternative approach to previous research investigating outward potassium channels, and partially agree with previous research. We next develop a stochastic extension of the model with consideration of other stochastic models to produce stochastic spike timing and behavior observed in experimental data. We find that a stochastic Kv7/KCNQ ion channel with correlated spike-to-spike noise is able to reproduce neuron variability in experimental data and is consistent with the theoretical parameters derived from a stochastic dynamic threshold model."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/121459"],"dc:language":["en","eng"],"dc:rights":["Copyright 2023 Alexander Asilador"],"dc:subject":["Biophysical Model","Neural Coding","Sensory Neurons","Temporal Coding"],"dc:title":["A biophysical conductance-based model of neural spike timing and interspike interval correlations"],"dc:type":["text"],"thesis:degree_discipline":["Neuroscience"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:57Z"}