{"id":{"repo_id":"toronto-retro","oai_identifier":"oai:utoronto.scholaris.ca:1807/123142"},"canonical_url":"https://search.dev.ndltd.org/etd/toronto-retro/oai:utoronto.scholaris.ca:1807/123142","repository":{"repo_id":"toronto-retro","name":"University of Toronto","base_url":"https://utoronto.scholaris.ca/server/oai/request"},"display":{"title":"Impact of Noise and Spike Initiation Properties on the Encoding and Transmission of Neural Information","abstract":"Neurons use action potentials, or spikes, to process information. Different aspects of spiking, such as its rate or timing, are used to encode information about different features of an input. But noise can influence how robustly information is represented in each coding scheme. Additionally, information can be lost if neural representations are not transmitted with high fidelity to downstream neurons. In both cases, properties of the input (its amplitude and kinetics) and properties of the neuron (its spike initiation mechanism and excitability) impact neural information processing. In my thesis, I first investigated how axons are optimized to transmit spike-based representations. Using patch clamp electrophysiology combined with optogenetics, I showed that the axon of CA1 pyramidal neurons spikes transiently in response to sustained depolarization, in contrast to the soma and axon initial segment, which spike repetitively. These distinct spiking patterns are due to the differential expression of ion channels, supporting functional specialization of neuronal compartments. Specifically, low-threshold potassium channels (Kv1) cause the axon to behave as a high-pass filter, enabling high fidelity transmission of spike-based information so that the axon selectively responds to inputs with fast kinetics. Together with biophysical modeling, my findings demonstrate that spike initiation properties in each part of the neuron are well matched to the signals normally processed in that neuronal compartment. I then investigated how background synaptic activity (noise) affects rate and temporal coding of vibrotactile stimuli. Using patch clamp electrophysiology and dynamic clamp in vitro, I found that layer 2/3 pyramidal neurons in primary somatosensory cortex spike intermittently to inputs repeated at frequencies perceived as vibration. The fraction of inputs evoking a spike varies with input amplitude, enabling firing rate to encode stimulus intensity. Despite being small in amplitude, inputs are abrupt in onset, which allows them to evoke precisely timed spikes, even under noisy conditions. Unreliable spiking allows noise to produce irregular skipping, enabling spike times (patterns) to encode stimulus frequency. The reliability and precision of spikes depend on input amplitude and kinetics, respectively. With the help of simulations, my results show that noise helps multiplexed rate and temporal coding.","abstract_html":"Neurons use action potentials, or spikes, to process information. Different aspects of spiking, such as its rate or timing, are used to encode information about different features of an input. But noise can influence how robustly information is represented in each coding scheme. Additionally, information can be lost if neural representations are not transmitted with high fidelity to downstream neurons. In both cases, properties of the input (its amplitude and kinetics) and properties of the neuron (its spike initiation mechanism and excitability) impact neural information processing. In my thesis, I first investigated how axons are optimized to transmit spike-based representations. Using patch clamp electrophysiology combined with optogenetics, I showed that the axon of CA1 pyramidal neurons spikes transiently in response to sustained depolarization, in contrast to the soma and axon initial segment, which spike repetitively. These distinct spiking patterns are due to the differential expression of ion channels, supporting functional specialization of neuronal compartments. Specifically, low-threshold potassium channels (Kv1) cause the axon to behave as a high-pass filter, enabling high fidelity transmission of spike-based information so that the axon selectively responds to inputs with fast kinetics. Together with biophysical modeling, my findings demonstrate that spike initiation properties in each part of the neuron are well matched to the signals normally processed in that neuronal compartment. I then investigated how background synaptic activity (noise) affects rate and temporal coding of vibrotactile stimuli. Using patch clamp electrophysiology and dynamic clamp in vitro, I found that layer 2/3 pyramidal neurons in primary somatosensory cortex spike intermittently to inputs repeated at frequencies perceived as vibration. The fraction of inputs evoking a spike varies with input amplitude, enabling firing rate to encode stimulus intensity. Despite being small in amplitude, inputs are abrupt in onset, which allows them to evoke precisely timed spikes, even under noisy conditions. Unreliable spiking allows noise to produce irregular skipping, enabling spike times (patterns) to encode stimulus frequency. The reliability and precision of spikes depend on input amplitude and kinetics, respectively. With the help of simulations, my results show that noise helps multiplexed rate and temporal coding.","abstract_has_math":false,"creators":["Kamaleddin Ezabadi, Seyed Mohammad Amin"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Biomedical Engineering","school":null,"contributors":[],"advisors":["Prescott, Steven A"],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-06","date_published":"2022-06","updated_at":"2026-07-27T21:28:11Z","subjects":[],"languages":[],"rights":["Attribution 4.0 International"],"rights_urls":["http://creativecommons.org/licenses/by/4.0/"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1807/123142","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Prescott, Steven A"]},{"key":"dc:contributor.department","label":"Department","values":["Biomedical Engineering"]},{"key":"dc:creator","label":"Author","values":["Kamaleddin Ezabadi, Seyed Mohammad Amin"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2022-06"]},{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2022-06-29T15:05:25Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2022-06-29T15:05:25Z"]},{"key":"dc:date.issued","label":"Date","values":["2022-06"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Attribution 4.0 International"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://creativecommons.org/licenses/by/4.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1807/123142"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Neurons use action potentials, or spikes, to process information. Different aspects of spiking, such as its rate or timing, are used to encode information about different features of an input. But noise can influence how robustly information is represented in each coding scheme. Additionally, information can be lost if neural representations are not transmitted with high fidelity to downstream neurons. In both cases, properties of the input (its amplitude and kinetics) and properties of the neuron (its spike initiation mechanism and excitability) impact neural information processing. In my thesis, I first investigated how axons are optimized to transmit spike-based representations. Using patch clamp electrophysiology combined with optogenetics, I showed that the axon of CA1 pyramidal neurons spikes transiently in response to sustained depolarization, in contrast to the soma and axon initial segment, which spike repetitively. These distinct spiking patterns are due to the differential expression of ion channels, supporting functional specialization of neuronal compartments. Specifically, low-threshold potassium channels (Kv1) cause the axon to behave as a high-pass filter, enabling high fidelity transmission of spike-based information so that the axon selectively responds to inputs with fast kinetics. Together with biophysical modeling, my findings demonstrate that spike initiation properties in each part of the neuron are well matched to the signals normally processed in that neuronal compartment. I then investigated how background synaptic activity (noise) affects rate and temporal coding of vibrotactile stimuli. Using patch clamp electrophysiology and dynamic clamp in vitro, I found that layer 2/3 pyramidal neurons in primary somatosensory cortex spike intermittently to inputs repeated at frequencies perceived as vibration. The fraction of inputs evoking a spike varies with input amplitude, enabling firing rate to encode stimulus intensity. Despite being small in amplitude, inputs are abrupt in onset, which allows them to evoke precisely timed spikes, even under noisy conditions. Unreliable spiking allows noise to produce irregular skipping, enabling spike times (patterns) to encode stimulus frequency. The reliability and precision of spikes depend on input amplitude and kinetics, respectively. With the help of simulations, my results show that noise helps multiplexed rate and temporal coding."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph.D."]},{"key":"dc:title","label":"Title","values":["Impact of Noise and Spike Initiation Properties on the Encoding and Transmission of Neural Information"]}]}],"canonical_facts":{"dc:contributor.advisor":["Prescott, Steven A"],"dc:contributor.department":["Biomedical Engineering"],"dc:creator":["Kamaleddin Ezabadi, Seyed Mohammad Amin"],"dc:date":["2022-06"],"dc:date.accessioned":["2022-06-29T15:05:25Z"],"dc:date.available":["2022-06-29T15:05:25Z"],"dc:date.issued":["2022-06"],"dc:description.abstract":["Neurons use action potentials, or spikes, to process information. Different aspects of spiking, such as its rate or timing, are used to encode information about different features of an input. But noise can influence how robustly information is represented in each coding scheme. Additionally, information can be lost if neural representations are not transmitted with high fidelity to downstream neurons. In both cases, properties of the input (its amplitude and kinetics) and properties of the neuron (its spike initiation mechanism and excitability) impact neural information processing. In my thesis, I first investigated how axons are optimized to transmit spike-based representations. Using patch clamp electrophysiology combined with optogenetics, I showed that the axon of CA1 pyramidal neurons spikes transiently in response to sustained depolarization, in contrast to the soma and axon initial segment, which spike repetitively. These distinct spiking patterns are due to the differential expression of ion channels, supporting functional specialization of neuronal compartments. Specifically, low-threshold potassium channels (Kv1) cause the axon to behave as a high-pass filter, enabling high fidelity transmission of spike-based information so that the axon selectively responds to inputs with fast kinetics. Together with biophysical modeling, my findings demonstrate that spike initiation properties in each part of the neuron are well matched to the signals normally processed in that neuronal compartment. I then investigated how background synaptic activity (noise) affects rate and temporal coding of vibrotactile stimuli. Using patch clamp electrophysiology and dynamic clamp in vitro, I found that layer 2/3 pyramidal neurons in primary somatosensory cortex spike intermittently to inputs repeated at frequencies perceived as vibration. The fraction of inputs evoking a spike varies with input amplitude, enabling firing rate to encode stimulus intensity. Despite being small in amplitude, inputs are abrupt in onset, which allows them to evoke precisely timed spikes, even under noisy conditions. Unreliable spiking allows noise to produce irregular skipping, enabling spike times (patterns) to encode stimulus frequency. The reliability and precision of spikes depend on input amplitude and kinetics, respectively. With the help of simulations, my results show that noise helps multiplexed rate and temporal coding."],"dc:description.degree":["Ph.D."],"dc:identifier.uri":["http://hdl.handle.net/1807/123142"],"dc:rights":["Attribution 4.0 International"],"dc:rights.uri":["http://creativecommons.org/licenses/by/4.0/"],"dc:title":["Impact of Noise and Spike Initiation Properties on the Encoding and Transmission of Neural Information"],"dc:type":["Thesis"]},"updated_at":"2026-07-27T21:28:11Z"}