Neuronal Stochastic Variability: Influences on Spiking Dynamics and Network Activity
Stochastic fluctuations are intrinsic to and unavoidable at every stage of neural dynamics. For example, ion channels undergo random conformational changes, neurotransmitter release at synapses is discrete and probabilistic, and neural networks are embedded in spontaneous background activity. The ma...
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| Formatua: | Online |
| Hizkuntza: | ingelesa |
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Frontiers Media SA
2021
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| Sarrera elektronikoa: | 18271 |
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| _version_ | 1869520688457449472 |
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| author | Benjamin Lindner Joshua H. Goldwyn Mark D. McDonnell |
| author_browse | Benjamin Lindner Joshua H. Goldwyn Mark D. McDonnell |
| author_facet | Benjamin Lindner Joshua H. Goldwyn Mark D. McDonnell |
| author_sort | Benjamin Lindner |
| collection | Directory of Open Access Books |
| description | Stochastic fluctuations are intrinsic to and unavoidable at every stage of neural dynamics. For example, ion channels undergo random conformational changes, neurotransmitter release at synapses is discrete and probabilistic, and neural networks are embedded in spontaneous background activity. The mathematical and computational tool sets contributing to our understanding of stochastic neural dynamics have expanded rapidly in recent years. New theories have emerged detailing the dynamics and computational power of the balanced state in recurrent networks. At the cellular level, novel stochastic extensions to the classical Hodgkin-Huxley model have enlarged our understanding of neuronal dynamics and action potential initiation. Analytical methods have been developed that allow for the calculation of the firing statistics of simplified phenomenological integrate-and-fire models, taking into account adaptation currents or temporal correlations of the noise. This Research Topic is focused on identified physiological/internal noise sources and mechanisms. By "internal", we mean variability that is generated by intrinsic biophysical processes. This includes noise at a range of scales, from ion channels to synapses to neurons to networks. The contributions in this Research Topic introduce innovative mathematical analysis and/or computational methods that relate to empirical measures of neural activity and illuminate the functional role of intrinsic noise in the brain. |
| format | Online |
| id | doab-20.500.12854ir-54520 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | Frontiers Media SA |
| publisherStr | Frontiers Media SA |
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| spelling | doab-20.500.12854ir-545202024-04-05T12:36:07Z Neuronal Stochastic Variability: Influences on Spiking Dynamics and Network Activity Benjamin Lindner Joshua H. Goldwyn Mark D. McDonnell RC321-571 Q1-390 Balanced network Hodgkin-Huxley model neuronal variability Channel noise neural networks heterogeneity stochastic dynamics thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences Stochastic fluctuations are intrinsic to and unavoidable at every stage of neural dynamics. For example, ion channels undergo random conformational changes, neurotransmitter release at synapses is discrete and probabilistic, and neural networks are embedded in spontaneous background activity. The mathematical and computational tool sets contributing to our understanding of stochastic neural dynamics have expanded rapidly in recent years. New theories have emerged detailing the dynamics and computational power of the balanced state in recurrent networks. At the cellular level, novel stochastic extensions to the classical Hodgkin-Huxley model have enlarged our understanding of neuronal dynamics and action potential initiation. Analytical methods have been developed that allow for the calculation of the firing statistics of simplified phenomenological integrate-and-fire models, taking into account adaptation currents or temporal correlations of the noise. This Research Topic is focused on identified physiological/internal noise sources and mechanisms. By "internal", we mean variability that is generated by intrinsic biophysical processes. This includes noise at a range of scales, from ion channels to synapses to neurons to networks. The contributions in this Research Topic introduce innovative mathematical analysis and/or computational methods that relate to empirical measures of neural activity and illuminate the functional role of intrinsic noise in the brain. 2021-02-11T20:50:41Z 2021-02-11T20:50:41Z 2016-01-19 14:05:46 2016 book 18271 16648714 9782889198849 https://directory.doabooks.org/handle/20.500.12854/54520 eng Frontiers Research Topics image/jpeg Attribution 4.0 International http://www.frontiersin.org/books/Neuronal_Stochastic_Variability_Influences_on_Spiking_Dynamics_and_Network_Activity/923#nogo http://journal.frontiersin.org/researchtopic/1936/neuronal-stochastic-variability-influences-on-spiking-dynamics-and-network-activity Frontiers Media SA 10.3389/978-2-88919-884-9 10.3389/978-2-88919-884-9 bf5ce210-e72e-4860-ba9b-c305640ff3ae 9782889198849 156 open access |
| spellingShingle | RC321-571 Q1-390 Balanced network Hodgkin-Huxley model neuronal variability Channel noise neural networks heterogeneity stochastic dynamics thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences Benjamin Lindner Joshua H. Goldwyn Mark D. McDonnell Neuronal Stochastic Variability: Influences on Spiking Dynamics and Network Activity |
| title | Neuronal Stochastic Variability: Influences on Spiking Dynamics and Network Activity |
| title_full | Neuronal Stochastic Variability: Influences on Spiking Dynamics and Network Activity |
| title_fullStr | Neuronal Stochastic Variability: Influences on Spiking Dynamics and Network Activity |
| title_full_unstemmed | Neuronal Stochastic Variability: Influences on Spiking Dynamics and Network Activity |
| title_short | Neuronal Stochastic Variability: Influences on Spiking Dynamics and Network Activity |
| title_sort | neuronal stochastic variability influences on spiking dynamics and network activity |
| topic | RC321-571 Q1-390 Balanced network Hodgkin-Huxley model neuronal variability Channel noise neural networks heterogeneity stochastic dynamics thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences |
| topic_facet | RC321-571 Q1-390 Balanced network Hodgkin-Huxley model neuronal variability Channel noise neural networks heterogeneity stochastic dynamics thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences |
| url | 18271 |
| work_keys_str_mv | AT benjaminlindner neuronalstochasticvariabilityinfluencesonspikingdynamicsandnetworkactivity AT joshuahgoldwyn neuronalstochasticvariabilityinfluencesonspikingdynamicsandnetworkactivity AT markdmcdonnell neuronalstochasticvariabilityinfluencesonspikingdynamicsandnetworkactivity |