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dc.contributor.author
Chialva, Ulises
dc.contributor.author
González Boscá, Vicente
dc.contributor.author
Rotstein, Horacio
dc.date.available
2024-12-26T12:12:12Z
dc.date.issued
2023-04
dc.identifier.citation
Chialva, Ulises; González Boscá, Vicente; Rotstein, Horacio; Low-dimensional models of single neurons: a review; Springer; Biological Cybernetics; 117; 3; 4-2023; 163-183
dc.identifier.issn
0340-1200
dc.identifier.uri
http://hdl.handle.net/11336/251268
dc.description.abstract
The classical Hodgkin-Huxley (HH) point-neuron model of action potential generation is four-dimensional. It consists of four ordinary differential equations describing the dynamics of the membrane potential and three gating variables associated to a transient sodium and a delayed-rectifier potassium ionic currents. Conductance-based models of HH type are higher-dimensional extensions of the classical HH model. They include a number of supplementary state variables associated with other ionic current types, and are able to describe additional phenomena such as sub-threshold oscillations, mixed-mode oscillations (subthreshold oscillations interspersed with spikes), clustering and bursting. In this manuscript we discuss biophysically plausible and phenomenological reduced models that preserve the biophysical and/or dynamic description of models of HH type and the ability to produce complex phenomena, but the number of effective dimensions (state variables) is lower. We describe several representative models. We also describe systematic and heuristic methods of deriving reduced models from models of HH type.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Springer
dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Computational neuroscience
dc.subject
Dimensional reduction
dc.subject
Hodgkin-Huxley
dc.subject.classification
Matemática Aplicada
dc.subject.classification
Matemáticas
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
dc.title
Low-dimensional models of single neurons: a review
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2024-12-13T14:13:20Z
dc.identifier.eissn
1432-0770
dc.journal.volume
117
dc.journal.number
3
dc.journal.pagination
163-183
dc.journal.pais
Alemania
dc.journal.ciudad
Berlin
dc.description.fil
Fil: Chialva, Ulises. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Matemática; Argentina
dc.description.fil
Fil: González Boscá, Vicente. University Of New York. Courant Institute Of Mathematical Sciences.; Estados Unidos
dc.description.fil
Fil: Rotstein, Horacio. New Jersey Institute of Technology; Estados Unidos. Rutgers University; Estados Unidos
dc.journal.title
Biological Cybernetics
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007/s00422-023-00960-1
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1007/s00422-023-00960-1
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