A two-state neuronal model with alternating exponential excitation

We develop a stochastic neural model based on point excitatory inputs. The nerve cell depolarisation is determined by a two-state point process corresponding the two states of the cell. The model presumes state-dependent excitatory stimuli amplitudes and decay rates of membrane potential. The state...

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Autores:
Tipo de recurso:
Fecha de publicación:
2019
Institución:
Universidad del Rosario
Repositorio:
Repositorio EdocUR - U. Rosario
Idioma:
eng
OAI Identifier:
oai:repository.urosario.edu.co:10336/22559
Acceso en línea:
https://doi.org/10.3934/mbe.2019171
https://repository.urosario.edu.co/handle/10336/22559
Palabra clave:
Decay (organic)
Depolarization
Excited states
Laplace transforms
Neurons
Stochastic systems
Time switches
Asymptotical behaviour
First passage time
Laplace transform techniques
Membrane potentials
Neural activity
Neural modeling
Neuronal model
State-dependent
Stochastic models
Article
Depolarization
Excitation
Laplace transform
Membrane potential
Nerve cell
Probability
Stochastic model
Asymptotical behaviour
Firing probability
First passage time
Jump-telegraph process
Neural activity
Rights
License
Abierto (Texto Completo)