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...
- 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)