Your browser doesn't support javascript.
loading
Double inverse stochastic resonance with dynamic synapses.
Uzuntarla, Muhammet; Torres, Joaquin J; So, Paul; Ozer, Mahmut; Barreto, Ernest.
Afiliação
  • Uzuntarla M; Department of Biomedical Engineering, Bulent Ecevit University, 67100 Zonguldak, Turkey.
  • Torres JJ; Department of Electromagnetism and Physics of the Matter and Institute Carlos I for Theoretical and Computational Physics, University of Granada, E-18071 Granada, Spain.
  • So P; Department of Physics and Astronomy and the Krasnow Institute for Advanced Study, George Mason University, Fairfax, Virginia 22030, USA.
  • Ozer M; Department of Electrical and Electronics Engineering, Bulent Ecevit University, 67100 Zonguldak, Turkey.
  • Barreto E; Department of Physics and Astronomy and the Krasnow Institute for Advanced Study, George Mason University, Fairfax, Virginia 22030, USA.
Phys Rev E ; 95(1-1): 012404, 2017 Jan.
Article em En | MEDLINE | ID: mdl-28208458
ABSTRACT
We investigate the behavior of a model neuron that receives a biophysically realistic noisy postsynaptic current based on uncorrelated spiking activity from a large number of afferents. We show that, with static synapses, such noise can give rise to inverse stochastic resonance (ISR) as a function of the presynaptic firing rate. We compare this to the case with dynamic synapses that feature short-term synaptic plasticity and show that the interval of presynaptic firing rate over which ISR exists can be extended or diminished. We consider both short-term depression and facilitation. Interestingly, we find that a double inverse stochastic resonance (DISR), with two distinct wells centered at different presynaptic firing rates, can appear.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sinapses / Modelos Neurológicos / Neurônios Limite: Animals Idioma: En Revista: Phys Rev E Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Turquia

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sinapses / Modelos Neurológicos / Neurônios Limite: Animals Idioma: En Revista: Phys Rev E Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Turquia