Monosynaptic inference via finely-timed spikes.

Platkiewicz, Jonathan; Saccomano, Zachary; McKenzie, Sam; English, Daniel; Amarasingham, Asohan

Platkiewicz, Jonathan; Saccomano, Zachary; McKenzie, Sam; English, Daniel; Amarasingham, Asohan.

Afiliação

Platkiewicz J; Department of Mathematics, The City College of New York, The City University of New York, New York, NY, 10031, USA.
Saccomano Z; Department of Biology, The Graduate Center, The City University of New York, New York, NY, 10016, USA.
McKenzie S; Neuroscience Institute, New York University, New York, NY, 10016, USA.
English D; School of Neuroscience, Virginia Tech, Blacksburg, VA, 24060, USA.
Amarasingham A; Department of Mathematics, The City College of New York, The City University of New York, New York, NY, 10031, USA. aamarasingham@ccny.cuny.edu.

J Comput Neurosci ; 49(2): 131-157, 2021 05.

Article em En | MEDLINE | ID: mdl-33507429

Assuntos

Modelos Neurológicos; Neurônios; Potenciais de Ação; Modelos Estatísticos

Palavras-chave

Integrate-and-fire neuron; Noise models; Nonstationarity; Spike correlogram; Synaptic connectivity; Synchrony

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Modelos Neurológicos / Neurônios Tipo de estudo: Prognostic_studies / Qualitative_research / Risk_factors_studies Idioma: En Revista: J Comput Neurosci Ano de publicação: 2021 Tipo de documento: Article

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google