On a spike train probability model with interacting neural units

DOI10.3934/mbe.2014.11.217zbMath1279.60096OpenAlexW2324116447WikidataQ51140462 ScholiaQ51140462MaRDI QIDQ395724

Barbara Martinucci, Antonio Di Crescenzo, Maria Longobardi

Publication date: 30 January 2014

Published in: Mathematical Biosciences and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3934/mbe.2014.11.217

zbMATH Keywords

Poisson processneural modelfiring raterefractory periodconditional intensitycumulative firing raterecovery function

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Applications of Markov renewal processes (reliability, queueing networks, etc.) (60K20) Applications of continuous-time Markov processes on discrete state spaces (60J28)

Cites Work

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