Modeling the temporal network dynamics of neuronal cultures

Jose Cadena, Ana Paula Sales, Doris Lam, Heather A. Enright, Elizabeth K. Wheeler, Nicholas O. Fischer

Research output: Contribution to journalArticle

Abstract

Neurons form complex networks that evolve over multiple time scales. In order to thoroughly characterize these networks, time dependencies must be explicitly modeled. Here, we present a statistical model that captures both the underlying structural and temporal dynamics of neuronal networks. Our model combines the class of Stochastic Block Models for community formation with Gaussian processes to model changes in the community structure as a smooth function of time. We validate our model on synthetic data and demonstrate its utility on three different studies using in vitro cultures of dissociated neurons.

Original languageEnglish (US)
Article numbere1007834
JournalPLoS computational biology
Volume16
Issue number5
DOIs
StatePublished - May 2020
Externally publishedYes

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Modeling and Simulation
  • Ecology
  • Molecular Biology
  • Genetics
  • Cellular and Molecular Neuroscience
  • Computational Theory and Mathematics

Fingerprint Dive into the research topics of 'Modeling the temporal network dynamics of neuronal cultures'. Together they form a unique fingerprint.

  • Cite this