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Modeling the temporal network dynamics of neuronal cultures.


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.

SUBMITTER: Cadena J 

PROVIDER: S-EPMC7274455 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Modeling the temporal network dynamics of neuronal cultures.

Cadena Jose J   Sales Ana Paula AP   Lam Doris D   Enright Heather A HA   Wheeler Elizabeth K EK   Fischer Nicholas O NO  

PLoS computational biology 20200526 5


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 synt  ...[more]

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