Modeling the temporal network dynamics of neuronal cultures.
PLoS Comput Biol
; 16(5): e1007834, 2020 05.
Article
in En
| MEDLINE
| ID: mdl-32453727
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.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Action Potentials
/
Models, Neurological
/
Nerve Net
/
Neurons
Type of study:
Health_economic_evaluation
/
Prognostic_studies
Limits:
Animals
Language:
En
Journal:
PLoS Comput Biol
Journal subject:
BIOLOGIA
/
INFORMATICA MEDICA
Year:
2020
Document type:
Article
Affiliation country:
United States