A statistical model for brain networks inferred from large-scale electrophysiological signals

Catalina Obando Forero 1, 2 Fabrizio de Vico Fallani 1, 2
1 ARAMIS - Algorithms, models and methods for images and signals of the human brain
UPMC - Université Pierre et Marie Curie - Paris 6, ICM - Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute, Inria de Paris
Abstract : In this work we adopted a statistical model based on exponential random graph (ERGM) to reproduce electroencephalographic (EEG) brain networks.
Document type :
Poster communications
Complete list of metadatas

https://hal.inria.fr/hal-01564952
Contributor : Catalina Obando Forero <>
Submitted on : Wednesday, July 19, 2017 - 11:54:21 AM
Last modification on : Tuesday, April 30, 2019 - 3:43:01 PM

File

NetSci2017_Poster_Catalina.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01564952, version 1

Citation

Catalina Obando Forero, Fabrizio de Vico Fallani. A statistical model for brain networks inferred from large-scale electrophysiological signals. NetSci, Jun 2017, Indianapolis, United States. ⟨hal-01564952⟩

Share

Metrics

Record views

195

Files downloads

202