Robust dynamic community detection with applications to human brain functional networks
Understanding how brain networks evolve in time remains a challenge, with the potential for significant impact to human health and disease. Here, the authors introduce a new methodology to track dynamic functional networks that is robust to edge noise, and yields well-defined spatiotemporal communit...
Enregistré dans:
Auteurs principaux: | L.-E. Martinet, M. A. Kramer, W. Viles, L. N. Perkins, E. Spencer, C. J. Chu, S. S. Cash, E. D. Kolaczyk |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2020
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/8f7cd92cb2444562a9abbe7affa09f59 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Detecting network communities: an application to phylogenetic analysis.
par: Roberto F S Andrade, et autres
Publié: (2011) -
Human seizures couple across spatial scales through travelling wave dynamics
par: L-E Martinet, et autres
Publié: (2017) -
Brain network dynamics in high-functioning individuals with autism
par: Takamitsu Watanabe, et autres
Publié: (2017) -
The dynamic functional core network of the human brain at rest
par: A. Kabbara, et autres
Publié: (2017) -
Abnormal Brain Functional Network Dynamics in Acute CO Poisoning
par: Hongyi Zheng, et autres
Publié: (2021)