Predicting Functional Connectivity From Observed and Latent Structural Connectivity via Eigenvalue Mapping

Understanding how complex dynamic activity propagates over a static structural network is an overarching question in the field of neuroscience. Previous work has demonstrated that linear graph-theoretic models perform as well as non-linear neural simulations in predicting functional connectivity wit...

Descripción completa

Detalles Bibliográficos
Autores principales: Cummings, Jennifer A., Sipes, Benjamin, Mathalon, Daniel H., Raj, Ashish
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8964629/
https://www.ncbi.nlm.nih.gov/pubmed/35368264
http://dx.doi.org/10.3389/fnins.2022.810111

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8964629/
https://www.ncbi.nlm.nih.gov/pubmed/35368264
http://dx.doi.org/10.3389/fnins.2022.810111

Ejemplares similares