Forecasting brain activity based on models of spatiotemporal brain dynamics: A comparison of graph neural network architectures

Comprehending the interplay between spatial and temporal characteristics of neural dynamics can contribute to our understanding of information processing in the human brain. Graph neural networks (GNNs) provide a new possibility to interpret graph-structured signals like those observed in complex br...

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Detalles Bibliográficos
Autores principales: Wein, S., Schüller, A., Tomé, A. M., Malloni, W. M., Greenlee, M. W., Lang, E. W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MIT Press 2022
Materias:
Methods
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9810370/
https://www.ncbi.nlm.nih.gov/pubmed/36607180
http://dx.doi.org/10.1162/netn_a_00252

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9810370/
https://www.ncbi.nlm.nih.gov/pubmed/36607180
http://dx.doi.org/10.1162/netn_a_00252

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