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Nonlinear manifold learning in functional magnetic resonance imaging uncovers a low‐dimensional space of brain dynamics

Large‐scale brain dynamics are believed to lie in a latent, low‐dimensional space. Typically, the embeddings of brain scans are derived independently from different cognitive tasks or resting‐state data, ignoring a potentially large—and shared—portion of this space. Here, we establish that a shared,...

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Detalles Bibliográficos
Autores principales: Gao, Siyuan, Mishne, Gal, Scheinost, Dustin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8410525/
https://www.ncbi.nlm.nih.gov/pubmed/34184812
http://dx.doi.org/10.1002/hbm.25561