Embedding Functional Brain Networks in Low Dimensional Spaces Using Manifold Learning Techniques

Background: fMRI data is inherently high-dimensional and difficult to visualize. A recent trend has been to find spaces of lower dimensionality where functional brain networks can be projected onto manifolds as individual data points, leading to new ways to analyze and interpret the data. Here, we i...

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Detalles Bibliográficos
Autores principales: Casanova, Ramon, Lyday, Robert G., Bahrami, Mohsen, Burdette, Jonathan H., Simpson, Sean L., Laurienti, Paul J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Neuroinformatics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8739961/
https://www.ncbi.nlm.nih.gov/pubmed/35002665
http://dx.doi.org/10.3389/fninf.2021.740143

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8739961/
https://www.ncbi.nlm.nih.gov/pubmed/35002665
http://dx.doi.org/10.3389/fninf.2021.740143

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