Hand classification of fMRI ICA noise components

We present a practical “how-to” guide to help determine whether single-subject fMRI independent components (ICs) characterise structured noise or not. Manual identification of signal and noise after ICA decomposition is required for efficient data denoising: to train supervised algorithms, to check...

Descripción completa

Detalles Bibliográficos
Autores principales: Griffanti, Ludovica, Douaud, Gwenaëlle, Bijsterbosch, Janine, Evangelisti, Stefania, Alfaro-Almagro, Fidel, Glasser, Matthew F., Duff, Eugene P., Fitzgibbon, Sean, Westphal, Robert, Carone, Davide, Beckmann, Christian F., Smith, Stephen M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Academic Press 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5489418/
https://www.ncbi.nlm.nih.gov/pubmed/27989777
http://dx.doi.org/10.1016/j.neuroimage.2016.12.036

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5489418/
https://www.ncbi.nlm.nih.gov/pubmed/27989777
http://dx.doi.org/10.1016/j.neuroimage.2016.12.036

Ejemplares similares