de.mpg.escidoc.pubman.appbase.FacesBean
Deutsch
 
Hilfe Wegweiser Impressum Kontakt Einloggen
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Zeitschriftenartikel

Automatic classification of brain resting states using fMRI temporal signals

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons84133

Robinson S, Persello,  C
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

Externe Ressourcen
Es sind keine Externen Ressourcen verfügbar
Volltexte (frei zugänglich)
Es sind keine frei zugänglichen Volltexte verfügbar
Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Soldati, N., Robinson S, Persello, C., Jovicich, J., & Bruzzone, L. (2009). Automatic classification of brain resting states using fMRI temporal signals. Electronics Letters, 45(1), 19-21. doi:10.1049/el:20092178.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-C5E1-5
Zusammenfassung
A novel technique is presented for the automatic discrimination between networks of dasiaresting statesdasia of the human brain and physiological fluctuations in functional magnetic resonance imaging (fMRI). The method is based on features identified via a statistical approach to group independent component analysis time courses, which may be extracted from fMRI data. This technique is entirely automatic and, unlike other approaches, uses temporal rather than spatial information. The method achieves 83 accuracy in the identification of resting state networks.