Automatic classification of brain resting states using fMRI temporal signals

N. Soldati, S. Robinson, C. Persello, J. Jovicich, L. Bruzzone

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

A novel technique is presented for the automatic discrimination between networks of 'resting states' 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.

Original languageEnglish
Pages (from-to)19-21
Number of pages3
JournalElectronics Letters
Volume45
Issue number1
DOIs
Publication statusPublished - 2009

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Brain
Independent component analysis
Magnetic Resonance Imaging

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

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. https://doi.org/10.1049/el:20092178

Automatic classification of brain resting states using fMRI temporal signals. / Soldati, N.; Robinson, S.; Persello, C.; Jovicich, J.; Bruzzone, L.

In: Electronics Letters, Vol. 45, No. 1, 2009, p. 19-21.

Research output: Contribution to journalArticle

Soldati, N, Robinson, S, Persello, C, Jovicich, J & Bruzzone, L 2009, 'Automatic classification of brain resting states using fMRI temporal signals', Electronics Letters, vol. 45, no. 1, pp. 19-21. https://doi.org/10.1049/el:20092178
Soldati, N. ; Robinson, S. ; Persello, C. ; Jovicich, J. ; Bruzzone, L. / Automatic classification of brain resting states using fMRI temporal signals. In: Electronics Letters. 2009 ; Vol. 45, No. 1. pp. 19-21.
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