Abstract:
:A novel method for detecting neural activity in functional magnetic resonance imaging (fMRI) data is introduced. It is based on canonical correlation analysis (CCA), which is a multivariate extension of the univariate correlation analysis widely used in fMRI. To detect homogeneous regions of activity, the method combines a subspace modeling of the hemodynamic response and the use of spatial relationships. The spatial correlation that undoubtedly exists in fMR images is completely ignored when univariate methods such as as t-tests, F-tests, and ordinary correlation analysis are used. Such methods are for this reason very sensitive to noise, leading to difficulties in detecting activation and significant contributions of false activations. In addition, the proposed CCA method also makes it possible to detect activated brain regions based not only on thresholding a correlation coefficient, but also on physiological parameters such as temporal shape and delay of the hemodynamic response. Excellent performance on real fMRI data is demonstrated. Magn Reson Med 45:323-330, 2001.
journal_name
Magn Reson Medjournal_title
Magnetic resonance in medicineauthors
Friman O,Cedefamn J,Lundberg P,Borga M,Knutsson Hdoi
10.1002/1522-2594(200102)45:2<323::aid-mrm1041>3.0subject
Has Abstractpub_date
2001-02-01 00:00:00pages
323-30issue
2eissn
0740-3194issn
1522-2594pii
10.1002/1522-2594(200102)45:2<323::AID-MRM1041>3.0journal_volume
45pub_type
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