Activation detection in multi-subject studies of fMRI using GLRT

A new method based on generalized likelihood ratio test (GLRT) for activation detection in multi-subject studies of functional MRI (fMRI) is proposed. In this method, we test the correlation between the fMRI time series of different subjects and the bases of a signal subspace which increases the fle...

Full description

Saved in:
Bibliographic Details
Published inIEEE Symposium Conference Record Nuclear Science 2004 Vol. 5; pp. 2778 - 2782
Main Authors Shams, S.M., Hossein-Zadeh, G.A., Soltanian-Zadeh, H.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2004
Subjects
Brain modeling
Data analysis
Hemodynamics
Intelligent control
Magnetic resonance imaging
Mathematics
Physics computing
Process control
Testing
Time series analysis
Online AccessGet full text
ISBN9780780387003
0780387007
ISSN1082-3654
DOI10.1109/NSSMIC.2004.1466265

Cover

More Information
Summary:A new method based on generalized likelihood ratio test (GLRT) for activation detection in multi-subject studies of functional MRI (fMRI) is proposed. In this method, we test the correlation between the fMRI time series of different subjects and the bases of a signal subspace which increases the flexibility of method in detecting different shapes of hemodynamic response. The proposed multivariate method can be applied to group studies where the conventional cross-correlation method cannot be used due to its univariate property. This method is applied to both experimental and simulated fMRI data and the results are compared to those of general linear model (GLM). We show that the proposed method detects more significant activated regions in analyzing experimental data and more true voxels in simulated data
ISBN:9780780387003
0780387007
ISSN:1082-3654
DOI:10.1109/NSSMIC.2004.1466265