Title :
Controlling the false discovery rate in modeling brain functional connectivity
Author :
Li, Junning ; Wang, Z. Jane ; McKeown, Martin J.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of British Columbia, Vancouver, BC
fDate :
March 31 2008-April 4 2008
Abstract :
Graphical models of brain functional connectivity have matured from confirming a priori hypotheses to an exploratory tool for discovering unknown connectivity. However, exploratory methods must control the error rate of "discovered" connectivity networks. Here we explore an error-rate-control method for graphical models which controls the false-discovery-rate (FDR) of the conditional-dependence relationships that a graphical model encodes. The application of this method to a group analysis of fMRI study on Parkinson\´s disease shows that it effectively controls the errors introduced by randomness, and yields meaningful and consistent results. The proposed approach appears promising for functional-connectivity modeling and deserves further investigation.
Keywords :
biomedical MRI; brain; diseases; graph theory; Parkinson´s disease; brain functional connectivity modeling; conditional-dependence relationships; error-rate-control method; fMRI study; false discovery rate control; functional magnetic resonance imaging; graphical models; group analysis; Bayesian methods; Brain modeling; Encoding; Error analysis; Error correction; Graphical models; Magnetic resonance imaging; Numerical analysis; Parkinson´s disease; Testing; brain connectivity; false discovery rate; functional magnetic resonance imaging (fMRI); graphical model;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on
Conference_Location :
Las Vegas, NV
Print_ISBN :
978-1-4244-1483-3
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2008.4518057