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ICASSP
2008
IEEE

Controlling the false discovery rate in modeling brain functional connectivity

8 years 9 months ago
Controlling the false discovery rate in modeling brain functional connectivity
Graphical models of brain functional connectivity have matured from con rming 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-discoveryrate (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.
Junning Li, Z. Jane Wang, Martin J. McKeown
Added 30 May 2010
Updated 30 May 2010
Type Conference
Year 2008
Where ICASSP
Authors Junning Li, Z. Jane Wang, Martin J. McKeown
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