Department of Biostatistics Seminar/Workshop Series

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Determining Significant Functional Connectivity of the Human Brain with fMRI and Wavelets

Rajan Patel, PhD, Senior Biostatistician
Medical Science - Biostatistics, Amgen, Inc.

January 24, 2007, 1:30-2:30pm
MRBIII Conference Room 1220

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An active area of neuroimaging research involves examining functional relationships between spatially remote brain regions. When determining whether two brain regions exhibit significant correlation due to neurophysiological connectivity, one must account for the background spatiotemporal correlation inherent in neuroimaging data such as fMRI or PET. Background correlation is defined as spatiotemporal correlation in the data caused by factors other than neurophysiologically based functional associations such as scanner induced correlations and image preprocessing. We developed a 4D spatiotemporal wavelet packet resampling method which generates surrogate data that preserves only the average background spatial correlation within an axial slice, across axial slices, and through each voxel time series, while excluding the specific correlations due to true functional relationships. The method provides an estimate of the null spatiotemporal correlation inherent in fMRI which allows us to better evaluate true neurophysiological relationships in neuroimaging data. Our method improves upon existing wavelet based methods and extends them to 4D. We apply our resampling technique to determine significant functional connectivity from resting state and motor task fMRI datasets.