Assessing the extent of high frequency resting state connectivity (> 0.15 Hz) across different brain networks has been hampered by the presence of physiological noise. Much of the high frequency information is lost when global filters are applied to stop respiratory and cardiac frequency bands. A spatially selective automated filtering method is developed in order to preserve high frequency signal information in regions where physiological contamination is weak. Preliminary results show significant reduction in artifactual correlations compared to unfiltered data.
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