Ali Mohammad Golestani1, Bradley G. Goodyear2,3
1Electrical & Computer Engineering,
University of Calgary, Calgary, AB, Canada; 2Radiology &
Clinical Neuroscience, University of Calgary, Calgary, AB, Canada; 3Seaman
Family MR Research Centre, Calgary, AB, Canada
Resting-state
fMRI analysis techniques that determine the similarity between time varying
signals of seed and target regions assume the signals are stationary; however,
the resting-state varies between subjects and is susceptible to unwanted
brain activity due to inadvertent movements or cognition. In this study, we
introduce a time-frequency approach based on the Stockwell transform to
temporally resolve coherence between resting-state signals. We demonstrate
S-Coherence can reduce the contribution of unwanted hand movements in the
determination of the resting-state connectivity within the motor network, and
hence reduce within-subject variability in comparison with existing
techniques (temporal cross-correlation and coherence).