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).