Ali Mohammad Golestani1, Bradley G. Goodyear1,2
1Biomedical Engineering, University of Calgary, Calgary, Alberta, Canada; 2Radiology & Clinical Neuroscience, University of Calgary, Calgary, Alberta, Canada
Resting-state fMRI analysis is often performed by averaging the time courses in seed and target ROIs and then computing the strength of connectivity using temporal cross-correlation. A good connectivity index should be sensitive to meaningful physiological changes (e.g. change in connectivity strength in response to a disease), but remain insensitive to SNR and CNR, which can change between sessions. We introduce a resting-state connectivity index that is normalized to the connectivity of the seed to itself. This normalization of connectivity within the given data set removes the dependence on changes in SNR and CNR.