The influence of heart beat and respiration on functional connectivity networks

We investigate the influence of physiological measures like heart beat and respiration on functional connectivity networks from fMRI. Cardiac and respiratory effects were measured simultaneously during high rate MRI data acquisition and the functional connectivity networks were determined in a data driven manner using graph theory. One of our findings is that removing the physiological effects from the data leads to disappearance of a considerable part of the functional connectivity networks and to the appearance of small, but consistent networks. We found further that high signal variance loss due to physiological effect removal does not coincide with a high correlation loss, on the contrary, a considerable part of the networks appears preferably at locations with high variance loss.