Michael Czisch1, Renate Wehrle1, Victor I. Spoormaker1, David Hhn1, Henning Peters1, Florian Holsboer1, Philipp G. Smann1
1Max-Planck-Institute of Psychiatry, Munich, Germany
Independent component analysis (ICA) has recently gained broad interest in the field of fMRI as the method allows for hypothesis-free analysis of functional imaging data. Resting state networks can reliably be detected using ICA. Today, most research focuses on the default mode network (DMN), comprising cerebral regions with increased activity during rest as compared to specific tasks, and assumed to be linked to intrinsic awareness1-3. Using sleep as an example of transient changes in brain activation, we propose a new iterative ICA to follow changes in the DMN integrity over time.