Dynamic Adaptation of Default Mode Network in Resting state and Autobiographical Episodic Memory Retrieval State

The default mode network is a brain network processing mental states featuring an internal representation of subjective experiences like autobiographical episodic memory retrieval and a resting state. If the default mode network is the common spatial domain processing such mental states, then the temporal domain might present the differences in the mental states. To detect adaptations in dynamics of a single brain network dependent on the mental states it processes, we suggested a novel analysis method called one-to-many dynamic functional connectivity analysis for fMRI. The analysis method assesses the variance in the partial correlations of a center that are time-windowed functional correlations of a brain region (a center) to the rest of the regions in a brain network, then compares the similarities in the directions of their major variance from the same or distinct mental states. We applied one-to-many dynamic functional connectivity analysis to the default mode network and measured the similarity between the major variances of the partial correlations from three autobiographical episodic memory retrieval states and a resting state. If the major direction of the variance is a configuration presenting the mental states of the brain network, we expect to see the high similarity for the same mental states and less similarity for the distinct mental states. To test our hypothesis with the new analysis method, we chose a single subject who is a late blind with advanced mental imagery ability. The results showed that the dynamic adaption in the default mode network in the two mental states could be well depicted when the posterior cingulate cortex is the center in this single case. Furthermore, we could observe that the weight of the correlation between the posterior cingulate cortex and the right parahippocampal cortex varied mostly and therefore its contribution to the dynamic adaptation was relatively higher than the other correlations. ### Competing Interest Statement The authors have declared no competing interest.