Distinct brain networks for time-varied characteristics of acupuncture

Clinical acupuncture typically involves an effective treatment phase several hours post-therapy. We previously identified regions that carry the time-varied signals based on the BLOCK experimental paradigm. Here we characterize the brain network by applying the graph theory analysis during the post-acupuncture resting state. Our results show gradually increasing connections in the brainstem during verum acupuncture (ACU). The anterior insula plays an important role in connecting the components of the brain networks following ACU. We suggest that acupuncture can induce significant complex response patterns with relatively more robust magnitudes. Our findings provide direct evidence that the post-needling resting state contains acupuncture-related effects that are due to the slow-acting nature of acupuncture.