Integration patterns of functional brain networks can predict the response to abdominal acupuncture in patients with major depressive disorder

The requested reference [a63ad27db437b82c47faaf1a973401c9ae77b934] no longer exists in our database. It has been replaced by the current reference: [5cd3e78d06b17c6e72e27aedd656fb23cab23088]

Authors
Category Primary study
JournalNeuroscience
Year 2024
Abdominal acupuncture has definite efficacy for major depressive disorder (MDD). Our study examined how abdominal acupuncture regulates the integration within and between brain networks of MDD patients by neuroimaging and whether this functional integration can predict the efficacy. Forty-six female MDD patients were randomly divided into a fluoxetine + real acupuncture group (n = 22) and a fluoxetine + sham acupuncture group (n = 24). The differences in functional magnetic resonance imaging data in the intra- and inter-network functional connectivity (FC) of the default mode network (DMN), affective network (AN), salience network (SN), and cognitive control network (CCN) between the two groups were analyzed. The FCs in brain regions with the inter-group differences and support vector regression were used to predict the efficacy of abdominal acupuncture. Our results showed: that the intra- and inter-network FCs of DMN, AN, SN, and CCN could be changed by abdominal acupuncture. Using the baseline FCs within AN and DMN or AN–DMN as characteristics, combined with support vector regression, could better predict the efficacy of acupuncture. Our study suggests that abdominal acupuncture could treat MDD by regulating the integration of the functional networks DMN, AN, SN, and CCN. The baseline FCs within the DMN and AN or between them could be used as neural markers for predicting the efficacy of abdominal acupuncture.
Epistemonikos ID: 9a36800551f558d7a868f3ca91ddf1b642fd0ae9
First added on: Oct 08, 2024