Functional Connectivity of Salience Network Predicts Treatment Outcome for rTMS in Mild Cognitive Impairment

Repetitive transcranial magnetic stimulation (rTMS) has been proved a potential therapeutic approach for improving the cognitive performance of patients with mild cognitive impairment (MCI). However, no biomarker is available for identifying who is most likely to respond to rTMS. The purpose of this study was to demonstrate that cognitive improvement after rTMS may be associated with functional connectivity of salience network at baseline. Resting-state functional magnetic resonance imaging (rs-fMRI) data of fifty-three MCI patients were collected before a 10-day of rTMS treatment. Multivoxel pattern analysis was applied to realize the classification of the MCI patients responded or not to rTMS treatment, and the prediction to the cognitive scores. The analysis yielded a significant overall accuracy of 84.91% (90.00% sensitivity, 78.26% specificity). Right anterior cingulate cortex contributed most to the classification. Besides, regression analysis also showed the predictive value of salience network to the changes of cognitive performance. Our study demonstrated that the functional connectivity of salience network is predictive of treatment response to rTMS.