Functional network connectivity patterns predicting the efficacy of repetitive transcranial magnetic stimulation in the spectrum of Alzheimer's disease.

ABSTRACT:

Background

Neuro-navigated repetitive transcranial magnetic stimulation (rTMS) is potentially effective in enhancing cognitive performance in the spectrum of Alzheimer's disease (AD). We explored the effect of rTMS-induced network reorganization and its predictive value for individual treatment response.

Methods

Sixty-two amnestic mild cognitive impairment (aMCI) and AD patients were recruited. These subjects were assigned to multimodal magnetic resonance imaging scanning before and after a 4-week stimulation. Then, we investigated the neural mechanism underlying rTMS treatment based on static functional network connectivity (sFNC) and dynamic functional network connectivity (dFNC) analyses. Finally, the support vector regression was used to predict the individual rTMS treat

SUBMITTER: Chen H 

PROVIDER: S-EPMC10593644 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature