ABSTRACT
INTRODUCTION: Neuro-navigated repetitive transcranial magnetic stimulation (rTMS) of the left angular gyrus has been broadly investigated for the treatment of amnestic mild cognitive impairment (aMCI). Although abnormalities in two hippocampal networks, the anterior-temporal (AT) and posterior-medial (PM) networks, are consistent with aMCI and are potential therapeutic targets for rTMS, the underlying mechanisms of the therapeutic effects of rTMS on hippocampal network connections remain unknown. Here, we assessed the impact of left angular gyrus rTMS on activity in these networks and explored whether the treatment response was due to the distance between the clinically applied target (the group average optimal site) and the personalized target in patients with aMCI. METHODS: Sixty subjects clinically diagnosed with aMCI participated in this study after 20 sessions of sham-controlled rTMS targeting the left angular gyrus. Resting-state functional magnetic resonance imaging and neuropsychological assessments were performed before and after rTMS. Functional connectivity alterations in the PM and AT networks were assessed using seed-based functional connectivity analysis and two-factor repeated measures analysis of variance (ANOVA). We then computed the correlations between the functional connectivity changes and clinical rating scales. Finally, we examined whether the Euclidean distance between the clinically applied and personalized targets predicted the subsequent treatment response. RESULTS: Compared with the sham group, the active rTMS group showed rTMS-induced deactivation of functional connectivity within the medial temporal lobe-AT network, with a negative correlation with episodic memory score changes. Moreover, the active rTMS lowers the interdependency of changes in the PM and AT networks. Finally, the Euclidean distance between the clinically applied and personalized target distances could predict subsequent network lever responses in the active rTMS group. CONCLUSIONS: Neuro-navigated rTMS selectively modulates widespread functional connectivity abnormalities in the PM and AT hippocampal networks in aMCI patients, and the modulation of hippocampal-AT network connectivity can efficiently reverse memory deficits. The results also highlight the necessity of personalized targets for fMRI.
ABSTRACT
Alzheimer's disease (AD) is associated with disruption at the level of a large-scale complex network. To explore the underlying mechanisms in the progression of AD, graph theory was used to quantitatively analyze the topological properties of structural and functional connections. Although an increasing number of studies have shown altered global and nodal network properties, little is known about the topologically convergent and divergent patterns between structural and functional networks among AD-spectrum patients. In this review, we summarized the topological patterns of the large-scale complex networks using multimodal neuroimaging graph theory analysis in AD spectrum patients. Convergent deficits in the connectivity characteristics were primarily in the default mode network (DMN) itself both in the structural and functional networks, while a divergent changes in the neighboring regions of the DMN were also observed between the patient groups. Together, the application of graph theory to large-scale complex brain networks provides quantitative insights into topological principles of brain network organization, which may lead to increasing attention in identifying the underlying neuroimaging pathological changes and predicting the progression of AD.
