Dataset Information

Repetitive transcranial magnetic stimulation regulates effective connectivity patterns of brain networks in the spectrum of preclinical Alzheimer's disease.

ABSTRACT:

Objectives

Subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) are considered as the spectrum of preclinical Alzheimer's disease (AD), with abnormal brain network connectivity as the main neuroimaging feature. Repetitive transcranial magnetic stimulation (rTMS) has been proven to be an effective non-invasive technique for addressing neuropsychiatric disorders. This study aims to explore the potential of targeted rTMS to regulate effective connectivity within the default mode network (DMN) and the executive control network (CEN), thereby improving cognitive function.

Methods

This study included 86 healthy controls (HCs), 72 SCDs, and 86 aMCIs. Among them, 10 SCDs and 11 aMCIs received a 2-week rTMS course of 5-day, once-daily. Cross-sectional analysis with the spectral dynamic causal model (spDCM) was used to analyze the DMN and CEN effective connectivity patterns of the three groups. Afterwards, longitudinal analysis was conducted on the changes in effective connectivity patterns and cognitive function before and after rTMS for SCD and aMCI, and the correlation between them was analyzed.

Results

Cross-sectional analysis showed different effective connectivity patterns in the DMN and CEN among the three groups. Longitudinal analysis showed that the effective connectivity pattern of the SCD had changed, accompanied by improvements in episodic memory. Correlation analysis indicated a negative relationship between effective connectivity from the left angular gyrus (ANG) to the anterior cingulate gyrus and the ANG.R to the right middle frontal gyrus, with visuospatial and executive function, respectively. In patients with aMCI, episodic memory and executive function improved, while the effective connectivity pattern remained unchanged.

Conclusion

This study demonstrates that PCUN-targeted rTMS in SCD regulates the abnormal effective connectivity patterns in DMN and CEN, thereby improving cognition function. Conversely, in aMCI, the mechanism of improvement may differ. Our findings further suggest that rTMS is more effective in preventing or delaying disease progression in the earlier stages of the AD spectrum.

Clinical trial registration

http://www.chictr.org.cn, ChiCTR2000034533.

SUBMITTER: Liang X

PROVIDER: S-EPMC10894951 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature

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Publications

Repetitive transcranial magnetic stimulation regulates effective connectivity patterns of brain networks in the spectrum of preclinical Alzheimer's disease.

Liang Xuhong X Xue Chen C Zheng Darui D Yuan Qianqian Q Qi Wenzhang W Ruan Yiming Y Chen Shanshan S Song Yu Y Wu Huimin H Lu Xiang X Xiao Chaoyong C Chen Jiu J

Frontiers in aging neuroscience 20240212

<h4>Objectives</h4>Subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) are considered as the spectrum of preclinical Alzheimer's disease (AD), with abnormal brain network connectivity as the main neuroimaging feature. Repetitive transcranial magnetic stimulation (rTMS) has been proven to be an effective non-invasive technique for addressing neuropsychiatric disorders. This study aims to explore the potential of targeted rTMS to regulate effective connectivity within ...[more]

PMID: 38410745

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Project description:BackgroundNeuro-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.MethodsSixty-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 treatment response through these functional features at baseline.ResultsWe found that rTMS at the left angular gyrus significantly induced cognitive improvement in multiple cognitive domains. Participants after rTMS treatment exhibited significantly the increased sFNC between the right frontoparietal network (rFPN) and left frontoparietal network (lFPN) and decreased sFNC between posterior visual network and medial visual network. We revealed remarkable dFNC characteristics of brain connectivity, which was increased mainly in higher-order cognitive networks and decreased in primary networks or between primary networks and higher-order cognitive networks. dFNC characteristics in state 1 and state 4 could further predict individual higher memory improvement after rTMS treatment (state 1, R = 0.58; state 4, R = 0.54).ConclusionOur findings highlight that neuro-navigated rTMS could suppress primary network connections to compensate for higher-order cognitive networks. Crucially, dynamic regulation of brain networks at baseline may serve as an individualized predictor of rTMS treatment response.Relevance statementDynamic reorganization of brain networks could predict the efficacy of repetitive transcranial magnetic stimulation in the spectrum of Alzheimer's disease.Key points• rTMS at the left angular gyrus could induce cognitive improvement. • rTMS could suppress primary network connections to compensate for higher-order networks. • Dynamic reorganization of brain networks could predict individual treatment response to rTMS.

Project description:The aim of the current resting-state functional magnetic resonance imaging (fMRI) study was to investigate the potential mechanism of schizophrenia through the posterior-anterior cerebrum imbalance in methylazoxymethanol acetate (MAM) rats and to evaluate the effectiveness of repetitive transcranial magnetic stimulation (rTMS) as an early-stage intervention. The rats were divided into four groups: the MAM-sham group, vehicle-sham group, MAM-rTMS group, and vehicle-rTMS group. The rTMS treatment was targeted in the visual cortex (VC) in adolescent rats. Granger Causality Analysis (GCA) was used to evaluate the effective connectivity between regions of interest. Results demonstrated a critical right VC-nucleus accumbens (Acb)-orbitofrontal cortex (OFC) pathway in MAM rats; significant differences of effective connectivity (EC) were found between MAM-sham and vehicle-sham groups (from Acb shell to OFC: t = -2.553, p = 0.021), MAM-rTMS and MAM-sham groups (from VC to Acb core: t = -2.206, p = 0.043; from Acb core to OFC: t = 4.861, p < 0.001; from Acb shell to OFC: t = 4.025, p = 0.001), and MAM-rTMS and vehicle-rTMS groups (from VC to Acb core: t = -2.482, p = 0.025; from VC to Acb shell: t = -2.872, p = 0.012; from Acb core to OFC: t = 4.066, p = 0.001; from Acb shell to OFC: t = 3.458, p = 0.004) in the right hemisphere. Results of the early-stage rTMS intervention revealed that right nucleus accumbens played the role as a central hub, and VC was a potentially novel rTMS target region during adolescent schizophrenia. Moreover, the EC of right nucleus accumbens shell and orbitofrontal cortex was demonstrated to be a potential biomarker. To our knowledge, this was the first resting-state fMRI study using GCA to assess the deficits of a visual-reward neural pathway and the effectiveness of rTMS treatment in MAM rats. More randomized controlled trials in both animal models and schizophrenia patients are needed to further elucidate the disease characteristics.

Dataset Information

Repetitive transcranial magnetic stimulation regulates effective connectivity patterns of brain networks in the spectrum of preclinical Alzheimer's disease.

Objectives

Methods

Results

Conclusion

Clinical trial registration

Publications

Repetitive transcranial magnetic stimulation regulates effective connectivity patterns of brain networks in the spectrum of preclinical Alzheimer's disease.

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