ArticleEuropean radiology experimental2023
Functional network connectivity patterns predicting the efficacy of repetitive transcranial magnetic stimulation in the spectrum of Alzheimer's disease.
Article in European radiology experimental, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Effectiveness of technology-based exercise on motor function and quality of life in individuals with multiple sclerosis: an umbrella review.Journal of health, population, and nutrition · 2025Pooled it
- 40 Hz biparietal transcranial alternating current stimulation for Alzheimer's disease: a prospective study.BMC medicine · 2026Trial
- Comparative efficacy and safety of photobiomodulation, transcranial direct current stimulation, and repetitive transcranial magnetic stimulation in Alzheimer's disease: a network meta-analysis of randomized controlled trials.Lasers in medical science · 2026Article
- A meta-analysis of the effect of non-invasive neuromodulation techniques on improving cognitive function in patients with Alzheimer's disease.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Review
- fNIRS reveals comparable reductions in cortical hyperconnectivity following once-daily and twice-daily rTMS in poststroke aphasia.Biomedical optics express · 2026Article
- Individualized functional connectome biomarkers predict clinical symptoms after rTMS treatment in Alzheimer's disease.Translational psychiatry · 2025Article
- Treating Depression With Repetitive Transcranial Magnetic Stimulation: A Clinician's Guide.The American journal of psychiatry · 2025Review
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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 STATEMENT: Dynamic 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.
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