Exploring the Therapeutic Impact of Repetitive Transcranial Magnetic Stimulation (rTMS) in Individuals With Alzheimer's Disease: A Comprehensive Narrative Review
Bibliographic record
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disorder marked by cognitive deterioration and behavioral symptoms, significantly impacting patients and caregivers. Behavioral and psychological symptoms of dementia (BPSD), including agitation, depression, and apathy, are common in AD and complicate its management. Conventional treatments, such as cholinesterase inhibitors and antipsychotics, offer limited benefits and often carry adverse effects. Repetitive transcranial magnetic stimulation (rTMS), a non-invasive neuromodulatory technique, has emerged as a promising alternative by modulating cortical excitability and promoting neuroplasticity. This narrative review aims to evaluate the current literature on the therapeutic effects of rTMS in AD, with a focus on its impact on cognitive function and behavioral symptoms. A comprehensive literature search was conducted across PubMed, MEDLINE, PsycINFO, Embase, and the Cochrane Library. Studies were selected based on predefined inclusion and exclusion criteria, with quality assessed using the Cochrane Risk of Bias Tool and the Newcastle-Ottawa Scale. Findings indicate that high-frequency rTMS can improve memory, language, and executive functions, while also reducing neuropsychiatric symptoms such as agitation and depression. Mechanistically, rTMS appears to influence cortical plasticity, neurotransmitter regulation, and neurotrophic factor expression. Despite these encouraging outcomes, heterogeneity in study design, stimulation protocols, and patient populations limit generalizability. Further research through large-scale, standardized, multicentric trials is necessary to confirm its efficacy and define optimal therapeutic parameters. In conclusion, rTMS holds promise as an adjunctive intervention in AD, potentially improving cognitive and behavioral outcomes while offering a favorable safety profile.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".