RETRACTED: Application of Repetitive Transcranial Magnetic Stimulation over the Dorsolateral Prefrontal Cortex in Alzheimer’s Disease: A Pilot Study
Post-publication record
OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.
Bibliographic record
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is reportedly a potential tool to understand the neural network; however, the pathophysiological mechanisms underlying cognitive function change remain unclear. This study aimed to explore the cognitive function changes by rTMS over the bilateral dorsolateral prefrontal cortex (DLPFC) in Alzheimer's disease (AD). We evaluated the feasibility of rTMS application for mild cognitive dysfunction in patients with AD in an open-label trial (UMIN000027013). An rTMS session involved 15 trains at 120% resting motor threshold on each side (40 pulses/train at 10 Hz). Efficacy outcome measures were changes from baseline in cognitive function, assessed based on the AD Assessment Scale-cognitive subscale, Mini-Mental State Examination, Japanese version of Montreal Cognitive Assessment (MoCA-J), Behavioral and Psychological Symptom of Dementia, and Instrumental Activity of Daily Living scores. Sixteen patients with AD underwent five daily sessions of high-frequency rTMS over the bilateral DLPFC for 2 weeks. All participants completed the study; no major adverse effects were recorded. The MoCA-J score increased by 1.4 points (±0.15%) following 2 weeks of stimulation. At 1 month following rTMS cessation, all cognitive functional scores returned to the original state. Our findings suggest that the DLPFC plays an important role in the neural network in AD.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".