Transcranial Magnetic Stimulation Improves Executive Functioning through Modulation of Social Cognitive Networks in Patients with Mild Cognitive Impairment: Preliminary Results
Bibliographic record
Abstract
(1) Background: Patients with mild cognitive impairment (MCI) often present impairment in executive functions (EFs). This study aimed to investigate the effect of high-frequency repetitive transcranial magnetic stimulation (rTMS) on EFs in patients with MCI. (2) Methods: A prospective trial was conducted on 11 patients with MCI. Participants underwent 25 min of 20 Hz rTMS for ten days on the right temporo-parietal junction (RTPJ) and medial prefrontal cortex (MPFC). Before (T0) and after rTMS treatment (T1), global cognitive profile and EFs were investigated using the Montreal cognitive assessment (MoCA), trial making test (TMT) A and B, and frontal assessment battery (FAB). Depression symptoms were assessed using the geriatric depression scale (GDS). Statistical analysis included Wilcoxon signed-rank test. (3) Results: After treatment, patients showed a significant improvement in the MoCA EFs subtask (T0 vs. T1, p = 0.015) and TMT-B (T0 vs. T1, p = 0.028). Five MCI patients with EF impairment showed full recovery of these deficits. No significant changes in the GDS were observed. (4) Conclusions: rTMS stimulation over the TPJ and MPFC induced significant short-term improvements in EFs in MCI patients. These findings suggest that the TPJ and MPFC may be involved in the attention-executive skills to redirect attention toward behaviorally relevant stimuli.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".