Quantitative assessment of cortical excitability in Alzheimer’s dementia and its association with clinical symptoms: A systematic review and meta‐analyses
Bibliographic record
Abstract
Abstract Background Alzheimer’s Disease (AD) is characterized by cognitive and neuropsychiatric symptoms (NPS). Studies using electroencephalography (EEG) have shown increased epileptiform and epileptic activity in AD. Transcranial magnetic stimulation (TMS) studies have also shown abnormal cortical excitability in AD, however findings have been inconsistent. Further, relationship between cortical excitability and clinical symptoms of AD is not clear. This review and meta‐analyses aims to synthesize the existing evidence for abnormal cortical excitability in AD and its relationship with clinical symptoms. Method We systematically searched and reviewed publications that quantitatively assessed cortical excitability, using TMS resting motor threshold (rMT), active motor threshold (aMT), motor evoked potential (MEP) or directly from the cortex using TMS‐EEG via TMS‐evoked potential (TEP). Effect sizes and 95% confidence intervals (CI) of rMT and aMT were calculated using Hedges’ g and meta‐analyzed using a random effects model. Heterogeneity among studies was assessed by Cochran’s Q and I2 statistic. Result We identified 895 publications out of which 68 were reviewed in full‐text and 37 were included in the final review. Thirty studies using rMT and seven using aMT were included in the meta‐analyses. The AD group had reduced rMT (Hedges’ g = ‐0.99, 95% CI [‐1.29, ‐0.68], p < 0.00001) and aMT (Hedges’ g = ‐0.87, 95% CI [‐1.50, ‐0.24], p < 0.00001) as compared with control groups, indicative of higher cortical excitability. Evidence of considerable heterogeneity was found across the studies (Q (29) = 85.68, p < 0.00001, I2 =81%). Qualitative review of the literature showed some evidence of increased MEP amplitude (n = 2 studies), however findings related to TEP were inconsistent. Further, there was some evidence (n = 4 studies) supporting an inverse association between cortical excitability and global cognition. No publications reported on the relationship between cortical excitability and neuropsychiatric symptoms (NPS). Conclusion There is strong evidence of increased motor cortex excitability in AD and some evidence of an inverse association between excitability and cognition. Future studies should assess cortical excitability from non‐motor areas and examine its relationship with cognition and NPS.
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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 | 0.014 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.039 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".