Reproducibility of Single-Pulse, Paired-Pulse, and Intermittent Theta-Burst TMS Measures in Healthy Aging, Type-2 Diabetes, and Alzheimer’s Disease
Bibliographic record
Abstract
Background. Transcranial magnetic stimulation (TMS) can be used to assess neurophysiology and the mechanisms of cortical brain plasticity in humans in vivo. As the use of these measures in specific population (e.g., Alzheimer’s disease; AD) increases, it is critical to understand their reproducibility (i.e., test-retest reliability) in the populations of interest. Objective. Reproducibility of TMS measures was evaluated in older adults, including healthy, AD, and Type-2 diabetes mellitus (T2DM) groups. Methods. Participants received two identical neurophysiological assessments within a year including, motor thresholds, baseline motor evoked potentials (MEPs), short- and long-interval intracortical inhibition (SICI, LICI) and intracortical facilitation (ICF), and MEP changes following intermittent theta-burst stimulation (iTBS). Cronbach’s α coefficients were calculated to assess reproducibility. Multiple linear regression analyses were used to investigate factors related to intra-individual variability. Results. Reproducibility was highest for motor thresholds, followed by baseline MEPs, SICI and LICI, and was lowest for ICF and iTBS after-effects. The AD group tended to show higher reproducibility than T2DM or controls. Intra-individual variability of baseline MEPs was related to age and variability of RMT, while the intra-individual variability in post-iTBS measures was related to baseline MEP variability, inter-visit duration, and Brain-derived neurotrophic factor (BDNF) polymorphism. Conclusions. Increased reproducibility in AD may reflect pathophysiological declines in the efficacy of neuroplastic mechanisms. Reproducibility of iTBS after-effects can be improved by keeping baseline MEPs consistent, controlling for BDNF genotype, and waiting at least a week between visits. Significance. These findings provide the first direct assessment of reproducibility of TMS measures in older clinical populations. Reproducibility coefficients may be used to adjust effect- and sample-size calculations for future studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".