Transcranial Magnetic Stimulation Measures in the Elderly: Reliability, Smallest Detectable Change and the Potential Influence of Lifestyle Habits
Bibliographic record
Abstract
Background: Transcranial magnetic stimulation (TMS) is a noninvasive technique that can be used to evaluate cortical function and corticospinal pathway in normal and pathological aging. Yet, the psychometric evaluation of TMS-related measurements is still limited in the aging population. Objectives: The aim of this cross-sectional study was to document the reliability and smallest detectable change of TMS measurements among community-dwelling seniors. A secondary objective was to test if TMS measurements differ between elders based on lifestyle, medical and socio-demographic factors. Methods: Motor evoked potentials (MEPs) elicited by single-pulse TMS were recorded in the first dorsal interosseous (FDI) in 26 elderly individuals (mean age = 70 ± 3.8 years). Resting motor threshold (rMT), MEP amplitudes and cortical silent period (cSP) were measured on 2 separate occasions (1-week interval), and the standard error of the measurement (SEMeas), intraclass correlation coefficient (ICC) and smallest detectable change in an individual (SDCindv) were calculated. Lifestyle, medical and socio-demographic factors were collected using questionnaires. TMS-related outcomes were compared using independent sample t-test based on the presence of chronic health diseases, chronic medication intake, obesity, history of smoking, physical activity levels, gender, and level of education. Results: rMT and cSP measures were the most reliable outcomes, with the lowest SEMeas and highest ICCs, whereas MEP amplitude-related measures were less reliable. SDCindv levels were generally high, even for rMT (7.29 %MSO) and cSP (43.16-50.84 ms) measures. Although not systematically significant, results pointed toward a higher corticospinal excitability in elderly individuals who were regularly active, who had no chronic medical conditions and who did not take any medication. Conclusion: Even though SDCindv levels were relatively high, these results show that rMT and cSP are the most reliable outcomes to investigate age-related changes in the corticomotor system and suggest that the influence of factors such as life habits and medications on TMS measures should be investigated further.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 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".