Functional and Neurophysiological Correlates of Corticospinal Function in Human Aging
Bibliographic record
Abstract
Transcranial magnetic stimulation (TMS) is a non-invasive technique that can be used to assess the integrity neuronal circuits in the motor cortex, both at the intrahemispheric and interhemispheric level. In the present study, TMS was used to examine age-related modulation of corticospinal function. Participants underwent hand function testing to examine possible links between TMS measures and manual ability. Participants consisted of healthy young (n=13) and senior (n=17) right-handed individuals. Hand function testing consisted of a battery of tests administered bilaterally to assess each participant’s dexterity, strength, movement speed and reaction time. The following TMS measures were assessed bilaterally: resting motor threshold, recruitment curve and silent periods of the contralateral and ipsilateral hand. Both young and senior subjects showed significant intermanual differences in most behavioral measures, favoring their dominant right hand. There was an age-related difference in TMS measures indicating a decline in intrahemispheric excitability and interhemispheric inhibition. A general trend linking specific TMS measures in the active state with age-related changes in hand function on the dominant hand was found. Our results suggest that TMS markers of corticospinal excitability can be used to predict declining hand function with age and thus could provide an early diagnosis of pathological aging.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.000 |
| 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".