Chronotype Influences Diurnal Variations in the Excitability of the Human Motor Cortex and the Ability to Generate Torque during a Maximum Voluntary Contraction
Bibliographic record
Abstract
The ability to generate torque during a maximum voluntary contraction (MVC) changes over the day. The present experiments were designed to determine the influence of an individual's chronotype on this diurnal rhythm and on cortical, spinal, and peripheral mechanisms that may be related to torque production. After completing a questionnaire to determine chronotype, 18 subjects (9 morning people, 9 evening people) participated in 4 data collection sessions (at 09:00, 13:00, 17:00, and 21:00) over 1 day. We used magnetic stimulation of the cortex, electrical stimulation of the tibial nerve, electromyographic (EMG) recordings of muscle activity, and isometric torque measurements to evaluate the excitability of the motor cortex, the spinal cord, and the torque-generating capacity of the triceps surae (TS) muscles. We found that for morning people, cortical excitability was highest at 09:00, spinal excitability was highest at 21:00, and there were no significant differences in TS EMG or torque produced during MVCs over the day. In contrast, evening people showed parallel increases in cortical and spinal excitability over the day, and these were associated with increased TS EMG and MVC torque. There were no differences at the level of the muscle over the day between morning and evening people. We propose that the simultaneous increases in cortical and spinal excitability increased central nervous system drive to the muscles of evening people, thus increasing torque production over the day. These differences in cortical excitability and performance of a motor task between morning and evening people have implications for maximizing human performance and highlight the influence of chronotype on an individual's diurnal rhythms.
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".