Factors influencing corticospinal excitability during arm cycling
Bibliographic record
Abstract
Humans can effortlessly navigate their environments and perform a variety of motor tasks, yet the neural processes underlying these movements are complex. The corticospinal pathway, a major descending pathway involved in the voluntary control of human movement, can be assessed non-invasively using various stimulation techniques. However, despite continued advancements in neurophysiology, our understanding of the corticospinal pathway’s role in dynamic, functional movements remains limited. This is partly because most research has focused on corticospinal excitability during static or minimally demanding tasks, leaving a substantial gap in our knowledge of its role during more natural, rhythmic motor outputs. In our lab, we use arm cycling, which resembles other forms of locomotion, to study the modulation of corticospinal pathway excitability under different conditions. This dissertation aims to advance our understanding of the neural control of arm cycling in healthy participants, specifically examining some of the factors that influence descending corticospinal drive and spinal motoneurone excitability during arm cycling. Chapter 2 presents an invited review paper outlining methodological considerations for studying corticospinal excitability during dynamic locomotor outputs, providing a foundation for the subsequent experiments. Chapters 3 to 5 contain studies published in peer-reviewed journals, each addressing specific research questions. In Chapter 3, we investigated whether focusing on maintaining a specified cadence during arm cycling would affect corticospinal excitability and found no significant effect. Chapter 4, explored how varying cycling and stimulation intensities would influence corticospinal and spinal excitability, revealing that both increased with cycling intensity up to a plateau, with differences observed by stimulation intensity. At high cycling intensities, we suggested that greater contributions from supraspinal centres may occur to produce the motor output. Chapter 5 examined the effects of a two-week arm cycling sprint interval training intervention on corticospinal and spinal excitability during arm cycling. The results showed enhanced spinal excitability post-training, with no change in corticospinal excitability. Given that no changes occurred in controls, we suggested that the increase in spinal excitability post-training represented a neural adaptation to training. Collectively, these findings enhance our understanding of the corticospinal pathway’s role during locomotor outputs and highlight the need for future work.
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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 | 0.000 | 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) | 0.002 | 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".