Cardiac cycle modulates alpha and beta suppression during motor imagery
Bibliographic record
Abstract
Previous interoception research has demonstrated that sensory processing is reduced during cardiac systole, an effect associated with diminished cortical excitability, possibly due to heightened baroreceptor activity. This study aims to determine how phases of the cardiac cycle-systole and diastole-modulate neural sensorimotor activity during motor imagery (MI) and motor execution (ME). We hypothesised that MI performance, indexed by enhanced suppression of contralateral sensorimotor alpha (8-13 Hz) and beta (14-30 Hz) activity, would be modulated by the cardiac phases, with improved performance during diastole due to enhanced sensory processing of movement cues. Additionally, we investigated whether movement cues during systole or diastole enhance muscle activity. To test these hypotheses, 29 participants were instructed to perform or imagine thumb abductions, while we recorded their electroencephalography, electrocardiogram, and electromyogram (EMG) activity. We show that imaginary movements instructed during diastole lead to more pronounced suppression of alpha and beta activity in contralateral sensorimotor cortices, with no significant cardiac timing effects observed during ME as confirmed by circular statistics. Additionally, diastole was associated with significantly increased EMG on the side of actual and, to a lesser degree, imagined movements. Our study identifies optimal cardiac phases for MI performance, suggesting potential pathways to enhance MI-based assistive technologies.
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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) | 0.001 | 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".