Preparatory Cortical Modulations for Stepping Tasks with Varying Postural Complexity
Bibliographic record
Abstract
Abstract We examined whether preparatory cortical activity indexed by the contingent negative variation (CNV) scales with postural complexity during step initiation. Participants performed straight and diagonal stepping in a Warning-Go paradigm while EEG was recorded; CNV epochs spanned the 2s fore period and were summarized into eight 0.25-s bins for electrode and eLORETA source-level analyses using linear mixed-effects models (n=31). Diagonal stepping produced greater early CNV negativity at the scalp (bin 1: C1, CP3, CP1, P1, FC4; bin 2: F1, F3, FC1, Fz, F2, F4, FC2, FCz), with no electrodes favoring straight stepping. Source analysis showed stronger engagement for diagonal stepping in bins 1-3 (0-0.75 s) across fronto-parietal sensorimotor regions, including paracentral, transverse frontopolar, superior frontal (gyrus/sulcus), supramarginal, superior parietal, intraparietal, and precentral sulcus; no regions were greater for straight stepping. These effects concentrated in the early CNV suggest enhanced anticipatory selective attention and sensory up-weighting under higher postural demands, providing a richer state estimate for scaling anticipatory postural adjustments.
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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 | 0.002 |
| 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".