Adaptation of motor control strategies and physiological arousal during repeated blocks of split-belt walking
Bibliographic record
Abstract
Abstract Physiological arousal, mediated by the autonomic nervous system (ANS), is known to co-modulate with adaptation of motor control strategies, governed by the central nervous system (CNS), in response to repeated standing perturbations. However, adaptation of the ANS physiological arousal response during repeat exposure to walking challenges remains unknown. This study examines the physiological arousal response (electrodermal activation, EDA) and motor control strategy of gait during a single session of repeated exposure to blocks of split-belt walking. Twenty young adults completed three repeated blocks (3.5 min each) of split-belt walking (2:1 speed ratio) alternating with three blocks of tied-belt walking. Step length symmetry (SLS), EDA, bilateral tibialis anterior (TA) and gastrocnemius medialis (GM) muscle activation and ground reaction forces (GRFs) were measured. For each walking block, the first (early) and last (late) 15 strides were analyzed. A linear mixed-effects model (LMM) tested the effect of repeated blocks and phases (early/late) on SLS. Statistical parametric mapping (SPM) examined patterns of within-block changes in EDA, muscle activation, and GRFs. The greatest within-block adaptation of SLS occurred during first exposure to split-belt walking (S1; p <.001). Similarly, the largest magnitude of within-block adaptation in muscle activation, GRFs, and EDA occurred during S1 ( p <.05). Attenuated EDA responses together with lower magnitude of motor adaptation in subsequent split blocks 2 and 3 were observed, indicating savings across the ANS and CNS. Taken together, these findings demonstrate that the ANS-mediated physiological arousal response modulates alongside the CNS-driven locomotor adaptation to repeated exposure to blocks of split-belt walking.
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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".