Reaching to Multiple Targets When Standing: The Spatial Organization of Feedforward Postural Adjustments
Bibliographic record
Abstract
We examined the spatial organization of feedforward postural adjustments produced prior to and during voluntary arm reaching movements executed while standing. We sought to investigate whether the activity of postural muscles before and during reaching was directionally tuned and whether a strategy of horizontal force constraint could be observed. To this end, eight human subjects executed self-paced reach-to-point movements on the random illumination of one of 13 light targets placed within a 180 degrees array centered along the midline of the body. Analysis was divided into two periods: a first corresponding to the 250 ms preceding the onset of the reaching movements (termed pPA period) and a second 250-ms period immediately preceding target attainment (the aPA period). For both periods, electromyographic activity of the lower limb muscles revealed a clear directional tuning, with groups of muscles being activated for similar directions of reach. Analysis of horizontal ground reaction forces supported the existence of a force constraint strategy only for the pPA period, however, with those in the aPA period being more widely dispersed. We suggest that the strategy adopted for feedforward pPAs is one where the tuned muscle synergies constrain the forces diagonally away from the center of mass (CoM) to move it within the support base. However, the need to control for final finger and body position for each target during the aPA phase resulted in a distribution of vectors across reaching directions. Overall, our results would support the idea that endpoint limb force during postural tasks depends on the use of functional muscle synergies, which are used to displace the CoM or decelerate the body at the end of the reach.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".