Cortical Mechanisms for Online Control of Hand Movement Trajectory: The Role of the Posterior Parietal Cortex
Bibliographic record
Abstract
The parietal mechanisms for the control of hand movement trajectory were studied by recording cell activity in area 5 of monkeys making direct reaches to visual targets and online corrections of movement trajectory, after change of target location in space. The activity of hand-related cells was fitted with a linear model including hand position, movement direction, and speed. The neural activity modulation mostly led, but also followed, hand movement. When a change of hand trajectory occurred, the pattern of activity associated with the movement to the first target evolved into that typical of the movement to the second one, thus following the corresponding variations of the hand kinematics. The visual signal concerning target location in space did not influence the firing activity associated with the direction of hand movement within the first 150 ms after target presentation. This might be the time necessary for the visuo-motor transformation underlying reaching. We conclude that online control of hand trajectory not only resides in the relationships between neural activity and kinematics, but, under specific circumstances, also on the coexistence of signals about ongoing and future hand movement direction.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".