Neural Activity in Primary Motor and Dorsal Premotor Cortex In Reaching Tasks With the Contralateral Versus Ipsilateral Arm
Bibliographic record
Abstract
To investigate the effector dependence of task-related neural activity in dorsal premotor (PMd) and primary motor cortex (M1), directional tuning functions were compared between instructed-delay reaching tasks performed separately with either the contralateral or the ipsilateral limb. During presentation of the instructional cue, the majority (55/90, 61%) of cells in PMd were tuned with both arms, and their dynamic range showed a trend for stronger discharge with the contralateral arm. Most strikingly, however, the preferred direction of most of these latter cells (41/55, 75%) was not significantly different between arms. During movement, many PMd cells continued to be tuned with both arms (53/90, 59%), with a trend for increasing directional differences between the arms over the course of the trial. In contrast, during presentation of the instructional cue only 5/74 (7%) cells in M1 were tuned with both arms. During movement, about half of M1 cells (41/74, 55%) were tuned with both arms but the preferred directions of their tuning functions were often very different and there was a strong bias toward greater discharge rates when the contralateral arm was used. Similar trends were observed for EMG activity. In conclusion, M1 is strongly activated during movements of the contralateral arm, but activity during ipsilateral arm movements is also common and usually different from that seen with the contralateral arm. In contrast, a major component of task-related activity in PMd represents movement in a more abstract or task-dependent and effector-independent manner, especially during the instructed-delay period.
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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".