Cortical Areas for Planning Sequences before and during Movement
Bibliographic record
Abstract
Production of rapid movement sequences relies on preparation before (preplanning) and during (online planning) movement. Here, we compared these processes and asked whether they recruit different cortical areas. Human participants performed three single-finger and three multifinger sequences in a delayed-movement paradigm while undergoing a 7 T functional MRI. During preparation, primary motor (M1) and somatosensory (S1) areas showed preactivation of the first movement, even without increases in overall activation. During production, the temporal summation of activity patterns corresponding to constituent fingers explained activity in these areas (M1 and S1). In contrast, the dorsal premotor cortex (PMd) and anterior superior parietal lobule (aSPL) showed substantial activation during the preparation (preplanning) of multifinger compared with single-finger sequences. These regions (PMd and aSPL) were also more active during production of multifinger sequences, suggesting that pre- and online planning may recruit the same regions. However, we observed small but robust differences between the two contrasts, suggesting distinct contributions to pre- and online planning. Multivariate analysis revealed sequence-specific representations in both PMd and aSPL, which remained stable across both preparation and production phases. Our analyses show that these areas maintain a sequence-specific representation before and during sequence production, likely guiding the execution-related areas in the production of rapid movement sequences.
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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 | 0.001 |
| 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".