Microstimulation of dorsal premotor and primary motor cortex delays the volitional commitment to an action choice
Bibliographic record
Abstract
Humans and other animals are faced with decisions about actions on a daily basis. These typically include a period of deliberation that ends with the commitment to a choice, which then leads to the overt expression of that choice through action. Previous studies with monkeys have demonstrated that neural activity in sensorimotor areas correlates with the deliberation process and reflects the moment of commitment before movement initiation, but the causal roles of these regions are challenging to establish. Here, we tested whether dorsal premotor (PMd) and primary motor cortex (M1) are causally involved in the volitional commitment to a reaching choice. We found that brief subthreshold microstimulation in PMd or M1 delayed commitment to an action but not the initiation of the action itself. Importantly, microstimulation only had a significant effect when it was delivered close to and before commitment time. These results are consistent with the proposal that PMd and M1 participate in the commitment process, which occurs when a critical firing rate difference is reached between cells voting for the selected option and those voting for the competing one. NEW & NOTEWORTHY The neural substrates of decisions between actions are typically investigated by correlating neural activity and subjects’ decision behavior, but this does not establish causality. In a reaching decision task, we demonstrate that subthreshold microstimulation of the monkey dorsal premotor cortex or primary motor cortex delays the deliberation duration if applied shortly before choice commitment. This result suggests a causal role of the sensorimotor cortex in the determination of decisions between actions.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".