Response Competition in the Primary Motor Cortex: Corticospinal Excitability Reflects Response Replacement During Simple Decisions
Bibliographic record
Abstract
It has been suggested that, during decisions about actions, multiple options are initially specified in parallel and then gradually eliminated in a competition for overt execution. To further test this hypothesis, we studied the modulation of human corticospinal excitability during the reaction time of the Eriksen flanker task. In the task, subjects responded with finger flexion or extension to a central arrow while ignoring congruent or incongruent flanker arrows. Single-pulse transcranial magnetic stimulation (TMS) was applied over primary motor cortex (M1) at one of five different latencies after stimulus onset, and motor-evoked potentials (MEPs) were measured in the contralateral index finger. During the control (no flankers) and congruent conditions, MEP size in the agonist increased gradually over the course of reaction time, indicating an increase in corticospinal excitability. Conversely, when the same muscle acted as an antagonist, MEP size decreased, suggesting inhibition. Critically, in the incongruent condition, MEPs briefly increased in the muscle corresponding to an initial default response to the flanker arrows and were later replaced by MEPs corresponding to the correct response to the central arrow. Finally, we found that the gradually growing MEPs for the three conditions reached a constant maximum level just before movement initiation. We propose that this dynamic modulation in corticospinal excitability reflects the competition process, leading to the selection of one response and the rejection of the other. Our results suggest that response competition influences activity in primary motor cortex and that its timing directly influences motor output latency.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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".