From movements to words: action monitoring in the medial frontal cortex along a caudal to rostral prediction error gradient
Bibliographic record
Abstract
Abstract Speech error monitoring recruits the medial frontal cortex (MFC) region in the human brain. Error monitoring-related activity in the MFC has been interpreted both in terms of conflict monitoring and feedback-driven control, but as similar regions of the MFC are implicated in various levels of behavioral control ranging from basic motor movement control to high-level cognitive control functions, a more comprehensive account is needed. Moreover, as speech errors and other actions that involve varying control demands engage a widespread yet partially overlapping set of regions of the MFC, such an account should ideally explain the anatomical distribution of error-related functional activations within the MFC. Here we wanted to assess the hypothesis that the MFC has a similar role in the evaluation of action outcomes for motor and mental actions, operating along a rostral-caudal gradient of higher-lower level control demands involving prediction errors from both sensory and epistemic sources. To this end, we conducted an individual-specific annotation of task-fMRI BOLD activation peaks related to speech errors versus correct productions (i.e. that involve the largest cognitive control demands, Study I and II), tongue movement monitoring (i.e. that involve an intermediate level of cognitive and motor control demands) and tongue movement (i.e. that involve only motor control demands, Study II) in the MFC region. Results revealed overlapping clusters across the three contrasts across the MFC, but importantly both the number of peaks and their relative position along the rostral caudal axis were consistent with a hierarchical rostral caudal processing gradient in the MFC. While tongue movement showed more caudal activation in the MFC, speech errors showed more rostral activation, and tongue movement monitoring patterned in between. Furthermore, the combined results of both studies suggested that activation peaks were located more dorsally for participants that had a paracingulate gyrus, replicating a previously documented effect for movement and further supporting a common functional role of the MFC across very distinct 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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".