The Location of Feedback-Related Activity in the Midcingulate Cortex Is Predicted by Local Morphology
Bibliographic record
Abstract
Information processing in the medial frontal cortex is often said to be modulated in pathological conditions or by individual traits. This has been observed in neuroimaging and event-related potential studies centered in particular on midcingulate cortex (MCC) functions. This region of the brain is characterized by considerable intersubject morphological variability. Whereas in a subset of hemispheres only a single cingulate sulcus (cgs) is present, a majority of hemispheres exhibit an additional sulcus referred to as the paracingulate sulcus (pcgs). The present functional magnetic resonance imaging study defined the relationship between the local morphology of the cingulate/paracingulate sulcal complex and feedback-related activity. Human subjects performed a trial-and-error learning task in which they had to discover which one of a set of abstract stimuli was the best option. Feedback was provided by means of fruit juice, as in studies with monkeys. A subject-by-subject analysis revealed that the feedback-related activity during exploration was systematically located in the cgs when no pcgs was observed, but in the pcgs when the latter sulcus was present. The activations had the same functional signature when located in either the cgs or in the pcgs, confirming that both regions were homologues. Together, the results show that the location of feedback-related MCC activity can be predicted from morphological features of the cingulate/paracingulate complex.
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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".