Bibliographic record
Abstract
Functional neuroimaging studies in normal humans suggest that dorsal anterior cingulate cortex (dACC) plays an important role in cognitive control. This brain area is reliably activated when tasks require the ongoing adjustment of the allocation of attention. The dACC has come to occupy a central role in theories of attention and cognitive control, which hold that dACC either monitors response conflict, signalling the need for adjustments in cognitive processes, or directly mediates such adjustments. However, functional imaging results cannot establish that a brain area is necessary for a particular cognitive process. This requires evidence from loss-of-function studies. Here we assessed cognitive control in four human subjects with damage to dACC and 12 age- and education-matched control subjects using several measures drawn from the functional imaging literature. All four subjects with dACC damage showed normal adjustments in performance following manipulation of response conflict in both Stroop and go-no go tasks. Furthermore, damage to the dACC did not impair the phenomenon of post-error slowing, nor alter the ability to adjust performance in response to explicit speed or accuracy instructions. Thus, cognitive control, as assessed by four different measures in two different tasks, appears to be intact in these subjects, arguing against a necessary role for dACC in this process.
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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 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".