Lesion mapping of cognitive control and value-based decision making in the prefrontal cortex
Bibliographic record
Abstract
A considerable body of previous research on the prefrontal cortex (PFC) has helped characterize the regional specificity of various cognitive functions, such as cognitive control and decision making. Here we provide definitive findings on this topic, using a neuropsychological approach that takes advantage of a unique dataset accrued over several decades. We applied voxel-based lesion-symptom mapping in 344 individuals with focal lesions (165 involving the PFC) who had been tested on a comprehensive battery of neuropsychological tasks. Two distinct functional-anatomical networks were revealed within the PFC: one associated with cognitive control (response inhibition, conflict monitoring, and switching), which included the dorsolateral prefrontal cortex and anterior cingulate cortex and a second associated with value-based decision-making, which included the orbitofrontal, ventromedial, and frontopolar cortex. Furthermore, cognitive control tasks shared a common performance factor related to set shifting that was linked to the rostral anterior cingulate cortex. By contrast, regions in the ventral PFC were required for decision-making. These findings provide detailed causal evidence for a remarkable functional-anatomical specificity in the human PFC.
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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 | 0.001 | 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".