Deciding how to decide: ventromedial frontal lobe damage affects information acquisition in multi-attribute decision making
Bibliographic record
Abstract
Ventromedial frontal lobe (VMF) damage is associated with impaired decision making. Recent efforts to understand the functions of this brain region have focused on its role in tracking reward, punishment and risk. However, decision making is complex, and frontal lobe damage might be expected to affect it at other levels. This study used process-tracing techniques to explore the effect of VMF damage on multi-attribute decision making under certainty. Thirteen subjects with focal VMF damage were compared with 11 subjects with frontal damage that spared the VMF and 21 demographically matched healthy control subjects. Participants chose rental apartments in a standard information board task drawn from the literature on normal decision making. VMF subjects performed the decision making task in a way that differed markedly from all other groups, favouring an 'alternative-based' information acquisition strategy (i.e. they organized their information search around individual apartments). In contrast, both healthy control subjects and subjects with damage predominantly involving dorsal and/or lateral prefrontal cortex pursued primarily 'attribute-based' search strategies (in which information was acquired about categories such as rent and noise level across several apartments). This difference in the pattern of information acquisition argues for systematic differences in the underlying decision heuristics and strategies employed by subjects with VMF damage, which in turn may affect the quality of their choices. These findings suggest that the processes supported by ventral and medial prefrontal cortex need to be conceptualized more broadly, to account for changes in decision making under conditions of certainty, as well as uncertainty, following damage to these areas.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".