Decision-making impairments following insular and medial temporal lobe resection for drug-resistant epilepsy
Bibliographic record
Abstract
Besides the prefrontal cortex, the insula and medial structures of the temporal lobe are thought to be involved in risky decision-making. However, their respective contributions to decision processes remain unclear due to the lack of studies involving patients with isolated insular damage. We assessed adult patients who underwent resection of the insula (n = 13) or of the anterior temporal lobe (including medial structures) (n = 13) as part of their epilepsy surgery, and a group of healthy volunteers (n = 20), on the Iowa Gambling Task (IGT) and on the Cups Task. Groups were matched on sociodemographic, estimated-IQ and surgery-related factors. On the IGT, patients with temporal lobe resection performed significantly worse than both the insular and healthy control groups, as they failed to learn which decks were advantageous on the long-term. On the Cups Task, the insular and temporal groups both showed impaired sensitivity to expected value in the loss domain, when compared with healthy controls. These findings provide clinical evidence that the insula and mesiotemporal structures are specifically involved in risky decision-making when facing a potential loss, and that temporal structures are also involved in learning the association between behavior and consequences in the long-term.
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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 | 0.000 |
| 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 | 0.000 |
| 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".