Neural Substrates of Decision Making as Measured With the Iowa Gambling Task in Men With Alexithymia
Bibliographic record
Abstract
OBJECTIVE: Individuals with alexithymia have a reduced ability to use their feelings to guide their behavior appropriately in social situations. To reveal the capacity to use emotional signals in alexithymia under conditions of uncertainty, this study investigates neural substrates and performance on the Iowa Gambling Task (IGT), which was developed to assess decision making based on emotion-guided evaluation. METHODS: The participants were 10 men with alexithymia and 13 without. Alexithymia was assessed by the 20-item Toronto Alexithymia Scale. Regional cerebral blood flow (rCBF) was measured by [¹⁵O]-H₂O positron emission tomography during four trials of the IGT and two visuomotor control tasks. RESULTS: The participants with alexithymia failed to learn an advantageous decision-making strategy, with performance differing significantly from the nonalexithymic group in the fourth IGT trial (p = .029). Comparing performance between the IGT and the control tasks, both groups showed brain activation in the dorsolateral frontal area, inferior frontal lobe, pre-supplementary motor area, inferior parietal lobe, fusiform gyrus, and cerebellum. Men with alexithymia showed lower rCBF in the medial frontal area (Brodmann area [BA] 10) and higher rCBF in the caudate and occipital areas in the first and second IGT trials, which are within a learning phase according to test performance data. All brain data were significant at p ≤ .001, uncorrected. CONCLUSIONS: BA10 activity may be associated with using internal signals accompanying affective evaluation of the stimuli, which is crucial for successful decision making. Reduced BA10 activity in participants with alexithymia suggests that they may not use an emotion-based biasing signal to lead to advantageous decision making.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".