Structural neural correlates of impairments in social cognition in first episode psychosis
Bibliographic record
Abstract
Several studies have demonstrated that patients with schizophrenia show impairments in social cognition and current evidence indicate that this deficit is associated with abnormal activity in specific brain regions. In addition to functional imaging studies, we believe that the identification of structural correlates of social cognitive processes may help to better understand the neural underpinnings of these specific skills. The main objective of this study was to investigate the relationship between gray matter density and social cognitive deficits in first episode of schizophrenia spectrum psychosis, using a comprehensive assessment that we previously demonstrated to be a highly sensitive measure of social cognitive deficits in this population. Thirty-eight patients with a first episode of psychosis participated in this study, and the Four Factor Test of Social Intelligence was used as a measure of social cognition. Social cognitive impairments in first episode psychosis were significantly correlated with reduced gray-matter density in the left middle frontal gyrus other regions within the mirror neuron system network (MSN), namely the right supplementary motor cortex, the left superior temporal gyrus and the left inferior parietal lobule. We concluded that structural abnormalities within the MSN may account for the social cognitive deficits present in some psychiatric disorders, such as schizophrenia.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".