Correlations between sadness-induced cerebral activations and schizophrenia symptoms: An fMRI study of sex differences
Bibliographic record
Abstract
BACKGROUND: The functional neuroimaging studies of emotion processing in schizophrenia have revealed variable results attributed partly to differential symptomatology and sex of tested patients. The aim of the present study was to investigate the relationship between cerebral activations during exposure to emotional material and schizophrenia symptoms in men versus women. METHOD: Fifteen men and 10 women with schizophrenia, equivalent in terms of age, medication and experienced symptomatology, underwent functional MRI during viewing sad and neutral film excerpts. Data were analyzed using Statistical Parametric Mapping Software (SPM2). RESULTS: Across all the patients there was a significant inverse relationship between negative symptoms and activations in the right prefrontal cortex during processing of sad versus neutral stimuli. In men, activations during sad versus neutral stimuli in the prefrontal, temporal and anterior cingulate cortex, as well as the caudate and cerebellum, were positively correlated with negative symptoms. In women, there were inverse correlations between positive symptoms and activations in the hippocampus, parietal and occipital cortex during the same condition. CONCLUSION: Present results confirmed association of prefrontal hypofunction with negative symptoms in schizophrenia. More interestingly, the results revealed a diametrically different pattern of symptom-correlated brain activity in men and women with schizophrenia, suggesting that the processing of sadness is mediated via neurophysiological mechanism related to negative symptoms in men and the mechanism related to positive symptoms in women.
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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 | 0.000 | 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) | 0.003 | 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".