Sex Differences in the Cerebral Function Associated with Processing Of Aversive Stimuli by Schizophrenia Patients
Bibliographic record
Abstract
OBJECTIVE: Impaired processing of various emotions is considered one of the fundamental features of schizophrenia. In the recent study intriguing sex differences were observed in the cerebral function associated with the experience of sadness in schizophrenia patients. The aim of the present study was to explore this phenomenon during exposure to aversive stimuli. METHOD: Fifteen men and 10 women with the DSM-IV diagnosis of schizophrenia underwent functional magnetic resonance imaging (fMRI) while viewing alternating blocks of negative and neutral pictures. Data were analysed using random-effects model within statistical parametric mapping (SPM99) software. RESULTS: Processing of negative stimuli evoked significantly greater activations in men in the thalamus, cerebellum, temporal, occipital and posterior cingulate cortex, while women exhibited greater activations in the left middle frontal gyrus. CONCLUSIONS: The sex differences in the cerebral activations in schizophrenia patients deviate from what has been observed in the general population during exposure and experience of negative affect. As such the present study supports and extends the authors' preliminary observation of the anomalous sexual dimorphism in schizophrenia at the functional neuroanatomical level, suggesting potential masculinization of female subjects and feminization of male subjects with 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 | 0.000 | 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".