The Structural Neural Substrates of Persistent Negative Symptoms in First-Episode of Non-Affective Psychosis: A Voxel-Based Morphometry Study
Bibliographic record
Abstract
OBJECTIVES: An important subset of patients with schizophrenia present clinically significant persistent negative symptoms (PNS). Identifying the neural substrates of PNS could help improve our understanding and treatment of these symptoms. METHODS: This study included 64 non-affective first-episode of psychosis (FEP) patients and 60 healthy controls; 16 patients displayed PNS (i.e., at least one primary negative symptom at moderate or worse severity sustained for at least six consecutive months). Using voxel-based morphometry (VBM), we explored for gray matter differences between PNS and non-PNS patients; patient groups were also compared to controls. All comparisons were performed at p < 0.05, corrected for multiple comparisons. RESULTS: PNS patients had smaller gray matter in the right frontal medial-orbital gyrus (extending into the inferior frontal gyrus) and right parahippocampal gyrus (extending into the fusiform gyrus) compared to non-PNS patients. Compared to controls, PNS patients had smaller gray matter in the right parahippocampal gyrus (extending into the fusiform gyrus and superior temporal gyrus); non-PNS patients showed no significant differences to controls. CONCLUSION: Neural substrates of PNS are evident in FEP patients. A better understanding of the neural etiology of PNS may encourage the search for new medications and/or alternative treatments to better help those affected.
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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".