Mapping Convergent and Divergent Cortical Thinning Patterns in Patients With Deficit and Nondeficit Schizophrenia
Bibliographic record
Abstract
Deficit schizophrenia (DS) is a homogeneous subtype of schizophrenia characterized by primary and enduring negative symptoms. However, the underlying neuroanatomical substrate of DS remains poorly understood. Here, we collected high-resolution structural magnetic resonance images of 115 participants, including 33 DS patients, 41 nondeficit schizophrenia (NDS) patients, and 41 healthy controls (HCs), and calculated the cortical thickness and surface area for statistical comparisons among the 3 groups. Relative to the control group, both the DS and NDS groups exhibited convergent cortical thinning in the bilateral inferior frontal gyri and the left superior temporal gyrus. The cortical thinning in the right inferior frontal cortex in the patient group was significantly positively correlated with declines of cognitive flexibility and visuospatial memory. Importantly, compared to the NDS group, the DS group exhibited a more widespread cortical thinning pattern, with the most significant differences in the left temporo-parietal junction area. For the surface area measurement, no significant group differences were observed. Collectively, these results highlight the convergent and divergent cortical thinning patterns between patients with DS and NDS, which provide critical insights into the neuroanatomical substrate of DS and improve our understanding of the biological mechanism that contributes to the negative symptoms and cognitive impairments in DS.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".