Aberrant cortical gyrification in schizophrenia: a surface-based morphometry study
Bibliographic record
Abstract
BACKGROUND: Schizophrenia is considered to be a disorder of cerebral connectivity associated with disturbances of cortical development. Disturbances in connectivity at an early period of cortical maturation can result in widespread defects in gyrification. Investigating the anatomic distribution of gyrification defects can provide important information about neurodevelopment in patients with schizophrenia. METHODS: We undertook an automated surface-based morphometric assessment of gyrification on 3-dimensionally reconstructed cortical surfaces across multiple vertices that cover the entire cortex. We used a sample from our previous research of 57 patients (50 men) with schizophrenia and 41 controls (39 men) in whom we had tested a specific hypothesis regarding presence of both hypo and hypergyria in the prefrontal cortex using a frontal region-of-interest approach. RESULTS: Regions with significant reductions in gyrification (hypogyria) were seen predominantly in the left hemisphere, involving the insula and several regions of the multimodal association cortex. Although the prefrontal hypergyria documented earlier did not survive the statistical correction required for a whole brain search (cluster inclusion at p = 0.0001), significant hypergyric frontal clusters emerged when the threshold was lowered (cluster inclusion at p = 0.05). In the insula, a reduction in gyrification was related to reduced cortical thickness in patients with schizophrenia. LIMITATIONS: We studied a sample of patients taking antipsychotic medications, which could have confounded the results. Our sample was predominantly male, limiting the generalizability of our findings. CONCLUSION: Our observations suggest that the disturbances in cortical gyrification seen in patients with schizophrenia might be related to a disrupted interaction between the paralimbic and the multimodal association cortex and thus might contribute to the pathogenesis of the illness.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.001 | 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".