Longitudinal trajectories of cortical folding in schizophrenia spectrum disorders: a 13-year follow-up study
Bibliographic record
Abstract
Abstract Background and Hypothesis Altered cortical folding is a putative marker of neurodevelopmental disruption in schizophrenia spectrum disorders (SSD). Patients with SSD have been hypothesized to exhibit an accelerated decline in age-related cortical folding, quantified with the Local Gyrification Index (LGI). Here, we assessed longitudinal and cross-sectional LGI differences in patients with chronic SSD relative to healthy controls across 13 years. Study Design The sample comprised patients with SSD (mean baseline age=41.28 years) and healthy controls (mean baseline age=41.56 years) with MRI acquisitions at baseline (103 SSD; 99 controls) and follow-up after 5 (50 SSD; 57 controls) and 13 years (42 SSD; 60 controls). T1-weighted images were processed with the longitudinal pipeline in FreeSurfer. Spatio-temporal linear mixed-effects models were used to test for longitudinal and cross-sectional case-control differences in LGI, as well as the impact of symptom severity and antipsychotic medication dose among patients. Study Results Although cross-sectional LGI was lower in patients in extensive frontal, parietal, and occipital regions, we observed no significant differences in longitudinal trajectories between patients and controls after FDR correction. Medication dose was linked cross-sectionally to lower LGI of the anterior cingulate and orbitofrontal cortex, and the postcentral gyrus. Conclusion In the longest longitudinal study on cortical folding in SSD to date, we found no accelerated progressive decline in cortical folding in patients. Thus, chronic SSD appears to be characterized by a state of stable hypogyria relative to healthy controls, supporting the interpretation of LGI as a marker of neurodevelopmental or early-life disturbances in SSD.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".