Altered Cortical Gyrification Is Associated with Cortical and White Matter Microstructure in Individuals with Early Psychosis: A Multimodal Neuroimaging Study
Bibliographic record
Abstract
BACKGROUND AND HYPOTHESIS: Deviated brain folding patterns in psychosis may reflect dysfunctional brain development, more specifically cortical growth and white matter myelination. However, mechanisms that underlie the cortical folding disturbances and their relationship to clinical phenotypes in psychosis remain unknown. STUDY DESIGN: This cross-sectional multimodal neuroimaging study combines structural and diffusion magnetic resonance imaging (MRI) in 203 individuals with early psychosis and 73 healthy individuals. The primary goal is to use local gyrification index (LGI), which quantifies cortical folding, to assess possible cortical abnormalities in subjects with early psychosis. The secondary goal is to combine gyrification measures with advanced diffusion MRI indices, namely, heterogeneity of fractional anisotropy (FA), a proxy for cortical cytoarchitecture, and free-water corrected FA, the latter associated with the tissue-related white matter microstructure. Finally, the relationship between these imaging measures with psychiatric symptoms and cognitive abilities are examined. STUDY RESULTS: Compared to healthy individuals, the early psychosis group exhibited a significant LGI reduction, potentially reflecting sulcal widening and shallowing in the left temporo-parietal region. Local gyrification index was significantly associated with heterogeneity of FA in the corresponding region. Lower LGI was also associated with reduced FA in the white matter tracts connecting this region to the frontal lobe. Finally, lower LGI at the temporo-parietal junction was associated with more severe negative symptoms. CONCLUSIONS: We present the first in vivo evidence that anomalies in cortical folding may be linked to alterations in both the underlying cortical cytoarchitecture and associated microstructure of ipsilateral long-range white matter connections in psychosis.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".