Temporal Lobe Volume Abnormalities Precede the Prodrome: A Study of Children Presenting Antecedents of Schizophrenia
Bibliographic record
Abstract
Distributed abnormalities of gray matter (GM) and white matter (WM) volume characterize individuals experiencing their first episode of schizophrenia. Regions of abnormality are present already, albeit less extensively, during the prodromal phase of illness. This study aimed to determine whether putatively at-risk children, aged 9-12 years, who present multiple antecedents of schizophrenia (ASz), display GM and WM volume abnormalities relative to typically developing (TD) children presenting no antecedents. Structural magnetic resonance images were acquired for 20 ASz children and 20 TD children matched on age, sex, and IQ. Whole-brain differences in GM and WM volume were determined using voxel-based morphometry. Relative to the TD group, ASz children showed significantly decreased GM volume in the right middle temporal gyrus (MTG) and increased GM volume in the left superior-middle temporal gyri (P < 0.05, cluster correction). WM volume was significantly increased in ASz children relative to TD children in a cluster encompassing the left inferior parietal lobe, occipital lobe, and superior temporal gyrus. Post-hoc analyses indicated that these abnormalities were not limited to ASz children who self-reported auditory hallucinations on questionnaire. Our findings suggest that children aged 9-12 years who present multiple ASz are characterized by abnormalities of GM and WM volume in the temporal lobes, comprising a subset of the regions affected in first-episode schizophrenia and in the prodromal phase of illness. These preliminary findings indicate that structural brain abnormalities associated with schizophrenia may be detected in putatively at-risk, preprodromal children. Prospective studies following the brain development of at-risk children are needed.
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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 | 0.001 |
| 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".