A magnetic resonance imaging family study of cortical thickness in schizophrenia
Bibliographic record
Abstract
Schizophrenia is associated with abnormalities in cortical thickness, including both thicker and thinner cortices than controls. Although less reliably than in patients, non-psychotic relatives of schizophrenia patients have also demonstrated both thicker and thinner cortices than controls, suggesting an effect of familial or genetic liability. We investigated cortical thickness in 25 schizophrenia patients, 26 adult non-psychotic first-degree biological relatives, and 23 community controls using the automated program FreeSurfer. Contrary to hypotheses, we found relatives of schizophrenia patients had greater cortical thickness in all lobes compared to patients and controls; however, this finding was not as widespread when compared to controls. In contrast, schizophrenia patients only demonstrated a thinner right fusiform region than controls and relatives. Our finding of greater thickness in adult biological relatives could represent a maladaptive abnormality or alternatively, a compensatory mechanism. Previous literature suggests that the nature of abnormalities in relatives can vary by the age of relatives and change across the developmental period. Abnormalities in patients may depend on lifestyle factors and on current and previous anti-psychotic medication use. Our results speak to the need to study various populations of patients and relatives across the lifespan to better understand different developmental periods and the impact of environmental factors. © 2015 Wiley Periodicals, Inc.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".