Structural asymmetries in the planum temporale in patients with schizophrenia: A meta-analysis
Bibliographic record
Abstract
Research on planum temporale (PT) asymmetries in schizophrenia has yielded inconsistent findings: Some studies suggest a link between atypical PT asymmetries and schizophrenia, their conclusions are often limited by low statistical power or limited representativeness, while others find no association. The PT, a region crucial for auditory and language processing, seems particularly relevant in schizophrenia because of the disorder’s symptomatology regarding changes in language processing. This meta-analysis synthesizes literature on structural PT asymmetries in schizophrenia compared to controls, employing robust meta-analytical methods. Following PRISMA guidelines, we conducted a systematic search process in 2024 with the keywords (schizophrenia) OR (schizophrenic) OR (psychosis) AND (planum temporale) OR (asymmetries) OR (asymmetry) OR (laterality) on the databases PubMed, PubPsych, GoogleScholar, and ResearchGate. This search yielded 28 results with a total of n = 1409 participants (760 schizophrenia patients, 649 unaffected controls). Studies fulfilled the inclusion criteria: reporting of primary MRI/CT data on PT asymmetry in schizophrenia and controls; DSM/ICD schizophrenia diagnosis; sufficient PT size data for analysis and specification of measurement units, peer-reviewed and published in English, French, German, or Greek. Random effects meta-analyses revealed a significant atypical asymmetry and a significant size reduction of the left PT in patients with schizophrenia relative to controls. Further analyses did not identify any significant moderating effects. Risk of Bias assessment (following the Newcastle-Ottawa scale) revealed that most studies were of moderate to high quality with relatively low bias. The findings extend our understanding of the neurobiological underpinnings of schizophrenia. • Meta-analysis on PT asymmetries in schizophrenia vs. unaffected controls • Integrating frequentist & Bayesian statistics and further meta-regression analyses • Results: Significant weaker leftward PT asymmetry & smaller left PT in schizophrenia • Influence of symptom severity: Meta-regression underpowered to assess effects • Risk of bias analysis: most studies rated as moderate-high quality
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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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.035 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".