Cognitive Brain Signatures of Youth With Early Onset and Relatives With Schizophrenia: Evidence From fMRI Meta-analyses
Bibliographic record
Abstract
Deficits in cognitive function are a major characteristic of schizophrenia. Many functional magnetic resonance imaging (fMRI) studies examine brain correlates of cognitive function in adults with schizophrenia, showing altered implication of associative areas such as the prefrontal cortex and temporal cortex. fMRI studies also examine brain representation of cognitive function in adolescents with early onset schizophrenia and those at risk of the disorder, yet results are often inconsistent. We compile and analyze data from eligible fMRI studies using quantitative meta-analyses to reveal concordant brain activity associated with adolescent relatives of patients with schizophrenia and those with early onset schizophrenia. Results show similar functional hubs of brain activity (eg, precuneus) yet in opposite hemispheres and clusters in ventrolateral rather than dorsolateral prefrontal cortices. Other areas of altered implication include the middle temporal gyrus, insula, and cerebellum. We discuss the findings in reference to the protracted maturation of the prefrontal cortex and possible effects due to the medication status of the two groups.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".