Association between urban upbringing and functional brain connectivity in schizophrenia
Bibliographic record
Abstract
Background: Environmental factors considerably influence the development of the human cortex during the perinatal period, early childhood, and adolescence. Urban upbringing in the first 15 years of life is a known risk factor for schizophrenia (SCZ). Though the risk of urban birth and upbringing is well-examined from an epidemiological perspective, the biological mechanisms underlying urban upbringing remain unknown. The effect of urban birth and upbringing on functional brain connectivity in SCZ patients is not yet examined. Methods: This is a secondary data analysis of three studies that included 87 patients with SCZ and 70 healthy volunteers (HV) aged 18 to 50 years. We calculated the developmental urbanicity index using a validated method in earlier studies. Following standard pre-processing of resting functional magnetic resonance imaging (fMRI) scans, seed-return on investment (ROI) functional connectivity analysis was performed. Results: The results showed a significant association between urban birth and upbringing on functional connectivity in SCZ patients and HV ( P < 0.05). In SCZ patients, connections from the right caudate, anterior cingulate cortex, left and right intracalcarine cortices, left and right lingual gyri, left posterior parahippocampal cortex to the cerebellum, fusiform gyri, lateral occipital cortex, and amygdala were significantly associated with the urbanicity index ( P < 0.05). Conclusions: These study findings suggest a significant association between urban birth and upbringing on functional brain connectivity in regions involved in reward processing and social cognition in SCZ. Assessment of social cognition could have implications in developing an in-depth understanding of this impairment in persons with SCZ.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".