Impaired illness awareness in schizophrenia and posterior corpus callosal white matter tract integrity
Bibliographic record
Abstract
Impaired illness awareness (Imp-IA) in schizophrenia is associated with interhemispheric imbalance, resulting in left hemisphere dominance, primarily within the posterior parietal area (PPA). This may represent an interhemispheric "disconnection syndrome" between PPAs. To test this hypothesis, we aimed to determine if diffusion-based measures of white matter integrity were disrupted in the corpus callosal tracts linking PPAs (i.e., splenium) in patients with Imp-IA in schizophrenia. T1-weighted and diffusion-weighted scans were acquired on a 1.5T GE scanner for 100 participants with a DSM-IV-TR diagnosis of schizophrenia and 134 healthy controls aged 18 to 79 years. The corpus callosal white matter tracts were compared among patients with Imp-IA (n = 40), intact illness awareness (n = 60), and healthy controls. White matter disruption was measured with fractional anisotropy (FA) and mean diffusivity (MD). Group differences in FA were found in the splenium, with patients with Imp-IA having the lowest FA, which remained significant after controlling for sex, age, global cognition, and premorbid intelligence. No group differences in MD were observed. Splenial white matter tracts of the corpus callosum appear compromised in patients with Imp-IA. Transcallosal interhemispheric PPA white matter disruption may represent a "disconnection syndrome", manifesting as Imp-IA in schizophrenia. Future studies are required to investigate the effects of noninvasive brain stimulation interventions, such as transcranial direct current or magnetic stimulation, on Imp-IA in association with white matter changes in patients with schizophrenia.
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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) | 0.001 | 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".