Functional dysconnectivity of anterior cingulate subregions in schizophrenia and psychotic and nonpsychotic bipolar disorder
Bibliographic record
Abstract
Aberrant resting-state functional connectivity (FC) of anterior cingulate cortex (ACC) has been implicated in the pathophysiology of schizophrenia and bipolar disorder (BP). This study investigated the subregional FC of ACC across schizophrenia and psychotic (PBP) and nonpsychotic BP (NPBP) and the relationship between brain functional alterations and clinical manifestations. A total of 174 first-episode medication-naive patients with schizophrenia (FES), 80 patients with PBP, 77 patients with NPBP and 173 demographically matched healthy controls (HCs) underwent resting-state functional magnetic resonance imaging. Brain-wide FC of ACC subregions was computed for each individual, and compared between the groups. General intelligence was evaluated using the short version of the Wechsler Adult Intelligence Scale. Relationships between FC and various clinical and cognitive variables were estimated using the skipped correlation. The FES, PBP and NPBP groups showed differing connectivity patterns in the left caudal, dorsal and perigenual ACC. Transdiagnostic dysconnectivity was found in the subregional ACC associated with cortical, limbic, striatal and cerebellar regions. Disorder-specific dysconnectivity in FES was identified between the left perigenual ACC and bilateral orbitofrontal cortex, and the left caudal ACC coupling with the default mode network (DMN) and visual processing region was correlated with psychotic symptoms. In the PBP group, FC between the left dorsal ACC and the right caudate was correlated with psychotic symptoms, and FC connected with the DMN was associated with affective symptoms. The current findings confirmed that subregional ACC dysconnectivity could be a key transdiagnostic feature and associated with differing clinical symptomology across schizophrenia and PBP.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".