Theory of Mind Skills Are Related to Resting-State Frontolimbic Connectivity in Schizophrenia
Bibliographic record
Abstract
Patients with schizophrenia (SCH) often demonstrate impairment in social-cognitive functions as well as disturbances in large-scale network connectivity. The ventromedial prefrontal cortex (vmPFC) is a core region of the default mode network, with projections to limbic structures. It plays an important role in social and emotional decision-making. We investigated whether resting-state functional connectivity (FC) relates to the cognitive and affective domains of theory of mind (ToM). Twenty-three SCH patients and 19 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging scanning. vmPFC seed connectivity was correlated with behavioral measures assessing ToM domains. SCH performed less well than HCs in both ToM task domains. An analysis of the resting-state FC revealed that SCH had reduced connectivity from the vmPFC to the subcallosal cortex, right amygdala, and right hippocampus as a function of behavioral scores in both ToM domains. Within-group analyses indicated that in HCs, the performance in ToM was positively associated with frontoamygdalar resting-state connectivity, whereas in SCH, the performance in ToM was negatively associated with the frontosubcallosal connectivity. Differences in the pattern of the resting-state frontolimbic connectivity and its associations with performance in ToM tasks between the two study groups might represent a different setup for processing social information in patients with SCH.
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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".