Dysfunction of a distributed neural circuitry in schizophrenia patients during a working-memory performance
Bibliographic record
Abstract
BACKGROUND: In a recent longitudinal study of first-episode schizophrenia patients, we found that while dysfunction of the right dorsolateral prefrontal cortex (DLPFC), right thalamus, left cerebellum and cingulate gyrus normalized with antipsychotic treatment and significant reduction in symptomatology, the left DLPFC, left thalamus, and right cerebellum remained disturbed. In the present study we investigated whether these abnormalities are also present in clinically stable, relatively well-functioning schizophrenia patients in comparison to control subjects during performance of the N-back working-memory task. METHOD: Twelve schizophrenia and 12 control subjects completed the study. The functional images collected during scanning were analyzed using a random-effects model in a restricted set of six regions of interest (ROIs). In addition, the exploratory search in the entire brain volume was performed. RESULTS: The ROI analyses revealed relative underactivation in the region of the left DLPFC and the right cerebellum, as well as overactivation in the left cerebellum. The exploratory whole-brain search exposed additional overactivation in the medial frontal, anterior cingulate, and left parietal cortices. CONCLUSIONS: The present study provides evidence of significant underactivations in stable schizophrenia patients in regions that we have previously observed to be dysfunctional in acutely psychotic and partially remitted patients, together with extensive overactivations in several regions that potentially reflect some compensatory mechanism or increased effort on the working-memory task.
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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 | 0.000 | 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".