Improving causality perception judgments in schizophrenia spectrum disorder via transcranial direct current stimulation
Bibliographic record
Abstract
BACKGROUND: Deficient causality perception and attribution may underlie key symptoms of schizophrenia spectrum disorder (SSD), such as delusions and ideas of reference. Although transcranial direct current stimulation (tDCS) can increase the influence of spatial information on perceptual causality judgments among healthy participants, its effect among patients with SSD remains unknown. We sought to determine whether tDCS modulates the contribution of stimulus characteristics to perceptual causality judgments among patients with SSD; we predicted that right parietal tDCS would increase the influence of spatial stimulus characteristics on patients' causality perception. METHODS: Patients with SSD received frontal, parietal, frontoparietal and sham tDCS in 4 separate sessions. Pre- and post-tDCS, patients viewed video clips of ball A colliding with ball B. Spatial linearity (ball B's angle of egress) and temporal contiguity (delay between collision and ball B's movement) varied parametrically. After each launching event, patients rated perceived causality. RESULTS: Among 19 patients with SSD, we found a brain region-dependent effect of tDCS regarding sensitivity to violations of spatial linearity. After right parietal anodal tDCS, the influence of angle variations on patients' perceptual causality judgments increased, reflected by a higher probability of perceived causality for stimuli with small angles and a lower probability of perceived causality for stimuli with high angles. CONCLUSION: Transcranial direct current stimulation increased the influence of spatial stimulus characteristics on causality perception among patients with SSD. Future research should explore potential links between tDCS-induced changes in basic perceptual processes and clinical symptoms, such as delusions and ideas of reference.
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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) | 0.001 | 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".