Early Visual Processing Is Associated With Social Cognitive Performance in Recent-Onset Schizophrenia
Bibliographic record
Abstract
Background: Early-stage visual processing deficits are evident in chronic schizophrenia. Consistent with a cascade model of information processing, whereby early perceptual processes have downstream effects on higher-order cognition, impaired visual processing is associated with deficits in social cognition in this clinical population. However, the nature of this relationship in the early phase of illness is unknown. Here, we present data from a study of early visual processing and social cognitive performance in recent-onset schizophrenia (ROSz). Method: Thirty-two people with ROSz and 20 healthy controls (HC) completed a visual backward masking task using stimuli of real world objects (Object Masking) to assess early-stage (i.e., 0 - 125 ms post-stimulus onset) visual processing. Subjects also completed two tasks of social cognition, one assessing relatively low-level processes of emotion identification (Emotion Biological Motion, EmoBio), and another assessing more complex, higher-order theory of mind abilities (The Awareness of Social Inference Test, TASIT). Group differences were tested with repeated measures ANOVAs and t-tests. Bivariate correlations tested the strength of associations between early-stage visual processing and social cognitive performance in ROSz. Results: For Object Masking, the mask interfered with object identification over a longer interval for ROSz than for HC [F (3.01, 150.57) = 3.04, p = 0.03]. ROSz were less accurate on the EmoBio task [t (50) = -3.36, p = 0.001] and on the TASIT compared to HC [F (1, 50) = 38.37, p < 0.001]. For the TASIT ROSz were disproportionately impaired on items assessing sarcasm detection [F (1, 50) = 4.30, p = 0.04]. In ROSz, better Object Masking performance was associated with better social cognitive performance [r EmoBio = 0.45, p < 0.01; r TASIT = 0.41, p < 0.02]. Conclusion: Early-stage visual processing, low-level social cognition, and high-level social cognition were all significantly impaired in ROSz. Early-stage visual processing was associated with performance on the social cognitive tasks in ROSz, consistent with a cascade model of information processing. These data suggest that interventions directed at early visual processing may yield downstream effects on social cognitive processes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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".