Symptom severity is associated with leftward lateralization upon contextual modulation of visual vertical in patients with schizophrenia
Bibliographic record
Abstract
Background Contextual processing dysfunction in patients with schizophrenia (SCZ) is not uniform and task-dependent. In SCZ, studies on the rod and frame test (RFT), which evaluates contextual modulation of verticality perception, are sparse. A main study that utilized a two-alternative forced choice design for judging rod verticality reported equivalent strength of RFT contextual modulation in healthy controls and SCZ. The current study aims to uncover any potential differences in contextual modulation between controls and SCZ with an adjustment method on a computerized RFT. Materials and methods A total of 17 healthy controls and 15 SCZ aligned an oriented rod to their perceived vertical with a computer mouse under four randomized frame presentations: absent frame, non-tilted (Frame 0° ), or tilted by 18 degrees leftward (Frame –18° ) or rightward (Frame +18° ). Rod deviation error was assigned a negative or positive value when aligned leftward or rightward, respectively, of 0°. Signed and absolute errors, the rod and frame effect (RFE), and intra-individual variability (inconsistency) were used for analysis. Results There was no group difference in rod alignment errors or derived measures, except that SCZ displayed greater inconsistency in rod alignment, compared to controls. The negative symptom scale (PANSS-N) scores correlated positively with the variability measure and with unsigned Frame –18° error. Conclusions Only the variability measure was sensitive enough to distinguish between controls and SCZ. SCZ with more severe negative symptoms had larger variability in rod alignment, probably reflecting a state of indifference. The larger deviation errors only with a leftward tilted frame, as PANSS-N scores increased, may indicate a lateralized attentional abnormality that is correlated with severity of symptoms in SCZ.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".