Biological motion perception among persons with schizophrenia
Bibliographic record
Abstract
People with schizophrenia (SCZ) show alterations in several domains of visual processing, including visual motion processing. However, less is known about biological motion perception among persons with SCZ. Such knowledge is important because humans utilize biological motion for understanding socio-emotional aspects (e.g., intentions) of actors in their environment and people with SCZ are well known to have deficiencies in this area. In the current study, groups of healthy community based controls (N = 20) and patients with SCZ (N = 16) were asked to discriminate the direction of motion of four types of point-light walkers: upright normal walkers, inverted normal walkers, upright scrambled walkers (which contained only local motion information), and upright random-position walkers (which contained only global form information). Normal and inverted walkers were also presented in a dynamic random noise mask. Both groups of observers were able to accurately discriminate the direction of motion of normal and inverted walkers when presented without the mask. However, performance in SCZ participants was significantly lower than that of healthy observers when the stimuli were presented in the mask. Additionally, although both healthy and SCZ participants performed accurately when observing random position walkers, both groups also performed less accurately when observing scrambled walkers. The results suggest that, like healthy observers, people with SCZ rely more on global form rather than local motion in making direction discriminations of biological motion. These results also suggest that people with SCZ are able to discriminate the direction of biological motion of normal and inverted walkers; however, they are less efficient than healthy observers at extracting the relevant motion signal from noise, consistent with the notion that people with SCZ suffer from more noisy perceptual systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.004 | 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 teacher head, 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".