ArticleiScience2026
Atypical integration of temporal evidence and priors in causality judgment along the autism-schizotypy continuum.
Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Psychosocial Interventions, Recovery, and Mediating Mechanisms in Schizophrenia-Spectrum Disorders: A Systematic Review and Meta-Analysis of Longitudinal Studies.Brain sciences · 2026Review
- Placebo and nocebo effects on pain through the lens of the predictive brain: Neurobiological mechanisms and translational implications.Experimental physiology · 2026Review
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Authors and funding
3 authors.
Funding
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Abstract
Perceptual inference arises from integrating sensory evidence with prior knowledge. Causality perception-deciding whether one event causes another-offers a window into this process. We examined how prior experience and individual differences shape causal inference in 150 neurotypical individuals spanning the autism-schizotypy (ASD-SSD) spectrum. Participants judged causality in dynamic collision events with varying temporal delays. Causality judgments were influenced by physical timing (sensory driven) and serial dependence on previous decisions (prior driven). SSD-like individuals showed the strongest serial dependence and ASD-like individuals the weakest. Hierarchical drift diffusion modeling revealed increased causality bias and lower decision thresholds in SSD-like individuals, reflecting a prior-dominated style. ASD-like individuals showed reduced perceptual-history influence and higher thresholds, indicating a sensory-driven approach. Crucially, prior biases and perceptual history were interrelated, suggesting a hierarchical organization of perceptual inference across timescales and linking causality perception to predictive processes shaped by distinct cognitive-perceptual profiles.
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