Aberrant uncertainty processing is linked to psychotic‑like experiences, autistic traits, and is reflected in pupil dilation during probabilistic learning
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https://hdl.handle.net/10037/29059Date
2023-03-28Type
Journal articleTidsskriftartikkel
Peer reviewed
Author
Kreis, Isabel; Zhang, Lei; Mittner, Matthias Bodo; Syla, Leonard Parks; Claus, Lamm; Pfuhl, GeritAbstract
Aberrant belief updating due to misestimation of uncertainty and an increased perception of the world as volatile (i.e.,
unstable) has been found in autism and psychotic disorders. Pupil dilation tracks events that warrant belief updating, likely reflecting the adjustment of neural gain. However, whether subclinical autistic or psychotic symptoms affect this adjustment and how they relate to learning in volatile environments remains to be unraveled. We investigated the relationship between behavioral and pupillometric markers of subjective volatility (i.e., experience of the world as unstable), autistic traits, and psychotic-like experiences in 52 neurotypical adults with a probabilistic reversal learning task. Computational modeling revealed that participants with higher psychotic-like experience scores overestimated volatility in low-volatile task periods. This was not the case for participants scoring high on autistic-like traits, who instead showed a diminished adaptation of choice-switching behavior in response to risk. Pupillometric data indicated that individuals with higher autistic- or psychotic-like trait and experience scores differentiated less between events that warrant belief updating and those that do not when volatility was high. These findings are in line with misestimation of uncertainty accounts of psychosis and autism spectrum disorders and indicate that aberrancies are already present at the subclinical level.
Publisher
SpringerCitation
Kreis IV, Zhang L, Mittner M, Syla S, Claus, Pfuhl G. Aberrant uncertainty processing is linked to psychotic‑like experiences, autistic traits, and is reflected in pupil dilation during probabilistic learning. Cognitive, Affective, & Behavioral Neuroscience. 2023Metadata
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