The preference for surprise in reinforcement learning underlies the differences in developmental changes in risk preference between autistic and neurotypical youth.
Motofumi Sumiya, Kentaro Katahira, Hironori Akechi and 1 others
PMID 39819491WHAT IT FOUND
Autistic and non-autistic people aged 6 to 30 did not differ overall in choosing risky options.
Their age pattern differed: non-autistic participants tended to choose risky options more in adolescence then less; autistic participants tended to choose them less in adolescence then more.
Key findings
01There was no significant overall difference between autistic and non-autistic participants in risk preference.
02The way risk preference changed with age differed significantly between groups.
03A model that changes the value of outcomes based on how surprising they were was the most common best-fitting model (42% autistic, 41% non-autistic), and its surprise measure showed a significant age-by-group interaction.
STILL TO COME
How it was doneWhat they found
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What it does not show
The final analysis included 75 participants, although 125 participants completed the task, because many were excluded for not engaging with the task or low accuracy. Participants completed the task at home during the pandemic on computers or tablets, so the environment and device varied. Autistic and non-autistic groups differed in age and IQ, and IQ was not measured directly for all participants. Risk preference was measured in a game-like treasure task, not everyday risky behaviour or clinical outcomes. The study used cross-sectional data, so it cannot show how risk preference changes within the same person over time.
Declared interests
Funded by the Japan Society for the Promotion of Science. The supplied text does not report other author conflicts of interest.
The easy way to misread this
Do not conclude that autistic young people are generally more or less risk-averse than non-autistic young people. The overall group difference was not significant, and the age-related curves and surprise model come from a cross-sectional game-like task, not from everyday behaviour or treatment outcomes.