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Risky choice entails a need to appraise all possible outcomes and integrate this information with individual risk preference. Risk is frequently quantified solely by statistical variance of outcomes, but here we provide evidence that individuals' choice behaviour is sensitive to both dispersion (variance) and asymmetry (skewness) of outcomes. Using a novel behavioural paradigm in humans, we independently manipulated these 'summary statistics' while scanning subjects with fMRI. We show that a behavioural sensitivity to variance and skewness is mirrored in neuroanatomically dissociable representations of these quantities, with parietal cortex showing sensitivity to the former and prefrontal cortex and ventral striatum to the latter. Furthermore, integration of these objective risk metrics with subjective risk preference is expressed in a subject-specific coupling between neural activity and choice behaviour in anterior insula. Our findings show that risk is neither monolithic from a behavioural nor neural perspective and its decomposition is evident both in distinct behavioural preferences and in segregated underlying brain representations.

Original publication




Journal article



Publication Date





1139 - 1149


Adult, Algorithms, Brain, Choice Behavior, Corpus Striatum, Decision Making, Female, Gambling, Humans, Image Processing, Computer-Assisted, Individuality, Linear Models, Magnetic Resonance Imaging, Male, Models, Psychological, Models, Statistical, Parietal Lobe, Prefrontal Cortex, Psychomotor Performance, Risk-Taking, Young Adult