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How do people sample and weight information when they make decisions? We ask this question for both simple (e.g., perceptual) and complex (e.g., multiattribute, risky) decisions.


Human decisions exhibit intriguing patterns –including biases and irrational preference reversals – that are barely understood in mechanistic terms. We aspire to do so at various levels (computational, algorithmic, neural) and to provide neurophysiologically grounded insights on human decision-making.

Decisions entail complex information and engage multiple cognitive and neural processes. Thus, understanding human decisions in information processing terms is elusive. This is why we study human decisions using elaborate experimental techniques (such as cognitive psychophysics, pharmacological manipulations & MEG) that allow us to trace the flow of decision-related quantities, and the transformations they undergo, as decisions take shape. We combine experimental data with computational modelling to unveil the general principles governing human decisions.



We aspire to make our curiosity-driven, blue-skies research societally relevant. We strive to elucidate big open questions in the cognitive & decision sciences at multiple levels: from the level of neurotransmitters, to large-scale brain networks, to cognitive mechanisms, to behaviour. Our insights can inform clinical practice, by shedding new light on how information processing & decision behaviour go awry in neuropsychiatric disorders; and help revolutionise applied behavioural science by offering mechanistic lenses to understand, predict and foster behavioural change.


We are keen to understand how lab-based insights play out in real-world situations. We are thus interested in extending our research to naturalistic & natural settings. 

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