In our everyday life we often have to make decisions with uncertain consequences, for instance in the context of investment decisions. To successfully cope with these situations, the nervous system has to be able to estimate, represent, and eventually resolve uncertainty at various levels. An understanding of the biological basis of decision-making under uncertainty is therefore important not only scientifically, but also clinically due to disruptions of decision-making processes in neuropsychiatric disorders.
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We study social decision-making through the lens of game theory, which captures an important class of competitive and cooperative social behavior. Social behavior is often disrupted in disorders such as schizophrenia and frontotemporal dementia. The goals of our research involves characterizing the underlying neural systems as well as molecular and genetic mechanisms.
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A primary goal of our lab is to understand the neural mechanisms underlying choice behavior. We use functional MRI to characterize the neural correlates of putative computational variables driving behavior, as well as testing causal mechanisms using focal lesion studies.

This work is conducted in collaboration with the Knight Lab at University of California, Berkeley.


The common underpinning of our empirical approach is a set of computational models developed out of behavioral economics and computational neuroscience. By providing a mechanistic account of choice behavior, these models provide for rigorous, quantitative predictions that can be tested across behavioral, neural, and genetic levels.


Genes exert their effects on behavior through their effects on the brain. By identifying how genomic variation modifies circuits of neurons and the molecular pathways, we are seeking a better understanding of the neurogenetics of choice behavior.

This work is conducted in collaboration with the B2ESS Lab at the National University of Singapore, and the Kayser Lab at University of California, San Francisco.