Theory of mind through the lens of algorithms | Andreea Diaconescu | TEDxZurich

This talk was given at a local TEDx event, produced independently of the TED Conferences. Adequate representation of others’ intentions is the cornerstone of social interactions. This is particularly important when we have to make decisions based on someone else’s advice. Using ecologically valid, socially interactive games and mathematical models, we can capture from people’s responses how they learn about others’ intentions and decide to trust their expert advice.

This computational learning “fingerprint” reflects how any given individual builds and refines an internal model of another person. By fitting learning trajectories from this model to neuroimaging data, we captured where learning about socially-relevant information is represented in the brain. Furthermore, we found that individuals with a specific genetic predisposition, which governs the metabolism of the neuromodulator dopamine, represent intentions uniquely in the brain, in particular in situations when trust is broken. By combining neurocomputational models with genetics, I will highlight how we can obtain a deeper understanding of the neural mechanisms underlying social cognition, a domain where many psychiatric disorders are characterized by particularly salient deficiencies.

Andreea Diaconescu (born in 1982 in Craiova, Romania) is a researcher at the Translational Neuromodeling Unit (TNU) of the Institute for Biomedical Engineering, University of Zurich & ETH Zurich. Andreea obtained her PhD in Cognitive Neuroscience at the University of Toronto and led projects at world-renown research institutes, such as Rotman Research Institute and the Center for Addiction and Mental Health in Toronto.

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