Descrizione del progetto
Studiare la capacità umana di comprendere le azioni altrui
Nonostante i notevoli progressi compiuti nelle neuroscienze cognitive e nelle discipline correlate, manca un modello plausibile a livello informatico e neurobiologico per l’interpretazione umana del comportamento delle altre persone. Il progetto TrackingMinds, finanziato dall’UE, implementerà un approccio multimodale e matematicamente accurato per fare luce sulla capacità mentale degli esseri umani di seguire il pensiero altrui e di dedurne convinzioni e preferenze. TrackingMinds concentrerà l’attenzione sul modo in cui osserviamo gli altri, nonché su come prevediamo le loro decisioni e impariamo da esse. Inoltre, il progetto intende contribuire allo sviluppo di sistemi di intelligenza artificiale più interattivi, alle previsioni di equilibrio nella teoria economica e persino ad approcci innovativi per combattere le difficoltà sociali nella malattia mentale.
Obiettivo
A core research question in cognitive neuroscience and many other disciplines is to understand how humans interpret the behavior of others. Despite the plethora of empirical work on human Theory of Mind, we still lack a computationally and neurobiologically plausible model. The goal of the current project is to fill this gap by leveraging our extensive knowledge of decision making, which has been formalized as a process of evidence accumulation. Thus, my central hypothesis is that humans utilize their own evidence-accumulation machinery to track others’ minds and to infer their hidden beliefs and preferences. Importantly, my theory goes far beyond previous accounts (e.g. the mirror neuron system), as it specifies not only how we observe others, but also how we predict and learn from their decisions.
I will subject this hypothesis to a series of studies that test its behavioral, physiological and neurobiological implications. Thereto, I will employ cutting-edge cognitive neuroscience tools, including cognitive modeling, eye tracking, functional magnetic resonance imaging, and electroencephalography (EEG). Moreover, I will use EEG hyperscanning to probe the synchronization of brain signals related to evidence accumulation in interacting people. Finally, I will develop a multi-agent artificial intelligence (AI) system that can infer the hidden beliefs of other agents on the basis of their decision processes. I will then show that this AI system provides superior performance in coordinating its actions with human partners.
The multi-modal and mathematically rigorous approach of TrackingMinds will advance our understanding of human mentalizing abilities profoundly. Thereby, it will stimulate further research and applications. First, it can help to devise better interactive AI systems. Second, it has strong implications for equilibrium predictions in economic theory. Third, it can foster new interventions of social mental disorders such as autism and social anxiety.
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Meccanismo di finanziamento
ERC-STG - Starting GrantIstituzione ospitante
20148 Hamburg
Germania