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TrackingMinds

Financiado

Tracking the decisions of others with the own mind

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 computatio... ver más

30/09/2026

UHAM

1M€

Presupuesto del proyecto: 1M€

Líder del proyecto

UNIVERSITY OF HAMBURG No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Ver 2 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2020-11-30

Línea de financiación objetivo El proyecto se financió a través de la siguiente ayuda:

ERC-2020-STG: ERC STARTING GRANTS

I+D

Cerrada hace 5 años

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2 Participantes

UHAM

1.50M€ | Lider

TEJAS Y LADRILLOS DEL MEDITE...

628.68K€ | Participante

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Últimas noticias

29-11-2024: IDAE En las últimas 48 horas el Organismo IDAE ha otorgado 4 concesiones

29-11-2024: ECE En las últimas 48 horas el Organismo ECE ha otorgado 2 concesiones

29-11-2024: CMVAMADRID En las últimas 48 horas el Organismo CMVAMADRID ha otorgado 37 concesiones

Duración del proyecto: 70 meses Fecha Inicio: 2020-11-30
Fecha Fin: 2026-09-30

Líder del proyecto

UNIVERSITY OF HAMBURG

TRL 4-5

Presupuesto del proyecto 1M€

Descripción del proyecto 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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