The team combined computational models with brain imaging to map the processes that support continuous updating of others’ mental states. Computational approaches let researchers test precise hypotheses about what information people track and how much weight they give to new evidence. Neuroimaging reveals where in the brain those computations happen, and how neural systems flexibly coordinate when social signals are ambiguous or surprising.
Why this matters for human potential is straightforward. Learning how our brains adapt to shifting social information can improve education, teamwork, and tools that support people with social learning challenges. The study opens pathways to design interventions and technologies that help people stay attuned to changing intentions in real time. Follow the full article to see which brain circuits and computational rules the authors identified and how those findings could reshape support for social learning and inclusion.
‘Theory of mind’ (ToM) is classically investigated with ‘static’ inference tasks, which miss the dynamic nature of social interactions. In a recent article, Buergi, Aydogan, and colleagues combined computational modeling and neuroimaging to study the adaptive nature of mentalization (i.e., the ability to infer the continuous change of others’ thoughts and intentions).
