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Journal Articles Scientific Reports Year : 2017

Neural coding of prior expectations in hierarchical intention inference


The ability to infer other people's intentions is crucial for successful human social interactions. Such inference relies on an adaptive interplay of sensory evidence and prior expectations. Crucially, this interplay would also depend on the type of intention inferred, i.e., on how abstract the intention is. However, what neural mechanisms adjust the interplay of prior and sensory evidence to the abstractness of the intention remains conjecture. We addressed this question in two separate fMRI experiments, which exploited action scenes depicting different types of intentions (Superordinate vs. Basic; Social vs. Non-social), and manipulated both prior and sensory evidence. We found that participants increasingly relied on priors as sensory evidence became scarcer. Activity in the medial prefrontal cortex (mPFC) reflected this interplay between the two sources of information. Moreover, the more abstract the intention to infer (Superordinate > Basic, Social > Non-Social), the greater the modulation of backward connectivity between the mPFC and the temporo-parietal junction (TPJ), resulting in an increased influence of priors over the intention inference. These results suggest a critical role for the fronto-parietal network in adjusting the relative weight of prior and sensory evidence during hierarchical intention inference.
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hal-03041336 , version 1 (04-12-2020)



Valerian Chambon, Philippe Domenech, Pierre Jacquet, Guillaume Barbalat, Sophie Bouton, et al.. Neural coding of prior expectations in hierarchical intention inference. Scientific Reports, 2017, 7 (1), pp.1278. ⟨10.1038/s41598-017-01414-y⟩. ⟨hal-03041336⟩
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