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Human social interactions depend on the ability to resolve uncertainty about the mental states of others. The context in which social interactions take place is crucial for mental state attribution as sensory inputs may be perceived differently depending on the context. In this paper, we introduce a mental state attribution task where a target-face with either an ambiguous or an unambiguous emotion is embedded in different social contexts. The social context is determined by the emotions conveyed by other faces in the scene. This task involves mental state attribution to a target-face (either happy or sad) depending on the social context. Using active inference models, we provide a proof of concept that an agent's perception of sensory stimuli may be altered by social context. We show with simulations that context congruency and facial expression coherency improve behavioural performance in terms of decision times. Furthermore, we show through simulations that the abnormal viewing strategies employed by patients with schizophrenia may be due to (i) an imbalance between the precisions of local and global features in the scene and (ii) a failure to modulate the sensory precision to contextualise emotions. [ABSTRACT FROM AUTHOR]

Information gathering comprises actions whose (sensory) consequences resolve uncertainty (i.e., are salient). In other words, actions that solicit salient information cause the greatest shift in beliefs (i.e., information gain) about the causes of our sensations. However, not all information is relevant to the task at hand: this is especially the case in complex, naturalistic scenes. This paper introduces a formal model of selective attention based on active inference and contextual epistemic foraging. We consider a visual search task with a special emphasis on goal-directed and task-relevant exploration. In this scheme, attention modulates the expected fidelity (precision) of the mapping between observations and hidden states in a state-dependent or context-sensitive manner. This ensures task-irrelevant observations have little expected information gain, and so the agent – driven to reduce expected surprise (i.e., uncertainty) – does not actively seek them out. Instead, it selectively samples task-relevant observations, which inform (task-relevant) hidden states. We further show, through simulations, that the atypical exploratory behaviours in conditions such as autism and anxiety may be due to a failure to appropriately modulate sensory precision in a context-specific way. [ABSTRACT FROM AUTHOR]