Viewers Actively Extract and Maintain Spontaneous Theory of Mind Representations in Dramatic Irony Scenes

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Abstract

Understanding others’ mental states is a cornerstone of human cognition, yet how spontaneousbelief attribution operates in complex, naturalistic perception remains underexplored. Dramaticirony (DI)—a narrative device through which viewers are made aware of crucial informationwhich is unknown to characters of the narrative—provides a controlled but naturalistic contextto examine these processes. Using a curated DI film corpus (Cabañas et al., 2023), wecombined eye-tracking with a Self-Paced Viewing (SPV) paradigm to investigate how SToMshapes real-time processing. In a pre-registered between-subjects study (https://osf.io/by56s),participants viewed edited Harold Lloyd film excerpts that either provided viewers withprivileged information unknown to a character (Installation group) or withheld it to alignviewer and character knowledge (Control group), reflecting false-belief and true-beliefscenarios, respectively. We analysed narrative comprehension, reaction times, and eye-tracking measures indexing cognitive effort and attentional allocation. Results showed that theInstallation group exhibited longer viewing times at moments of representational conflict andlonger overall fixation durations, indicating greater cognitive effort. Gaze analyses revealedselective attention to belief-relevant characters and objects, suggesting top-down controlguided by mental state representations. Extended dwell times on characters’ mouths in theInstallation group further reflected deliberate information seeking. These findings indicate thatviewers spontaneously construct and maintain complex false-belief representations during DIcomprehension, dynamically modulating cognitive processing and attention. By integratingnaturalistic film stimuli with controlled manipulations, this study extends theories of scenecomprehension to include spontaneous mentalizing, offering a tractable model of socialreasoning in dynamic visual contexts.

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