Beschreibung
Attention to socially important regions of the face is a key component of daily social interaction and precedes fundamental social skills such as emotion recognition, nonverbal communication and mentalizing. It is also an essential prerequisite to social learning, i. e. when integrating emotional feedback to one’s behavior. Direct eye contact is a salient social signal and, along with the aforementioned social skills, is often found to be atypical in disorders characterized by social impairments such as autism spectrum disorder (ASD). However, studies investigating eye gaze on faces often rely on static picture stimuli, which differ remarkably from real-life social interaction. Here, we developed a novel eye tracking paradigm which uses mobile eye tracking in conjunction with AI face-recognition software, to allow fixations to eyes, mouth and face to be measured during a real-life conversation. Performance in the task was investigated in association to 1) social learning in a reinforcement learning task using point-light-displays (PLD’s) of emotional faces and 2) levels of autistic traits in a neurotypical sample measured by the Autism Spectrum Quotient (AQ). Computational modelling of trial-by-trial responses was used to determine more comprehensively which parameters of learning were modulated by attention to socially relevant regions and autistic traits. With this study, we aim to provide a method to investigate social attention in a more naturalistic context, which will pave the way for more precise and valid studies on social attention and ASD.| Zeitraum | 20 Juli 2022 |
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| Ereignistitel | 6th bi-annual ESCAN meeting: European Society for Cognitive and Affective Neuroscience |
| Veranstaltungstyp | Konferenz |
| Ort | Vienna, ÖsterreichAuf Karte anzeigen |
| Bekanntheitsgrad | International |