Brain networks processing temporal information in dynamic facial expressions

Abstract

Acknowledgments:We would like to thank Lucas Tamarit for his help with the FACSGen program. Finally, we are grateful to Prof. Karl Friston for his guidance in the DCM analysis. 2 AbstractPerception of emotional expressions in faces relies on the integration of distinct facial features. We used fMRI to examine the role of local and global motion information in facial movements during exposure to novel dynamic face stimuli. We found that synchronous expressions distinctively engaged medial prefrontal areas in the ventral anterior cingulate cortex (vACC), supplementary premotor areas, and bilateral superior frontal gyrus (global temporal-spatial processing). Asynchronous expressions in which one part of the face (e.g., eyes) unfolded before the other (e.g., mouth) activated more the right superior temporal sulcus (STS) and inferior frontal gyrus (local temporal-spatial processing). DCM analysis further showed that processing of asynchronous expression features was associated with a differential information flow, centered on STS, which received direct input from occipital cortex and projected to the amygdala. Moreover, STS and amygdala displayed selective interactions with vACC where the integration of both local and global motion cues (present in synchronous expressions) could take place. These results provide new evidence for a role of both local and global temporal dynamics in emotional expressions, extracted in partly separate brain pathways. Importantly, we show that dynamic expressions with synchronous movement cues may distinctively engage brain areas responsible for motor execution of expressions.

Levels of naturalism in social neuroscience research

“…Although some studies have observed an uncanny valley effect in humans and monkeys (Saygin et al, 2012;Siebert et al, 2020;Steckenfinger and Ghazanfar, 2009), they do not necessarily negate the validity of using avatars as potential social stimuli. The dip of the uncanny valley curve depends on the stimuli and may be related to ambiguous categorization, less realistic appearance, or asynchronous emotional, motor, and audio cues (Burleigh et al, 2013;Cheetham et al, 2015;Skiba and Vuilleumier, 2020). For example, in macaques, the most naturalistic avatars have been found to elicit similar facial expressions as videos of real monkeys (Siebert et al, 2020).…”