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  Face processing regions are sensitive to distinct aspects of temporal sequence in facial dynamics

Reinl, M., & Bartels, A. (2014). Face processing regions are sensitive to distinct aspects of temporal sequence in facial dynamics. NeuroImage, 102(2), 407-415. doi:10.1016/j.neuroimage.2014.08.011.

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Reinl, M1, 2, Author              
Bartels, A1, 2, Author              
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1Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: Facial movement conveys important information for social interactions, yet its neural processing is poorly understood. Computational models propose that shape- and temporal sequence sensitive mechanisms interact in processing dynamic faces. While face processing regions are known to respond to facial movement, their sensitivity to particular temporal sequences has barely been studied. Here we used fMRI to examine the sensitivity of human face-processing regions to two aspects of directionality in facial movement trajectories. We presented genuine movie recordings of increasing and decreasing fear expressions, each of which were played in natural or reversed frame order. This two-by-two factorial design matched low-level visual properties, static content and motion energy within each factor, emotion-direction (increasing or decreasing emotion) and timeline (natural versus artificial). The results showed sensitivity for emotion-direction in FFA, which was timeline-dependent as it only occurred within the natural frame order, and sensitivity to timeline in the STS, which was emotion-direction-dependent as it only occurred for decreased fear. The occipital face area (OFA) was sensitive to the factor timeline. These findings reveal interacting temporal sequence sensitive mechanisms that are responsive to both ecological meaning and to prototypical unfolding of facial dynamics. These mechanisms are temporally directional, provide socially relevant information regarding emotional state or naturalness of behavior, and agree with predictions from modeling and predictive coding theory.

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 Dates: 2014-11
 Publication Status: Published in print
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 Identifiers: DOI: 10.1016/j.neuroimage.2014.08.011
BibTex Citekey: ReinlB2014
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Title: NeuroImage
Source Genre: Journal
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Pages: - Volume / Issue: 102 (2) Sequence Number: - Start / End Page: 407 - 415 Identifier: -