September 2017
Volume 17, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   August 2017
Neurodynamics of reading crowd emotion: Independent visual pathways and hemispheric contributions
Author Affiliations
  • Hee Yeon Im
    Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
    Department of Radiology, Harvard Medical School, Boston, MA, USA
  • Cody Cushing
    Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
  • Daniel Albohn
    Department of Psychology, The Pennsylvania State University, State College, PA, USA
  • Troy Steiner
    Department of Psychology, The Pennsylvania State University, State College, PA, USA
  • Noreen Ward
    Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
  • Reginald Adams, Jr.
    Department of Psychology, The Pennsylvania State University, State College, PA, USA
  • Kestutis Kveraga
    Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
    Department of Radiology, Harvard Medical School, Boston, MA, USA
Journal of Vision August 2017, Vol.17, 261. doi:10.1167/17.10.261
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      Hee Yeon Im, Cody Cushing, Daniel Albohn, Troy Steiner, Noreen Ward, Reginald Adams, Jr., Kestutis Kveraga; Neurodynamics of reading crowd emotion: Independent visual pathways and hemispheric contributions. Journal of Vision 2017;17(10):261. doi: 10.1167/17.10.261.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Introduction: The visual system exploits redundancies by extracting summary statistics from groups of similar items. In social situations, extracting average emotion from crowds of faces helps us to avoid potential threats (e.g., mob violence or panic). We conducted fMRI, MEG, and behavioral experiments to investigate contributions of magnocellular (M) and parvocellular (P) visual pathways, and of hemispheric lateralization in reading of crowd emotion. Methods: Participants in fMRI (N=32), MEG (N=38), and behavioral (N=36) experiments were presented bilaterally with either arrays of faces or single faces with varying emotional expressions. Participants performed a 2AFC task as to which facial crowd, or single face comparison to avoid. In the behavioral experiment, the original stimuli were converted to M-biased (low-luminance contrast) or P-biased (isoluminant chromatic) stimuli to isolate visual field contributions. Results: fMRI and MEG results revealed that reading crowd emotion evoked highly lateralized activations along the dorsal stream, including the prefrontal and parietal cortex. Conversely, individual emotion processing activated the ventral stream, including the FFA. MEG activity in the precuneus (dorsal stream) differentially increased for facial crowds from 180 ms after stimulus onset, indicating early engagement of M-pathway, whereas the FFA (ventral stream) showed higher activation for individual faces 200 ms after stimulus onset. Furthermore, we found goal-dependent hemispheric asymmetry for crowd emotion processing: the right hemisphere was superior for task-congruent (e.g., angry crowd to avoid) decisions and the left hemisphere for processing task-incongruent cues (e.g., happy crowd). However, the right hemisphere was superior for individual emotion processing regardless of task demands. Finally, in the behavioral task, we found crowd emotion extraction to be more accurate from M- than P-stimuli, and observed goal-dependent hemispheric asymmetry only for M-stimuli. Conclusion: Unlike individual emotion processing, reading crowd emotion is predominantly carried out by the M/dorsal stream, with the right hemisphere superiority for task-congruent decisions.

Meeting abstract presented at VSS 2017

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