September 2015
Volume 15, Issue 12
Vision Sciences Society Annual Meeting Abstract  |   September 2015
Neural correlates of processing elastic moving faces: A functional near-infrared spectroscopy (fNIRS) study
Author Affiliations
  • Naiqi Xiao
    University of Toronto
  • Qiandong Wang
    Zhejiang Normal University
  • Guowei Chen
    Zhejiang Normal University
  • Genyue Fu
    Zhejiang Normal University
  • Kang Lee
    University of Toronto
Journal of Vision September 2015, Vol.15, 425. doi:
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      Naiqi Xiao, Qiandong Wang, Guowei Chen, Genyue Fu, Kang Lee; Neural correlates of processing elastic moving faces: A functional near-infrared spectroscopy (fNIRS) study. Journal of Vision 2015;15(12):425.

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

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Recent behavioral studies showed that moving faces optimize face processing efficiency by facilitating part-based face processing as opposed to static faces (Xiao et al., 2012 & 2013). However, the mechanism of this facial movement facilitation effect is less clear. This study using functional near-inferred spectroscopy (fNIRS) methodology explored the neural mechanisms underlying this moving face effect. Thirty-one adults participated in the current study. The classic Composite Face Effect was used to examine holistic versus part-based face processing. In the dynamic condition, participants first learned a 2-second silent moving face video, depicting chewing and blinking movements in the learning phase. In the testing phase, a static composite face was presented. The test face consisted of upper and lower face halves from different people, displayed either aligned or misaligned. Participants decided whether the upper half was the same person as the one they just learned. The static condition was identical to the dynamic one, except that the learned faces were static pictures. NIRS data were acquired in the temporal and occipital regions. A functional connectivity analysis indicated that learning moving faces led to significantly more positive and negative functional connectivities between brain regions than learning static faces. GLM results revealed a significant greater cortical [deoxy-Hb] response in the middle temporal gyrus for watching moving faces than static faces. In addition, learning moving faces led to decreased [deoxy-Hb] responses to process aligned composite faces (beta = -0.08) but increased responses to misaligned composite faces (beta = 0.11). However, static faces led to similar amount of [deoxy-Hb] activation for aligned (beta = 0.08) and misaligned composite faces (beta = 0.06). This face motion effect in neural activities suggests that facial movement might exert a top-down influence on the primary visual cortex by inhibiting holistic processing when viewing aligned composite faces.

Meeting abstract presented at VSS 2015


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