Frontiers in Neuroscience (May 2017)

Revealing the Dysfunction of Schematic Facial-Expression Processing in Schizophrenia: A Comparative Study of Different References

  • Shenglin She,
  • Haijing Li,
  • Yuping Ning,
  • Jianjuan Ren,
  • Zhangying Wu,
  • Rongcheng Huang,
  • Jingping Zhao,
  • Jingping Zhao,
  • Qian Wang,
  • Yingjun Zheng

DOI
https://doi.org/10.3389/fnins.2017.00314
Journal volume & issue
Vol. 11

Abstract

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The use of event-related potential (ERP) recording technology during perceptual and cognitive processing has been studied in order to develop objective diagnostic indexes for people with neuropsychiatric disorders. For example, patients with schizophrenia exhibit consistent abnormalities in face-evoked early components of ERPs and mismatch negativities (MMNs). In most studies, the choice of reference has been the average reference (AVE), but whether this is the most suitable choice is still unknown. The aim of this study was to systematically compare the AVE and reference electrode standardization technique (REST) methods for assessing expressional face-evoked early visual ERPs and visual MMNs (vMMNs) in patients with schizophrenia and healthy controls. The results showed that both the AVE and REST methods could: (1) obtain primary visual-evoked ERPs in the two groups, (2) reveal the neutral and emotional expression discrimination deficit of the P1 component in the patients, which was normal in the healthy controls, (3) reflect reductions of happy vMMNs in the patients compared to the healthy controls, and (4) show right-dominant sad vMMNs only in the patients. On the other hand, compared to the energy distributions of the AVE-obtained potentials, those of REST-obtained early visual ERPs and vMMNs were more concentrated around the temporo-occipital areas. Furthermore, only the REST-obtained vMMNs revealed a significant difference between happy and sad mismatch stimuli in patients with schizophrenia. These results demonstrate that REST technology might provide new insights into neurophysiological factors associated with neuropsychiatric disorders.

Keywords