Integrating high-density ERP and fMRI measures of face-elicited brain activity in 9–12-year-old children: An ERP source localization study

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Abstract

Social information processing is a critical mechanism underlying children's socio-emotional development. Central to this process are patterns of activation associated with one of our most salient socioemotional cues, the face. In this study, we obtained fMRI activation and high-density ERP source data evoked by parallel face dot-probe tasks from 9-to-12-year-old children. We then integrated the two modalities of data to explore the neural spatial-temporal dynamics of children's face processing. Our results showed that the tomography of the ERP sources broadly corresponded with the fMRI activation evoked by the same facial stimuli. Further, we combined complementary information from fMRI and ERP by defining fMRI activation as functional ROIs and applying them to the ERP source data. Indices of ERP source activity were extracted from these ROIs at three a priori ERP peak latencies critical for face processing. We found distinct temporal patterns among the three time points across ROIs. The observed spatial-temporal profiles converge with a dual-system neural network model for face processing: a core system (including the occipito-temporal and parietal ROIs) supports the early visual analysis of facial features, and an extended system (including the paracentral, limbic, and prefrontal ROIs) processes the socio-emotional meaning gleaned and relayed by the core system. Our results for the first time illustrate the spatial validity of high-density source localization of ERP dot-probe data in children. By directly combining the two modalities of data, our findings provide a novel approach to understanding the spatial-temporal dynamics of face processing. This approach can be applied in future research to investigate different research questions in various study populations.

Original languageEnglish (US)
Pages (from-to)599-608
Number of pages10
JournalNeuroImage
Volume184
DOIs
StatePublished - Jan 1 2019

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Magnetic Resonance Imaging
Brain
Information Storage and Retrieval
Neural Networks (Computer)
Automatic Data Processing
Cues
Tomography
Research
Population

All Science Journal Classification (ASJC) codes

  • Neurology
  • Cognitive Neuroscience

Cite this

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title = "Integrating high-density ERP and fMRI measures of face-elicited brain activity in 9–12-year-old children: An ERP source localization study",
abstract = "Social information processing is a critical mechanism underlying children's socio-emotional development. Central to this process are patterns of activation associated with one of our most salient socioemotional cues, the face. In this study, we obtained fMRI activation and high-density ERP source data evoked by parallel face dot-probe tasks from 9-to-12-year-old children. We then integrated the two modalities of data to explore the neural spatial-temporal dynamics of children's face processing. Our results showed that the tomography of the ERP sources broadly corresponded with the fMRI activation evoked by the same facial stimuli. Further, we combined complementary information from fMRI and ERP by defining fMRI activation as functional ROIs and applying them to the ERP source data. Indices of ERP source activity were extracted from these ROIs at three a priori ERP peak latencies critical for face processing. We found distinct temporal patterns among the three time points across ROIs. The observed spatial-temporal profiles converge with a dual-system neural network model for face processing: a core system (including the occipito-temporal and parietal ROIs) supports the early visual analysis of facial features, and an extended system (including the paracentral, limbic, and prefrontal ROIs) processes the socio-emotional meaning gleaned and relayed by the core system. Our results for the first time illustrate the spatial validity of high-density source localization of ERP dot-probe data in children. By directly combining the two modalities of data, our findings provide a novel approach to understanding the spatial-temporal dynamics of face processing. This approach can be applied in future research to investigate different research questions in various study populations.",
author = "Pan Liu and Xiaoxiao Bai and P{\'e}rez-Edgar, {Koraly E.}",
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AB - Social information processing is a critical mechanism underlying children's socio-emotional development. Central to this process are patterns of activation associated with one of our most salient socioemotional cues, the face. In this study, we obtained fMRI activation and high-density ERP source data evoked by parallel face dot-probe tasks from 9-to-12-year-old children. We then integrated the two modalities of data to explore the neural spatial-temporal dynamics of children's face processing. Our results showed that the tomography of the ERP sources broadly corresponded with the fMRI activation evoked by the same facial stimuli. Further, we combined complementary information from fMRI and ERP by defining fMRI activation as functional ROIs and applying them to the ERP source data. Indices of ERP source activity were extracted from these ROIs at three a priori ERP peak latencies critical for face processing. We found distinct temporal patterns among the three time points across ROIs. The observed spatial-temporal profiles converge with a dual-system neural network model for face processing: a core system (including the occipito-temporal and parietal ROIs) supports the early visual analysis of facial features, and an extended system (including the paracentral, limbic, and prefrontal ROIs) processes the socio-emotional meaning gleaned and relayed by the core system. Our results for the first time illustrate the spatial validity of high-density source localization of ERP dot-probe data in children. By directly combining the two modalities of data, our findings provide a novel approach to understanding the spatial-temporal dynamics of face processing. This approach can be applied in future research to investigate different research questions in various study populations.

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