An EEG-based real-time cortical functional connectivity imaging system.

In the present study, we introduce an EEG-based, real-time, cortical functional connectivity imaging system capable of monitoring and tracing dynamic changes in cortical functional connectivity between different regions of interest (ROIs) on the brain cortical surface. The proposed system is based o...

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Published in:Medical & Biological Engineering & Computing Vol. 49; no. 9; pp. 985 - 996
Main Authors: Hwang HJ, Kim KH, Jung YJ, Kim DW, Lee YH, Im CH, Hwang, Han-Jeong, Kim, Kyung-Hwan, Jung, Young-Jin, Kim, Do-Won, Lee, Yong-Ho, Im, Chang-Hwan
Format: research Journal Article
Published: Springer Nature Sep2011
Online Access:View this record in EBSCOhost
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      dt: Sep2011
      vid: 49
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      pub: Springer Nature
      place: New York, New York
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        atl: An EEG-based real-time cortical functional connectivity imaging system.
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          Hwang HJ
          Kim KH
          Jung YJ
          Kim DW
          Lee YH
          Im CH
          Hwang, Han-Jeong
          Kim, Kyung-Hwan
          Jung, Young-Jin
          Kim, Do-Won
          Lee, Yong-Ho
          Im, Chang-Hwan
        affil: Department of Biomedical Engineering, Hanyang University, 17 Haengdang-dong, Seongdong-gu, Seoul 133-791, South Korea
      sug:
        subj:
          Cerebral Cortex Physiology
          Electroencephalography Methods
          Neural Pathways Physiology
          Adult
          Brain Mapping Methods
          Pilot Studies
          Male
          Signal Processing, Computer Assisted
          Young Adult
          Adult: 19-44 years
          Male
      ab: In the present study, we introduce an EEG-based, real-time, cortical functional connectivity imaging system capable of monitoring and tracing dynamic changes in cortical functional connectivity between different regions of interest (ROIs) on the brain cortical surface. The proposed system is based on an EEG-based dynamic neuroimaging system, which is capable of monitoring spatiotemporal changes of cortical rhythmic activity at a specific frequency band by conducting real-time cortical source imaging. To verify the implemented system, we performed three test experiments in which we monitored temporal changes in cortical functional connectivity patterns in various frequency bands during structural face processing, finger movements, and working memory task. We also traced the changes in the number of connections between all possible pairs of ROIs whose correlations exceeded a predetermined threshold. The quantitative analysis results were consistent with those of previous off-line studies, thereby demonstrating the possibility of imaging cortical functional connectivity in real-time. We expect our system to be applicable to various potential applications, including real-time diagnosis of psychiatric diseases and EEG neurofeedback.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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