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 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.

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This work was supported in part by the KRISS-WCL project (Development of Measurement Technology for Cognitive Process) and in part by the Original Technology Research Program for Brain Science through the National Research Foundation of Korea (NRF) grant funded by the Ministry of Education, Science and Technology (No. 2010-0018840)

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Correspondence to Chang-Hwan Im.

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H-.J. Hwang and K.-H. Kim are co-first authors and contributed equally to this work.

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Hwang, H., Kim, K., Jung, Y. et al. An EEG-based real-time cortical functional connectivity imaging system. Med Biol Eng Comput 49, 985–995 (2011) doi:10.1007/s11517-011-0791-6

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  • Electroencephalography (EEG)
  • Functional connectivity
  • Real-time neuroimaging
  • Diagnosis of psychiatric diseases
  • Inverse problems