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Related Experiment Video

Updated: May 31, 2026

Recording Human Electrocorticographic (ECoG) Signals for Neuroscientific Research and Real-time Functional Cortical Mapping
13:32

Recording Human Electrocorticographic (ECoG) Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Published on: June 26, 2012

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

Han-Jeong Hwang1, Kyung-Hwan Kim, Young-Jin Jung

  • 1Department of Biomedical Engineering, Hanyang University, 17 Haengdang-dong, Seongdong-gu, Seoul 133-791, South Korea.

Medical & Biological Engineering & Computing
|June 25, 2011
PubMed
Summary
This summary is machine-generated.

We developed a novel real-time system using electroencephalography (EEG) to image dynamic cortical functional connectivity. This breakthrough allows for immediate monitoring of brain network changes, advancing neuroscience research and clinical applications.

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Related Experiment Videos

Last Updated: May 31, 2026

Recording Human Electrocorticographic (ECoG) Signals for Neuroscientific Research and Real-time Functional Cortical Mapping
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Recording Human Electrocorticographic (ECoG) Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Published on: June 26, 2012

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging
11:28

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

Published on: June 30, 2018

Neuroimaging-Guided TMS–EEG for Real-Time Cortical Network Mapping
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Neuroimaging-Guided TMS–EEG for Real-Time Cortical Network Mapping

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Cortical functional connectivity analysis is crucial for understanding brain function.
  • Existing methods often rely on offline processing, limiting real-time insights.
  • Dynamic monitoring of brain networks is essential for various neurological and psychiatric conditions.

Purpose of the Study:

  • To introduce and validate an electroencephalography (EEG)-based system for real-time cortical functional connectivity imaging.
  • To monitor and trace dynamic changes in functional connectivity between brain regions of interest (ROIs).
  • To demonstrate the system's capability in capturing spatiotemporal alterations in cortical rhythmic activity.

Main Methods:

  • Development of an EEG-based dynamic neuroimaging system.
  • Real-time cortical source imaging to monitor rhythmic activity in specific frequency bands.
  • Quantitative analysis of temporal changes in functional connectivity patterns during cognitive tasks.

Main Results:

  • The system successfully monitored dynamic changes in cortical functional connectivity during face processing, finger movements, and working memory tasks.
  • Analysis revealed temporal shifts in connectivity patterns across different frequency bands.
  • Quantitative results aligned with previous offline studies, confirming the system's accuracy.

Conclusions:

  • The developed system enables real-time imaging of cortical functional connectivity.
  • This technology holds significant potential for advancing the diagnosis of psychiatric diseases.
  • Applications include real-time EEG neurofeedback and enhanced understanding of brain dynamics.