• DocumentCode
    2181593
  • Title

    Neural Mass Modeling for Multi-Channel EEG Synchronization Analyzing

  • Author

    Dong Cui ; Li, Xiaoli ; Gu, Guanghua

  • Author_Institution
    Inst. of Electr. Eng., Yanshan Univ., Qinhuangdao, China
  • fYear
    2009
  • fDate
    17-19 Oct. 2009
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Multiple neural population synchronization measure plays an important role in the interaction dynamics in brain. To understand the synchronization physiologically, this paper develops a multi-channel neural mass model (NMM) and used to generate multiple EEG signals, then a coherence and correlation matrix analysis (CMA) method was used to analyze the dynamic and synchronous characteristic of the new model. Results showed that the new model was able to generate complex EEG signals that range from delta band (1-4 Hz) to gamma band (30-70 Hz), and the coupling has a direct effect on the coherence and the global synchronization among coupled areas.
  • Keywords
    electroencephalography; neurophysiology; synchronisation; brain interaction dynamics; coherence; correlation matrix analysis; multichannel EEG synchronization; multichannel neural mass model; multiple neural population synchronization; neural mass modeling; Brain modeling; Coherence; Electroencephalography; Epilepsy; Frequency synchronization; Helium; Kinetic theory; Rhythm; Signal analysis; Signal generators;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Engineering and Informatics, 2009. BMEI '09. 2nd International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-1-4244-4132-7
  • Electronic_ISBN
    978-1-4244-4134-1
  • Type

    conf

  • DOI
    10.1109/BMEI.2009.5305060
  • Filename
    5305060