Mutual-Information-Based Approach for Neural Connectivity during Self-Paced Finger Lifting Task

Chun Chuan Chen, Jen Chuen Hsieh, Yu Zu Wu, Po Lei Lee, Shyan Shiou Chen, David M. Niddam, Tzu Chen Yeh, Yu Te Wu

Research output: Contribution to journalArticle

26 Citations (Scopus)

Abstract

Frequency-dependent modulation between neuronal assemblies may provide insightful mechanisms of functional organization in the context of neural connectivity. We present a conjoined time-frequency cross mutual information (TFCMI) method to explore the subtle brain neural connectivity by magnetoencephalography (MEG) during a self-paced finger lifting task. Surface electromyogram (sEMG) was obtained from the extensor digitorum communis. Both within-modality (MEG-MEG) and between-modality studies (sEMG-MEG) were conducted. The TFCMI method measures both the linear and nonlinear dependencies of the temporal dynamics of signal power within a pre-specified frequency band. Each single trial of MEG across channels and sEMG signals was transformed into time-frequency domain with use of the Morlet wavelet to obtain better temporal spectral (power) information. As compared to coherence approach (linear dependency only) in broadband analysis, the TFCMI method demonstrated advantages in encompassing detection for the mesial frontocentral cortex and bilateral primary sensorimotor areas, clear demarcation of event- and non-event-related regions, and robustness for sEMG - MEG between-modality study, i.e., corticomuscular communication. We conclude that this novel TFCMI method promises a possibility to better unravel the intricate functional organizations of brain in the context of oscillation-coded communication.

Original languageEnglish
Pages (from-to)265-280
Number of pages16
JournalHuman Brain Mapping
Volume29
Issue number3
DOIs
Publication statusPublished - 2008 Mar 1

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Keywords

  • Coherence
  • Corticomuscular communication
  • Functional connectivity
  • Magnetoencephalography
  • Surface electromyogram
  • TFCMI
  • Time-frequency cross mutual information

ASJC Scopus subject areas

  • Anatomy
  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Neurology
  • Clinical Neurology

Cite this

Chen, C. C., Hsieh, J. C., Wu, Y. Z., Lee, P. L., Chen, S. S., Niddam, D. M., Yeh, T. C., & Wu, Y. T. (2008). Mutual-Information-Based Approach for Neural Connectivity during Self-Paced Finger Lifting Task. Human Brain Mapping, 29(3), 265-280. https://doi.org/10.1002/hbm.20386