Search Results - "Hui, Hua Brian"

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  1. 1

    Identifying true cortical interactions in MEG using the nulling beamformer by Hui, Hua Brian, Pantazis, Dimitrios, Bressler, Steven L., Leahy, Richard M.

    Published in NeuroImage (Orlando, Fla.) (15-02-2010)
    “…Modeling functional brain interaction networks using non-invasive EEG and MEG data is more challenging than using intracranial recording data. This is because…”
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    Journal Article
  2. 2

    Linearly constrained MEG beamformers for MVAR modeling of cortical interactions by Hua Brian Hui, Leahy, R.M.

    “…Among the many methods for modeling cortical interactions using EEG and MEG data, multivariate autoregressive (MVAR) functional connectivity measures have the…”
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    Conference Proceeding Journal Article
  3. 3

    Signal processing methods for interaction analysis of functional brain imaging data by Hui, Hua Brian

    Published 01-01-2010
    “…Modeling functional brain interaction networks using non-invasive EEG and MEG data is more challenging than using intracranial recordings data. This is because…”
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    Dissertation
  4. 4

    Statistically optimal graph partition method based on modularity by Yu-Teng Chang, Pantazis, Dimitrios, Hui, Hua Brian, Leahy, Richard M

    “…Graph theory provides a formal framework to investigate the functional and structural connectome of the brain. We extend previous work on modularity-based…”
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    Conference Proceeding
  5. 5

    Generalized sidelobe canceller for magnetoencephalography arrays by Mosher, J.C., Hamalainen, M.S., Pantazis, D., Hui, H.B., Burgess, R.C., Leahy, R.M.

    “…In the last decade, large arrays of sensors for magnetoencephalography (MEG) (and electroencephalography (EEG)) have become more common place, allowing new…”
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    Conference Proceeding Journal Article
  6. 6

    Signal processing methods for interaction analysis of functional brain imaging data by Hui, Hua Brian

    “…Modeling functional brain interaction networks using non-invasive EEG and MEG data is more challenging than using intracranial recordings data. This is because…”
    Get full text
    Dissertation