Non-parametric permutation thresholding for adaptive nonlinear beamformer analysis on MEG revealed oscillatory neuronal dynamics in human brain

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Détails sur la publication

Liste des auteurs: Canuet L
Editeur: IEEE
Année de publication: 2013
Page d'accueil: 4807
Dernière page: 4810
Nombre de pages: 4
ISBN: 978-1-4577-0216-7
Languages: Anglais-Royaume-Uni (EN-GB)


Adaptive nonlinear beamformer technique for analyzing
magnetoencephalography (MEG) data has been proved to be powerful tool
for both brain research and clinical applications. A general method of
analyzing multiple subject data with a formal statistical treatment for
the group data has been developed and applied for various types of MEG
data. Our latest application of this method was frontal midline theta
rhythm (Fmθ), which indicates focused attention and appears widely
distributed over medial prefrontal areas in EEG recordings. To localize
cortical generators of the magnetic counterpart of Fmθ precisely and
identify cortical sources and underlying neural activity associated with
mental calculation processing (i.e., arithmetic subtraction), we
applied adaptive nonlinear beamformer and permutation analysis on MEG
data. As a result, it was indicated that Fmθ is generated in the dorsal
anterior cingulate and adjacent medial prefrontal cortex. Gamma
event-related synchronization is as an index of activation in right
parietal regions subserving mental subtraction associated with basic
numerical processing and number-based spatial attention. Gamma
desynchronization appeared in the right lateral prefrontal cortex,
likely representing a mechanism to interrupt neural activity that can
interfere with the ongoing cognitive task. We suggest that the
combination of adaptive nonlinear beamformer and permutation analysis on
MEG data is quite powerful tool to reveal the oscillatory neuronal
dynamics in human brain.


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Dernière mise à jour le 2019-13-08 à 00:45