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

Abstract

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.