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Recent research efforts in studying brain connectivity has provided new perspectives to understanding of neurophysiology of brain function. Connectivity measures are typically computed from electroencephalogram (EEG) signals, yet the presence of volume conduction makes interpretation of results difficult. One possible alternative is to model the connectivity in the source space. In this study, we...
Monitoring the dynamics of networks in the brain is of central importance in normal and disease states. Current methods of detecting networks in the recorded EEG such as correlation and coherence only explore linear dependencies, which may be unsatisfactory. We propose applying mutual information as an alternative metric for assessing possible nonlinear statistical dependencies between EEG channels...
EEG-EMG coherence has been recently used to investigate the motor system in humans. Typically this is performed by calculating the coherence between a single EEG electrode and a rectified EMG channel. However, there are strong biological reasons to expect that the cortical to muscular communication is many-to-many as opposed to one-to-one. Here we describe the use of independent component analysis...
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