Abstract
In this study, we further investigate electroencephalographic (EEG) data recorded during October 2014 in the ultra-shielded capsule at LSBB, with a focus on the study of task-specific Granger-causal effective connectivity pat-terns. In previous studies, we showed that noise-free EEG signals acquired in LSBB are suitable for analysis of activity patterns in high frequency bands, i.e. 30 Hz and above. We previously demonstrated that increases in task/rest gamma band (30-70 Hz) energy ratios during ankle and wrist movements are more prominent in the LSBB capsule than in an above-ground hospital environ-ment. The present study extends previous analyses by examining gamma-band connectivity, i.e. the functional patterns of interaction between 64 channels of EEG within the gamma band during motor tasks. We use parameters from a MultiVariate Auto-Regressive (MVAR) model to estimate effective connectivity in 10-second batches of EEG and report the average patterns across all batches in which subjects repetitively move their ankle/wrist. We report the gamma-band connectivity results in a reduced form as strength of hemispheric and inter-regional connections. The analysis reveals that for some subjects, significant channel-wise connections in the LSBB capsule outnumber those in the hospital, suggesting that patterns of gamma-band connectivity are better reflected in low-noise environments. This study again demonstrates the poten-tial of the ultra-shielded capsule and motivates further protocol enhancements and analysis methods for conducting future high-frequency EEG studies within LSBB.
Highlights
In two previous studies [1], [2] we have demonstrated the potential of the ultra-low noise shielded capsule at the heart of LSBB is an ideal environment for acquiring ultra-high, wideband electroencephalographic (EEG) signals without the need of filtering
In [1], and in particular in [2] the use of time-frequency analysis revealed that the task-induced increase in gamma band (>30 Hz) energy relative to the resting state EEG is more prominent in signals acquired at LSBB than in a typical hospital environment, suggesting that task-specific changes in EEG are better reflected and more readily detected in signals acquired at LSBB
3. fitting an MultiVariate AutoRegressive (MVAR) model (p = 10) to each epoch, calculating the epoch Directed Transfer Function (dDTF) measure (Equation (17)), and integrating the dDTF values in the gamma band, 4. statistically comparing the motor dDTF values with those of the resting state and obtaining the K × K pair-wise significance matrices per subject, where values corresponding to the rejected channels are left empty 1, 5. averaging the K × K pair-wise significance matrices across subjects to determine significant dDTF connections which are common to all subjects and survive averaging
Summary
In two previous studies [1], [2] we have demonstrated the potential of the ultra-low noise shielded capsule at the heart of LSBB is an ideal environment for acquiring ultra-high, wideband electroencephalographic (EEG) signals without the need of filtering. EEG frequencies are most often studied from 0.5 to 30 Hz with the gamma (γ) band being ignored. The gamma band is often ignored due to the use of filters to suppress unwanted electromagnetic noise from powered (50 or 60 Hz) electrical outlets. In [1], and in particular in [2] the use of time-frequency analysis revealed that the task-induced increase in gamma band (>30 Hz) energy relative to the resting state EEG is more prominent in signals acquired at LSBB than in a typical hospital environment, suggesting that task-specific changes in EEG are better reflected and more readily detected in signals acquired at LSBB. In this report we go further by analyzing the connectivity in the gamma band of EEG acquired during motor tasks
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