About the cortical origin of the low-delta and high-gamma rhythms observed in EEG signals during treadmill walking

Sitting and standing intention can be decoded from scalp EEG recorded prior to movement execution

Low frequency signals recorded from non-invasive electroencephalography (EEG), in particular movement-related cortical potentials (MRPs), are associated with preparation and execution of movement and thus present a target for use in brain-machine interfaces. We investigated the ability to decode movement intent from delta-band (0.1-4 Hz) EEG recorded immediately before movement execution in healthy volunteers. We used data from epochs starting 1.5 s before movement onset to classify future movements into one of three classes: stand-up, sit-down, or quiet. We assessed classification accuracy in both externally triggered and self-paced paradigms. Movement onset was determined from electromyography (EMG) recordings synchronized with EEG signals. We employed an artifact subspace reconstruction (ASR) algorithm to eliminate high amplitude noise before building our time-embedded EEG features. We applied local Fisher's discriminant analysis to reduce the dimensionality of our spatio-temporal features and subsequently used a Gaussian mixture model classifier for our three class problem. Our results demonstrate significantly better than chance classification accuracy (chance level = 33.3%) for the self-initiated (78.0 ± 2.6%) and triggered (74.7 ± 5.7%) paradigms. Surprisingly, we found no significant difference in classification accuracy between the self-paced and cued paradigms when using the full set of non-peripheral electrodes. However, accuracy was significantly increased for self-paced movements when only electrodes over the primary motor area were used. Overall, this study demonstrates that delta-band EEG recorded immediately before movement carries discriminative information regarding movement type. Our results suggest that EEG-based classifiers could improve lower-limb neuroprostheses and neurorehabilitation techniques by providing earlier detection of movement intent, which could be used in robot-assisted strategies for motor training and recovery of function.

EEG beta suppression and low gamma modulation are different elements of human upright walking

Cortical involvement during upright walking is not well-studied in humans. We analyzed non-invasive electroencephalographic (EEG) recordings from able-bodied volunteers who participated in a robot-assisted gait-training experiment. To enable functional neuroimaging during walking, we applied source modeling to high-density (120 channels) EEG recordings using individual anatomy reconstructed from structural magnetic resonance imaging scans. First, we analyzed amplitude differences between the conditions, walking and upright standing. Second, we investigated amplitude modulations related to the gait phase. During active walking upper μ (10-12 Hz) and β (18-30 Hz) oscillations were suppressed [event-related desynchronization (ERD)] compared to upright standing. Significant β ERD activity was located focally in central sensorimotor areas for 9/10 subjects. Additionally, we found that low γ (24-40 Hz) amplitudes were modulated related to the gait phase. Because there is a certain frequency band overlap between sustained β ERD and gait phase related modulations in the low γ range, these two phenomena are superimposed. Thus, we observe gait phase related amplitude modulations at a certain ERD level. We conclude that sustained μ and β ERD reflect a movement related state change of cortical excitability while gait phase related modulations in the low γ represent the motion sequence timing during gait. Interestingly, the center frequencies of sustained β ERD and gait phase modulated amplitudes were identified to be different. They may therefore be caused by different neuronal rhythms, which should be taken under consideration in future studies.

Your brain on speed: cognitive performance of a spatial working memory task is not affected by walking speed

When humans walk in everyday life, they typically perform a range of cognitive tasks while they are on the move. Past studies examining performance changes in dual cognitive-motor tasks during walking have produced a variety of results. These discrepancies may be related to the type of cognitive task chosen, differences in the walking speeds studied, or lack of controlling for walking speed. The goal of this study was to determine how young, healthy subjects performed a spatial working memory task over a range of walking speeds. We used high-density electroencephalography to determine if electrocortical activity mirrored changes in cognitive performance across speeds. Subjects stood (0.0 m/s) and walked (0.4, 0.8, 1.2, and 1.6 m/s) with and without performing a Brooks spatial working memory task. We hypothesized that performance of the spatial working memory task and the associated electrocortical activity would decrease significantly with walking speed. Across speeds, the spatial working memory task caused subjects to step more widely compared with walking without the task. This is typically a sign that humans are adapting their gait dynamics to increase gait stability. Several cortical areas exhibited power fluctuations time-locked to memory encoding during the cognitive task. In the somatosensory association cortex, alpha power increased prior to stimulus presentation and decreased during memory encoding. There were small significant reductions in theta power in the right superior parietal lobule and the posterior cingulate cortex around memory encoding. However, the subjects did not show a significant change in cognitive task performance or electrocortical activity with walking speed. These findings indicate that in young, healthy subjects walking speed does not affect performance of a spatial working memory task. These subjects can devote adequate cortical resources to spatial cognition when needed, regardless of walking speed.