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Front Hum Neurosci. 2015 May 12;9:247. doi: 10.3389/fnhum.2015.00247. eCollection 2015.

Prefrontal, posterior parietal and sensorimotor network activity underlying speed control during walking.

Author information

1
Functional and Applied Biomechanics Section, Rehabilitation Medicine Department, National Institutes of Health Bethesda, MD, USA.
2
Robotics Engineering Department, Daegu Gyeongbuk Institute of Science and Technology Daegu, South Korea.
3
Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology Daejeon, South Korea.

Abstract

Accumulating evidence suggests cortical circuits may contribute to control of human locomotion. Here, noninvasive electroencephalography (EEG) recorded from able-bodied volunteers during a novel treadmill walking paradigm was used to assess neural correlates of walking. A systematic processing method, including a recently developed subspace reconstruction algorithm, reduced movement-related EEG artifact prior to independent component analysis and dipole source localization. We quantified cortical activity while participants tracked slow and fast target speeds across two treadmill conditions: an active mode that adjusted belt speed based on user movements and a passive mode reflecting a typical treadmill. Our results reveal frequency specific, multi-focal task related changes in cortical oscillations elicited by active walking. Low γ band power, localized to the prefrontal and posterior parietal cortices, was significantly increased during double support and early swing phases, critical points in the gait cycle since the active controller adjusted speed based on pelvis position and swing foot velocity. These phasic γ band synchronizations provide evidence that prefrontal and posterior parietal networks, previously implicated in visuo-spatial and somotosensory integration, are engaged to enhance lower limb control during gait. Sustained μ and β band desynchronization within sensorimotor cortex, a neural correlate for movement, was observed during walking thereby validating our methods for isolating cortical activity. Our results also demonstrate the utility of EEG recorded during locomotion for probing the multi-regional cortical networks which underpin its execution. For example, the cortical network engagement elicited by the active treadmill suggests that it may enhance neuroplasticity for more effective motor training.

KEYWORDS:

electroencephalography; event-related desynchronization; gait; gamma oscillations; motor cortex; motor learning; neurorehabilitation; source localization

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