Supraspinal Control of Human Locomotor Adaptation

Title Supraspinal Control of Human Locomotor Adaptation Abstract Advances in electroencephalography (EEG) technology have made it feasible to study electrical brain dynamics during human gait.

Active electrodes, novel signal processing approaches, and subject-specific inverse electrical head models allow for unprecedented insight into how the human brain controls locomotion.

Further advances in EEG based mobile brain imaging will increase our fundamental understanding of how the human brain works in real world situations, improve diagnosis and treatment of movement disorders, and result in new brain- computer interfaces. We recently developed a novel noise-cancelling EEG system that can greatly improve the signal to noise ratio for EEG.

We propose to use our novel EEG system to investigate human locomotor adaptation.

Many studies have used blood-oxygen-level dependent imaging (e.g. fMRI or fNIRS) to study supraspinal control of upper limb motor adaptation or imagined human walking, but the timescale of those imaging modalities do not allow for identifying brain activity relative to the biomechanics of the gait cycle.

We propose to use our novel EEG system to document the brain areas involved in locomotor adaptation.

Specifically, we will quantify brain activity spectral fluctuations within the gait cycle that demonstrate correlations with locomotor adaptation.

We expect that multiple brain areas, including the anterior cingulate, cerebellum, somatosensory cortex, and motor cortex are likely involved in the control and adaptation of walking.

We also expect that areas involved in locomotor adaptation will decrease spectral power fluctuations with improvements in locomotor performance during challenging gait tasks.

The specific tasks that we will investigate are walking at different speeds, walking on a split-belt treadmill, walking with a unilateral robotic ankle exoskeleton, and walking on a balance beam with visual perturbations.

The high temporal resolution of EEG provides particularly valuable insight into both amplitude and timing of brain activity within the gait cycle.

Our preliminary data suggest that there are more cortical areas involved in controlling human walking than are generally recognized in the literature.

The results from these studies will increase our basic science understanding of the supraspinal control of human locomotor adaptation and should lead to further advances in EEG mobile brain imaging technology.