Transient visual perturbations boost short-term balance learning in virtual reality by modulating electrocortical activity.

Immersive virtual reality can expose humans to novel training and sensory environments, but motor training with virtual reality has not been able to improve motor performance as much as motor training in real-world conditions. An advantage of immersive virtual reality that has not been fully leveraged is that it can introduce transient visual perturbations on top of the visual environment being displayed. The goal of this study was to determine whether transient visual perturbations introduced in immersive virtual reality modify electrocortical activity and behavioral outcomes in human subjects practicing a novel balancing task during walking. We studied three groups of healthy young adults (5 male and 5 female for each) while they learned a balance beam walking task for 30 min under different conditions. Two groups trained while wearing a virtual reality headset, and one of those groups also had half-second visual rotation perturbations lasting ~10% of the training time. The third group trained without virtual reality. We recorded high-density electroencephalography (EEG) and movement kinematics. We hypothesized that virtual reality training with perturbations would increase electrocortical activity and improve balance performance compared with virtual reality training without perturbations. Our results confirmed the hypothesis. Brief visual perturbations induced increased theta spectral power and decreased alpha spectral power in parietal and occipital regions and improved balance performance in posttesting. Our findings indicate that transient visual perturbations during immersive virtual reality training can boost short-term motor learning by inducing a cognitive change, minimizing the negative effects of virtual reality on motor training. NEW & NOTEWORTHY We found that transient visual perturbations in virtual reality during balance training can boost short-term motor learning by inducing a cognitive change, overcoming the negative effects of immersive virtual reality. As a result, subjects training in immersive virtual reality with visual perturbations have equivalent performance improvement as training in real-world conditions. Visual perturbations elicited cortical responses in occipital and parietal regions and may have improved the brain's ability to adapt to variations in sensory input.

Quantitative simulation of extracellular single unit recording from the surface of cortex.

OBJECTIVE: Neural recording is important for a wide variety of clinical applications. Until recently, recording from the surface of the brain, even when using micro-electrocorticography (µECoG) arrays, was not thought to enable recording from individual neurons. Recent results suggest that when the surface electrode contact size is sufficiently small, it may be possible to record single neurons from the brain's surface. In this study, we use computational techniques to investigate the ability of surface electrodes to record the activity of single neurons. APPROACH: The computational model included the rat head, µECoG electrode, two existing multi-compartmental neuron models, and a novel multi-compartmental neuron model derived from patch clamp experiments in layer 1 of the cortex. MAIN RESULTS: Using these models, we reproduced single neuron recordings from µECoG arrays, and elucidated their possible source. The model resembles the experimental data when spikes originate from layer 1 neurons that are less than 60 µm from the cortical surface. We further used the model to explore the design space for surface electrodes. Although this model does not include biological or thermal noise, the results indicate the electrode contact area should be 100 µm2 or smaller to maintain a detectable waveform amplitude. Furthermore, the model shows the width of lateral insulation could be reduced, which may reduce scar formation, while retaining 95% of signal amplitude. SIGNIFICANCE: Overall, the model suggests single-unit surface recording is limited to neurons in layer 1 and further improvement in electrode design is needed.