An Experimental Approach for Investigating Freezing of Gait in Parkinson's Disease Using Virtual Reality and Neural Sensing: A Pilot Study

Abstract

Freezing of gait (FOG) is a disabling symptom associated with Parkinson's disease (PD). Its understanding and effective treatment is compromised due to the difficulty in reliably triggering FOG in clinical and laboratory environments. The Cleveland Clinic-Virtual Home Environment (CC-VHE) platform was developed to address the challenges of eliciting FOG by combining an omnidirectional treadmill with immersive virtual reality (VR) environments to induce FOG under physical, emotional, and cognitive triggers. Recent developments in deep brain stimulation devices that sense neural signals from the subthalamic nucleus in real time offer the potential to understand the underlying neural mechanism(s) of FOG. This manuscript presents the coupling of the CC-VHE technology, VR paradigms, and the experimental and analytical methods for recording and analyzing synchronous cortical, subcortical, and kinematic data as an approach to begin to understand the nuanced neural pathology associated with FOG. To evaluate the utility and feasibility of coupling VR and neural sensing technology, initial data from one participant are included.

Keywords: Parkinson’s disease; deep brain stimulation; electroencephalography; freezing of gait; virtual reality.

Figure 1

An illustration of the Cleveland Clinic-Virtual Home Environment (CC-VHE) hardware and software components. The participant walks and turns on an omnidirectional treadmill to navigate three virtual home environment scenarios that operationalize the theoretical models of FOG. Synchronized local field potential, electroencephalogram, kinematic, and electrocardiogram data are simultaneously recorded while a clinician notes the onset and offset of freezing of gait episodes.

Figure 2

First-person views of the CC-VHE assessment modules that include the following: (1) The Physical module includes narrow doorways and changes in flooring patterns; (2) The Anxiety module requires the navigation of elevated, narrow walkways over a forest of trees; and (3) The Cognitive module requires walking while performing a simultaneous cognitive-motor task identifying congruent or incongruent stimuli. The example illustrated in this figure represents an incongruent stimulus: the word “Spider” is incongruent with the picture of a cat; the correct response from the participant would be to activate the hand controller in the left hand.

Figure 3

Temporally aligned kinematic, EEG and LFP data from a representative trial in the off–Off condition. Two devices were utilized to inject artifacts into the data streams to facilitate temporal alignment between the EEG, LFP and the kinematic data: the Raspberry Pi (Sync A) and the TENS (Sync B). The insert illustrates the alignment between the EEG and LFP data streams.

Figure 4

Power spectral densities of local field potential data from the left and right subthalamic nucleus (STN) in both medication states.

Figure 5

Kinematic, EEG, and LFP data with FOG episodes and Walk epochs in the off–Off condition. (A) Top-to-bottom: Shank angular speed, EEG, and right and left STN LFP data during a sample, 80 s (40–120 s) period from the Cognitive module. Four FOG epochs are identified with green horizontal bars. The EEG and STN activity spectrograms are color-coded according to the key presented below. (B) Shank angular speed, EEG, and STN data from 30 s of the Reference module, with a Walk epoch identified with a black horizontal bar. (C) Power spectral densities of the EEG and LFP data during all FOG (green traces) and Walk epochs (black traces) during the Cognitive module. The width of the green and black traces in the PSDs represents the 95% confidence intervals of the mean.

Figure 6

(A) In the example participant, power spectral densities of local field potentials from the left (LSTN) and right (RSTN) subthalamic nucleus showed elevated PSDs during FOG (blue, red, and green traces) compared to Walk epochs (single-task, straight-line walking epochs averaged across all modules, black trace) for Anxiety and Cognitive modules; left > right. Gray shaded areas (panels A and B) represent the 1 Hz frequency bands between 8 and 35 Hz that were significantly increased (p < 0.05, FDR correction) during FOG compared to Walk. In (A), the width of the PSD traces represents the 95% confidence interval of the mean. (B) depicts the number (N) and range of 1 Hz frequencies that were significantly elevated during FOG compared to Walk per module.

Figure 7

Cortical EEG (channel P4—navigational movement area) power in the navigational movement during FOG was elevated compared to Walk epochs, with the largest differences in the Anxiety and Cognitive modules. Neural synchrony was increased during FOG (color traces) compared to Walk (single-task, straight-line walking epochs averaged across all modules, black trace) in the Anxiety and Cognitive modules. Gray shaded areas represent the 1 Hz frequency bands between 1 and 35 Hz that were significantly increased (p < 0.05, FDR correction) during FOG compared to Walk. The width of the traces in the PSDs represents the 95% confidence intervals of the mean.