A novel methodological approach to understanding the cortical and subcortical effects of aerobic exercise in Parkinson's disease

Abstract

Introduction: Aerobic exercise mitigates symptoms of Parkinson's disease (PD) and may slow disease progression; however, the neural mechanisms underlying these improvements are not well understood. In this study, we discuss the methodology for simultaneously recording local field potentials (LFP) from the subthalamic nucleus (STN), cortical activity using scalp electroencephalography (EEG), and exercise performance metrics during a 40-min aerobic cycling session. Data from a single patient with PD are presented to illustrate the utility, feasibility, and data integrity of the experimental set up.

Methods: The Medtronic Percept™ DBS system was used to record and stream bilateral STN-LFP in the OFF-therapy condition (OFF-DBS and OFF-antiparkinson medications) during a 40-min aerobic exercise session. A 64-channel mobile EEG system recorded cortical data. The neural data streams were synchronized using a TENS device that injected a specified electrical signal into the EEG and LFP recordings. Exercise performance metrics, heart rate, cadence, and power were synchronized with neural data and collected during the exercise session. The study is registered on ClinicalTrials.gov, trial identifying numbers NCT05905302 and NCT05972759.

Results: STN-LFP, EEG, and exercise performance data can be synchronized, recorded for more than 40 min, and analyzed to evaluate how aerobic exercise impacts patterns of cortical and subcortical neural activity.

Conclusion: While exercise positively affects symptoms of PD, the precise effects of exercise on network activity remain unclear. The methods utilized for collecting and analyzing neural (cortical and subcortical) and exercise-related data during a typical bout of aerobic exercise suggest that this approach can be adopted for larger, long-term exercise studies in patients with PD and deep brain stimulation (DBS). The described protocol provides a roadmap for future projects aiming to combine STN-LFP and cortical data to better understand how exercise may alter cortico-basal-ganglia-thalamic dynamics in PD.

Keywords: Parkinson’s disease; aerobic exercise; electroencephalogram; local field potential; subthalamic nucleus.

Figure 1

Illustration of the experimental set up. Pre-, during, and post-exercise data from a 64-electrode EEG system were continuously recorded throughout the session and visualized on a control computer. Manual inputs in the control computer denoted key events such as the start and end of the exercise session. The STN-LFP data were streamed to a tablet device in 15-min intervals and synchronized with the EEG data by injecting a known electrical artifact using a superficial TENS unit attached to the wires extending from the IPG and contralateral mastoid.

Figure 2

Neural data synchronization process. The EEG computer served as the control computer. Manual inputs denoted the cycling start and stop times (black vertical line at 0 and 40 min). The insert highlights the electrical artifact injected via the TENS device, delivered through electrodes placed near the IPG on the extension cable and on the contralateral mastoid. The artifact was visible in both the EEG (blue) and STN-LFP (red) data streams and facilitated precise temporal alignment between the data streams, resulting in an average 12.3 ms of error across all trials. Over the entire 40-min exercise and data recording session, bilateral STN-LFP data were recorded for 90% (36 min, 7 s/40 min) of the total time, demonstrating the feasibility of prolonged STN recording during exercise.

Figure 3

Spectrograms of local field potential (STN-LFP) data from the left STN and right STN electrodes are shown in the top and bottom rows, respectively. The data collection session was divided into five distinct phases: 1-min rest before exercise initiation, 5-min warm-up, 30-min main exercise period, 5-min cool-down, and 5-min post-exercise rest. The power spectral density plots on the right indicate a decrease in alpha and beta-band power during the main exercise period (red) compared to the pre-exercise (blue) and post-exercise (green) periods.

Figure 4

Time series of neural and exercise data over the 45-min data collection session. (A) Normalized beta-band power in 60-s epochs from left (blue) and right (red) STN contacts, (B) normalized 60-s beta-band power epochs from EEG electrodes over the left (C3, blue) and right (C4, red) M1, (C) heart rate (black) and pedaling cadence (purple), and (D) pedaling power output during the 40-min exercise period. The FE bike maintained a steady cadence of 60 rpms, which was approximately 30% greater than the participant’s self-selected cadence. The participant’s heart rate and power increased, reflecting the increased effort during the main exercise set. The figure illustrates the capability of the design paradigm to capture and synchronize multiple distinct data streams (STN-LFP, EEG, and exercise performance) over a prolonged bout of aerobic exercise.

Figure 5

Spectrograms of EEG data from the left and right M1 electrodes are shown in the top and bottom rows, respectively, across the following segments of the data collection session: (1) 1-min rest before exercise, (2) 5-min warm-up, (3) 30-min main exercise period, (4) 5-min cool-down, and (5) 5-min post-exercise rest. The power spectral density plots on the right demonstrate an increase in beta-band power during the main exercise (red) compared to both pre-exercise (blue) and post-exercise (green) periods.