Krugliakova E, Karpovich A, Stieglitz L, Huwiler S, Lustenberger C, Imbach L, Bujan B, Jedrysiak P, Jacomet M, Baumann CR, Fattinger S. Exploring the local field potential signal from the subthalamic nucleus for phase-targeted auditory stimulation in Parkinson's disease.
Brain Stimul 2024;
17:769-779. [PMID:
38906529 DOI:
10.1016/j.brs.2024.06.007]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 05/26/2024] [Accepted: 06/12/2024] [Indexed: 06/23/2024] Open
Abstract
BACKGROUND
Enhancing slow waves, the electrophysiological (EEG) manifestation of non-rapid eye movement (NREM) sleep, could potentially benefit patients with Parkinson's disease (PD) by improving sleep quality and slowing disease progression. Phase-targeted auditory stimulation (PTAS) is an approach to enhance slow waves, which are detected in real-time in the surface EEG signal.
OBJECTIVE
We aimed to test whether the local-field potential of the subthalamic nucleus (STN-LFP) can be used to detect frontal slow waves and assess the electrophysiological changes related to PTAS.
METHODS
We recruited patients diagnosed with PD and undergoing Percept™ PC neurostimulator (Medtronic) implantation for deep brain stimulation of STN (STN-DBS) in a two-step surgery. Patients underwent three full-night recordings, including one between-surgeries recording and two during rehabilitation, one with DBS+ (on) and one with DBS- (off). Surface EEG and STN-LFP signals from Percept PC were recorded simultaneously, and PTAS was applied during sleep in all three recording sessions.
RESULTS
Our results show that during NREM sleep, slow waves of the cortex and STN are time-locked. PTAS application resulted in power and coherence changes, which can be detected in STN-LFP.
CONCLUSION
Our findings suggest the feasibility of implementing PTAS using solely STN-LFP signal for slow wave detection, thus without a need for an external EEG device alongside the implanted neurostimulator. Moreover, we propose options for more efficient STN-LFP signal preprocessing, including different referencing and filtering to enhance the reliability of cortical slow wave detection in STN-LFP recordings.
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