Basal Ganglia Local Field Potentials as a Potential Biomarker for Sleep Disturbance in Parkinson's Disease

Abstract

Sleep disturbances, specifically decreases in total sleep time and sleep efficiency as well as increased sleep onset latency and wakefulness after sleep onset, are highly prevalent in patients with Parkinson's disease (PD). Impairment of sleep significantly and adversely impacts several comorbidities in this patient population, including cognition, mood, and quality of life. Sleep disturbances and other non-motor symptoms of PD have come to the fore as the effectiveness of advanced therapies such as deep brain stimulation (DBS) optimally manage the motor symptoms. Although some studies have suggested that DBS provides benefit for sleep disturbances in PD, the mechanisms by which this might occur, as well as the optimal stimulation parameters for treating sleep dysfunction, remain unknown. In patients treated with DBS, electrophysiologic recording from the stimulating electrode, in the form of local field potentials (LFPs), has led to the identification of several findings associated with both motor and non-motor symptoms including sleep. For example, beta frequency (13–30 Hz) oscillations are associated with worsened bradykinesia while awake and decrease during non-rapid eye movement sleep. LFP investigation of sleep has largely focused on the subthalamic nucleus (STN), though corresponding oscillatory activity has been found in the globus pallidus internus (GPi) and thalamus as well. LFPs are increasingly being recognized as a potential biomarker for sleep states in PD, which may allow for closed-loop optimization of DBS parameters to treat sleep disturbances in this population. In this review, we discuss the relationship between LFP oscillations in STN and the sleep architecture of PD patients, current trends in utilizing DBS to treat sleep disturbance, and future directions for research. In particular, we highlight the capability of novel technologies to capture and record LFP data in vivo, while patients continue therapeutic stimulation for motor symptoms. These technological advances may soon allow for real-time adaptive stimulation to treat sleep disturbances.

Sleep alterations in a mouse model of Spinocerebellar ataxia type 3

“…The copyright holder for this preprint (which this version posted July 5, 2022. ; https://doi.org/10.1101/2022.07.05.498300 doi: bioRxiv preprint during REM and NREM in Q84 mice is reminiscent of increased beta oscillations observed in other neurodegenerative diseases and sleep disorders. Alterations, most frequently increases, in beta oscillations have been observed during wake and sleep states in patients or animal models of PD [60][61][62][63][64][65][66][67][68] , HD 69,70,[79][80][81][82][83][84][71][72][73][74][75][76][77][78] , dementia with Lewy bodies 85,86 , insomnia 60,87 , and RBD 63,[88][89][90] . In PD, beta oscillations in the basal ganglia are usually pathological 60,62,64,67,68,91 and appear to be linked to basal ganglia dysfunction or compensation.…”

“…Alterations, most frequently increases, in beta oscillations have been observed during wake and sleep states in patients or animal models of PD [60][61][62][63][64][65][66][67][68] , HD 69,70,[79][80][81][82][83][84][71][72][73][74][75][76][77][78] , dementia with Lewy bodies 85,86 , insomnia 60,87 , and RBD 63,[88][89][90] . In PD, beta oscillations in the basal ganglia are usually pathological 60,62,64,67,68,91 and appear to be linked to basal ganglia dysfunction or compensation. Thus, the triad of RBD, beta oscillations, and basal ganglia appears to be a unifying feature of these diseases, including SCA3.…”

Embedding digital chronotherapy into bioelectronic medicines

“…Overall, it has been found that open-loop DBS improves sleep structure as a fortuitous byproduct ( Hjort et al., 2004 ; Mizrahi-Kliger et al., 2020 ). However, it is not currently optimized for nighttime or within sleep stages ( Baumgartner et al., 2021 ; Zahed et al., 2021 ). Recently, investigational trials have used newer sensing-enabled DBS devices to deliver closed loop DBS in response to biomarkers correlated with motor performance ( Gilron et al., 2021 ; Little et al., 2016 ; Velisar et al., 2019 ).…”

Excessive cortical beta oscillations are associated with slow-wave sleep dysfunction in mild parkinsonism

“…In addition to their recognized role in the development of PD motor signs 20 , our findings provide further support for the role of beta oscillations in the sleep dysfunction observed in patients with PD 11,13 . It has recently been hypothesized that parkinsonism-related excessive beta oscillations in the basal ganglia are transmitted to the cortex, disrupting the initiation or maintenance of slow wave oscillations during sleep 11,21 , though the exact mechanisms by which this occurs remain unclear. Additional investigations utilizing simultaneous recordings at the single neuron and field potential level across the basal ganglia-thalamocortical (BGTC) network will be needed to further test this hypothesis and provide key insight into the neuronal mechanisms driving the disruption of cortical delta oscillations in parkinsonian sleep and the role beta oscillations in the BGTC network may play in the emergence of sleep dysfunction in PD.…”

“…Future preclinical studies that explore neuromodulation (e.g., both non-invasive as well as DBS 33 ) techniques for suppressing beta oscillations during sleep and characterizing its effect on cortical SWS to further support the notion that suppression of excessive beta oscillations during sleep can profoundly improve sleep quality. Moreover, simultaneous neural recordings across the basal ganglia thalamocortical network and directed connectivity analysis can help decipher the mechanisms by which beta oscillations in the cortex are elevated during SWS in the early stage of parkinsonism 11,21,34 . Lastly, a higher number of sleep recordings across normal and early PD along with machine learning algorithms will be necessary to generalize the efficacy of features discussed in this study for early-stage disease classification.…”