Pathological pallidal beta activity in Parkinson's disease is sustained during sleep and associated with sleep disturbance

Role of the globus pallidus in motor and non-motor symptoms of Parkinson's disease

The globus pallidus plays a pivotal role in the basal ganglia circuit. Parkinson's disease is characterized by degeneration of dopamine-producing cells in the substantia nigra, which leads to dopamine deficiency in the brain that subsequently manifests as various motor and non-motor symptoms. This review aims to summarize the involvement of the globus pallidus in both motor and non-motor manifestations of Parkinson's disease. The firing activities of parvalbumin neurons in the medial globus pallidus, including both the firing rate and pattern, exhibit strong correlations with the bradykinesia and rigidity associated with Parkinson's disease. Increased beta oscillations, which are highly correlated with bradykinesia and rigidity, are regulated by the lateral globus pallidus. Furthermore, bradykinesia and rigidity are strongly linked to the loss of dopaminergic projections within the cortical-basal ganglia-thalamocortical loop. Resting tremors are attributed to the transmission of pathological signals from the basal ganglia through the motor cortex to the cerebellum-ventral intermediate nucleus circuit. The cortico-striato-pallidal loop is responsible for mediating pallidi-associated sleep disorders. Medication and deep brain stimulation are the primary therapeutic strategies addressing the globus pallidus in Parkinson's disease. Medication is the primary treatment for motor symptoms in the early stages of Parkinson's disease, while deep brain stimulation has been clinically proven to be effective in alleviating symptoms in patients with advanced Parkinson's disease, particularly for the movement disorders caused by levodopa. Deep brain stimulation targeting the globus pallidus internus can improve motor function in patients with tremor-dominant and non-tremor-dominant Parkinson's disease, while deep brain stimulation targeting the globus pallidus externus can alter the temporal pattern of neural activity throughout the basal ganglia-thalamus network. Therefore, the composition of the globus pallidus neurons, the neurotransmitters that act on them, their electrical activity, and the neural circuits they form can guide the search for new multi-target drugs to treat Parkinson's disease in clinical practice. Examining the potential intra-nuclear and neural circuit mechanisms of deep brain stimulation associated with the globus pallidus can facilitate the management of both motor and non-motor symptoms while minimizing the side effects caused by deep brain stimulation.

Local Field Potential Biomarkers of Non-Motor Symptoms in Parkinson's Disease: Insights From the Subthalamic Nucleus in Deep Brain Stimulation

Non-motor symptoms can severely affect the quality of life of Parkinson's disease-afflicted patients, with the most common ones being pain, sleep impairments, and neuropsychiatric manifestations. In advanced cases, complex fluctuations of motor and non-motor symptoms can occur despite optimal medication. Research on deep brain stimulation of the subthalamic nucleus suggests that it may provide benefits for treating non-motor symptoms in addition to improving motor symptoms. With recent advancements in deep brain stimulation technology, simultaneous recording of local field potentials and delivery of therapeutic stimulation is possible. This opens new possibilities for better understanding the pathophysiology of non-motor symptoms in Parkinson's disease and for identifying potential electrophysiological biomarkers that accurately represent these symptoms. Specifically, this review aims to highlight potential local field potential biomarkers of non-motor symptoms in the subthalamic nucleus. The main findings indicate that activities in the beta frequency band are associated with nociception and sleep impairments such as insomnia and rapid eye movement sleep behavior disorders. Additionally, activities in the theta and alpha frequency bands seem to reflect neurocognitive manifestations, including depression and impulse control disorders. A better understanding of these biomarkers could improve the clinical management of non-motor symptoms in Parkinson's disease. They hold promise for adjusting deep brain stimulation parameters in open-loop settings and might eventually be applied in closed-loop deep brain stimulation systems, though their true impact remains uncertain.

Subthalamic γ Oscillation Underlying Rapid Eye Movement Sleep Abnormality in Parkinsonian Patients

BACKGROUND

Abnormal rapid eye movement (REM) sleep, including REM sleep behavior disorder (RBD) and reduced REM sleep, is common in Parkinson's disease (PD), highlighting the importance of further study on REM sleep. However, the biomarkers of REM disturbances remain unknown, leading to the lack of REM-specific neuromodulation interventions.

OBJECTIVE

This study aims to investigate the neurophysiological biomarkers of REM disturbance in parkinsonian patients.

METHODS

Ten PD patients implanted with bilateral subthalamic nucleus-deep brain stimulation (STN-DBS) were included in this study, of whom 4 were diagnosed with RBD. Sleep monitoring was conducted 1 month after surgery. Subthalamic local field potentials (LFP) were recorded through sensing-enabled DBS. The neurophysiological features of subthalamic LFP during phasic and tonic microstates of REM sleep and their correlation with REM sleep fragmentation and RBD were analyzed.

RESULTS

Differences in subthalamic γ oscillation between phasic and tonic REM correlated positively with the severity of REM sleep fragmentation. Patients with RBD also exhibited stronger γ oscillations during REM sleep compared with non-RBD patients, and both increased β and γ were found before the onset of RBD episodes. Stimulation changes in simulated γ-triggered feedback modulation followed more closely with phasic REM density, whereas an opposite trend was found in simulated β-triggered feedback modulation.

CONCLUSION

Excess subthalamic γ oscillations may contribute to REM instability and RBD, suggesting that γ oscillation could serve as a feedback signal for adaptive DBS for REM sleep disorders. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Proceedings of the 12th annual deep brain stimulation think tank: cutting edge technology meets novel applications

The Deep Brain Stimulation (DBS) Think Tank XII was held on August 21st to 23rd. This year we showcased groundbreaking advancements in neuromodulation technology, focusing heavily on the novel uses of existing technology as well as next-generation technology. Our keynote speaker shared the vision of using neuro artificial intelligence to predict depression using brain electrophysiology. Innovative applications are currently being explored in stroke, disorders of consciousness, and sleep, while established treatments for movement disorders like Parkinson's disease are being refined with adaptive stimulation. Neuromodulation is solidifying its role in treating psychiatric disorders such as depression and obsessive-compulsive disorder, particularly for patients with treatment-resistant symptoms. We estimate that 300,000 leads have been implanted to date for neurologic and neuropsychiatric indications. Magnetoencephalography has provided insights into the post-DBS physiological changes. The field is also critically examining the ethical implications of implants, considering the long-term impacts on clinicians, patients, and manufacturers.

Stimulation-Evoked Resonant Neural Activity in the Subthalamic Nucleus Is Modulated by Sleep

BACKGROUND

Deep brain stimulation is a treatment for advanced Parkinson's disease and currently tuned to target motor symptoms during daytime. Parkinson's disease is associated with multiple nocturnal symptoms such as akinesia, insomnia, and sleep fragmentation, which may require adjustments of stimulation during sleep for best treatment outcome.

OBJECTIVES

There is a need for a robust biomarker to guide stimulation titration across sleep stages. This study aimed to investigate whether evoked resonant neural activity (ERNA) is modulated by sleep.

METHODS

We recorded local field potentials from the subthalamic nucleus of four Parkinson's patients with externalized electrodes while applying single stimulation pulses to investigate the effect of sleep on ERNA.

RESULTS

We found that ERNA features change with wakefulness and sleep stages and are correlated with canonical frequency bands and heart rate.

CONCLUSIONS

Given that ERNA modulates with sleep, it could be used as a robust marker for automatic stimulation titration during sleep. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Insomnia in Parkinson's Disease: Causes, Consequences, and Therapeutic Approaches

Sleep disorders represent prevalent non-motor symptoms in Parkinson's disease (PD), affecting over 90% of the PD population. Insomnia, characterized by difficulties in initiating and maintaining sleep, emerges as the most frequently reported sleep disorder in PD, with prevalence rates reported from 27 to 80% across studies. Insomnia not only significantly impacts the quality of life of PD patients but is also associated with cognitive impairment, motor disabilities, and emotional deterioration. This comprehensive review aims to delve into the mechanisms underlying insomnia in PD, including neurodegenerative changes, basal ganglia beta oscillations, and circadian rhythms, to gain insights into the neural pathways involved. Additionally, the review explores the risk factors and comorbidities associated with insomnia in PD, providing valuable insights into its management. Special attention is given to the challenges faced by healthcare providers in delivering care to PD patients and the impact of caregiving roles on patients' quality of life. Overall, this review provides a comprehensive understanding of insomnia in PD and highlights the importance of addressing this common sleep disorder in PD patients.

Cortical beta oscillations map to shared brain networks modulated by dopamine

Brain rhythms can facilitate neural communication for the maintenance of brain function. Beta rhythms (13-35 Hz) have been proposed to serve multiple domains of human ability, including motor control, cognition, memory, and emotion, but the overarching organisational principles remain unknown. To uncover the circuit architecture of beta oscillations, we leverage normative brain data, analysing over 30 hr of invasive brain signals from 1772 channels from cortical areas in epilepsy patients, to demonstrate that beta is the most distributed cortical brain rhythm. Next, we identify a shared brain network from beta-dominant areas with deeper brain structures, like the basal ganglia, by mapping parametrised oscillatory peaks to whole-brain functional and structural MRI connectomes. Finally, we show that these networks share significant overlap with dopamine uptake as indicated by positron emission tomography. Our study suggests that beta oscillations emerge in cortico-subcortical brain networks that are modulated by dopamine. It provides the foundation for a unifying circuit-based conceptualisation of the functional role of beta activity beyond the motor domain and may inspire an extended investigation of beta activity as a feedback signal for closed-loop neurotherapies for dopaminergic disorders.

Unraveling the Complexity of Parkinson's Disease: Insights into Pathogenesis and Precision Interventions

Parkinson's disease (PD) is a neurodegenerative disorder characterized by dopaminergic neuron loss, leading to motor and non-motor symptoms. Early detection before symptom onset is crucial but challenging. This study presents a framework integrating circuit modeling, non-equilibrium dynamics, and optimization to understand PD pathogenesis and enable precision interventions. Neuronal firing patterns, particularly oscillatory activity, play a critical role in PD pathology. The basal ganglia network, specifically the subthalamic nucleus-external globus pallidus (STN-GPe) circuitry, exhibits abnormal activity associated with motor dysfunction. The framework leverages the non-equilibrium landscape and flux theory to identify key connections generating pathological activity, providing insights into disease progression and potential intervention points. The intricate STN-GPe interplay is highlighted, shedding light on compensatory mechanisms within this circuitry may initially counteract changes but later contribute to pathological alterations as disease progresses. The framework addresses the need for comprehensive evaluation methods to assess intervention outcomes. Cross-correlations between state variables provide superior early warning signals compared to traditional indicators relying on critical slowing down. By elucidating compensatory mechanisms and circuit dynamics, the framework contributes to improved management, early detection, risk assessment, and potential prevention/delay of PD development. This pioneering research paves the way for precision medicine in neurodegenerative disorders.

Structural Brain Connectivity Guided Optimal Contact Selection for Deep Brain Stimulation of the Subthalamic Nucleus

BACKGROUND

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective therapy in ameliorating the motor symptoms of Parkinson disease. However, postoperative optimal contact selection is crucial for achieving the best outcome of deep brain stimulation of the subthalamic nucleus surgery, but the process is currently a trial-and-error and time-consuming procedure that relies heavily on surgeons' clinical experience.

METHODS

In this study, we propose a structural brain connectivity guided optimal contact selection method for deep brain stimulation of the subthalamic nucleus. Firstly, we reconstruct the DBS electrode location and estimate the stimulation range using volume of tissue activated from each DBS contact. Then, we extract the structural connectivity features by concatenating fractional anisotropy and the number of streamlines features of activated regions and the whole brain regions. Finally, we use a convolutional neural network with convolutional block attention module to identify the structural connectivity features for the optimal contact selection.

RESULTS

We review the data of 800 contacts from 100 patients with Parkinson disease for the experiment. The proposed method achieves promising results, with the average accuracy of 97.63%, average precision of 94.50%, average recall of 94.46%, and average specificity of 98.18%, respectively. Our method can provide the suggestion for optimal contact selection.

CONCLUSIONS

Our proposed method can improve the efficiency and accuracy of DBS optimal contact selection, reduce the dependence on surgeons' experience, and has the potential to facilitate the development of advanced DBS technology.

Chronic intracranial recordings in the globus pallidus reveal circadian rhythms in Parkinson's disease

Circadian rhythms have been shown in the subthalamic nucleus (STN) in Parkinson's disease (PD), but only a few studies have focused on the globus pallidus internus (GPi). This retrospective study investigates GPi circadian rhythms in a large cohort of subjects with PD (130 recordings from 93 subjects) with GPi activity chronically recorded in their home environment. We found a significant change in GPi activity between daytime and nighttime in most subjects (82.4%), with a reduction in GPi activity at nighttime in 56.2% of recordings and an increase in activity in 26.2%. GPi activity in higher frequency bands ( > 20 Hz) was more likely to decrease at night and in patients taking extended-release levodopa medication. Our results suggest that circadian fluctuations in the GPi vary across individuals and that increased power at night might be due to the reemergence of pathological neural activity. These findings should be considered to ensure successful implementation of adaptive neurostimulation paradigms in the real-world.

Generalized sleep decoding with basal ganglia signals in multiple movement disorders

Sleep disturbances profoundly affect the quality of life in individuals with neurological disorders. Closed-loop deep brain stimulation (DBS) holds promise for alleviating sleep symptoms, however, this technique necessitates automated sleep stage decoding from intracranial signals. We leveraged overnight data from 121 patients with movement disorders (Parkinson's disease, Essential Tremor, Dystonia, Essential Tremor, Huntington's disease, and Tourette's syndrome) in whom synchronized polysomnograms and basal ganglia local field potentials were recorded, to develop a generalized, multi-class, sleep specific decoder - BGOOSE. This generalized model achieved 85% average accuracy across patients and across disease conditions, even in the presence of recordings from different basal ganglia targets. Furthermore, we also investigated the role of electrocorticography on decoding performances and proposed an optimal decoding map, which was shown to facilitate channel selection for optimal model performances. BGOOSE emerges as a powerful tool for generalized sleep decoding, offering exciting potentials for the precision stimulation delivery of DBS and better management of sleep disturbances in movement disorders.

Multi-night cortico-basal recordings reveal mechanisms of NREM slow-wave suppression and spontaneous awakenings in Parkinson's disease

Sleep disturbance is a prevalent and disabling comorbidity in Parkinson's disease (PD). We performed multi-night (n = 57) at-home intracranial recordings from electrocorticography and subcortical electrodes using sensing-enabled Deep Brain Stimulation (DBS), paired with portable polysomnography in four PD participants and one with cervical dystonia (clinical trial: NCT03582891). Cortico-basal activity in delta increased and in beta decreased during NREM (N2 + N3) versus wakefulness in PD. DBS caused further elevation in cortical delta and decrease in alpha and low-beta compared to DBS OFF state. Our primary outcome demonstrated an inverse interaction between subcortical beta and cortical slow-wave during NREM. Our secondary outcome revealed subcortical beta increases prior to spontaneous awakenings in PD. We classified NREM vs. wakefulness with high accuracy in both traditional (30 s: 92.6 ± 1.7%) and rapid (5 s: 88.3 ± 2.1%) data epochs of intracranial signals. Our findings elucidate sleep neurophysiology and impacts of DBS on sleep in PD informing adaptive DBS for sleep dysfunction.

Slow-wave sleep dysfunction in mild parkinsonism is associated with excessive beta and reduced delta oscillations in motor cortex

Increasing evidence suggests slow-wave sleep (SWS) dysfunction in Parkinson's disease (PD) is associated with faster disease progression, cognitive impairment, and excessive daytime sleepiness. Beta oscillations (8-35 Hz) in the basal ganglia thalamocortical (BGTC) network are thought to play a role in the development of cardinal motor signs of PD. The role cortical beta oscillations play in SWS dysfunction in the early stage of parkinsonism is not understood, however. To address this question, we used a within-subject design in a nonhuman primate (NHP) model of PD to record local field potentials from the primary motor cortex (MC) during sleep across normal and mild parkinsonian states. The MC is a critical node in the BGTC network, exhibits pathological oscillations with depletion in dopamine tone, and displays high amplitude slow oscillations during SWS. The MC is therefore an appropriate recording site to understand the neurophysiology of SWS dysfunction in parkinsonism. We observed a reduction in SWS quantity (p = 0.027) in the parkinsonian state compared to normal. The cortical delta (0.5-3 Hz) power was reduced (p = 0.038) whereas beta (8-35 Hz) power was elevated (p = 0.001) during SWS in the parkinsonian state compared to normal. Furthermore, SWS quantity positively correlated with delta power (r = 0.43, p = 0.037) and negatively correlated with beta power (r = -0.65, p < 0.001). Our findings support excessive beta oscillations as a mechanism for SWS dysfunction in mild parkinsonism and could inform the development of neuromodulation therapies for enhancing SWS in people with PD.

Multi-night cortico-basal recordings reveal mechanisms of NREM slow wave suppression and spontaneous awakenings at high-temporal resolution in Parkinson's disease

Background

Sleep disturbance is a prevalent and highly disabling comorbidity in individuals with Parkinson's disease (PD) that leads to worsening of daytime symptoms, reduced quality of life and accelerated disease progression.

Objectives

We aimed to record naturalistic overnight cortico-basal neural activity in people with PD, in order to determine the neurophysiology of spontaneous awakenings and slow wave suppression in non-rapid eye movement (NREM) sleep, towards the development of novel sleep-targeted neurostimulation therapies.

Methods

Multi-night (n=58) intracranial recordings were performed at-home, from chronic electrocorticography and subcortical electrodes, with sensing-enabled Deep Brain Stimulation (DBS), paired with portable polysomnography. Four participants with PD and one participant with cervical dystonia were evaluated to determine the neural structures, signals and functional connectivity modulated during NREM sleep and prior to spontaneous awakenings. Intracranial recordings were performed both ON and OFF DBS to evaluate the impact of stimulation. Sleep staging was then classified with machine-learning models using intracranial cortico-basal signals on classical (30 s) and rapid (5 s) timescales.

Results

We demonstrate an increase in cortico-basal slow wave delta (1-4 Hz) activity and a decrease in beta (13-31 Hz) activity during NREM (N2 and N3) versus wakefulness in PD. Cortical-basal ganglia coherence was also found to be higher in the delta range and lower in the beta range during NREM. DBS stimulation resulted in a further elevation in cortical delta and a decrease in alpha (8-13 Hz) and low beta (13-15 Hz) power compared to the OFF stimulation state. Within NREM sleep, we observed a strong inverse interaction between subcortical beta and cortical slow wave activity and found that subcortical beta increases prior to spontaneous awakenings at high-temporal resolution (5s). Our machine-learning models trained on intracranial cortical or subcortical power features achieved high accuracy in both traditional (30s) and rapid (5s) time windows for NREM vs. wakefulness classification (30s: 92.6±1.7%; 5s: 88.3±2.1%).

Conclusions

Chronic, multi-night recordings in PD reveal increased cortico-basal slow wave, decreased beta activity, and changes in functional connectivity in NREM vs wakefulness, effects that are enhanced in the presence of DBS. Within NREM, subcortical beta and cortical delta are strongly inversely correlated and subcortical beta power increases prior to spontaneous awakenings. Our findings elucidate the network-level neurophysiology of sleep dysfunction in PD and the mechanistic impact of conventional DBS. Additionally, through accurate machine-learning classification of spontaneous awakenings, this study also provides a foundation for future personalized adaptive DBS therapies for sleep dysfunction in PD.

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

Increasing evidence associates slow-wave sleep (SWS) dysfunction with neurodegeneration. Using a within-subject design in the nonhuman primate model of Parkinson's disease (PD), we found that reduced SWS quantity in mild parkinsonism was accompanied by elevated beta and reduced delta power during SWS in the motor cortex. Our findings support excessive beta oscillations as a mechanism for SWS dysfunction and will inform development of neuromodulation therapies for enhancing SWS in PD.