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Study Objectives: Deep brain stimulation (DBS) of the subthalamic nucleus (STN) may improve sleep dysfunction, a common non-motor symptom of Parkinson disease (PD). Improvement in motor symptoms correlates with DBS-suppressed local field potential (LFP) activity, particularly in the beta frequency (13 - 30 Hz). Although well-characterized in the short term, little is known about the innate progression of these oscillations across the sleep-wake cycle. We sought to characterize LFP fluctuations over several days and nights in the home setting in patients chronically treated with DBS., Methods: LFPs in the beta and alpha frequency range were recorded from the STN in 13 PD subjects (18 hemispheres) over 14.6 (interquartile range 4) days. Sleep and wake were determined by validated actigraphy. We calculated the mean difference between sleep and wakefulness in LFP power (µVp), probability density functions of normalized LFP, and the fraction of overlap between probability density histograms., Results: STN LFPs showed a consistent fluctuation based on behavioral state. LFP power was higher during wakefulness than during sleep, with little overlap in the magnitude of LFP power between these two states. Delineation of subject activity patterns revealed that LFP variance by time of day was more strongly correlated at night., Conclusions: STN LFP fluctuations represent a useful measure to distinguish between sleep and wakefulness in PD. These fluctuations can be detected in the home setting using commercially available devices, including in patients who have been treated with DBS for years. This technology may lead to opportunities for closed-loop DBS therapy., (© The Author(s) 2025. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Oscillatory activity within the beta frequency range (13-30 Hz) serves as a Parkinson's disease biomarker for tailoring deep brain stimulation (DBS) treatments. Currently, identifying clinically relevant beta signals, specifically frequencies of peak amplitudes within the beta spectral band, is a subjective process. To inform potential strategies for objective clinical decision making, we assessed algorithms for identifying beta peaks and devised a standardized approach for both research and clinical applications. Employing a novel monopolar referencing strategy, we utilized a brain sensing device to measure beta peak power across distinct contacts along each DBS electrode implanted in the subthalamic nucleus. We then evaluated the accuracy of ten beta peak detection algorithms against a benchmark established by expert consensus. The most accurate algorithms, all sharing similar underlying algebraic dynamic peak amplitude thresholding approaches, matched the expert consensus in performance and reliably predicted the clinical stimulation parameters during follow-up visits. These findings highlight the potential of algorithmic solutions to overcome the subjective bias in beta peak identification, presenting viable options for standardizing this process. Such advancements could lead to significant improvements in the efficiency and accuracy of patient-specific DBS therapy parameterization., (© 2024. The Author(s).)

Introduction: Sleep dysfunction is frequently experienced by people with Parkinson's disease (PD) and negatively influences quality of life. Although subthalamic nucleus (STN) deep brain stimulation (DBS) can improve sleep in PD, sleep microstructural features such as sleep spindles provide additional insights about healthy sleep. For example, sleep spindles are important for better cognitive performance and for sleep consolidation in healthy adults. We hypothesized that conventional STN DBS settings would yield a greater enhancement in spindle density compared to OFF and low frequency DBS., Methods: In a previous within-subject, cross-sectional study, we evaluated effects of low (60 Hz) and conventional high (≥130 Hz) frequency STN DBS settings on sleep macroarchitectural features in individuals with PD. In this post hoc , exploratory analysis, we conducted polysomnography (PSG)-derived quantitative electroencephalography (qEEG) assessments in a cohort of 15 individuals with PD who had undergone STN DBS treatment a median 13.5 months prior to study participation. Fourteen participants had unilateral DBS and 1 had bilateral DBS. During three nonconsecutive nights of PSG, the participants were assessed under three different DBS conditions: DBS OFF, DBS LOW frequency (60 Hz), and DBS HIGH frequency (≥130 Hz). The primary objective of this study was to investigate the changes in sleep spindle density across the three DBS conditions using repeated-measures analysis of variance. Additionally, we examined various secondary outcomes related to sleep qEEG features. For all participants, PSG-derived EEG data underwent meticulous manual inspection, with the exclusion of any segments affected by movement artifact. Following artifact rejection, sleep qEEG analysis was conducted on frontal and central leads. The measures included slow wave (SW) and spindle density and morphological characteristics, SW-spindle phase-amplitude coupling, and spectral power analysis during non-rapid eye movement (NREM) sleep., Results: The analysis revealed that spindle density was significantly higher in the DBS HIGH condition compared to the DBS LOW condition. Surprisingly, we found that SW amplitude during NREM was significantly higher in the DBS LOW condition compared to DBS OFF and DBS HIGH conditions. However, no significant differences were observed in the other sleep qEEG features during sleep at different DBS conditions., Conclusion: This study presents preliminary evidence suggesting that conventional HIGH frequency DBS settings enhance sleep spindle density in PD. Conversely, LOW frequency settings may have beneficial effects on increasing slow wave amplitude during sleep. These findings may inform mechanisms underlying subjective improvements in sleep quality reported in association with DBS. Moreover, this work supports the need for additional research on the influence of surgical interventions on sleep disorders, which are prevalent and debilitating non-motor symptoms in PD., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Memon, Edney, Baumgartner, Gardner, Catiul, Irwin, Joop, Miocinovic and Amara.)

Parkinson's disease (PD) is a neurodegenerative disorder characterized by loss of dopaminergic neurons and dysregulation of the basal ganglia. Cardinal motor symptoms include bradykinesia, rigidity, and tremor. Deep brain stimulation (DBS) of select subcortical nuclei is standard of care for medication-refractory PD. Conventional open-loop DBS delivers continuous stimulation with fixed parameters that do not account for a patient's dynamic activity state or medication cycle. In comparison, closed-loop DBS, or adaptive DBS (aDBS), adjusts stimulation based on biomarker feedback that correlates with clinical state. Recent work has identified several neurophysiological biomarkers in local field potential recordings from PD patients, the most promising of which are 1 ) elevated beta (∼13-30 Hz) power in the subthalamic nucleus (STN), 2 ) increased beta synchrony throughout basal ganglia-thalamocortical circuits, notably observed as coupling between the STN beta phase and cortical broadband gamma (∼50-200 Hz) amplitude, and 3 ) prolonged beta bursts in the STN and cortex. In this review, we highlight relevant frequency and time domain features of STN beta measured in PD patients and summarize how spectral beta power, oscillatory beta synchrony, phase-amplitude coupling, and temporal beta bursting inform PD pathology, neurosurgical targeting, and DBS therapy. We then review how STN beta dynamics inform predictive, biomarker-driven aDBS approaches for optimizing PD treatment. We therefore provide clinically useful and actionable insight that can be applied toward aDBS implementation for PD.

The neurosurgical treatment of movement disorders, primarily via deep brain stimulation (DBS), is a rapidly expanding and evolving field. Although conventional targets including the subthalamic nucleus (STN) and internal segment of the globus pallidus (GPi) for Parkinson's disease and ventral intermediate nucleus of the thalams (VIM) for tremor provide substantial benefit in terms of both motor symptoms and quality of life, other targets for DBS have been explored in an effort to maximize clinical benefit and also avoid undesired adverse effects associated with stimulation. These novel targets primarily include the rostral zona incerta (rZI), caudal zona incerta (cZI)/posterior subthalamic area (PSA), prelemniscal radiation (Raprl), pedunculopontine nucleus (PPN), substantia nigra pars reticulata (SNr), centromedian/parafascicular (CM/PF) nucleus of the thalamus, nucleus basalis of Meynert (NBM), dentato-rubro-thalamic tract (DRTT), dentate nucleus of the cerebellum, external segment of the globus pallidus (GPe), and ventral oralis (VO) complex of the thalamus. However, reports of outcomes utilizing these targets are scattered and disparate. In order to provide a comprehensive resource for researchers and clinicians alike, we have summarized the existing literature surrounding these novel targets, including rationale for their use, neurosurgical techniques where relevant, outcomes and adverse effects of stimulation, and future directions for research., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Baumgartner, Kushida, Summers, Kern, Abosch and Thompson.)

Objective: There is a harmful myth that persists in modern culture that one should place objects into a seizing person's mouth to prevent "swallowing the tongue." Despite expert guidelines against this, the idea remains alive in popular media and public belief. We aimed to investigate the myth's origins and discredit it., Methods: A medical and popular literature review was conducted for the allusions to "swallowing one's tongue" and practice recommendations for and against placing objects into a seizing person's mouth. Current prevalence of these beliefs and relevant anatomy and physiology were summarised., Results: The first English language allusions to placing objects in a patient's mouth occurred in the mid-19th century, and the first allusions to swallowing one's tongue during a seizure occurred in the late 19th century. By the mid-20th century, it was clear that some were recommending against the practice of placing objects in a patient's mouth to prevent harm. Relatively recent popular literature and film continue to portray incorrect seizure first aid through at least 2013. There is ample modern literature confirming the anatomical impossibility of swallowing one's tongue and confirming the potential harm of putting objects in a patient's mouth., Conclusion: One cannot swallow their tongue during a seizure. Foreign objects should not be placed into a seizing person's mouth. We must continue to disseminate these ideas to our patients and colleagues. As neurologists, we have an obligation to champion safe practices for our patients, especially when popular media and culture continue to propagate dangerous ones., (Copyright © 2020 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.)

The North Shore Community Mental Health Center has an unusual mental health delivery system. "Out-stationed" staff work in affiliated agencies, yet are employees of the NSCMHC. This service configuration is the result of an arduous planning process which weighed the advantages of several organizational models. On one extreme was a "Centralized" model, wherein one organization was solely responsible for delivering mental health services. On the other extreme was an "Umbrella" model, wherein the organization acted as a fiscal conduit to several service providers. Somewhere in the middle a compromise was found with a "Lead Agency" model. Here, an organization provides the administrative structure, provides some services, and subcontracts the remaining services. The North Shore Community Mental Health Center adapted this system one step further. Rather than subcontracting services, it outstationed CMHC staff to affiliate agencies. United Cerebral Palsy Association of the North Shore is one of the CMHC's affiliates. The service need for family and play therapists resulted in two CMHC therapists being outstationed at UCP. The affiliation agreement between the two organizations specify the responsibilities and roles each have. The hiring process between the two organizations is an example of the duality of the system. Both agencies had interviewing roles, yet the final hiring decision was the affiliate's, since the employee would spend the majority of his/her time outstationed at the affiliate side. Outstationed staff integration to the North Shore Community Mental Health Center presented problems, however. Since these were new staff hired with federal funds, and since their visibility at the Center was minimal, they had some difficulty being identified as Center staff by existing employees.(ABSTRACT TRUNCATED AT 250 WORDS)