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Determining the circuits and signals of sleep dysfunction in Parkinson's disease through chronic intracranial recordings and closed-loop Deep Brain Stimulation

Determining the circuits and signals of sleep dysfunction in Parkinson's disease through chronic intracranial recordings and closed-loop Deep Brain Stimulation
通过慢性颅内记录和闭环深部脑刺激确定帕金森病睡眠功能障碍的回路和信号
批准号:
10630021
负责人:
Simon Little
金额:
$66.62万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-04-01 至 2028-02-29

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英文摘要
ABSTRACT Sleep dysfunction is highly prevalent and disabling across a wide range of neurological and psychiatric conditions. In neurodegenerative diseases, including Alzheimer’s and Parkinson’s disease (PD), disruption of sleep architecture has been linked to worsening of daytime motor and neuropsychiatric symptoms, as well as accelerated disease progression. It therefore also marks a major, untapped therapeutic opportunity. However, it is currently not known which cortical and basal ganglia structures and signals are responsible for disrupting physiological sleep rhythms in PD. The rationale of this proposal is that identification of the cortical-basal signals which disrupt sleep architecture in PD is an essential next step for developing sleep-specific neuromodulation therapies. To date, a critical barrier to progress has been a lack of chronic intracranial neural recordings during sleep in PD. This urgent need can be addressed by leveraging recent developments in sensing-enabled Deep Brain Stimulation (DBS), supporting longitudinal, high-resolution, multi-site, intracranial recordings in patients’ own homes. The overall objective for this proposal is to establish the pathological network dynamics that disrupt healthy sleep in PD and how they are modulated by DBS. Our preliminary work demonstrates abnormal cortico- basal beta (13 - 30 Hz) and gamma (60 - 90 Hz) oscillations across different sleep phases in PD. Our central hypothesis is that these pathological overnight neural rhythms disrupt physiological sleep signals, including slow wave activity (<4 Hz), and induce maladaptive network changes during sleep to impact daytime cortico-basal neural activity and connectivity. We will use sensing-enabled, closed-loop, DBS devices that are chronically implanted in a cohort of 16 PD patients, combined with interpretable machine learning techniques, to identify cortico-basal signal and connectivity changes during sleep disruption in PD. We will then evaluate causal mechanisms of cortico-basal oscillations by measuring waking connectivity using cortical evoked responses and through applying sleep-stage dependent closed-loop DBS. Bridging this knowledge gap will characterize the pathological network dynamics of sleep in PD and uncover key mechanistic understandings linking sleep rhythms to waking network activity. This will provide a foundation for the development of closed-loop DBS approaches that can restore normal sleep in people with PD. Following successful completion of the proposed research, we expect our contribution to have determined the principal pathological oscillatory cortico-basal dynamics of sleep disruption in PD. The proposed research is innovative, using new sensing-enabled DBS for longitudinal sleep recordings plus closed-loop neuromodulation to evaluate cortico-basal network models of sleep dysfunction in PD. This contribution is expected to be significant because understanding the fundamental neurophysiology of sleep dysfunction in PD represents a critical knowledge gap towards developing precision neuromodulation therapies for sleep, daytime motor / non-motor symptoms and disease progression in PD, which will also inform on other neurological and psychiatric conditions.
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