Mobile electroencephalography & computational modelling to understand the role of sleep in disease progression in amnestic mild cognitive impairment

移动脑电图

• 批准号: 2749694
• 金额: --
• 依托单位: University of Bath
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2749694
• 关键词: Mobile; electroencephalography; computational; modelling; understand

Using mobile electroencephalography (EEG) and computational modelling to understand the role of sleep in disease progression in amnestic mild cognitive impairmentThe disruption of slow wave sleep (SWS) is implicated in the pathogenesis and functional consequences of dementia. SWS is critical for clearing toxic dementia-linked proteins, and plays an essential role in memory consolidation. Amnestic Mild Cognitive Impairment (aMCI) is the earliest identifiable stage of dementia, with the majority of patients progressing to Alzheimer's disease. Sleep quality is altered in aMCI, and linked to subsequent waking cognitive performance, however, study samples have been small and lacking EEG measures of sleep. Consequently, the link between SWS, aMCI and disease progression is unknown. Identifying SWS changes in aMCI could provide a significant therapeutic target for both disease-modification and symptom management. Historically sleep has been measured using polysomnography, requiring participants to stay overnight in sleep clinics, wearing sleep disruptive equipment. This project will be the first of its kind to harness cutting edge mobile, wearable EEG technology to revolutionise the clinical assessment of sleep in the home environment, with no experimenter present. DreemTM are market leader and project partner. The aims are to:1. Characterise changes to sleep in aMCI using remote, home-based EEG data collection.2. . Examine the relationship between SWS and waking cognitive performance3. Develop mathematical models using sleep EEG and predict the conversion of MCI to dementia Methods: 100 aMCI patients will be recruited from co-supervisor, Dr Coulthard's, ReMemBr Memory Clinic volunteer database of 1500 patients, over 2 years. They will complete standardised tests of cognition and sleep (ACE-III, PSQI), and be provided with a Dreem EEG headset and laptop. I will provide instructions to the patient and partner/carer via an online video call each night, for 1 acclimatisation + 7 test nights. Patients will also complete a novel EEG test battery (also via Dreem EEG), developed by Dr Stothart to assess attention, memory and language function. Patient clinical outcome, e.g. conversion to dementia, will be updated at 6 monthly intervals. Computational models will be developed using the spectral characteristics of sleep EEG to understand network dysfunction and predict conversion to dementia. Relevance to MRC: This research project fits within MRC's Neuroscience and Mental Health theme, which supports work that aims to advance our understanding of disorders of the brain and central nervous system so that new interventions and treatments can be developed.

使用移动脑电(EEG)和计算模型来了解睡眠在遗忘性轻度认知障碍疾病进展中的作用慢波睡眠(SWS)的中断与痴呆的发病机制和功能后果有关。SWS对清除有毒的痴呆症相关蛋白至关重要，并在记忆巩固中起着至关重要的作用。遗忘性轻度认知障碍是痴呆症的最早可识别阶段，大多数患者进展为阿尔茨海默病。睡眠质量在aMCI患者中会发生改变，并与随后的清醒认知表现有关，然而，研究样本一直很少，而且缺乏睡眠的脑电测量。因此，SWS、aMCI和疾病进展之间的联系尚不清楚。识别aMCI中SWS的变化可以为疾病改善和症状管理提供重要的治疗靶点。在历史上，睡眠测量是使用多导睡眠图来测量的，要求参与者戴着干扰睡眠的设备在睡眠诊所过夜。该项目将是第一个利用尖端移动可穿戴脑电技术来革命性地对家庭环境中的睡眠进行临床评估的项目，目前还没有实验人员出席。DreemTM是市场领导者和项目合作伙伴。其目的是：1.使用远程、基于家庭的脑电数据收集来描述睡眠在MCI中的变化。。研究主观幸福感和清醒认知表现之间的关系。使用睡眠脑电建立数学模型，并预测MCI向痴呆的转化。方法：100名aMCI患者将从共同主管，库特哈德博士的记忆诊所志愿者数据库中招募，为期两年。他们将完成标准化的认知和睡眠测试(ACE-III，PSQI)，并获得Dreem EEG耳机和笔记本电脑。我会每天晚上通过在线视频通话向患者和伴侣/护理员提供指导，进行1次适应+7次测试。患者还将完成一种新型的EEG测试组件(也通过Dreem EEG)，该测试组件由Stothart博士开发，用于评估注意力、记忆和语言功能。患者的临床结果，例如转化为痴呆症，将每6个月更新一次。将利用睡眠脑电的频谱特征开发计算模型，以了解网络功能障碍并预测转化为痴呆症。与MRC的相关性：这项研究项目符合MRC的神经科学和精神健康主题，该主题支持旨在促进我们对大脑和中枢神经系统疾病的了解的工作，以便开发新的干预和治疗方法。