Intrinsic Cortical Networks and Cognitive Dysfunction in Parkinson's Disease

帕金森病的内在皮质网络和认知功能障碍

• 批准号: 9084675
• 负责人: BENZI M KLUGER
• 金额: $ 13.24万
• 依托单位: UNIVERSITY OF COLORADO DENVER
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-23 至 2018-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9084675
• 关键词: Adult; Affect; Alzheimer' s Disease; Area; Biological Markers; Brain; Caregivers; Cephalic; Clinical Data; Clinical Trials; Cognition; Cognitive; Data; Dementia; Development; Double-Blind Method; Elderly; Foundations; Frequencies; Functional disorder; Funding; Future; Goals; Health; Impaired cognition; Intervention; K-Series Research Career Programs; Lead; Link; Machine Learning; Magnetism; Magnetoencephalography; Manuscripts; Measures; Medical; Memory; Mentors; Modeling; Motor Cortex; Neurodegenerative Disorders; Nursing Homes; Operative Surgical Procedures; Outcome; Parkinson Disease; Parkinson' s Dementia; Pathology; Patients; Pattern; Physiological; Physiology; Population; Prevention; Publications; Publishing; Randomized Controlled Trials; Research; Research Activity; Rest; Test Result; Testing; Therapeutic; Therapeutic Intervention; Thinking; Training; Transcranial magnetic stimulation; Work; base; biomarker development; biomarker identification; career; career development; clinically relevant; cognitive ability; cognitive change; cognitive function; cognitive testing; effective therapy; encephalography; graph theory; high risk; improved; innovation; mild cognitive impairment; motor symptom; neurobiological mechanism; neurophysiology; new therapeutic target; novel; novel marker; physiologic model; programs; screening; skills; theories; therapeutic target

DESCRIPTION (provided by applicant): Parkinson's disease (PD) affects 1% of adults over age 65. While traditionally defined by motor symptoms, up to 75% of PD patients will eventually develop dementia making it the leading cause of nursing home placement in this population. Although there is currently no cure for PD, our ability to treat motor symptoms has advanced tremendously since the 1960's based on advances in our understanding of motor symptom neurophysiology. I propose that the treatment and prevention of dementia in PD may also prove possible through advances in our understanding of the neurophysiology of cognitive dysfunction. I will use modern network theory as a theoretical and mathematical framework for this endeavor. My long-term goal is to advance our fundamental understanding of the neurophysiology of cognitive dysfunction in PD to provide empirically testable models, clinically relevant biomarkers, and novel therapeutic targets. The central hypothesis of this proposal is that patterns of cortical functional connectivity critical to normal cognitive function are disruptd by subcortical pathology in PD and that interventions which normalize these patterns will improve cognition. This hypothesis has been formulated on the basis of preliminary data presented in this proposal and other previously published work. The research objectives of this proposal are to further our understanding of how cortical connectivity relates to cognitive dysfunction in PD, develop a novel biomarker for cognitive dysfunction in PD based on cortical physiology and to determine whether modulation of cortical connectivity may result in cognitive improvements in PD. We will accomplish the objectives of this proposal through three Specific Aims: 1) Determine whether graph theory measures of functional cortical activity measured with magneto encephalography (MEG) are associated with cognitive dysfunction in PD subjects with and without mild cognitive impairment (MCI); 2) Develop a novel state-defining biomarker for cognitive dysfunction in PD based on MEG features through a machine learning approach; and 3) Determine the effects of repetitive trans cranial magnetic stimulation (rTMS) on MEG measures of cortical connectivity and cognitive outcomes in PD-MCI patients. The approach is innovative because it represents the first study to apply graph theory measures to understanding the relationship of cortical physiology and cognitive dysfunction in PD; the first study to apply machine learning approaches to cognitive PD biomarker development; and the first clinical trial or mechanistic study of rTMS in PD-MCI. The proposed research is significant because it is expected to advance our understanding of the pathophysiology of cognitive dysfunction in PD and will provide biomarkers and pilot data essential to planning future therapeutic interventions. The training objectives and related research activities of this proposal will provide new skills, manuscripts and pilot data related to advanced MEG analysis, graph theory, biomarker development and rTMS trials necessary to establish my independence in these areas and obtain R01 funding to advance this unique research program.

描述（由申请人提供）：帕金森病（PD）影响1%的65岁以上成年人。虽然传统上由运动症状定义，但高达75%的PD患者最终会发展为痴呆症，使其成为该人群中养老院安置的主要原因。虽然目前还没有治愈帕金森病的方法，但自20世纪60年代以来，基于我们对运动症状神经生理学的理解的进步，我们治疗运动症状的能力已经取得了巨大的进步。我认为，通过我们对认知功能障碍的神经生理学的理解的进步，PD中痴呆的治疗和预防也可能被证明是可能的。我将使用现代网络理论作为这一努力的理论和数学框架。我的长期目标是推进我们对帕金森病认知功能障碍的神经生理学的基本理解，以提供经验可测试的模型、临床相关的生物标志物和新的治疗靶点。该建议的中心假设是，对正常认知功能至关重要的皮层功能连接模式被PD的皮层下病理破坏，而使这些模式正常化的干预措施将改善认知。这一假设是在本提案和其他先前发表的工作中提出的初步数据的基础上制定的。本课题的研究目的是进一步了解皮层连通性与PD认知功能障碍的关系，基于皮质生理学开发PD认知功能障碍的新型生物标志物，并确定皮质连通性的调节是否可能导致PD的认知改善。我们将通过三个具体目标来实现本提案的目标：1)确定用脑磁图（MEG）测量的功能性皮质活动的图论测量是否与有或无轻度认知障碍（MCI）的PD受试者的认知功能障碍相关；2)通过机器学习方法，基于脑磁图特征开发PD认知功能障碍的新型状态定义生物标志物；3)确定重复性经颅磁刺激（rTMS）对PD-MCI患者皮质连通性和认知结果的MEG测量的影响。该方法是创新的，因为它代表了第一个应用图论方法来理解PD患者皮层生理学和认知功能障碍之间关系的研究；第一个将机器学习方法应用于认知帕金森病生物标志物开发的研究；以及首个PD-MCI中rTMS的临床试验或机制研究。这项研究具有重要意义，因为它有望促进我们对帕金森病认知功能障碍病理生理学的理解，并将为规划未来的治疗干预提供必要的生物标志物和试点数据。本课题的培养目标及相关研究活动