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Spatiotemporal Patterns of Network Dysfunction in Alzheimer's Disease

阿尔茨海默病网络功能障碍的时空模式

基本信息

批准号：
9051982
负责人：
Kamalini Gayathree Ranasinghe
金额：
$ 6.03万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-03-05 至 2019-03-04
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9051982
关键词：
Affect Age Alzheimer&apos s Disease Animal Model Area Auditory Auditory area Behavioral Bilateral Biological Markers Biological Neural Networks Brain Brain region Clinical Clinical Trials Cognition Cognitive deficits Communication Computer software Dementia Development Plans Disease Doctor of Philosophy Dorsal Early Diagnosis Elderly Feedback Frequencies Functional Magnetic Resonance Imaging Functional disorder Goals Hearing Human Image Impaired cognition Individual Knowledge Language Language Disorders Measures Mentors Methodology Methods Motor Neurobehavioral Manifestations Neurodegenerative Disorders Neurons Neurosciences Patient Care Patients Pattern Performance Phase Physicians Physiological Physiology Population Preparation Process Reproduction Research Research Proposals Resolution Rodent Scientist Sensory Speech Speech Sound Staging Stream Symptoms Synapses Techniques Training Transgenic Mice Translational Research Voice auditory feedback behavior measurement behavioral response career career development cognitive function design effective therapy experience improved innovation millisecond motor control mouse model network dysfunction neural patterning neurobehavioral neurodegenerative dementia neuroimaging neurophysiology novel prevent public health relevance relating to nervous system research study response spatiotemporal speech processing temporal measurement

项目摘要

DESCRIPTION (provided by applicant): Alzheimer's disease (AD) is the most frequent neurodegenerative disorder and the most common cause of dementia in the elderly. Unfortunately, there are still no effective treatments to prevent, halt, or reverse AD. As new clinical trials focus on the initial stages of disease, early diagnosis is now more important than ever. Human neuroimaging has greatly improved our knowledge of this disease by demonstrating selectively vulnerable large-scale networks whose connectivity declines in AD. Transgenic mouse models of AD have identified specific brain regions whose aberrant excitatory activity causes neuronal network dysfunction. However, the exact relationship between neural network abnormalities in animal models with that in the human condition remains unknown. To better understand the altered neural dynamics underlying clinical symptoms in AD will require novel techniques and methodologies. Speech and language abnormalities are evident in AD patients from the very early stages of the disease. We propose to use a novel magnetoencephalographic imaging (MEGI) approach to determine the speech- motor-network deficits of AD-spectrum patients. MEGI provides direct recordings of brain activity with precise millisecond resolution. The goal of this study is to understand the spatial patterns and temporal dynamics of speech encoding and speech execution in AD patients. Using customized software we will measure brain activity patterns across high and low frequency bands. We expect to find unique signatures of speech-motor- network dysconnectivity in AD. Such knowledge will be related to underlying synaptic dysfunctions of vulnerable neuronal populations as early biomarkers of the disease and will have important implications for translational research. The candidate is a physician-scientist with a strong commitment to a career in neurodegenerative dementia research. The candidate has an MD and a PhD in cognition and neuroscience. The research proposal and career development plan build upon her training in rodent neurophysiology and auditory and speech processing to provide expertise in human brain connectivity and its relationship to cognitive deficits in AD. Dr. Keith Vossel, a physician-scientist who cares for patients with dementia and specializes in transgenic mouse models of neurodegenerative disease, is the candidate's sponsor. The mentoring and research experience described in this proposal will facilitate the candidate's goal of developing a strong independent research career.