Spatiotemporal Patterns of Network Dysfunction in Alzheimer's Disease
Spatiotemporal Patterns of Network Dysfunction in Alzheimer's Disease
批准号:
9231998
负责人:
Kamalini Gayathree Ranasinghe
金额:
$6.53万
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-03-05 至 2019-03-04
关键词:
AffectAgeAlzheimer&aposs DiseaseAlzheimer&aposs disease modelAnimal ModelAreaAuditory areaAwarenessBehavioralBilateralBiological MarkersBiological Neural NetworksBrainBrain DiseasesBrain regionClinicalClinical TrialsCognitionCognitive deficitsCommunicationComputer softwareCustomDementiaDeteriorationDevelopment PlansDiseaseDoctor of PhilosophyDorsalEarly DiagnosisElderlyFeedbackFrequenciesFunctional Magnetic Resonance ImagingFunctional disorderGoalsHearingHumanImpaired cognitionImpairmentIndividualKnowledgeLanguageLanguage DisordersMagnetoencephalographyMeasuresMentorsMethodologyMethodsMotorNeurobehavioral ManifestationsNeurodegenerative DisordersNeuronsNeurosciencesPathologicPatient CarePatientsPatternPerformancePhasePhysiciansPhysiologicalPhysiologyPopulationPreparationReproductionResearchResearch ProposalsResolutionRodentScientistSensorySpeechSpeech SoundStreamSymptomsSynapsesTechniquesTrainingTransgenic MiceTranslational ResearchVoiceauditory feedbackauditory processingbehavior measurementbehavioral responsecareercareer developmentcognitive functiondesigneffective therapyexperienceexperimental studyimaging approachimaging studyimprovedinnovationmillisecondmotor controlmouse modelnetwork dysfunctionneural patterningneurobehavioralneurodegenerative dementianeuroimagingneurophysiologynovelpreventpublic health relevancerelating to nervous systemresponsespatiotemporalspeech processingtemporal measurement
中文摘要
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英文摘要
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.
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Multimodal imaging measures to assess synaptic dysfunction in Alzheimer's disease
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批准号:10448946
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项目类别:
-
资助金额:$48.4万
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财政年份:2022
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负责人:Kamalini Gayathree Ranasinghe
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依托单位:
Neurophysiological Assessments of Network Dysfunction in Alzheimer's Disease
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批准号:10377356
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项目类别:
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资助金额:$17.12万
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财政年份:2019
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负责人:Kamalini Gayathree Ranasinghe
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依托单位:
Neurophysiological Assessments of Network Dysfunction in Alzheimer's Disease
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批准号:9916699
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项目类别:
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资助金额:$17.21万
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财政年份:2019
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负责人:Kamalini Gayathree Ranasinghe
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依托单位:
Neurophysiological Assessments of Network Dysfunction in Alzheimer's Disease
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批准号:10623150
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项目类别:
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资助金额:$17.12万
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财政年份:2019
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负责人:Kamalini Gayathree Ranasinghe
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依托单位:
Spatiotemporal Patterns of Network Dysfunction in Alzheimer's Disease
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批准号:9051982
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项目类别:
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资助金额:$6.03万
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财政年份:2016
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负责人:Kamalini Gayathree Ranasinghe
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依托单位:
国内基金
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