Modeling TMS-induced Cortical Network Activity
Modeling TMS-induced Cortical Network Activity
批准号:
8581251
负责人:
Aapo Nummenmaa
金额:
$9.0万
依托单位国家:
美国
项目类别:
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-08-15 至 2015-07-31
关键词:
AnimalsAreaBoundary ElementsBrainBrain regionClinicalComplexComputational TechniqueComputer softwareComputing MethodologiesConsultationsDataDevelopmentDiffusionDistantEducationElectroencephalographyElectromagnetic FieldsElectromyographyElectrophysiology (science)ElementsEmerging TechnologiesEngineeringEvaluationFDA approvedFunctional Magnetic Resonance ImagingGoalsGrantHumanImageInstitutionInvestigationKnowledgeLengthLinkLocationMagnetic Resonance ImagingMagnetoencephalographyMathematicsMeasurementMeasuresMental DepressionMentorsMethodsModelingMotorMotor CortexMultimodal ImagingMuscleNeurosciencesOutcomePathway interactionsPerformancePhasePhysicsPhysiologicalPositioning AttributeResearchResearch PersonnelResolutionSecondary toSideSourceSystemTechniquesTestingTherapeutic StudiesTimeTrainingTranscranial magnetic stimulationValidationWeightWorkbasebioimagingcareercareer developmentclinical applicationdata acquisitionelectric fieldimprovedin vivoinstrumentationmillisecondneurophysiologynoveloperationpublic health relevancerelating to nervous systemresearch studyskillstool
中文摘要
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英文摘要
DESCRIPTION (provided by applicant): This project aims at developing novel methods for predicting the large-scale cortical network that is activated by spatially focused transcranial magnetic stimulation (TMS). Presently there is no integrated framework that would allow predicting how the activation will spread from the primary target area to secondary locations. The proposal will combine accurate and efficient electromagnetic field computation methods for calculating the primary activations with data from diffusion weighted magnetic resonance imaging (MRI) tractography to predict the effects of TMS on an anatomically connected cortical network. We will evaluate the modeling framework by measuring the effects of TMS with simultaneous electroencephalography EEG (TMS-EEG) and functional MRI (TMS-fMRI) in humans, and also using TMS adapted to small animals. During the mentored phase, I will utilize my training in theoretical physics, applied mathematics, and computational engineering to build a set of tools to model the TMS-induced network activity. Anatomical MRI data acquisitions and functional TMS-EEG and TMS-fMRI measurements will be carried out for verifying the proposed model. During the second phase, the software will be optimized for real-time operation and more extensive experiments for evaluation of the system performance and prediction accuracy will be carried out. This project optimally fits my long-term career goal of becoming a multi-disciplinary researcher capable of both methodological development and carrying out neuroscientific studies combining TMS with non-invasive imaging. The outcome of the proposed project will be an entirely novel framework for understanding the effects of TMS on cortical networks for scientific studies and therapeutic applications. The grant will allow me to reach the immediate goal of strengthening my skills in the experimental side of imaging neuroscience and broadening my knowledge of the neurophysiology of TMS. The mentored phase will be carried out at MGH-Harvard-MIT Martinos Center for Biomedical Imaging. The affiliated institutions offer first-rate education pertinent to my career development. Specifically, in addition to building my experimental expertise, I will audit courses on neural engineering and complex networks at Harvard and MIT. The collaborative effort for validating the models with a small animal TMS experiment will also provide hands-on training in electrophysiology. The Martinos Center has cutting edge imaging facilities for carrying out the experimental work and world-class experts available for mentoring and consultation.
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