Path Toward MRI with Direct Sensitivity to Neuro-Electro-Magnetic Oscillations
Path Toward MRI with Direct Sensitivity to Neuro-Electro-Magnetic Oscillations
批准号:
8826908
负责人:
ALLEN W SONG
金额:
$47.1万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-09-26 至 2017-06-30
关键词:
AddressAdvisory CommitteesBehaviorBehavioralBiological Neural NetworksBrainBrain MappingBrain imagingCerealsCommunitiesDetectionEducational workshopEnsureEtiologyEventFoundationsFunctional Magnetic Resonance ImagingGoalsGrowthHumanImageImaging technologyIndividualInterdisciplinary StudyIntrinsic driveInvestigationKnowledgeLaboratoriesLinkMagnetic Resonance ImagingMagnetismMapsMeasurementMeasuresMental disordersMethodologyMethodsModelingMonoclonal Antibody R24MotorNeuronsNeurosciencesNoiseOutputPatientsPatternPhysiologic pulsePilot ProjectsProcessRequest for ApplicationsResearchResearch ActivityResearch PersonnelResidual stateResolutionResourcesRoboticsSignal TransductionSolidStructureTechniquesTechnologyTimeValidationVisual Cortexbasebrain electrical activitybrain machine interfacebrain researchexoskeletonhemodynamicsin vivoinnovationinsightmagnetic fieldneuroimagingneurotechnologynext generationnonhuman primatepublic health relevancerelating to nervous systemresponsesensorimotor systemtoolultra high resolution
中文摘要
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英文摘要
DESCRIPTION (provided by applicant): In response to the NIH RFA-MH-14-217 on "Planning for Next Generation Human Brain Imaging", we propose a comprehensive plan to organize the much needed technological resources and interdisciplinary research team for developing the next generation MRI technology that can directly detect neuroelectric activities in the human brain with a high spatial and temporal resolution, using scanners with the 3 Tesla magnetic field strength that is accessible by the majority of neuroimaging researchers. Through our encouraging preliminary investigations, we have determined that it is possible to precisely map brain activities by directly sensitizing the MRI signal to the neuro-electro-magnetic oscillations (NEMO). At the same time, we have also identified key challenges in MRI hardware, acquisition methods, and contrast mechanisms to fully enable this approach. We will address these challenges by organizing three innovative technical cores (in the form of Technical Aims) for the purpose of enabling an ultra-uniform magnetic field throughout the brain to ensure a robust detection of the NEMO signal, reaching ultra-high spatial resolutions that can resolve fine-grained cortical microstructures, and building a non-invasive human brain-machine interface (BMI) that models and classifies the functional neuroimaging signals and drives an attached robotic exoskeleton. To establish convincing evidences toward a direct and sensitive MRI detection of neuroelectric activity, and based on our solid technical foundation, we also propose four innovative pilot projects (in the form of Scientific Aims) to construct a static neural networ with causal information using high-resolution MRI, to investigate dynamic NEMO signals in vivo with enhanced sensitivity during both driven and intrinsic neuronal oscillations, and to model and classify the dynamic neuroimaging signals and to replicate and validate the human behavior in the robotic exoskeleton through our non-invasive human BMI. To help evaluate our research progress and receive critical input from researchers and leaders in the brain research community, we will organize annual workshops coordinated by our interdisciplinary research team and our scientific advisory committee. We anticipate that through these comprehensive planning and research activities, we will be able to define a clear path to reach the next generation human brain imaging technology that can precisely, non-invasively, and unambiguously map brain activities with unprecedented spatial and temporal resolution.
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