Real-time fMRI Neurofeedback Based Stratification of Default Network Regulation
基于实时功能磁共振成像神经反馈的默认网络调节分层
基本信息
- 批准号:8849978
- 负责人:
- 金额:$ 60.96万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2013
- 资助国家:美国
- 起止时间:2013-07-23 至 2016-05-31
- 项目状态:已结题
- 来源:
- 关键词:AddressAdultAffectiveAgeArchitectureAttentionBehavioralBindingBrainBrain regionCatalogingCatalogsCategoriesClassificationClinicalCluster AnalysisCognitionCognitiveCommunitiesDataDiffusion Magnetic Resonance ImagingDimensionsDiseaseEmotionsEvolutionExclusion CriteriaFailureFeedbackFunctional Magnetic Resonance ImagingFunctional disorderFundingFutureGoalsHealthImageImpairmentIndividualIndividual DifferencesInstitutesInternationalInvestmentsLearningLeftLinkMapsMeasuresMemoryMental disordersMindNational Institute of Mental HealthNatureNeurocognitiveNeurosciencesParticipantPatternPerformancePhenotypeProcessPropertyProtocols documentationRegulationResearch Domain CriteriaResearch InfrastructureRestRiskSamplingSourceSpecificityStratificationSymptomsSystemTestingTimeTreatment outcomeVariantWorkbasecognitive taskcomputerizedcostdata sharingemotion regulationindexinginnovationinsightmultitaskneurofeedbackneuroimagingnoveloutcome forecastpreventtrait
项目摘要
DESCRIPTION (provided by applicant): The default network (DN) is a distributed pattern of brain regions associated with spontaneous cognition, internalized thought and emotional regulation that are consistently deactivated during the performance of goal- driven cognitive tasks. Failure to appropriately activate or deactivate the DN during performing of cognitive tasks is increasingly being implicated in psychiatric illness, with little specificity regarding disorderor attention to symptom domain. Further challenges arise from limitations of task-based and resting state functional MRI imaging approaches that have left the field with little insight into te nature of DN dysregulation (i.e. inability to modulate DN activity as opposed to the tendency to do so) in the various disorders. Consistent with the Research Domain Criteria Project (R-DoC), the proposed work capitalizes on recent innovations in real-time fMRI (RT-fMRI) based neurofeedback to provide a dimensional profile of DN regulation that can be linked to cognitive and psychiatric phenotyping profiles, as well as underlying brain architecture. Specifically, we propose a multi-faceted imaging study that characterizes DN regulation using a combination of neurofeedback RT-fMRI, to assess an individual's ability to modulate the DN, and task-based fMRI activation and deactivation (i.e., the self-referential processing task and the multi-source interference, respectively) to assess an individuals tendency to modulate the DN. Consistent with the "agnostic" approach promoted by R- DoC, we focus on a community-ascertained sample of 180 adults (ages: 25-40 years old), using minimally restrictive psychiatric exclusion criteria. The comprehensive phenotyping protocol established by the Nathan Kline Institute Rockland Sample (NKI-RS) will be used to characterize a range of psychiatric and cognitive domains. Successful completion of the proposed work will serve to: 1) Establish the relationship between DN modulation capacity as measured by RT-fMRI and DN modulation tendency as measured by task-related DN activation and deactivations, 2) link multidimensional imaging-based DN modulation and phenotypic profiles, and 3) link multidimensional DN modulation profiles to the brain's functional and structural architecture, as assessed by resting state fMRI and diffusion tensor imaging.
描述(由申请人提供):默认网络(DN)是与自发认知、内化思维和情绪调节相关的大脑区域的分布模式,在执行目标驱动的认知任务时,这些区域一直处于失活状态。在执行认知任务时未能适当激活或停用DN,越来越多地与精神疾病有关,但在症状领域的障碍注意方面几乎没有特异性。进一步的挑战来自基于任务和静息状态功能MRI成像方法的局限性,这些方法使该领域对各种疾病中DN失调的本质(即无法调节DN活性而不是倾向于这样做)知之甚少。与研究领域标准项目(R-DoC)一致,拟议的工作利用基于实时功能磁共振成像(RT-fMRI)的神经反馈的最新创新,提供DN调节的维度概况,可以与认知和精神表型概况以及潜在的大脑结构联系起来。具体来说,我们提出了一项多方面的成像研究,利用神经反馈RT-fMRI结合来表征DN调节,以评估个体调节DN的能力,以及基于任务的fMRI激活和失活(即自我参照处理任务和多源干扰)来评估个体调节DN的倾向。与R- DoC倡导的“不可知论”方法一致,我们重点研究了一个社区确定的180名成年人(年龄:25-40岁)的样本,使用最低限度的精神病排除标准。由内森克莱恩研究所罗克兰样本(NKI-RS)建立的综合表现型协议将用于表征一系列精神和认知领域。成功完成所提出的工作将有助于:1)建立RT-fMRI测量的DN调制能力与任务相关DN激活和失活测量的DN调制倾向之间的关系,2)将基于多维成像的DN调制和表型谱联系起来,3)将多维DN调制谱与大脑的功能和结构结构联系起来,通过静息状态fMRI和扩散张量成像评估。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Richard Cameron Craddock其他文献
Richard Cameron Craddock的其他文献
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{{ truncateString('Richard Cameron Craddock', 18)}}的其他基金
C-PAC: A configurable, compute-optimized, cloud-enabled neuroimaging analysis software for reproducible translational and comparative
C-PAC:一种可配置、计算优化、支持云的神经影像分析软件,用于可重复的转化和比较
- 批准号:
9894275 - 财政年份:2018
- 资助金额:
$ 60.96万 - 项目类别:
C-PAC: A configurable, compute-optimized, cloud-enabled neuroimaging analysis software for reproducible translational and comparative
C-PAC:一种可配置、计算优化、支持云的神经影像分析软件,用于可重复的转化和比较
- 批准号:
9766371 - 财政年份:2018
- 资助金额:
$ 60.96万 - 项目类别:
Real-time fMRI Neurofeedback Based Stratification of Default Network Regulation
基于实时功能磁共振成像神经反馈的默认网络调节分层
- 批准号:
9113698 - 财政年份:2013
- 资助金额:
$ 60.96万 - 项目类别:
Real-time fMRI Neurofeedback Based Stratification of Default Network Regulation
基于实时功能磁共振成像神经反馈的默认网络调节分层
- 批准号:
8574082 - 财政年份:2013
- 资助金额:
$ 60.96万 - 项目类别:
Real-time fMRI Neurofeedback Based Stratification of Default Network Regulation
基于实时功能磁共振成像神经反馈的默认网络调节分层
- 批准号:
8705608 - 财政年份:2013
- 资助金额:
$ 60.96万 - 项目类别:
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