课题基金 / 基金详情

Mapping and Manipulating Circuits for Emotion and Cognition in Anxiety and Depression

Mapping and Manipulating Circuits for Emotion and Cognition in Anxiety and Depression
绘制和操纵焦虑和抑郁情绪和认知的回路
批准号:
9109051
负责人:
Amit Etkin
金额:
$77.4万
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:
2014-09-05 至 2018-07-31

项目摘要

项目成果

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中文摘要
翻译
描述(申请人提供):目前,应用或开发基于认知神经科学的神经回路疗法的能力仍然极其有限,原因有两个:1)传统的神经成像研究提供了关于大脑和行为之间的相关性的信息,但没有提供一个大脑区域的活动如何直接驱动另一个大脑区域的激活或抑制的信息。了解不同大脑之间的因果关系 对于特定的区域或网络,有必要对特定的大脑区域进行直接的实验控制,同时想象对其他大脑区域或网络的影响。我们将其称为“因果电路图”。因此,2)尚不清楚这些因果电路图中哪些特定的神经通路是异常的,哪些在患者中是完整的,以及创伤暴露等特定临床因素如何影响这些大脑通路。例如,了解刺激应该指向完整的通路还是异常的通路(以使功能正常为目标),对于实施未来的电路靶向神经调节干预将具有基本的理论和实践意义。如果没有因果电路映射,目标识别和未来神经调制治疗的验证,如重复经颅磁刺激(RTMS),仍将是反复试验的猜测工作。以前关于情绪/焦虑相关障碍的研究的另一个局限性是,DSM没有涵盖临床上显著的负面影响症状学的全部范围,包括创伤在创伤后应激障碍以外的临床综合征中的作用。因此,我们在这项建议中的主要关注点是首次描绘与情绪调节(ER)和执行功能(EF)障碍相关的因果电路图,这与具有高度负面情绪症状的广泛慢性病患者有关,与研究领域标准项目(RDoC)的目标一致。之前使用相关成像对高负性情绪障碍进行的工作已经在几个定义良好的大规模神经元网络中发现了跨多个节点的异常。然而,与以前的相关研究不同,我们建议使用因果回路映射神经成像方法来获得前所未有的特异性,关于哪些因果脑通路是完整的,哪些是异常的。在这里,我们通过使用无创单脉冲兴奋性TMS(SPTMS)直接激活大脑,结合使用并发功能磁共振成像(FMRI)来可视化网络效应,提供了这一临时地图。SPTMS/fMRI的靶点是与ER/EF相关的定义明确的大规模网络中的皮质区域(8个双侧前额叶站点和1个对照站点),从而系统地将因果关系图与疾病的电路水平模型联系起来。这项研究的成功结果将直接有助于指导如何以及在哪里针对现有的长期神经调节干预措施,并为开发新方法奠定基础。
英文摘要
DESCRIPTION (provided by applicant): At present, the ability to apply or develop neurocircuitry-based treatments founded on cognitive neuroscience is still extremely limited for two fundamental reasons: 1) conventional neuroimaging studies provide information on correlations between brain and behavior, but not how activity in one brain region directly drives activation or inhibition in another. To understand the causal relationships between different brain regions or networks, it is necessary to exert direct experimental control over specific brain regions and simultaneously image the consequences on other brain regions or networks. We refer to this as a "causal circuit map." Consequently, 2) it is unknown which specific neural pathways within these causal circuit maps are abnormal and which are intact in patients, and how particular clinical factors such as trauma exposure impact these brain pathways. It would be of fundamental theoretical and practical importance for implementing a future circuit-targeting neuromodulatory intervention to know, for example, whether stimulation should be directed to intact pathways or to abnormal ones (with a goal of normalizing dysfunction). Without causal circuit mapping, target identification and validation for future neuromodulatory treatments, such as repetitive transcranial magnetic stimulation (rTMS), will remain as trial-and-error guesswork. An additional limitation of prior studies on mood/anxiety-related disorders is that the DSM does not capture the full spectrum of clinically-significant negative affect symptomatology, including the role of trauma in clinical syndromes beyond post-traumatic stress. Our primary focus in this proposal is therefore to delineate for the first time the causal circuit maps relevant for impairments in emotion regulation (ER) and executive function (EF) in a broad range of chronically ill patients with high negative affect symptoms, consistent with the aims of the Research Domain Criteria Project (RDoC). Prior work on high negative affect disorders with correlational imaging has found abnormalities across multiple nodes in several well-defined large-scale neuronal networks. However, unlike these prior correlational studies, we propose to employ a causal circuit mapping neuroimaging approach to achieve an unprecedented level of specificity with regard to which causal brain pathways are intact and which are abnormal. Here we provide this casual map by direct brain activation using non-invasive single pulse excitatory TMS (spTMS), combined with visualization of network effects using concurrent functional magnetic resonance imaging (fMRI). The targets for spTMS/fMRI are cortical regions within well-defined large-scale networks relevant to ER/EF (eight bilateral prefrontal sites as well as one control site), thus systematically linking causal maps to circuit-level models of the illnesses A successful outcome from this study would be directly useful in guiding how and where to target existing long-term neuromodulatory interventions, and lay the groundwork for the development of novel methods.
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Validating of Machine Learning-Based EEG Treatment Biomarkers in Depression
  • 批准号:
    10009501
  • 项目类别:
  • 资助金额:
    $98.81万
  • 财政年份:
    2020
  • 负责人:
    Amit Etkin
  • 依托单位:
Validating of Machine Learning-Based EEG Treatment Biomarkers in Depression
  • 批准号:
    10116492
  • 项目类别:
  • 资助金额:
    $118.41万
  • 财政年份:
    2020
  • 负责人:
    Amit Etkin
  • 依托单位:
Validating of Machine Learning-Based EEG Treatment Biomarkers in Depression
  • 批准号:
    10366060
  • 项目类别:
  • 资助金额:
    $101.65万
  • 财政年份:
    2020
  • 负责人:
    Amit Etkin
  • 依托单位:
Assessing an electroencephalography (EEG) biomarker of response to transcranial magnetic stimulation for major depression
海外基金