Neuroimaging Investigation of mTBI and its Potentiation of PTSD in Veterans

mTBI 的神经影像学研究及其对退伍军人 PTSD 的增强作用

基本信息

  • 批准号:
    8923101
  • 负责人:
  • 金额:
    --
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2011
  • 资助国家:
    美国
  • 起止时间:
    2011-10-01 至 2019-09-30
  • 项目状态:
    已结题

项目摘要

 DESCRIPTION (provided by applicant): Combat-related mild Traumatic brain injury (mTBI) is a leading cause of sustained physical, cognitive, emotional, and behavioral deficits in military service members, OEF/OIF/OND veterans, and generals public. Recent studies have also showed that mTBI substantially increases the risk of developing post-traumatic stress disorder (PTSD). However, the pathophysiology of mTBI is not completely understood and its long-term effects are controversial. Furthermore, the neuronal mechanisms for mTBI potentiating the likelihood of PTSD development are even less clear. A significant factor has been that conventional neuroimaging techniques such as MRI and CT have limited sensitivity in detecting physiological abnormalities caused by mTBI or PTSD, or predicting long-term cognitive and behavioral outcomes. CT and MRI are generally negative even in mTBI or PTSD patients who experience persistent post-concussive symptoms (PCS) and/or PTSD symptoms. A main goal of this application is to develop and validate a voxel-wise resting-state magnetoencephalography (rs-MEG) source imaging technique that will identify abnormalities and assist in the diagnosis of mTBI patients with and without PTSD on a single-subject basis. We will also apply rs-MEG source imaging to examine the abnormality in PTSD neurocircuitry in different frequency bands, and to use rs-MEG to investigate the neuroimaging basis of mTBI's potentiation of PTSD. We will study four groups of veterans (N=50 per group): 1) veterans diagnosed with mTBI without PTSD (mTBI-only group); 2) veterans diagnosed with PTSD without mTBI (PTSD-only group); 3) veterans diagnosed with comorbid mTBI and PTSD; 4) healthy control (HC) veterans. Specific Aim 1 will develop and validate a single-subject based, voxel-wise, MEG slow-wave (delta-band, 1-4 Hz) source imaging approach for assisting in mTBI diagnosis by detecting neuronal abnormalities not visible with conventional MRI/CT. We will establish a voxel-wise normative database for the rs-MEG slow-wave imaging approach using data from HC veterans, and assess specificity by cross-validating MEG data in a sample of HCs that are not part of the database. A non-parametric method based on bootstrapping will be studied to expand our analysis to voxels that fail to meet the required Gaussian distribution. We will then examine the positive detection rate (i.e., sensitivity) and test-retest-reliability of the MEG slow-wave source imaging approach for detecting injuries in veterans from mTBI-only and comorbid mTBI-PTSD groups. The spatial distribution of the abnormal MEG slow-wave generation will also be studied at the group level to identify the brain areas that are particularly vulnerable to mTBI. Specific Aim 2 will use rs-MEG source imaging to examine abnormalities in PTSD-based neurocircuitry and to investigate the neural basis of mTBI's potentiation of PTSD development. In PTSD-only and comorbid groups, we will examine whether a model of PTSD associated with dysfunction in emotion processing neurocircuitry (i.e., amygdala, ventro-medial prefrontal cortex (vmPFC), and hippocampus), can account for abnormalities detected by electromagnetic-based rs-MEG source imaging techniques for different frequency bands. We will also study the relationship between abnormal MEG signals in high-frequency bands from PTSD neurocircuitry and co-existing abnormal MEG slow-wave generation due to mTBI. Specific Aim 3 will use voxel-wise MEG source imaging to examine the neurophysiological basis of clinical symptoms and cognitive impairments in veterans with mTBI and/or PTSD. The success of this project will significantly improve neuroimaging-based techniques for efficient diagnosis of mTBI, and advance the understanding of the relationships among neurobiological, neuropsychological, and neuropsychiatric effects of mTBI, which are the foci of this Request for Applications.
 描述(由申请人提供): 与战斗有关的轻度创伤性脑损伤(MTBI)是持续的身体,认知,情感和行为的主要原因,在兵役成员,OEF/OIF/OIF/OND退伍军人和将军公众中定义。最近的研究还表明,MTBI大大增加了发展后应激障碍(PTSD)的风险。但是,MTBI的病理生理尚未完全了解,其长期影响是有争议的。此外,MTBI潜力的神经元机制更为明确。一个重要的因素是,传统的神经影像学技术(例如MRI和CT)在检测MTBI或PTSD引起的身体异常方面的敏感性有限,或者预测了长期的认知和行为结果。即使在经历持续的脑震荡症状(PC)和/或PTSD症状的MTBI或PTSD患者中,CT和MRI通常也为阴性。该应用的主要目的是开发和验证通过体素的静静静态磁摄影术(RS-MEG)源成像技术,该技术将鉴定异常并有助于诊断有和没有PTSD的MTBI患者。我们还将应用RS-MEG源成像来检查不同频带中PTSD神经通路的异常,并使用RS-MEG研究MTBI对PTSD增强的神经成像基础。我们将研究四组退伍军人(每组n = 50):1)被诊断为没有PTSD的MTBI的退伍军人(仅MTBI组); 2)被诊断为没有MTBI的PTSD的退伍军人(仅PTSD组); 3)被诊断为合并MTBI和PTSD的退伍军人; 4)健康对照(HC)退伍军人。特定的目标1将开发并验证基于体素的单一基于体素的MEG慢波(Delta-Band,1-4 Hz)源成像方法,以通过检测未在常规MRI/CT中可见的神经元异常来协助MTBI诊断。我们将使用来自HC退伍军人的数据为RS-MEG慢波成像方法建立Voxel的正常数据库,并通过在不属于数据库的HCS样本中对MEG数据进行交叉验证MEG数据来评估特异性。基于自举的非参数方法将研究将我们的分析扩展到无法满足所需高斯分布的体素。然后,我们将检查MEG慢波源的阳性检测率(即灵敏度)和测试重度可靠性 从仅MTBI和合并症MTBI-PTSD组中检测退伍军人受伤的成像方法。异常的MEG慢波产生的空间分布也将在小组级别进行研究,以识别特别容易受到MTBI攻击的大脑区域。特定的目标2将使用RS-MEG源成像检查基于PTSD的神经通路中的异常,并研究MTBI对PTSD开发增强的神经元基础。仅PTSD和合并的组,我们将检查与情绪处理神经循环中与功能障碍相关的模型(即杏仁核,腹膜前额叶皮层(VMPFC)和海马室),可以通过频率来探讨abrosef condersy condersy condersy condersy condersy condersy condersy condersy condersy corection。我们还将研究来自PTSD神经循环的高频频段中异常MEG信号与由于MTBI引起的异常MEG慢波产生。具体目标3将使用Voxel-MEG源成像检查MTBI和/或PTSD的退伍军人的临床症状和认知障碍的神经生理基础。该项目的成功将显着提高基于神经成像的技术,以有效地诊断MTBI,并提高对MTBI的神经生物学,神经心理学和神经精神效应之间关系的理解,MTBI是该应用程序的焦点。

项目成果

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MINGXIONG HUANG其他文献

MINGXIONG HUANG的其他文献

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{{ truncateString('MINGXIONG HUANG', 18)}}的其他基金

Diagnostic Machine Learning Algorithm to Identify MEG Features of Mild TBI and Comorbid PTSD
用于识别轻度 TBI 和共病 PTSD 的 MEG 特征的诊断机器学习算法
  • 批准号:
    10651625
  • 财政年份:
    2020
  • 资助金额:
    --
  • 项目类别:
Diagnostic Machine Learning Algorithm to Identify MEG Features of Mild TBI and Comorbid PTSD
用于识别轻度 TBI 和共病 PTSD 的 MEG 特征的诊断机器学习算法
  • 批准号:
    10398791
  • 财政年份:
    2020
  • 资助金额:
    --
  • 项目类别:
Diagnostic Machine Learning Algorithm to Identify MEG Features of Mild TBI and Comorbid PTSD
用于识别轻度 TBI 和共病 PTSD 的 MEG 特征的诊断机器学习算法
  • 批准号:
    9888520
  • 财政年份:
    2020
  • 资助金额:
    --
  • 项目类别:
Passive electrical neurofeedback treatment of mTBI: MEG and Behavioral Outcomes
mTBI 的被动电神经反馈治疗:MEG 和行为结果
  • 批准号:
    10189733
  • 财政年份:
    2018
  • 资助金额:
    --
  • 项目类别:
Passive electrical neurofeedback treatment of mTBI: MEG and Behavioral Outcomes
mTBI 的被动电神经反馈治疗:MEG 和行为结果
  • 批准号:
    9911992
  • 财政年份:
    2018
  • 资助金额:
    --
  • 项目类别:
Passive electrical neurofeedback treatment of mTBI: MEG and Behavioral Outcomes
mTBI 的被动电神经反馈治疗:MEG 和行为结果
  • 批准号:
    10383148
  • 财政年份:
    2018
  • 资助金额:
    --
  • 项目类别:
Neuroimaging Investigation of mTBI and its Potentiation of PTSD in Veterans
mTBI 的神经影像学研究及其对退伍军人 PTSD 的增强作用
  • 批准号:
    9486873
  • 财政年份:
    2011
  • 资助金额:
    --
  • 项目类别:
Diagnosing Mild TBI in VA and Active Duty Military Patients using MEG and DTI
使用 MEG 和 DTI 诊断 VA 和现役军人患者的轻度 TBI
  • 批准号:
    8391100
  • 财政年份:
    2011
  • 资助金额:
    --
  • 项目类别:
Diagnosing Mild TBI in VA and Active Duty Military Patients using MEG and DTI
使用 MEG 和 DTI 诊断 VA 和现役军人患者的轻度 TBI
  • 批准号:
    8142261
  • 财政年份:
    2011
  • 资助金额:
    --
  • 项目类别:
Diagnosing Mild TBI in VA and Active Duty Military Patients using MEG and DTI
使用 MEG 和 DTI 诊断 VA 和现役军人患者的轻度 TBI
  • 批准号:
    8590197
  • 财政年份:
    2011
  • 资助金额:
    --
  • 项目类别:

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