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:
    9486873
  • 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.


项目成果

期刊论文数量(0)
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会议论文数量(0)
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MINGXIONG HUANG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:
    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:
    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:
    10383148
  • 财政年份:
    2018
  • 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:
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:
    8923101
  • 财政年份:
    2011
  • 资助金额:
    --
  • 项目类别:
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