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A Virtual World/Neurofeedback Real Time Functional MRI Approach to PTSD Treatment

A Virtual World/Neurofeedback Real Time Functional MRI Approach to PTSD Treatment
虚拟世界/神经反馈实时功能 MRI 治疗 PTSD 的方法
批准号:
10174842
负责人:
RAMIRO SALAS
金额:
$0.0万
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-05-01 至 2020-10-31

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项目成果

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中文摘要
翻译
创伤后应激障碍(PTSD)非常普遍,难以治疗,后果非常严重 为退伍军人和他们的家人。暴露疗法是常用的疗法,并在很大程度上取得了积极的效果 这一比例很高,但亟需改善治疗效果。我们提出了一种新的战略 它结合了最先进的技术来开发一种改进的暴露治疗方法。 我们计划使用虚拟现实体验(虚拟伊拉克,参与者将在其中虚拟驾驶通过 将出现不同压力来源的伊拉克景观,如爆炸、敌方战斗人员等)。虚拟 事实已经证明,与常规暴露疗法相比,这一点有所改善。主要的创新是使用了真实的 在虚拟现实暴露期间进行时间功能磁共振成像(FMRI)。我们将首先收集两个以下的大脑图像 明确定义的状态:平静(开车穿过伊拉克,没有压力,也没有战争般的场景)和压力(战争般的 伊拉克)。然后,我们将使用机器学习算法根据神经活动来定义这两种大脑状态。 接下来,我们将向参与者展示一个虚拟的伊拉克环境,他们将能够在其中修改场景 从紧张到平静,通过让他们的大脑状态平静下来。屏幕上的实时信号会让他们知道 在平静-压力的连续体中,他们的大脑在每一个时刻都在哪里。我们假设这个反馈 Signal将允许参与者学习哪些心理策略(思考愉快的想法,专注于 呼吸等)在镇静大脑方面效果最好。一旦大脑平静下来,虚拟伊拉克场景就会出现 也会减少压力,提供额外的反馈。我们建议这次培训(两节课到 研究个人的平静/压力状态,6次神经反馈训练)将使患者发展 他们自己的个性化心理策略,能够在现实生活中平静他们的大脑,当他们接触到触发因素时。 第二项创新是使用可穿戴设备来持续收集体力活动、心率和 在整个9周的研究中,睡眠质量数据。我们假设这些措施可能会产生数据 比治疗期间的个人报告更可靠。 总之,我们建议在虚拟现实环境中使用神经反馈来研究 这些实时信号将帮助患有创伤后应激障碍的退伍军人制定个性化的心理策略,使他们变得平静 在压力下。由于核磁共振作为一种常见的干预手段非常昂贵,我们建议一旦我们 在这个试点项目、其他成本更低、更易于使用的项目上展示该方法的可行性 可以根据我们的数据开发技术(也许是脑电)。
英文摘要
Posttraumatic stress disorder (PTSD) is highly prevalent, difficult to treat, and has very serious consequences for veterans and their families. Exposure therapy is commonly used and has positive results in a large percentage of cases, but improvements in therapeutic effects are sorely needed. We propose a novel strategy that uses a combination of state-of-the-art technologies to develop an improved exposure therapy approach. We plan to use a virtual reality experience (Virtual Iraq, in which participants will be virtually driving through Iraqi landscapes where different stressors will be present, such as explosions, enemy combatants, etc.). Virtual reality has already been shown to improve on regular exposure therapy. The main innovation is the use of real time functional MRI (fMRI) during the virtual reality exposure. We will first collect brain images under two clearly defined states: CALM (driving though Iraq with no stressors or war-like scenes) and STRESS (war-like Iraq). We will then use a machine learning algorithm to define those two brain states in terms of neural activity. Next, we will expose participants to a virtual Iraq environment in which they will be able to modify the scenes from stressful to calm, by bringing their brain state to CALM. A real time signal in the screen will let them know where in the continuum CALM-STRESS their brain is at each moment. We hypothesize that this feedback signal will allow for the participant to learn which mental strategies (think pleasant thoughts, concentrate on breathing, etc.) work best in terms of calming the brain. Once the brain moves to CALM, the Virtual Iraq scene will also move to less stressful, providing additional feedback. We propose that this training (two sessions to study individual CALM/STRESS states, 6 sessions of neurofeedback training) will allow patients to develop their own personalized mental strategies to be able to calm their brain in real life, when exposed to triggers. A second innovation is the use of a wearable device to continuously collect physical activity, heart rate, and sleep quality data throughout the 9 weeks of the study. We hypothesize that these measures may result in data more reliable than personal reports during treatment. In conclusion, we propose to use neurofeedback in a virtual reality environment to study the possibility that these real time signals will help veterans with PTSD develop individualized mental strategies to become calm when under stress. Since MRI is very expensive to use as a common intervention, we propose that once we demonstrate the feasibility of the approach on this pilot project, other less expensive and easier to use techniques (perhaps EEG) can be developed based on our data.
期刊论文(6)
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会议论文
DOI: 10.1016/j.addbeh.2020.106457
发表时间: 2020-04
期刊: Addictive behaviors
影响因子: 4.4
作者: [Hyuntaek Oh;Jaehoon Lee;Savannah N. Gosnell;M. Patriquin;T. Kosten;R. Salas]
通讯作者: Hyuntaek Oh;Jaehoon Lee;Savannah N. Gosnell;M. Patriquin;T. Kosten;R. Salas
Framework for Accurate Classification of Self-Reported Stress From Multisession Functional MRI Data of Veterans With Posttraumatic Stress.
从事创伤后应激的退伍军人的多潜电功能性MRI数据准确分类的自我报告应力的框架。
DOI: 10.1177/24705470231203655
发表时间: 2023-01
期刊: Chronic stress (Thousand Oaks, Calif.)
影响因子: --
作者: [Goel, Rahul, Tse, Teresa, Smith, Lia J, Floren, Andrew, Naylor, Bruce, Williams, M Wright, Salas, Ramiro, Rizzo, Albert S, Ress, David]
通讯作者: Ress, David
DOI: 10.1016/j.bpsc.2021.05.010
发表时间: 2021-06
期刊: Biological psychiatry. Cognitive neuroscience and neuroimaging
影响因子: --
作者: [Hyuntaek Oh;Jaehoon Lee;M. Patriquin;J. Oldham;R. Salas]
通讯作者: Hyuntaek Oh;Jaehoon Lee;M. Patriquin;J. Oldham;R. Salas
DOI: 10.1177/2470547020906799
发表时间: 2020-01-01
期刊: Chronic stress (Thousand Oaks, Calif.)
影响因子: --
作者: [Gosnell, Savannah N, Meyer, Matthew J, Salas, Ramiro]
通讯作者: Salas, Ramiro
Brain connectivity and genetics as predictors of opioid abuse treatment outcomes
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Brain connectivity and genetics as predictors of opioid abuse treatment outcomes
Multimodal Imaging of Reward Brain Centers in Tobacco Smoking Veterans
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