Using real-time fMRI neurofeedback and motor imagery to enhance motor timing and precision in cerebellar ataxia

使用实时功能磁共振成像神经反馈和运动想象来增强小脑共济失调的运动计时和精度

• 批准号: 10354246
• 负责人: STEPHEN M LACONTE
• 金额: $ 27.57万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-12-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10354246
• 关键词: Adjuvant; Atrophic; Behavior; Brain; Brain Mapping; Cerebellar Ataxia; Cerebellar degeneration; Cerebellum; Cues; Data; Data Analyses; Disease Progression; Effectiveness; Equilibrium; Exercise; Eye Abnormalities; Eye Movements; Fingers; Follow-Up Studies; Functional Magnetic Resonance Imaging; Future; Hand; Heterogeneity; Home; Imagery; Individual; Injury; Learning; Machine Learning; Measures; Medicine; Methods; Modeling; Motor; Movement; Movement Disorders; Muscle; Nature; Neurologic Signs; Neurologic Symptoms; Occupational Therapy; Participant; Patients; Performance; Persons; Pharmacology; Physical therapy; Plant Roots; Population; Process; Protocols documentation; Psyche structure; Public Health; Quality of life; Rehabilitation Outcome; Rehabilitation therapy; Research; Signal Transduction; Spasm; Speech; Speech Therapy; Speed; Symptoms; System; Testing; Time; Training; Translating; Tremor; Visual; Walking; Work; base; design; experience; experimental study; high risk; improved; improved functioning; mental imagery; motor deficit; motor function improvement; motor rehabilitation; neurofeedback; neuroimaging; neuromechanism; next generation; palliative; relating to nervous system; skill acquisition; skills; strength training; success; technology development; tool; Adjuvant; Atrophic; Behavior; Brain; Brain Mapping; Cerebellar Ataxia; Cerebellar degeneration; Cerebellum; Cues; Data; Data Analyses; Disease Progression; Effectiveness; Equilibrium; Exercise; Eye Abnormalities; Eye Movements; Fingers; Follow-Up Studies; Functional Magnetic Resonance Imaging; Future; Hand; Heterogeneity; Home; Imagery; Individual; Injury; Learning; Machine Learning; Measures; Medicine; Methods; Modeling; Motor; Movement; Movement Disorders; Muscle; Nature; Neurologic Signs; Neurologic Symptoms; Occupational Therapy; Participant; Patients; Performance; Persons; Pharmacology; Physical therapy; Plant Roots; Population; Process; Protocols documentation; Psyche structure; Public Health; Quality of life; Rehabilitation Outcome; Rehabilitation therapy; Research; Signal Transduction; Spasm; Speech; Speech Therapy; Speed; Symptoms; System; Testing; Time; Training; Translating; Tremor; Visual; Walking; Work; base; design; experience; experimental study; high risk; improved; improved functioning; mental imagery; motor deficit; motor function improvement; motor rehabilitation; neurofeedback; neuroimaging; neuromechanism; next generation; palliative; relating to nervous system; skill acquisition; skills; strength training; success; technology development; tool

7. PROJECT SUMMARY Motor imagery, especially when used as an adjuvant treatment with physical practice, promises to be a powerful tool for improving function in individuals with movement disorders. Yet, due to its very nature, motor imagery cannot be directly observed. This makes it difficult to assist and evaluate a patient's motor imagery efforts. Brain activity associated with motor imagery is, however, observable through neuroimaging. Moreover, with the recent development of technologies like real-time functional magnetic resonance imaging neurofeedback (rtfMRI-NF), motor imagery “behavior” can be displayed to both the patient and the clinician. We hypothesize that if patients could learn to “exercise” their own motor brain networks directly, they could optimize their rehabilitation. In this proposal, we seek to examine the feasibility of applying rtfMRI-NF imagery training to individuals with cerebellar ataxia (CA), a movement disorder that results from progressive cerebellar degeneration. Current treatments can slow the rate of motor loss through methods such as physical therapy and core strengthening, but they focus on physical manifestations and do not target the underlying neural mechanisms involved, thereby missing the root cause. In addition to evaluating the feasibility of motor imagery rtfMRI-NF in CA, we will examine the utility of additional at-home therapy, subsequent to the rtfMRI session. Finally, we will use the rtfMRI-NF data for offline analyses for brain mapping, machine learning, and simulating additional rtfMRI approaches to develop future iterations of rtfMRI-NF protocols. Thus, future work aims to establish refined experimental medicine frameworks by identifying neural underpinnings (NF targets) of motor accuracy, and testing whether engaging these targets, through NF, improves motor performance. As outlined in the proposal, Aim 1 will use rtfMRI-NF during motor imagery to train CA participants to improve motor accuracy. Thirty CA participants will receive NF during motor imagery in an experiment in which we hypothesize that 1) CA participants will be able to control a NF interface; 2) imagery skill will be positively correlated to improvements in overt tapping accuracy; and 3) overt tapping accuracy will correlate with neurological signs, whereas motor imagery skill will correlate with assessed motor imagery ability. Aim 2 will translate rtfMRI-NF learning into at- home therapy strategies for three weeks of continued training in which we hypothesize that 1) continued practice with imagery strategies will lead to additional improvements in motor timing and precision, and 2) performance during rtfMRI-NF training will positively correlate with at-home motor imagery performance. In an exploratory Aim 3, we will examine three primary questions to establish future experimental medicine designs. Specifically, these question are 1) Are there group-level differences in fMRI activity in CA versus healthy controls?; 2) Are healthy models of motor imagery viable for CA NF?; and 3) Can the NF session be streamlined to deliver more accurate NF in shorter sessions? This proposal represents the first of its kind in the treatment of CA, with the potential to dramatically improve motor rehabilitation outcomes.

7。项目摘要 运动图像，尤其是在用作体育练习的调整治疗时，有望成为强大的 改善运动障碍个体功能的工具。然而，由于其本质，运动图像 无法直接观察到。这使得很难协助和评估患者的运动图像工作。脑 然而，与运动图像相关的活动是通过神经影像观察到的。而且，最近 实时功能磁共振成像神经反馈（RTFMRI-NF）等技术的开发， 运动图像“行为”可以显示给患者和临床。我们假设如果患者 可以学会直接“锻炼”自己的运动脑网络，他们可以优化他们的 康复。在此建议中，我们试图研究将RTFMRI-NF图像培训应用于 小脑共济失调（CA）的个体，这是一种由渐进小脑产生的运动障碍 退化。当前的治疗可以通过物理治疗和 核心加强，但它们专注于身体表现，并不针对基本的中性 涉及的机制，从而缺少根本原因。除了评估运动图像的可行性 RTFMRI-NF在CA中，我们将在RTFMRI会议之后研究其他原住民疗法的实用性。 最后，我们将使用RTFMRI-NF数据进行脱机分析，以进行大脑映射，机器学习和模拟 其他RTFMRI的方法来开发RTFMRI-NF协议的未来迭代。那是未来的工作旨在 通过识别电动机的神经基础（NF目标）来建立精致的实验医学框架 准确性并测试通过NF参与这些目标是否可以改善运动性能。如概述 该提案，AIM 1将在运动图像期间使用RTFMRI-NF来训练CA参与者以提高运动的准确性。 在一个实验中，三十名CA参与者将在运动图像期间获得NF，我们假设1）CA 参与者将能够控制NF接口； 2）图像技能将与改进成正相关 公开攻击精度； 3）明显的攻击精度将与神经迹象相关，而电动机 图像技能将与评估的运动图像能力相关。 AIM 2会将RTFMRI-NF学习转化为AT- 我们假设的三周持续培训的家庭治疗策略1）继续练习 借助图像策略将导致运动时机和精度的进一步改进，2）性能 在RTFMRI-NF期间，培训将与家庭运动成像性能正相关。在探索性中 AIM 3，我们将研究三个主要问题，以建立未来的实验医学设计。具体来说， 这些问题是1）CA与健康对照中的fMRI活性存在组级差异吗？ 2）是 适用于CA NF的运动图像的健康模型？ 3）可以简化NF会话以提供更多 较短的会议中的准确NF？该提议代表了CA的治疗中的第一个此类建议 显着改善运动康复结果的潜力。