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: 10609494
• 负责人: STEPHEN M LACONTE
• 金额: $ 20.32万
• 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/10609494
• 关键词: Adjuvant Therapy; 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; 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; design; experience; experimental study; functional improvement; high risk; improved; mental imagery; motor deficit; motor function improvement; motor rehabilitation; neural; neurofeedback; neuroimaging; neuromechanism; next generation; palliative; 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 运动想象，特别是当作为一种辅助治疗与物理实践，承诺是一个强大的 改善运动障碍患者功能的工具。然而，由于其本质，运动想象 不能直接观察到。这使得很难帮助和评估病人的运动想象的努力。大脑 然而，与运动想象相关的活动可通过神经成像观察到。此外，随着最近 实时功能性磁共振成像神经反馈（rtfMRI-NF）等技术的发展， 可以向患者和临床医生显示运动想象“行为”。我们假设，如果患者 他们可以学习直接“锻炼”自己的运动大脑网络，他们可以优化自己的运动大脑网络。 康复活动.在这个建议中，我们试图研究应用rtfMRI-NF图像训练的可行性， 患有小脑共济失调（CA）的个体，这是一种由进行性小脑性共济失调引起的运动障碍。 退化目前的治疗方法可以通过物理治疗等方法减缓运动功能丧失的速度， 核心强化，但他们专注于身体表现，不针对潜在的神经 涉及的机制，从而错过了根本原因。除了评估运动想象的可行性 在CA的rtfMRI-NF，我们将检查额外的在家治疗的效用，随后的rtfMRI会议。 最后，我们将使用rtfMRI-NF数据进行离线分析，用于脑映射，机器学习和模拟 额外的rtfMRI方法来开发rtfMRI-NF协议的未来迭代。因此，今后的工作旨在 通过识别运动神经基础（NF靶点）建立完善的实验医学框架 准确性，并测试是否从事这些目标，通过NF，提高电机性能。中概述的 在该提案中，目标1将在运动想象过程中使用rtfMRI-NF来训练CA参与者以提高运动准确性。 30名CA参与者将在实验中接受运动想象的NF，我们假设1）CA 参与者将能够控制NF界面; 2）图像技能将与以下方面的改善呈正相关： 明显的敲击准确性;和3）明显的敲击准确性将与神经体征相关，而运动 想象技能与评估运动想象能力相关。目标2将rtfMRI-NF学习转化为at- 三周持续训练的家庭治疗策略，我们假设1）持续训练 与想象策略将导致额外的改善运动时间和精度，和2）性能 在rtfMRI-NF训练期间，将与在家运动想象表现正相关。以探索性 目标3，我们将研究三个主要问题，以建立未来的实验药物设计。具体地说， 这些问题是：1）CA与健康对照组的fMRI活动是否存在组水平差异？2)是 健康的运动想象模型对CA NF可行吗？和3）NF会话是否可以简化以提供更多 在较短的会话中准确的NF？这项建议是处理CA的第一个此类建议， 有可能极大地改善运动康复的结果。