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

基本信息

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
项目类别：
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

项目摘要

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. 项目概要运动想象，特别是当作为身体练习的辅助治疗时，有望成为一种强大的治疗方法。运动想象是改善运动障碍患者功能的工具。这使得辅助和评估患者的运动想象大脑变得困难。然而，与运动想象相关的活动可以通过神经成像观察到。实时功能磁共振成像神经反馈（rtfMRI-NF）等技术的开发，运动想象“行为”可以向患者和临床医生显示。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在本提案中，我们试图研究将 rtfMRI-NF 图像训练应用于康复的可行性。患有小脑性共济失调 (CA) 的个体，这是一种由进行性小脑性运动障碍引起的运动障碍目前的治疗方法可以通过物理治疗和运动疗法等方法减缓运动丧失的速度。核心强化，但它们专注于身体表现，而不针对潜在的神经除了评估运动想象的可行性之外，还忽略了涉及的机制，从而错过了根本原因。在 CA 的 rtfMRI-NF 中，我们将在 rtfMRI 会议之后检查额外的家庭治疗的效用。最后，我们将使用 rtfMRI-NF 数据进行脑图谱、机器学习和模拟的离线分析额外的 rtfMRI 方法来开发 rtfMRI-NF 协议的未来迭代因此，未来的工作旨在通过识别运动的神经基础（NF目标）建立完善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提高运动性能，如中所述。该提案的目标 1 将在运动想象过程中使用 rtfMRI-NF 来训练 CA 参与者提高运动准确性。在我们进行的一项实验中，三十名 CA 参与者将在运动想象期间收到 NF，其中我们进行了 1) CA 参与者将能够控制 NF 界面；2）图像技能将与能力的提高呈正相关。明显的敲击准确性；3) 明显的敲击准确性与神经体征相关，而运动体征相关意象技能将与评估的运动意象能力相关联，目标 2 将把 rtfMRI-NF 学习转化为 at-。三周持续训练的家庭治疗策略，其中我们欺负 1）持续练习图像策略将导致运动计时和精度的额外改进，以及 2) 性能在一项探索性的研究中，rtfMRI-NF 训练期间的训练与家庭运动想象表现呈正相关。目标 3，我们将研究三个主要问题，以建立未来的实验医学设计。这些问题是 1) CA 与健康对照组的功能磁共振成像活动是否存在组别差异？；2) 健康的运动想象模型对 CA NF 是否可行？；3) 能否简化 NF 会议以提供更多内容在更短的时间内准确的 NF？该提案代表了治疗 CA 的首个此类提案，显着改善运动康复效果的潜力。