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Tuning Up the Old Brain with New Tricks: Attention Training via Neurofeedback

机译:通过新技巧调整旧大脑:通过神经反馈进行注意力训练

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摘要

Neurofeedback (NF) is a form of biofeedback that uses real-time (RT) modulation of brain activity to enhance brain function and behavioral performance. Recent advances in Brain-Computer Interfaces (BCI) and cognitive training (CT) have provided new tools and evidence that NF improves cognitive functions, such as attention and working memory (WM), beyond what is provided by traditional CT. More published studies have demonstrated the efficacy of NF, particularly for treating attention deficit hyperactivity disorder (ADHD) in children. In contrast, there have been fewer studies done in older adults with or without cognitive impairment, with some notable exceptions. The focus of this review is to summarize current success in RT NF training of older brains aiming to match those of younger brains during attention/WM tasks. We also outline potential future advances in RT brainwave-based NF for improving attention training in older populations. The rapid growth in wireless recording of brain activity, machine learning classification and brain network analysis provides new tools for combating cognitive decline and brain aging in older adults. We optimistically conclude that NF, combined with new neuro-markers (event-related potentials and connectivity) and traditional features, promises to provide new hope for brain and CT in the growing older population.
机译:神经反馈(NF)是生物反馈的一种形式,它使用大脑活动的实时(RT)调节来增强大脑功能和行为表现。脑机接口(BCI)和认知训练(CT)的最新进展提供了新的工具和证据,证明NF可以改善认知功能,例如注意力和工作记忆(WM),超越了传统CT所提供的功能。越来越多的已发表的研究证明了NF的功效,特别是对于治疗儿童的注意力缺陷多动障碍(ADHD)。相反,在有或没有认知障碍的老年人中进行的研究较少,但有一些明显的例外。这篇综述的重点是总结目前在老年大脑的RT NF训练中取得的成功,旨在在注意力/ WM任务中与年轻大脑相匹配。我们还概述了基于RT脑波的NF在改善老年人群注意力训练方面的潜在未来进展。无线记录大脑活动,机器学习分类和大脑网络分析的快速增长为对抗老年人的认知能力下降和大脑衰老提供了新的工具。我们乐观地得出结论,NF与新的神经标记(事件相关的电位和连接性)和传统功能相结合,有望为不断增长的老年人群提供大脑和CT的新希望。

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