Resting-State Functional Networks Correlate with Motor Performance in a Complex Visuomotor Task: An EEG Microstate Pilot Study on Healthy Individuals.

IF 2.3 3区 医学 Q3 CLINICAL NEUROLOGY
Brain Topography Pub Date : 2024-07-01 Epub Date: 2022-12-25 DOI:10.1007/s10548-022-00934-9
Joaquin A Penalver-Andres, Karin A Buetler, Thomas Koenig, René M Müri, Laura Marchal-Crespo
{"title":"Resting-State Functional Networks Correlate with Motor Performance in a Complex Visuomotor Task: An EEG Microstate Pilot Study on Healthy Individuals.","authors":"Joaquin A Penalver-Andres, Karin A Buetler, Thomas Koenig, René M Müri, Laura Marchal-Crespo","doi":"10.1007/s10548-022-00934-9","DOIUrl":null,"url":null,"abstract":"<p><p>Developing motor and cognitive skills is needed to achieve expert (motor) performance or functional recovery from a neurological condition, e.g., after stroke. While extensive practice plays an essential role in the acquisition of good motor performance, it is still unknown whether certain person-specific traits may predetermine the rate of motor learning. In particular, learners' functional brain organisation might play an important role in appropriately performing motor tasks. In this paper, we aimed to study how two critical cognitive brain networks-the Attention Network (AN) and the Default Mode Network (DMN)-affect the posterior motor performance in a complex visuomotor task: virtual surfing. We hypothesised that the preactivation of the AN would affect how participants divert their attention towards external stimuli, resulting in robust motor performance. Conversely, the excessive involvement of the DMN-linked to internally diverted attention and mind-wandering-would be detrimental for posterior motor performance. We extracted seven widely accepted microstates-representing participants mind states at rest-out of the Electroencephalography (EEG) resting-state recordings of 36 healthy volunteers, prior to execution of the virtual surfing task. By correlating neural biomarkers (microstates) and motor behavioural metrics, we confirmed that the preactivation of the posterior DMN was correlated with poor posterior performance in the motor task. However, we only found a non-significant association between AN preactivation and the posterior motor performance. In this EEG study, we propose the preactivation of the posterior DMN-imaged using EEG microstates-as a neural trait related to poor posterior motor performance. Our findings suggest that the role of the executive control system is to preserve an homeostasis between the AN and the DMN. Therefore, neurofeedback-based downregulation of DMN preactivation could help optimise motor training.</p>","PeriodicalId":55329,"journal":{"name":"Brain Topography","volume":" ","pages":"590-607"},"PeriodicalIF":2.3000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11199229/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brain Topography","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s10548-022-00934-9","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/12/25 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Developing motor and cognitive skills is needed to achieve expert (motor) performance or functional recovery from a neurological condition, e.g., after stroke. While extensive practice plays an essential role in the acquisition of good motor performance, it is still unknown whether certain person-specific traits may predetermine the rate of motor learning. In particular, learners' functional brain organisation might play an important role in appropriately performing motor tasks. In this paper, we aimed to study how two critical cognitive brain networks-the Attention Network (AN) and the Default Mode Network (DMN)-affect the posterior motor performance in a complex visuomotor task: virtual surfing. We hypothesised that the preactivation of the AN would affect how participants divert their attention towards external stimuli, resulting in robust motor performance. Conversely, the excessive involvement of the DMN-linked to internally diverted attention and mind-wandering-would be detrimental for posterior motor performance. We extracted seven widely accepted microstates-representing participants mind states at rest-out of the Electroencephalography (EEG) resting-state recordings of 36 healthy volunteers, prior to execution of the virtual surfing task. By correlating neural biomarkers (microstates) and motor behavioural metrics, we confirmed that the preactivation of the posterior DMN was correlated with poor posterior performance in the motor task. However, we only found a non-significant association between AN preactivation and the posterior motor performance. In this EEG study, we propose the preactivation of the posterior DMN-imaged using EEG microstates-as a neural trait related to poor posterior motor performance. Our findings suggest that the role of the executive control system is to preserve an homeostasis between the AN and the DMN. Therefore, neurofeedback-based downregulation of DMN preactivation could help optimise motor training.

静息状态功能网络与复杂视觉运动任务中的运动表现相关:对健康人的脑电图微状态试点研究。
要想获得专业的(运动)表现或从神经系统疾病(如中风后)中恢复功能,就必须发展运动和认知技能。虽然大量的练习对获得良好的运动表现起着至关重要的作用,但某些特定人的特质是否会预先决定运动学习的速度仍是未知数。特别是,学习者的大脑功能组织可能在适当完成运动任务中发挥重要作用。在本文中,我们旨在研究两个关键的认知脑网络--注意力网络(AN)和默认模式网络(DMN)--如何影响复杂视觉运动任务(虚拟冲浪)中的后天运动表现。我们假设,AN的预激活将影响参与者如何将注意力转移到外部刺激上,从而获得强劲的运动表现。相反,DMN的过度参与与内部注意力转移和思维游离有关,将不利于后部运动表现。在执行虚拟冲浪任务之前,我们从 36 名健康志愿者的脑电图(EEG)静息状态记录中提取了七种广为接受的微状态,它们代表了参与者在静息状态下的思维状态。通过将神经生物标志物(微状态)和运动行为指标相关联,我们证实后部 DMN 的预激活与运动任务中后部表现不佳相关。然而,我们仅发现 AN 预激活与后部运动表现之间存在不显著的关联。在这项脑电图研究中,我们提出后部DMN的前激活--通过脑电图微观状态成像--是与后部运动表现差相关的神经特征。我们的研究结果表明,执行控制系统的作用是保持 AN 和 DMN 之间的平衡。因此,基于神经反馈的DMN预激活下调有助于优化运动训练。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Brain Topography
Brain Topography 医学-临床神经学
CiteScore
4.70
自引率
7.40%
发文量
41
审稿时长
3 months
期刊介绍: Brain Topography publishes clinical and basic research on cognitive neuroscience and functional neurophysiology using the full range of imaging techniques including EEG, MEG, fMRI, TMS, diffusion imaging, spectroscopy, intracranial recordings, lesion studies, and related methods. Submissions combining multiple techniques are particularly encouraged, as well as reports of new and innovative methodologies.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信