The Reciprocal Relationship Between Short- and Long-Term Motor Learning and Neurometabolites

IF 3.5 2区 医学 Q1 NEUROIMAGING
Melina Hehl, Shanti Van Malderen, Svitlana Blashchuk, Stefan Sunaert, Richard A. E. Edden, Stephan P. Swinnen, Koen Cuypers
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Abstract

Skill acquisition requires practice to stimulate neuroplasticity. Changes in inhibitory and excitatory neurotransmitters, such as gamma-aminobutyric acid (GABA) and glutamate, are believed to play a crucial role in promoting neuroplasticity. Magnetic resonance spectroscopy (MRS) at 3 T, using the MEGA-PRESS sequence, and behavioral data were collected from 62 volunteers. Participants completed a 4-week protocol, practicing either complex (n = 32) or simple (n = 30) bimanual tracking tasks (BTT). Neurotransmitter levels and skill levels at baseline, after 2 and 4 weeks of motor training were compared for the left and right primary sensorimotor cortex (SM1) and the left dorsal premotor cortex (PMd). Furthermore, task-related modulations of neurotransmitter levels in the left PMd were assessed. The study yielded that baseline neurotransmitter levels in motor-related brain regions predicted training success. Furthermore, lower GABA+ (p = 0.0347) and higher Glx (glutamate + glutamine compound) levels (p = 0.0234) in left PMd correlated with better long-term learning of simple and complex tasks, respectively, whereas higher GABA+ in right SM1 correlated with complex task learning (p = 0.0064). Resting neurometabolite levels changed during the intervention: Left SM1 Glx decreased with complex training toward Week 4 (p = 0.0135), whereas right SM1 Glx was increased at Week 2 (p = 0.0043), regardless of training type. Group-level analysis showed no task-related neurometabolite modulation in the left PMd. However, individual baseline GABA+ and Glx modulation influenced short-term motor learning (interaction: p = 0.0213). These findings underscore the importance of an interplay between inhibitory and excitatory neurotransmitters during motor learning and suggest potential for future personalized approaches to optimize motor learning.

Abstract Image

短期和长期运动学习与神经代谢物的相互关系
技能习得需要通过练习来刺激神经可塑性。抑制性和兴奋性神经递质的变化,如γ -氨基丁酸(GABA)和谷氨酸,被认为在促进神经可塑性中起着至关重要的作用。使用MEGA-PRESS序列在3t时进行磁共振波谱(MRS),并收集了62名志愿者的行为数据。参与者完成了为期4周的方案,练习复杂(n = 32)或简单(n = 30)的双手跟踪任务(BTT)。在2周和4周的运动训练后,比较左、右初级感觉运动皮层(SM1)和左背运动前皮层(PMd)的神经递质水平和技能水平。此外,评估了左侧PMd中神经递质水平的任务相关调节。研究表明,运动相关大脑区域的基线神经递质水平预示着训练的成功。此外,左侧PMd较低的GABA+ (p = 0.0347)和较高的Glx(谷氨酸+谷氨酰胺化合物)水平(p = 0.0234)分别与较好的简单和复杂任务的长期学习相关,而右侧SM1较高的GABA+与复杂任务的学习相关(p = 0.0064)。静息神经代谢物水平在干预期间发生了变化:左侧SM1 Glx随着第4周的复杂训练而下降(p = 0.0135),而右侧SM1 Glx在第2周增加(p = 0.0043),与训练类型无关。组水平分析显示左侧PMd没有任务相关的神经代谢物调节。然而,个体基线GABA+和Glx调节影响短期运动学习(相互作用:p = 0.0213)。这些发现强调了运动学习过程中抑制性和兴奋性神经递质之间相互作用的重要性,并提出了未来优化运动学习的个性化方法的潜力。
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来源期刊
Human Brain Mapping
Human Brain Mapping 医学-核医学
CiteScore
8.30
自引率
6.20%
发文量
401
审稿时长
3-6 weeks
期刊介绍: Human Brain Mapping publishes peer-reviewed basic, clinical, technical, and theoretical research in the interdisciplinary and rapidly expanding field of human brain mapping. The journal features research derived from non-invasive brain imaging modalities used to explore the spatial and temporal organization of the neural systems supporting human behavior. Imaging modalities of interest include positron emission tomography, event-related potentials, electro-and magnetoencephalography, magnetic resonance imaging, and single-photon emission tomography. Brain mapping research in both normal and clinical populations is encouraged. Article formats include Research Articles, Review Articles, Clinical Case Studies, and Technique, as well as Technological Developments, Theoretical Articles, and Synthetic Reviews. Technical advances, such as novel brain imaging methods, analyses for detecting or localizing neural activity, synergistic uses of multiple imaging modalities, and strategies for the design of behavioral paradigms and neural-systems modeling are of particular interest. The journal endorses the propagation of methodological standards and encourages database development in the field of human brain mapping.
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