■在精密运动中实现最佳的视觉运动性能取决于在运动准备过程中保持最佳的心理状态。为了揭示最佳心理状态,广泛的EEG研究在视觉运动任务期间建立了Mu节律(Cz为8-13Hz)和认知资源分配之间的联系(即,高尔夫或射击)。此外,脑电图神经反馈训练(NFT)的新方法,称为特定于函数的指令(FSI)方法,运动涉及提供功能指导的口头指令,以帮助个人控制特定的EEG参数,并使其与目标大脑活动特征对齐。虽然这种方法最初被假设为帮助个人在NFT期间达到特定的精神状态,涉及Mu节律的EEG-NFT对视觉运动表现的影响,特别是在将传统教学(TI)方法与FSI方法进行对比时,强调了额外探索的必要性。因此,本研究的目的是探讨FSI方法在视觉运动表现背景下通过EEG-NFT调节Mu节律的影响.
■招募了30名新手参与者,并将其分为三组:特定于功能的指导(FSI,四位女性,六名男性;平均年龄=27.00±7.13),传统指令(TI,五女,五名男性;平均年龄=27.00±3.88),和假对照(SC,五女,五名男性;平均年龄=27.80±5.34)。这些小组进行了一次EEG-NFT,并在EEG-NFT之前和之后执行了高尔夫推杆任务。
■结果表明,在FSI组中,具有增强Mu能力的单会话NFT导致推杆性能显着下降(p=0.013)。此外,我们注意到边际意义,表明在EEG-NFT后,Mu功率略有增加,动作控制的主观感觉减少(p=0.119)。虽然高尔夫推杆表现中的穆力和平均径向误差之间存在正相关(p=0.043),在高尔夫推杆准确性下降的背景下,谨慎地解释这种关系是很重要的。
■研究结果强调了扩大调查的必要性,以更深刻地理解Mupower在视觉运动性能中的细微差别意义。该研究强调了FSI方法在EEG-NFT和增强视觉运动性能方面的潜在有效性,但它也强调了技能水平和注意力控制的潜在影响,特别是在复杂的视觉运动任务中。
UNASSIGNED: Achieving optimal visuomotor performance in precision sports relies on maintaining an optimal psychological state during motor preparation. To uncover the optimal psychological state, extensive EEG studies have established a link between the Mu rhythm (8-13 Hz at Cz) and cognitive resource allocation during visuomotor tasks (i.e., golf or shooting). In addition, the new approach in EEG neurofeedback training (NFT), called the function-specific instruction (FSI) approach, for sports involves providing function-directed verbal instructions to assist individuals to control specific EEG parameters and align them with targeted brain activity features. While this approach was initially hypothesized to aid individuals in attaining a particular mental state during NFT, the impact of EEG-NFT involving Mu rhythm on visuomotor performance, especially when contrasting the traditional instruction (TI) approach with the FSI approach, underscores the necessity for additional exploration. Hence, the objective of this study is to investigate the impact of the FSI approach on modulating Mu rhythm through EEG-NFT in the context of visuomotor performance.
UNASSIGNED: Thirty novice participants were recruited and divided into three groups: function-specific instruction (FSI, four females, six males; mean age = 27.00 ± 7.13), traditional instruction (TI, five females, five males; mean age = 27.00 ± 3.88), and sham control (SC, five females, five males; mean age = 27.80 ± 5.34). These groups engaged in a single-session EEG-NFT and performed golf putting tasks both before and after the EEG-NFT.
UNASSIGNED: The results showed that within the FSI group, single-session NFT with augmented Mu power led to a significant decrease in putting performance (p = 0.013). Furthermore, we noted a marginal significance indicating a slight increase in Mu power and a reduction in the subjective sensation of action control following EEG-NFT (p = 0.119). While there was a positive correlation between Mu power and mean radial error in golf putting performance (p = 0.043), it is important to interpret this relationship cautiously in the context of reduced accuracy in golf putting.
UNASSIGNED: The findings emphasize the necessity for extended investigation to attain a more profound comprehension of the nuanced significance of Mu power in visuomotor performance. The study highlights the potential effectiveness of the FSI approach in EEG-NFT and in enhancing visuomotor performance, but it also emphasizes the potential impact of skill level and attentional control, particularly in complex visuomotor tasks.