Beik Meysam, Taheri Hamidreza, Saberi Kakhki Alireza, Ghoshuni Majid
Motor Behavior Laboratory, Department of Motor Behavior, Faculty of Sport Sciences, Ferdowsi University of Mashhad, Mashhad, Iran.
Department of Biomedical Engineering, Islamic Azad University, Mashhad Branch, Mashhad, Iran.
Front Aging Neurosci. 2020 Jun 12;12:173. doi: 10.3389/fnagi.2020.00173. eCollection 2020.
The purpose of this study was to investigate the neural mechanisms of the contextual interference effect (CIE) and parameter similarity on motor learning in older adults. Sixty older adults (mean age, 67.68 ± 3.95 years) were randomly assigned to one of six experimental groups: blocked-similar, algorithm-similar, random-similar, blocked-dissimilar, algorithm-dissimilar, and random-dissimilar. Algorithm practice was a hybrid practice schedule (a combination of blocked, serial, and random practice) that switching between practice schedules were based on error trial number, ≤33%. The sequential motor task was used to record the absolute timing for the absolute timing goals (ATGs). In similar conditions, the participants' performance was near ATGs (1,350, 1,500, 1,650 ms) and in dissimilar conditions, they performed far ATGs (1,050, 1,500, 1,950 ms) with the same spatial sequence for all groups. EEG signals were continuously collected during the acquisition phase and delayed retention. Data were analyzed in different bands (alpha and beta) and scalp locations (frontal: Fp1, Fp2, F3, F4; central: C3, C4; and parietal: P3, P4) with repeated measures on the last factor. The analyses were included motor preparation and intertrial interval (motor evaluation) periods in the first six blocks and the last six blocks, respectively. The results of behavioral data indicated that algorithm practice resulted in medium error related to classic blocked and random practice during the acquisition, however, algorithm practice outperformed the classic blocked and random practice in the delayed retention test. The results of EEG data demonstrated that algorithm practice, due to optimal activity in the frontal lobe (medium alpha and beta activation at prefrontal), resulted in increased activity of sensorimotor areas (high alpha activation at C3 and P4) in older adults. Also, EEG data showed that similar conditions could affect the intertrial interval period (medium alpha and beta activation in frontal in the last six-block), while the dissimilar conditions could affect the motor preparation period (medium alpha and beta activation in frontal in the first six-block). In conclusion, algorithm practice can enhance motor learning and optimize the efficiency of brain activity, resulting in the achievement of a desirable goal in older adults.
本研究旨在探究情境干扰效应（CIE）和参数相似性对老年人运动学习的神经机制。60名老年人（平均年龄67.68±3.95岁）被随机分配到六个实验组之一：分组相似组、算法相似组、随机相似组、分组不相似组、算法不相似组和随机不相似组。算法练习是一种混合练习计划（分组、序列和随机练习的组合），练习计划之间的切换基于错误试验次数，≤33%。连续运动任务用于记录绝对计时目标（ATG）的绝对计时。在相似条件下，参与者的表现接近ATG（1350、1500、1650毫秒），在不相似条件下，他们在所有组中以相同的空间序列执行远离ATG的任务（1050、1500、1950毫秒）。在获取阶段和延迟保留期间持续收集脑电图信号。数据在不同频段（阿尔法和贝塔）和头皮位置（额叶：Fp1、Fp2、F3、F4；中央：C3、C4；顶叶：P3、P4）进行分析，对最后一个因素进行重复测量。分析分别包括前六个块和最后六个块中的运动准备和试间间隔（运动评估）期。行为数据结果表明，在获取过程中，算法练习导致的错误与经典分组和随机练习相关，但在延迟保留测试中，算法练习的表现优于经典分组和随机练习。脑电图数据结果表明，算法练习由于额叶的最佳活动（前额叶中等阿尔法和贝塔激活），导致老年人感觉运动区域的活动增加（C3和P4处高阿尔法激活）。此外，脑电图数据显示，相似条件会影响试间间隔期（最后六个块中额叶中等阿尔法和贝塔激活），而不相似条件会影响运动准备期（前六个块中额叶中等阿尔法和贝塔激活）。总之，算法练习可以增强运动学习并优化大脑活动效率，从而使老年人实现理想目标。
