School and Graduate Institute of Physical Therapy, College of Medicine, National Taiwan University, Taipei, Taiwan.
Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan.
J Neuroeng Rehabil. 2022 Jun 27;19(1):64. doi: 10.1186/s12984-022-01042-2.
Wearable devices have been found effective in training ankle control in patients with neurological diseases. However, the neural mechanisms associated with using wearable devices for ankle training remain largely unexplored. This study aimed to investigate the ankle tracking performance and brain white matter changes associated with ankle tracking learning using a wearable-device system and the behavior-brain structure relationships in middle-aged and older adults.
Twenty-six middle-aged and older adults (48-75 years) participated in this study. Participants underwent 5-day ankle tracking learning with their non-dominant foot using a custom-built ankle tracking system equipped with a wearable sensor and a sensor-computer interface for real-time visual feedback and data acquisition. Repeated and random sequences of target tracking trajectories were both used for learning and testing. Ankle tracking performance, calculated as the root-mean-squared-error (RMSE) between the target and actual ankle trajectories, and brain diffusion spectrum MR images were acquired at baseline and retention tests. The general fractional anisotropy (GFA) values of eight brain white matter tracts of interest were calculated to indicate their integrity. Two-way (Sex × Time) mixed repeated measures ANOVA procedures were used to investigate Sex and Time effects on RMSE and GFA. Correlations between changes in RMSE and those in GFA were analyzed, controlling for age and sex.
After learning, both male and female participants reduced the RMSE of tracking repeated and random sequences (both p < 0.001). Among the eight fiber tracts, the right superior longitudinal fasciculus II (R SLF II) was the only one which showed both increased GFA (p = 0.039) after learning and predictive power of reductions in RMSE for random sequence tracking with its changes in GFA [β = 0.514, R change = 0.259, p = 0.008].
Our findings implied that interactive tracking movement learning using wearable sensors may place high demands on the attention, sensory feedback integration, and sensorimotor transformation functions of the brain. Therefore, the SLF II, which is known to perform these brain functions, showed corresponding neural plasticity after such learning, and its plasticity also predicted the behavioral gains. The SLF II appears to be a very important anatomical neural correlate involved in such learning paradigms.
可穿戴设备已被证明在训练神经疾病患者的踝关节控制方面非常有效。然而，使用可穿戴设备进行踝关节训练的神经机制在很大程度上仍未得到探索。本研究旨在使用可穿戴设备系统调查与踝关节跟踪学习相关的踝关节跟踪性能和大脑白质变化，并研究中年和老年人的行为-大脑结构关系。
26 名中年和老年人（48-75 岁）参加了这项研究。参与者使用定制的踝关节跟踪系统进行了 5 天的非主导脚踝关节跟踪学习，该系统配备了可穿戴传感器和传感器-计算机接口，用于实时视觉反馈和数据采集。学习和测试都使用了目标跟踪轨迹的重复和随机序列。踝关节跟踪性能，计算为目标和实际踝关节轨迹之间的均方根误差（RMSE），以及大脑扩散光谱磁共振图像，在基线和保留测试时采集。计算了 8 个感兴趣的大脑白质束的总分数各向异性（GFA）值，以指示其完整性。使用双向（性别×时间）混合重复测量方差分析程序来研究性别和时间对 RMSE 和 GFA 的影响。分析了 RMSE 变化与 GFA 变化之间的相关性，同时控制了年龄和性别。
学习后，男性和女性参与者都降低了跟踪重复和随机序列的 RMSE（均 p<0.001）。在 8 条纤维束中，右侧上纵束 II（R SLF II）是唯一一条在学习后显示 GFA 增加（p=0.039），并且其 GFA 变化可以预测随机序列跟踪中 RMSE 的降低[β=0.514，R 变化=0.259，p=0.008]。
我们的发现表明，使用可穿戴传感器进行交互式跟踪运动学习可能对大脑的注意力、感觉反馈整合和感觉运动转换功能提出很高的要求。因此，已知执行这些大脑功能的 SLF II 在这种学习后显示出相应的神经可塑性，并且其可塑性也预测了行为上的收益。SLF II 似乎是涉及这种学习模式的非常重要的解剖神经相关物。
