Marchal-Crespo Laura, Hollnagel Christoph, Brügger Mike, Kollias Spyros, Riener Robert
Sensory-Motor Systems Lab, Department of Mechanical and Process Engineering, ETH Zurich, Zurich, Switzerland.
IEEE Int Conf Rehabil Robot. 2011;2011:5975371. doi: 10.1109/ICORR.2011.5975371.
The goal of robotic therapy is to provoke motor plasticity via the application of robotic training strategies. Although robotic haptic guidance is the commonly used motor-training strategy to reduce performance errors while training, research on motor learning has emphasized that errors are a fundamental neural signal that drives motor adaptation. Thus, researchers have proposed robotic therapy algorithms that amplify movement errors rather than decrease them. Studying the particular brain regions involved in learning under different training strategies might help tailoring motor training conditions to the anatomical location of a focal brain insult. In this paper, we evaluate the brain regions involved in locomotion adaptation when training with three different conditions: without robotic guidance, with a random-varying force disturbance, and with repulsive forces proportional to errors. We performed an fMRI pilot study with four healthy subjects who stepped in an fMRI compatible walking robotic device. Subjects were instructed to actively synchronize their left leg with respect to their right leg (passively guided by the robot) while their left leg was affected by any of the three conditions. We observed activation in areas known to be involved in error processing. Although we found that all conditions required the similar cortical network to fulfill the task, we observed a tendency towards more activity in the motor/sensory network as more "challenged" the subjects were.
机器人疗法的目标是通过应用机器人训练策略来激发运动可塑性。尽管机器人触觉引导是训练时常用的运动训练策略，用于减少操作误差，但运动学习研究强调，误差是驱动运动适应的基本神经信号。因此，研究人员提出了放大运动误差而非减少误差的机器人疗法算法。研究不同训练策略下参与学习的特定脑区，可能有助于根据局灶性脑损伤的解剖位置来定制运动训练条件。在本文中，我们评估了在三种不同条件下进行训练时参与运动适应的脑区：无机器人引导、有随机变化的力干扰以及有与误差成比例的排斥力。我们对四名健康受试者进行了一项功能磁共振成像（fMRI）初步研究，这些受试者在一台与fMRI兼容的步行机器人设备上行走。受试者被要求在左腿受到三种条件中的任何一种影响时，主动使左腿相对于右腿（由机器人被动引导）同步。我们观察到已知参与误差处理的区域有激活。尽管我们发现所有条件都需要相似的皮质网络来完成任务，但我们观察到，随着受试者受到的“挑战”越大，运动/感觉网络中的活动就有越多的趋势。
