Dipietro Laura, Poizner Howard, Krebs Hermano I
Massachusetts Institute of Technology.
J Cogn Neurosci. 2014 Sep;26(9):1966-80. doi: 10.1162/jocn_a_00593. Epub 2014 Feb 24.
The ability to control online motor corrections is key to dealing with unexpected changes arising in the environment with which we interact. How the CNS controls online motor corrections is poorly understood, but evidence has accumulated in favor of a submovement-based model in which apparently continuous movement is segmented into distinct submovements. Although most studies have focused on submovements' kinematic features, direct links with the underlying neural dynamics have not been extensively explored. This study sought to identify an electroencephalographic signature of submovements. We elicited kinematic submovements using a double-step displacement paradigm. Participants moved their wrist toward a target whose direction could shift mid-movement with a 50% probability. Movement kinematics and cortical activity were concurrently recorded with a low-friction robotic device and high-density electroencephalography. Analysis of spatiotemporal dynamics of brain activation and its correlation with movement kinematics showed that the production of each kinematic submovement was accompanied by (1) stereotyped topographic scalp maps and (2) frontoparietal ERPs time-locked to submovements. Positive ERP peaks from frontocentral areas contralateral to the moving wrist preceded kinematic submovement peaks by 220-250 msec and were followed by positive ERP peaks from contralateral parietal areas (140-250 msec latency, 0-80 msec before submovement peaks). Moreover, individual subject variability in the latency of frontoparietal ERP components following the target shift significantly predicted variability in the latency of the corrective submovement. Our results are in concordance with evidence for the intermittent nature of continuous movement and elucidate the timing and role of frontoparietal activations in the generation and control of corrective submovements.
控制在线运动校正的能力是应对我们所交互环境中出现的意外变化的关键。中枢神经系统如何控制在线运动校正目前尚不清楚,但已有证据支持基于子运动的模型,即看似连续的运动被分割为不同的子运动。尽管大多数研究都集中在子运动的运动学特征上,但与潜在神经动力学的直接联系尚未得到广泛探索。本研究旨在识别子运动的脑电图特征。我们使用双步位移范式诱发运动学子运动。参与者将手腕移向一个目标,该目标的方向在运动过程中有50%的概率会发生偏移。使用低摩擦机器人设备和高密度脑电图同时记录运动学和皮层活动。对大脑激活的时空动态及其与运动学的相关性分析表明,每个运动学子运动的产生伴随着(1)刻板的头皮地形图和(2)与子运动时间锁定的额顶区事件相关电位。与运动手腕对侧的额中央区的正性事件相关电位峰值比运动学子运动峰值提前220 - 250毫秒出现,随后是对侧顶叶区的正性事件相关电位峰值(潜伏期140 - 250毫秒,在子运动峰值前0 - 80毫秒)。此外,目标偏移后额顶叶事件相关电位成分潜伏期的个体差异显著预测了校正子运动潜伏期的差异。我们的结果与连续运动的间歇性本质的证据一致,并阐明了额顶叶激活在校正子运动产生和控制中的时间和作用。