Department of Neurobiology, Brain Research, Weizmann Institute of Science Rehovot, Israel ; Department of Computer Science and Applied Mathematics, Weizmann Institute of Science Rehovot, Israel.
Department of Computer Science and Applied Mathematics, Weizmann Institute of Science Rehovot, Israel.
Front Hum Neurosci. 2014 Apr 16;8:201. doi: 10.3389/fnhum.2014.00201. eCollection 2014.
There is growing experimental evidence that the engagement of different brain areas in a given motor task may change with practice, although the specific brain activity patterns underlying different stages of learning, as defined by kinematic or dynamic performance indices, are not well understood. Here we studied the change in activation in motor areas during practice on sequences of handwriting-like trajectories, connecting four target points on a digitizing table "as rapidly and as accurately as possible" while lying inside an fMRI scanner. Analysis of the subjects' pooled kinematic and imaging data, acquired at the beginning, middle, and end of the training period, revealed no correlation between the amount of activation in the contralateral M1, PM (dorsal and ventral), supplementary motor area (SMA), preSMA, and Posterior Parietal Cortex (PPC) and the amount of practice per-se. Single trial analysis has revealed that the correlation between the amount of activation in the contralateral M1 and trial mean velocity was partially modulated by performance gains related effects, such as increased hand motion smoothness. Furthermore, it was found that the amount of activation in the contralateral preSMA increased when subjects shifted from generating straight point-to-point trajectories to their spatiotemporal concatenation into a smooth, curved trajectory. Altogether, our results indicate that the amount of activation in the contralateral M1, PMd, and preSMA during the learning of movement sequences is correlated with performance gains and that high level motion features (e.g., motion smoothness) may modulate, or even mask correlations between activity changes and low-level motion attributes (e.g., trial mean velocity).
越来越多的实验证据表明，在给定的运动任务中，不同大脑区域的参与可能会随着练习而改变，尽管对于学习的不同阶段（由运动学或动力学性能指标定义）背后的特定大脑活动模式还不是很了解。在这里，我们研究了在 fMRI 扫描仪内进行手写轨迹序列练习时，运动区域的激活变化。研究人员要求被试“尽可能快、尽可能准确”地连接数字表上的四个目标点，记录他们的运动学和影像学数据。分析被试在训练期开始、中间和结束时的汇总运动学和成像数据，发现对侧 M1、PM（背侧和腹侧）、辅助运动区（SMA）、前运动区（PreSMA）和后顶叶皮层（PPC）中的激活量与练习量之间没有相关性。单试分析表明，对侧 M1 中的激活量与试验平均速度之间的相关性部分受到与性能增益相关的效应的调制，例如手运动平滑度的增加。此外，研究还发现，当被试从生成直线点对点轨迹转变为时空连接成平滑的曲线轨迹时，对侧 PreSMA 的激活量增加。总的来说，我们的研究结果表明，在学习运动序列期间，对侧 M1、PMd 和 PreSMA 的激活量与运动性能的提高相关，并且高级运动特征（例如运动平滑度）可能会调节，甚至掩盖活动变化与低级运动属性（例如试验平均速度）之间的相关性。
