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首页> 外文期刊>The European Journal of Neuroscience >The control of complex finger movements by directional information flow between mesial frontocentral areas and the primary motor cortex
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The control of complex finger movements by directional information flow between mesial frontocentral areas and the primary motor cortex

机译:通过中前额中央区和初级运动皮层之间的方向性信息流控制复杂的手指运动

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摘要

Complex movements require the interplay of local activation and interareal communication of sensorimotor brain regions. This is reflected in a decrease of task-related spectral power over the sensorimotor cortices and an increase in functional connectivity predominantly in the upper alpha band in the electroencephalogram (EEG). In the present study, directionality of information flow was investigated using EEG recordings to gain better understanding about the network architecture underlying the performance of complex sequential finger movements. This was assessed by means of Granger causality-derived directed transfer function (DTF). As DTF measures the influence one signal exerts on another based on a time lag between them, it allows implications to be drawn on causal relationships. To reveal causal connections between brain regions that are specifically modulated by task complexity, we contrasted the performance of right-handed sequential finger movements of different complexities (simple, scale, complex) that were either pre-learned (memorized) or novel instructed. A complexity-dependent increase in information flow from mesial frontocentral to the left motor cortex and, less pronounced, also to the right motor cortex specifically in the upper alpha range was found. Effective coupling during sequences of high complexity was larger for memorized sequences compared with novel sequences (P = 0.0037). These findings further support the role of mesial frontocentral areas in directing the primary motor cortex in the process of orchestrating complex movements and in particular learned sequences.
机译:复杂的运动需要感觉运动脑区域的局部激活和区域间交流的相互作用。这反映在感觉运动皮层上与任务相关的频谱功率的减少和功能连接性的增加,主要是在脑电图(EEG)的高α波段。在本研究中,使用EEG记录对信息流的方向性进行了研究,以更好地了解复杂的连续手指运动的性能背后的网络体系结构。这是通过格兰杰因果关系推导的直接传递函数(DTF)进行评估的。当DTF根据一个信号在它们之间的时滞来衡量一个信号对另一个信号施加的影响时,它就可以得出因果关系的含义。为了揭示受任务复杂度特别调节的大脑区域之间的因果关系,我们对比了预先学习(记忆)或新颖指示的不同复杂度(简单,规模,复杂)的右手顺序手指运动的性能。发现从中额额叶中央到左运动皮层,以及不太明显的,也到右运动皮层的信息流的复杂度依赖性增加,特别是在较高的alpha范围内。与新序列相比,记忆序列在高复杂度序列中的有效耦合更大(P = 0.0037)。这些发现进一步支持了在调节复杂运动,特别是学习序列的过程中,额中中央区在引导初级运动皮层中的作用。

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