Iversen John R, Ojeda Alejandro, Mullen Tim, Plank Markus, Snider Joseph, Cauwenberghs Gert, Poizner Howard
Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:4399-402. doi: 10.1109/EMBC.2014.6944599.
The planning of goal-directed movement towards targets in different parts of space is an important function of the brain. Such visuo-motor planning and execution is known to involve multiple brain regions, including visual, parietal, and frontal cortices. To understand how these brain regions work together to both plan and execute goal-directed movement, it is essential to describe the dynamic causal interactions among them. Here we model causal interactions of distributed cortical source activity derived from non-invasively recorded EEG, using a combination of ICA, minimum-norm distributed source localization (cLORETA), and dynamical modeling within the Source Information Flow Toolbox (SIFT). We differentiate network causal connectivity of reach planning and execution, by comparing the causal network in a speeded reaching task with that for a control task not requiring goal-directed movement. Analysis of a pilot dataset (n=5) shows the utility of this technique and reveals increased connectivity between visual, motor and frontal brain regions during reach planning, together with decreased cross-hemisphere visual coupling during planning and execution, possibly related to task demands.
朝向空间不同部位目标的目标导向运动规划是大脑的一项重要功能。已知这种视觉运动规划和执行涉及多个脑区，包括视觉皮层、顶叶皮层和额叶皮层。为了理解这些脑区如何协同工作以规划和执行目标导向运动，描述它们之间的动态因果相互作用至关重要。在此，我们使用独立成分分析（ICA）、最小范数分布式源定位（cLORETA）以及源信息流工具箱（SIFT）中的动态建模，对从无创记录的脑电图（EEG）中提取的分布式皮层源活动的因果相互作用进行建模。通过将快速伸手任务中的因果网络与不需要目标导向运动的对照任务中的因果网络进行比较，我们区分了伸手规划和执行的网络因果连通性。对一个试点数据集（n = 5）的分析显示了该技术的实用性，并揭示了伸手规划期间视觉、运动和额叶脑区之间连通性增加，以及规划和执行期间跨半球视觉耦合减少，这可能与任务需求有关。
