Cortical Processing of Movement Perception

描述(申请人提供)：视觉引导运动的产生发生在由许多相互连接的皮质区域组成的密集网络中。为了研究这一过程，我们开发了一项基于运动错觉的任务，将绘画的可视化与用于产生它的运动分离。多电极记录技术已经被证明，并将被用来记录网络顶额部分三个节点中的神经元群体的单个单位活动。许多高级分析将被用来识别与这一行为任务的不同方面相关的活动的细胞组。传统的种群向量算法将被应用于大种群细胞，而一种新的、更敏感的粒子过滤器将被用于小种群。这两种群体算法都将被用来提取手臂轨迹(绘制的形状)的神经表示。有了这些神经轨迹和错觉任务，就有可能确定群体是否与可视化或执行的运动有关，我们已经(在初步数据中)显示的确定可以对至少两个要研究的节点做出。这些技术将使我们能够测量表示相对于运动的时间，从而确定哪些组充当控制过程的前馈和反馈元素。这将有助于建立视觉运动行为中使用的整个过程的示意图。

DESCRIPTION (provided by applicant): The generation of visually guided movement takes place in a dense network comprised of many interconnected cortical regions. To study this process, we have developed a task based on a motor illusion that dissociates visualization of drawing from the movement used to produce it. Multielectrode recording techniques have been proven and will be used to record single-unit activity from populations of neurons in three nodes of the parietal-frontal portion of the network. A number of advanced analyses will be used to identify groups of cells with activity related to different aspects of this behavioral task. The conventional population vector algorithm will be applied to large populations of cells and a new, more sensitive; particle filter will be used on small groups. Both of these population algorithms wilt be used to extract neural representations of the arm trajectory (drawn shape). With these neural trajectories and the illusion task, it will be possible to determine whether a population is related to the visualized or executed movement, a determination that we have shown (in preliminary data) can be made for at least two of the nodes to be studied. These techniques will allow us to measure timing of the representations relative to the movement and thereby ascertain which groups are acting as feed forward and feedback elements of the control process. This will help build a schematic of the overall process used in visuomotor behavior.