Two-Dimensional Models of Distributed Neural Processing in the Saccadic System

眼动是人类能够完成的最快速、最准确的运动之一，但是与肢体运动相比，产生眼动的机械系统相对简单。因此，跳眼系统作为一种模型系统，用于深入了解大脑如何产生运动控制的一般问题。该项目旨在研究视觉系统的二维感官信息是如何转化为来自大脑的高度分布的神经元控制信号的，这些信号可以移动眼睛，从而对我们周围的环境进行高效的检查，例如在阅读过程中。这些科学家将使用人工神经网络和优化技术来模拟运动命令如何在大脑中的神经结构中发展，例如视觉空间的非线性地图和运动空间的地图。扫视是由运动过程中眼睛位置的内部反馈控制的，而不是直接的视觉输入，因为视觉信息太慢，无法在扫视过程中提供补偿。这些科学家正在测试他们的假设，即大脑中这些图中活跃细胞数量的变化是由内部反馈信号驱动的，并在运动过程中主动控制眼睛的运动轨迹。他们的工作将帮助我们了解眼球运动和其他类型的运动，如精细运动控制或人类步态，是如何由大脑控制的。

9511365 Edward Keller Saccadic eye movements are among the most rapid and accurate movements that humans are capable of executing, but the mechanical system producing eye movements is relatively simple in comparison to limb movements. Therefore, the saccadic system has served as a model system for gaining insights into the general problem of how the brain generates motor control. This project is to examine how two-dimensional sensory information from the visual system is turned into the highly distributed neuronal control signals from the brain that move the eyes to produce highly efficient examination of our surroundings, for example, during reading. These scientists will use artificial neural networks and optimization techniques to model how movement commands are developed in neural structures in the brain such as the nonlinear maps of visual space and maps of the motor space. Saccades are controlled by internal feedback about eye position during a movement, but not direct visual input, because the visual messages are too slow to provide compensation during the saccade. These scientists are testing their hypothesis that shifts in the populations of active cells in these maps in the brain are driven by the internal feedback signal and actively control the trajectory of the eyes during the movement. Their work will help us to understand both how eye movements and other kinds of movement, such as fine motor control or human gait, are controlled by the brain.