Frankfurt Institute for Advanced Studies (FIAS), Goethe University Frankfurt, Germany.
PLoS Comput Biol. 2011 Nov;7(11):e1002253. doi: 10.1371/journal.pcbi.1002253. Epub 2011 Nov 3.
Various optimality principles have been proposed to explain the characteristics of coordinated eye and head movements during visual orienting behavior. At the same time, researchers have suggested several neural models to underly the generation of saccades, but these do not include online learning as a mechanism of optimization. Here, we suggest an open-loop neural controller with a local adaptation mechanism that minimizes a proposed cost function. Simulations show that the characteristics of coordinated eye and head movements generated by this model match the experimental data in many aspects, including the relationship between amplitude, duration and peak velocity in head-restrained and the relative contribution of eye and head to the total gaze shift in head-free conditions. Our model is a first step towards bringing together an optimality principle and an incremental local learning mechanism into a unified control scheme for coordinated eye and head movements.
各种最优性原则被提出以解释在视觉定向行为中协调的眼睛和头部运动的特征。同时，研究人员提出了几种神经模型来作为扫视产生的基础，但这些模型都不包括在线学习作为优化的机制。在这里，我们建议一个带有局部适应机制的开环神经控制器，该控制器最小化一个提出的代价函数。模拟表明，这个模型生成的协调的眼睛和头部运动的特征在许多方面与实验数据相匹配，包括在头部固定条件下头部运动的幅度、持续时间和峰值速度之间的关系，以及眼睛和头部对总注视转移的相对贡献。我们的模型是将最优性原则和增量局部学习机制结合到一个协调的眼睛和头部运动的统一控制方案中的第一步。
