IMAGE REPRESENTATION IN THE PRIMARY VISUAL CORTEX

本申请中描述的调查旨在确定 信息处理的众所周知的原则可以在多大程度上 应用于建立中枢神经系统使用的方法， 有效地从环境中提取信息。中的办法 应用程序采用计算技术，期望 现有的生理结果将指导和检验计算结果。 初步结果表明，许多众所周知的特点， 初级视皮层可以从一个简单的视觉系统模型中获得 这同时优化了大脑皮层沿着 这样做的神经代价。将比较模型的输出 与现有的多维生理描述的细胞在 视觉皮层已经获得了非线性系统 识别技术。本文研究了细胞的系综性质， 模型皮层将被用来获得功能，可以与 心理物理学的结果。 这些研究的结果将用于指导 更复杂的神经信息处理模型， 适用于中枢神经系统的其他区域。此外，本发明还 这种材料提供了生物学和生物学之间重要的定量联系， 图像表示的合成方法。

The investigations described in this application are designed to determine the extent to which well known principles of information processing can be applied to establish the methods used by the central nervous system to efficiently extract information from its environment. The approach in the application employs computational techniques with the expectation that existing physiologic results will guide and test the computational ones. Preliminary results suggest that many of the well known features of the primary visual cortex can be obtained from a simple visual system model which simultaneously optimizes information transfer in the cortex along with the neural costs of doing so. Outputs of the model will be compared with existing multidimensional physiologic descriptions of cells in the visual cortex which have been obtained with nonlinear systems identification techniques. The ensemble properties of the cells in the model cortex will be used to obtain functions which can be compared with established psychophysical results. The results from these studies will be used to guide the development of more complex models of neural information processing, and may be applicable to other regions of the central nervous system. Additionally, this material provides an important quantitative link between biologic and synthetic methods for image representation.