论文标题
神经编码作为统计测试问题
Neural Coding as a Statistical Testing Problem
论文作者
论文摘要
我们采用测试的角度了解两种刺激之间的最小歧视时间是不同类型的速率编码神经元的最小歧视时间。我们的主要目标是描述两个不同编码系统的测试能力：位置单元和网格单元。特别是，通过适应的概念，我们表明固定位置细胞系统可以具有最小的歧视时间，而刺激距离较远时会减少。对于可以补充网格细胞系统的位置细胞系统来说，这可能是一个可观的优势，该系统能够区分比放置细胞更接近的刺激。
We take the testing perspective to understand what the minimal discrimination time between two stimuli is for different types of rate coding neurons. Our main goal is to describe the testing abilities of two different encoding systems: place cells and grid cells. In particular, we show, through the notion of adaptation, that a fixed place cell system can have a minimum discrimination time that decreases when the stimuli are further away. This could be a considerable advantage for the place cell system that could complement the grid cell system, which is able to discriminate stimuli that are much closer than place cells.
