Wheels：神经编码非凸性的一个新判据
Wheels: A New Criterion for Non-convexity of Neural Codes
摘要：
我们引入了新的几何和组合标准，排除了神经代码是凸的，并使用它们来解决分类问题的代码上的六个神经元。在此过程中，我们给出了第一个非凸代码的例子，该代码没有局部障碍，并且具有二维的单纯复形。我们还刻画了神经代码的凸性，其中单纯复形是纯的低维或高维。
英文摘要：
We introduce new geometric and combinatorial criteria that preclude a neural code from being convex, and use them to tackle the classification problem for codes on six neurons. Along the way, we give the first example of a code that is non-convex, has no local obstructions, and has simplicial complex of dimension two. We also characterize convexity for neural codes for which the simplicial complex is pure of low or high dimension.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
