In present paper we test different approaches to reconstructing the topology of the physical space from neural activity data in A1 fields of mice brains, in particular, having a Cognitome-focused approach in mind. Animals were placed in different new environments and discovered them while their physical and neural activity was recorded. We discuss possible approaches to identifying the place cells and make assumptions on how Cognitome theory might help with that. We also test and discuss various methods of dimension reduction and topology reconstruction. In particular, two main strategies we focus on are the Nerve theorem and point cloud-based methods. Conclusions on the results of reconstruction are supported with illustrations and mathematical background which is also briefly discussed.
翻译:在本文件中,我们从小鼠大脑的A1领域的神经活动数据中测试了重建物理空间的地形学的不同方法,特别是考虑到以COgnitom为重点的方法;动物被安置在不同的新环境中,并在记录其物理和神经活动时发现它们;我们讨论了确定地点细胞和假设Cognitom理论如何有助于这一点的可能方法;我们还测试和讨论各种减少尺寸和地表重建的方法;特别是,我们关注的两个主要战略是Nerve理论和点云方法;关于重建结果的结论得到了插图和数学背景的支持,这些也得到了简要的讨论。