Faculty of Information Technology, Beijing University of Technology, Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing 100124, China.
J Healthc Eng. 2021 Oct 26;2021:5607999. doi: 10.1155/2021/5607999. eCollection 2021.
Physiological studies have shown that the hippocampal structure of rats develops at different stages, in which the place cells continue to develop during the whole juvenile period of rats and mature after the juvenile period. As the main information source of place cells, grid cells should mature earlier than place cells. In order to make better use of the biological information exhibited by the rat brain hippocampus in the environment, we propose a position cognition model based on the spatial cell development mechanism of rat hippocampus. The model uses a recurrent neural network with parametric bias (RNNPB) to simulate changes in the discharge characteristics during the development of a single stripe cell. The oscillatory interference mechanism is able to fuse the developing stripe waves, thus indirectly simulating the developmental process of the grid cells. The output of the grid cells is then used as the information input of the place cells, whose development process is simulated by BP neural network. After the place cells matured, the position matrix generated by the place cell group was used to realize the position cognition of rats in a given spatial region. The experimental results show that this model can simulate the development process of grid cells and place cells, and it can realize high precision positioning in the given space area. Moreover, the experimental effect of cognitive map construction using this model is basically consistent with the effect of RatSLAM, which verifies the validity and accuracy of the model.
生理研究表明，大鼠的海马体结构在不同阶段发育，其中位置细胞在整个幼年期持续发育，并在幼年期后成熟。作为位置细胞的主要信息源，网格细胞应该比位置细胞更早成熟。为了更好地利用大鼠大脑海马体在环境中表现出的生物信息，我们提出了一种基于大鼠海马体空间细胞发育机制的位置认知模型。该模型使用具有参数偏差的递归神经网络（RNNPB）来模拟单个条纹细胞发育过程中的放电特性变化。振荡干扰机制能够融合正在发育的条纹波，从而间接模拟网格细胞的发育过程。然后，将网格细胞的输出用作位置细胞的信息输入，通过 BP 神经网络模拟位置细胞的发育过程。位置细胞成熟后，使用位置细胞群生成的位置矩阵来实现大鼠在给定空间区域的位置认知。实验结果表明，该模型可以模拟网格细胞和位置细胞的发育过程，并能在给定的空间区域实现高精度定位。此外，使用该模型构建认知图的实验效果与 RatSLAM 的效果基本一致，验证了该模型的有效性和准确性。
