Abstract
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.
Highlights
In the adult rat brain, space and orientation are expressed by the hippocampal structure, which is home to a variety of spatial cells with specific firing effects on spatial location, including head-direction cells [1], grid cells [2], and place cells [3]
Use the self-motion clue information in the physiological trajectory of Hafting et al [3] to obtain the velocity component of the velocity in the corresponding stripe wave direction and use it as the Parametric Bias (PB) bias node input of each stripe wave development unit. e theoretical stripe cell discharge rate during the physiological trajectory is used as a developmental sample. e simulation experiment sets the number of grid cells to be developed as 10, corresponding to the number of stripe cells to be developed as 3×10
It can be seen from the figure that as the number of learning and training times increases, the developed stripe wave gradually approaches the theoretical two-dimensional cos waveform, thereby simulating the changes in discharge characteristics during the development of stripe cells. e given spatial area is a square area of 200 cm ∗ 200 cm, the phase of the grid field to be developed is randomly selected in the given spatial area, and the orientation of the grid field is randomly selected within the range of 0°∼360°
Summary
In the adult rat brain, space and orientation are expressed by the hippocampal structure, which is home to a variety of spatial cells with specific firing effects on spatial location, including head-direction cells [1], grid cells [2], and place cells [3]. One is to build a neural network model based on the anatomical structure of the hippocampus and the cognitive mechanism of spatial cells and apply it to mobile robots that mimic the rat brain nervous system for autonomous navigation [20]. E “RatSLAM” framework has obtained extensive and in-depth research on the cognitive computational neurobehavioral model of the rat brain hippocampus environment and proposed a mature real-time positioning and map construction method, whose core part is called the pose cell [22, 23]. This model is the first to use neural networks to simulate the changes in discharge characteristics during the development of two spatial cells (grid cell and place cell) in the rat brain hippocampus structure. Compared with the positioning method of traditional mobile robots, the position recognition model is more bionic and suitable (low requirements on hardware and sensors) for navigation in different environments
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
