Abstract

Neural stem cell is a type of stem cell with self-renewal ability and multi-directional differentiation potential. Under certain conditions, neural stem cells can differentiate into neurons, oligodendrocytes, and astrocytes, thereby participating in the occurrence of the nervous system. Considering that deep convolutional neural networks have better feature learning capabilities for image data than feedforward neural networks, this paper studies how to apply deep convolutional neural networks to modeling based on imaging features, and constructs convolutional neural networks. In this paper, the distribution of CD133+ neural stem cells in different neuroanatomical regions of rat brain and possible migration flow were studied. The experimental results show that there are obvious differences in the distribution of neural stem cells in different neuroanatomical regions. With the growth and development of rats, a large number of CD133+ neural stem cells migrate from the subventricular zone to the surrounding ganglia, corpus callosum, and cerebral cortex. Seven days before the operation, the rats were trained in water maze, and the EL (Escape Latency) of the rats was recorded for 1 week, 2 weeks and 1 month. Compared with the control group of sham operation, EL was significantly increased in the cerebral ischemia-reperfusion group. Compared with cerebral ischemia-reperfusion + acupuncture group and cerebral ischemia-reperfusion group, EL was significantly smaller. The results show that electroacupuncture can induce the proliferation of newborn cells in the brain and promote the differentiation of newborn cells into glial cells and nerve cells. After electroacupuncture intervention, a small number of new nerve cells already have the activity and function of secreting Ach. Electroacupuncture intervention can promote the recovery of rat nerve function after cerebral ischemia and reperfusion.

Highlights

  • NSC exists during the embryonic period and adulthood of mammals, and the regeneration, differentiation, and migration capabilities of neural stem cells are closely related to degenerative diseases of the central nervous system [1]

  • Three-dimensional imaging and immunofluorescence staining results showed that rat CD133+ neural stem cells migrated from the SVZ area to the surrounding ganglia and cerebral cortex

  • CD133+ neural stem cells differentiated into other types of cells

Read more

Summary

INTRODUCTION

NSC (neural stem cell) exists during the embryonic period and adulthood of mammals, and the regeneration, differentiation, and migration capabilities of neural stem cells are closely related to degenerative diseases of the central nervous system [1]. The technical contributions of this paper can be summarized as follows: First: In order to better analyze the images of neural stem cell migration and functional reconstruction, a convolutional neural network model was constructed. It is of great scientific significance to study the distribution and migration of neural stem cells This topic can provide a new therapeutic idea for diseases related to the central nervous system. The weight sharing mechanism greatly reduces the number of training parameters required in the model, and the visual features learned at the same time are not sensitive to the absolute position in the field of view, thereby extracting image features more efficiently These characteristics make the convolutional neural network have better learning and generalization capabilities for visual tasks than ordinary feedforward neural networks

CONVOLUTIONAL LAYER AND POOLING LAYER
NETWORK PARAMETER LEARNING
PRE-TRAINING OF CONVOLUTIONAL NEURAL NETWORK MODELS
Findings
CONCLUSION
Full Text
Published version (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