Research on Neural Cell State Detection Based on Improved RCNN

Determining whether neurons are activated is of great significance in both scientific research and clinical applications. By detecting the activation state of neurons, researchers can gain a deeper understanding of brain mechanisms, revealing the specific functions of different brain regions in perception, cognition, motor control, and emotional regulation. This is crucial for decoding complex neural processes and establishing brain function maps. Additionally, many neurological disorders, such as epilepsy, Parkinson’s disease, depression, and schizophrenia, are associated with abnormal neuron activation. This study developed an improved RCNN model to detect and classify images of neurons in different states, achieving significant improvements in recognition accuracy. Average Precision reached 0.730 and Average Recall reached 0.720.