Neuroscience Model based on Computer Recognition Technology (CRT)

Neuroimaging has developed rapidly and become an interdisciplinary subject across the fields of mathematics, statistics, neuroscience, psychiatry, physics and computer technology. In addition, with the rapid development of genomics, more and more studies are trying to uncover the effects of heredity and variation on brain structure and function. This paper studies the design of neuroscience model based on CRT, discusses the recognition performance in computer vision, designs the neuroscience model under the recognition technology, establishes the neuroscience coupling model, puts forward the topology, and analyzes the influence of network topology attribute on the controllability of the model. The test results show that the overall controllability of the system decreases with the increase of the number of neural communities, and there is an optimal coupling strength, which makes the controllability of the model the highest. With the increase of the number of neural communities, the value of the optimal coupling strength gradually decreases, which provides a theoretical reference for the control and treatment of neuropsychiatric diseases caused by the change of brain network topology.