Investigating Information Redundancy in Neuronal Networks using Systems Biology and Neuronal Parameter Estimation
Autour(s)
- Lixuan Zhang, Chang Li, Lee Chen, Don Chen, Zheng Xiang, Bing Pan
Abstract
The human brain is a highly complex system that processes and stores vast amounts of information. Neurons are the basic building blocks of the brain, and their collective activity gives rise to the complex behavior of the brain. One of the challenges in studying neuronal networks is to understand how the system processes and stores information. In this article, we review the current state of knowledge regarding the use of systems biology and neuronal parameter estimation techniques to investigate information redundancy in neuronal networks. We also describe the research methodology used to estimate neuronal parameters and analyze information redundancy in neuronal networks. Our results suggest that information redundancy is an important feature of neuronal networks, and that it may play a role in the brain's ability to process and store information.