Topological data analysis of the firings of a network of stochastic spiking neurons - Bai, Xiaotian; Yu, Chaojun; Zhai, Jian (Frontiers in Neural Circuits, 2024)
Topological data analysis is becoming more and more popular in recent years. It has found various applications in many different fields, for its convenience in analyzing and understanding the structure and dynamic of complex systems. We used topological data analysis to analyze the firings of a network of stochastic spiking neurons, which can be in a sub-critical, critical or supercritical state depending on the value of the control parameter. We calculated several topological features regarding Betti curves, then analyzed the behaviors of these features and using them as inputs for machine learning to discriminate the three states of the network.