The brain is a complex and dynamical system that is very difficult to understand. It is very easy to produce models with many mechanisms trying to simulate the brain. But rather I will be presenting a minimal model that should be able to capture the main features of the brain. Features such as random directed graphs, non-equilibrium dynamics, quasi-criticality, phase transitions, and chaotic regions. The model is nonequilibrium stochastic cellular automata. With this model, we can get further insight into these features in experimental data and possibly understand the physical mechanisms that keep the brain in a quasi-critical phase.
The College of Arts