Neural systems can perform incredibly complex computations, but what are the features that underlie their autonomy? How do healthy embodied brains remain independent from the dynamics of the world while also being responsive? How do neural networks find balance yet avoid infinite repetition or silence?
Emerging techniques in complexity sciences and neural modelling provide the tools to explore dynamics in such systems but have yet to explain how daily computational tasks are accomplished in a continuous and autonomous fashion. These questions regarding system autonomy are often independently explored in physics, mathematics, philosophy and other fields. The issue of increasing freedom in systems is at the foundations of cognitive and social sciences.