Metastability in Neurodynamics - Murray Shanahan

A dynamical system is said to be metastable if it migrates between transient attractor-like states without converging on a stable attractor. In his groundbreaking book Dynamic Patterns, Scott Kelso suggested that metastability is an important property of neurodynamics. Since then, a few labs, including Gustavo Deco's in Barcelona and my own at Imperial  College London, have explored this idea both empirically and with computer models. In this talk I will overview this work and relate it to other important topics in neurodynamics, such as criticality and dynamical complexity.