Phase Transitions in Mesoscopic Brain Dynamics – Implications for Cognition and Consciousness

Mesoscopic brain dynamics, typically studied with electroand magnetoencephalography (EEG and MEG) display a rich complexity of oscillatory and chaotic-like states, including many different frequencies, amplitudes and phases. Presumably, these different dynamical states correspond to different mental states and functions, and to study transitions between such states could give us valuable insight in brain-mind relations that should also be of clinical interest. We use computational methods to address these problems, with an objective to find relations between structure, dynamics and function. In particular, we have developed models of paleo- and neocortical structures, in order to study their mesoscopic neurodynamics, as a link between the microscopic neuronal and macroscopic mental events and processes. In this presentation, I will describe different types of models, where the emphasis is on network connectivity and structure, but also including molecular and cellular properties at varying detail, depending on the particular problem and experimental data available. We use these models to study how phase transitions can be induced in the mesoscopic neurodynamics of cortical networks by internal (natural) and external (artificial) factors. We relate and discuss the models and simulation results to macroscopic phenomena, such as arousal, attention, anaesthesia, learning, and mental disorders