Information Structures and Consciousness

This course explores the concept of brain states emerging through evolving dynamics of brain networks, focusing on informational structures (IS) that change over time and impact the system's behavior. Participants will learn about the relationship between IS and Integrated Information Theory (IIT) postulates, as well as how different brain networks interact through IS measures. The course covers properties such as metastability, information integration, and synchronization, which are relevant to conscious activity. Machine learning classifiers are used to identify states of consciousness in healthy individuals and post-comatose patients with high precision. The teaching method involves a joint presentation by experts in the field. This course is intended for individuals interested in neuroscience, consciousness studies, and computational modeling of brain activity.