Andrea Luppi

The paper uses multivariate information theory to analyze brain states and finds that higher-order interactions distinguish wakefulness, anaesthesia, and recovery.

This paper quantifies the energy cost of non-equilibrium brain computation using a new framework, showing the human brain is more energy-efficient than other mammals and cognitive tasks vary in their energy demands.

The paper introduces a whole-brain model called NEMO that uses neurotransmitter maps to simulate brain dynamics and shows it correlates with behavioral performance and intelligence.