The human brain is a complex dynamical system that is continuously perturbed by bottom-up sensory evidence as well as top-down executive processes. It has the remarkable capacity to learn from its environment and use stored knowledge in order to guide its actions in the face of uncertainty. This allows for the generation of adaptive behavior, ensuring our survival in a world that is in a continuous state of flux.
The Computational Cognitive Neuroscience (CCN) lab investigates the theoretical principles and neurobiological substrates that mediate such adaptive behavior. To this end, we combine computational modeling, which has its roots in machine learning and computational neuroscience, with empirical research where we measure the brain at work in naturalistic settings. Ultimately, our research aims to provide a deeper understanding of neural information processing in healthy subjects as well as in patients that suffer from various neurodegenerative disorders.