The Information Theory of Cognitive Systems group aims at understanding learning processes of cognitive systems in terms of information theory. The research is guided by the belief that these processes are consistent with information-theoretic optimization principles referred to as infomax principles within theoretical neuroscience. Several classical approaches along these lines do provide explanations for experimental findings such as the development of receptive fields in the primary visual cortex. However, these approaches usually suffer from an intrinsic restriction on network and model class primarily addressing only networks with feed-forward structure similar to the unidirectional sender-receiver setting of classical information theory. The group is working on extensions that include various kinds of essential feedbacks. On one hand, feedbacks are predominant within brain structures such as in thalamo-cortical interactions including the interaction between LGN and visual cortex. On the other hand, the sensori-motor integration involves feedbacks that are of utmost importance for information representation, information processing, and control. In this sense, the group aims at combining information-theoretic approaches within theoretical neuroscience with the field of embodied artificial intelligence, thereby relating information flows through neuronal systems to system-theoretic concepts. We feel confident that such a holistic approach addressing feedbacks at all system levels is necessary for understanding cognition.