Evolving complexity, cognition, and consciousness

All through the history of the universe there is an apparent tendency for increasing complexity, with the organization of matter in evermore elaborate and interactive systems. The living world in general, and the human brain in particular, provides the highest complexity known. It seems obvious that all of this complexity must be the result of physical, chemical and biological evolution, but it was only with Darwin that we began to get a scientific understanding of biological evolution. Darwinian principles are guiding in our understanding of such complex systems as the nervous system, but also for the evolution of human society and technology. Living organisms have to survive in a complex and changing environment. This implies response and adaption to environmental events and changes at several time scales. The interaction with the environment depends on the present state of the organism, as well as on previous experiences stored in its molecular and cellular structures. At a longer time scale, organisms can adapt to slow environmental changes, by storing information in the genetic material carried over from generation to generation. This phylogenetic learning is complemented by ontogenetic learning, which is adaptation at a shorter time scale, occuring in non -genetic structures. The evolution of a nervous system is a major transition in biological evolution and allows for an increasing capacity for information storage and processing, increasing chances of survival. Such neural knowledge processing, cognition, shows the same principal features as non neural adaptive processes. Similarly, consciousness might appear, to different degrees, at different stages in evolution. Both cognition and consciousness depends critically on the organization and complexity of the organism. In this presentation, I will briefly discuss general principles for evolution of complexity, focussing on the evolution of the nervous system, which provides organisms with ever increasing capacity for complex behaviour, cognition and consciousness. I will also discuss some computational approaches, as tools for understanding relations between structure, dynamics and function of the nervous system.