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Abstract:
Understanding the complex dynamics of the human brain is one of the most exciting challenges in modern science. Novel experimental methods allow acquiring unprecedented amounts of high-quality data. However, making sense of all these data requires an integrative theoretical approach to foster a deeper understanding of brain activity. Here I will discuss the critical dynamics approach that provides an explanation for a plethora of empirical results regarding scale-free spatiotemporal dynamics observed through a multitude of experimental methodologies across different spatial and temporal scales. The hypothesis that the brain operates close to the critical state is supported by the theoretical evidence suggesting multiple aspects of information processing to be optimized at the second order phase transition. I will give an overview of the experimental evidence and theoretical modeling of criticality in neuronal systems. Using an example of an efficient coding network, I will demonstrate how optimization of the network for particular function might result in a critical-like dynamics. Considering the problem from the other side, I present evidence that approaching critical state can improve the general computational capabilities in the developing cortical and hippocampal cultures.
