Neurophysics: Emergence and Phase Transitions in Neural Systems

Every second, millions of neurons in your brain communicate with each other, encoding information that your brain then converts into behavior to help you survive in this world. But from the point of view of physics, how do you even begin to try to understand these processes? Well, their mechanisms can be understood using ideas of Statistical Physics and Dynamical Systems, two fields that are the core of what we now call Complexity Science. In this talk, I will present some of our findings to understand how complex, collective behavior emerges in neural systems. Neurons grown in isolation self-organize and spontaneously develop coherent activity patterns, a phenomenon linked to the presence of phase transitions in networks. These kinds of phase transitions are also linked to what is called "the critical brain hypothesis", which theorizes that the brain operates at the edge of two different dynamical regimes, or more precisely, at a critical point. Operating near a critical point has been theoretically shown to be optimal for information transmission in networks, which would be a highly desirable feature for any computational device, like the brain.