ABSTRACT

The brain epitomizes a complex dynamical system, where the emergent properties that result from the interactions of the ‘stuff’ that makes it up, e.g. molecules, neurons, glia, and networks, far surpasses the properties of the individual components. From an engineering and design perspective, the question is how is this achieved? How do these components interact together as a dynamical system and what are the rules (algorithms) implemented in the biological substrate that achieve this? The answer to this has neurobiological and clinical implications because it would allow us to understand how the brain works in health and how it fails in disease, as well as what might be done to fix it. But it also has possible non-biological applications to engineered neuromimetic systems that attempt to reproduce the computational power and robustness of the biological brain. For example in areas such as robotics or big data analytics. This talk will discuss some of our own work past and present towards these goals in the areas of cellular neural signaling, applied nanotechnology to neural systems, and theoretical and computational neuroscience. And we will speculate on what might drive the field moving forward.