The human brain is one of the most complex biological systems known but we are far from understandings its workings as do with other organs. Significant efforts have been dedicated to unravel its mysteries. Over the years Theoretical and Computational Neuroscience have made significant contributions to understanding this paradigm. We could set the start of the field after publications by Santiago Ramon y Cajal in the 1890s. He identified neurons as the basic processing unit in the brain. Important discoveries were made by the action potential Hodgkin-Huxley model, by Hebbs’ plasticity and memory rules, and Barlow’s efficient coding hypothesis. In most of these instances feedback between experimental and theoretical analysis was essential. The brain performs probabilistic computations when facing our everyday evolutionary challenges, following adaptive behavioral strategies that demand making optimal decisions. An experimental and technological revolution has recently been happening in neuroscience, thus the need to have theoretical and computational approaches that may allow extracting relevant information from the wealth of experimental data being generated. In this talk I will briefly discuss the past, what’s is happening today and the promise for significant advances due to big government initiatives involving close collaborations between, biologists, physicians, physicists, engineers, mathematicians, computer scientists as well as private research institutes, in particular the Kavli Foundation.