Breakthroughs in studies of the nervous system over the past centuries have been dramatic, with key findings in experimental and theoretical neuroscience. These breakthroughs have helped to understand important aspects of how the brain works, which also provides new inspiration for technology and artificial intelligence. Moreover, the continuous development of new automatic data and image processing methods that arise out of neuroscience and genetics experiments, control technology applied to neurophysiology experiments and the use of computational neuroscience to represent and integrate information, feeds back knowledge about the brain and creates new opportunities for interaction between the nervous system and computational intelligence paradigms, robotics, brain-machine interfaces and all sorts of prosthetic and augmented reality devices. Among the maze of disciplines and approaches that try to understand how the brain works, there is a multidisciplinary approach to Neuroscience which looks at the nervous system in terms of its function: processing information. Theoretical models and experiments draw on closed-loop technology to reveal aspects of neuronal dynamics which do not come under traditional experimental protocols, hybrid circuits comprising live neurons and artificial neurons in a bidirectional interaction, behavior experiments with activity-dependent stimulation, and new protocols to personalize brain-machine interfaces.