Our research is focused on the study of several neural networks of the nervous system using both theoretical/computational models and novel experimental techniques based on activity-dependent stimulation. We are interested in some general issues such as the neural mechanisms to encode, store and process information, as well as several particular problems of the systems under our study (from sensory and motor systems to the hippocampus and the cortex).  Our work uses computational models of neurons and networks to draw hypotheses about the functioning of the nervous system beyond those provided from the analysis of experimental data in living neural networks. Modeling allows to implement experiments that are not achievable with present techniques in the wet laboratories. The models provide new predictions and results that can be tested through new experiments. In some of our protocols models directly interact with the experimental preparations through closed-loop technologies. Our group is also actively working in the application of the mechanisms of information processing that we learn from biology to the development of new paradigms of artificial neural networks, robotics, artificial noses, brain-machine interfaces and multipurpose neurotechnology.