The innovation is in the minds

The brain is an amazingly complex and efficient machine. While it may not be considered "general purpose" in terms of its computational capabilities, it performs a set of functions such as feature extraction, classification, synthesis, recognition, learning, and higher-order decision-making amazingly well. Unfortunately the dynamic behavior of the brain at large is still marginally understood. One of the major charters in the neuroscience community for the next decade is to create a dynamic map of the brain (as articulated by the Obama administration in the US). Doing so will require the most advanced imaging capabilities operating at the scale of 10\´s of microns. Recent advances in microscopic sensing, processing and communications are leading to brain-machine interfaces that may be able to observe thousands if not millions of active neurons in vivo. These nanomorphic systems represent the frontier in miniaturization and integration of electronic information processing systems. This whole effort may in turn have some interesting repercussions on how information-processing systems themselves are conceived in the nanoscale regime. Neuro-inspired processing presents an attractive alternative to the classical Von-Neumann computing paradigm in deeply scaled regimes: it thrives on randomness and variability, processing is performed in the continuous or discrete domains, and massive parallelism, major redundancy and adaptivity are of essence. Computational paradigms inspired by neural information processing hence may lead to energy-efficient, low-cost, dense and/or reliable implementations of the functions the brain excels at. In this presentation, we will explore both sides of this neuroscience-information technology interaction. One thing is for sure - the joint future will be exciting.