Nervous systems are efficient computing substrates that outperform conventional architectures in many real-world tasks, particularly in pattern recognition, classification and sensory-motor integration. Computational neuroscience has made tremendous progress in uncovering the key principles by which neural systems process information, and ICT has advanced to a point where it is possible to integrate a comparable number of transistors in a VLSI system as neurons in a mammalian brain. This session provides a forum for researchers, engineers, and students from all over the world to discuss the state-of-the-art in computational neuroscience, neural representations and processing primitives in soft- and hardware, signal processing models and machine intelligence by learning from nature and mimicking nervous system function.