In recent years a new class of neuromorphic multi-chip systems started to emerge that comprise one or more neuromorphic sensors, interfaced to general-purpose neural network architectures based on spiking neurons and dynamic synapses. The strategy used to transmit signals across chip boundaries in these types of systems is based on asynchronous 'address-events': output signals are represented by stereotyped pulse signals (events, or spikes). The analog nature of the signal being transmitted can be encoded in the mean frequency of the neuron’s pulse sequence (spike rates), or in the precise timing of the spike. Both types of representations are still an active topic of research in neural computation, and can be investigated in real-time with these hardware systems.
EU research groups started to contribute significantly to the state-of-the-art in this field thanks also to strong investments by the EU FET program, e.g. see the ALAVLSI, CAVIAR, DAISY, FACETS, eMorph, BrainScales projects. CSNII provides support to the CapoCaccia Cognitive Neuromorphic Engineering Workshops.
Neuroprosthetics aims to restore broken sensory, motor or cognitive function and compensate neural dysfunctions through electrical stimulation of myogenic and/or neuronal structures in the peripheral, spinal and central nervous system. During the last decades neuroprosthetic devices successfully made their way to clinical practice, e.g., cardiac pacemakers, cochlear implants, deep brain stimulation implants for paraplegics and stroke patients, visual neuroprosthetics. In addition, ongoing research awaiting clinical test approval includes development of neuroprosthetics for motor, sensory / motor, and cognitive dysfunctions.
The multidisciplinary field of neuroprosthetics research requires wide dissemination of research outcomes, and intense discussions on possible roadmaps and development strategies involving improved spatiotemporal resolution and communication methods, biocompatibility, ethical issues, implant flexibility, etc.