During the past two decades, philosophers, psychologists, cognitive scientists,
clinicians and neuroscientists strived to provide authoritative definitions of consciousness
within a neurobiological framework. Engineers have more recently joined this quest by
developing neuromorphic VLSI circuits for emulating biological functions. Yet, to date artificial
systems have not been able to faithfully recreate natural attributes such as true processing
locality (memory and computation) and complexity (1010 synapses per cm2), preventing the
achievement of a long-term goal: the creation of autonomous cognitive systems.
This project aspires to develop experimental platforms capable of perceiving, learning
and adapting to stimuli by leveraging on the latest developments of five leading European
institutions in neuroscience, nanotechnology, modeling and circuit design. The non-linear
dynamics as well as the plasticity of the newly discovered memristor are shown to support
Spike-based- and Spike-Timing-Dependent-Plasticity (STDP), making this extremely
compact device an excellent candidate for realizing large-scale self-adaptive circuits; a step
towards autonomous cognitive systems. The intrinsic properties of real neurons and
synapses as well as their organization in forming neural circuits will be exploited for
optimizing CMOS-based neurons, memristive grids and the integration of the two into realtime
biophysically realistic neuromorphic systems. Finally, the platforms would be tested with
conventional as well as abstract methods to evaluate the technology and its autonomous
capacity.