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BrainScaleS (Brain-inspired multiscale computation in neuromorphic hybrid systems) was an EU FET-Proactive FP7 funded research project. The project started on 1 January 2011 and ended in 2015. It was a collaboration of 19 research groups from 10 European countries.

The BrainScaleS project aimed at understanding function and interaction of multiple spatial and temporal scales in brain information processing.

The fundamentally new approach of BrainScaleS lay in the in-vivo biological experimentation and computational analysis. Spatial scales range from individual neurons over larger neuron populations to entire functional brain areas. Temporal scales range from milliseconds relevant for event based plasticity mechanisms to hours or days relevant for learning and development. In the project generic theoretical principles were extracted to enable an artificial synthesis of cortical-like cognitive skills. Both, numerical simulations on petaflop supercomputers and a fundamentally different non-von Neumann hardware architecture will bewere employed for this purpose.

Neurobiological data from the early perceptual visual and somatosensory systems were combined with data from specifically targeted higher cortical areas. Functional databases as well as novel project-specific experimental tools and protocols were developed and used. New theoretical concepts and methods were developed for understanding the computational role of the complex multi-scale dynamics of neural systems in-vivo. Innovative in-vivo experiments were carried out to guide this analytical understanding.

Multiscale architectures were synthesized into a non-von Neumann computing device realised in custom designed electronic hardware. The proposed Hybrid Multiscale Computing Facility (HMF) combined microscopic neuromorphic physical model circuits with numerically calculated mesoscopic and macroscopic functional units and a virtual environment providing sensory, decision-making and motor interfaces. The project employed petaflop supercomputing to obtain new insights into the specific properties of the different hardware architectures. A set of demonstration experiments linked multiscale analysis of biological systems with functionally and architecturally equivalent synthetic systems and offered the possibility for quantitative statements on the validity of theories bridging multiple scales. The demonstration experiments explored non-von Neumann computing outside the realm of brain-science.