Brain-inspired approaches emphasize the need for highly connected complex networks with long-range adaptive connections (the distant synapses). If implemented with non-biological technologies, these are raising problems with respect to: charging/discharging, cross-talk, delays, losses and heating, i.e. scalability issues well-known from CMOS technologies. Instead, we will explore the functionalities of bio-inspired scalable near-neighbour (locallyconnected) networks and systolic-like array architectures. The long-term vision is to build multi-scale bio-/neuroinspired systems interfacing/connecting molecular-scale devices to macroscopic systems for unconventional information processing with scalable neuromorphic architectures. The computational substrate is a memristive/synaptic network controlled by a multi-terminal structure of input/output ports and internal gates embedded in a classical digital CMOS environment. The goal is to explore a multiscale platform connecting molecular-scale devices into networks for the development and testing of synaptic devices and scalable neuromorphic architectures, and for investigating materials and components with new functionalities.