Neuromorphic electronics have great potential in the emulation of the sensory, cognitive, self-
learning, and actuating functions of robots. While typically implemented in rigid silicon …

Combined efforts in the fields of neuroscience, computer science, and biology allowed to
design biologically realistic models of the brain based on spiking neural networks. For a …

In traditional robotics, model-based controllers are usually needed in order to bring a robotic
plant to the next desired state, but they present critical issues when the dimensionality of the …

Bio-inspired robots still rely on classic robot control although advances in neurophysiology
allow adaptation to control as well. However, the connection of a robot to spiking neuronal …

The 'red-green'pathway of the retina is classically recognized as one of the retinal
mechanisms allowing humans to gather color information from light, by combining …

Combining Fable robot, a modular robot, with a neuroinspired controller, we present the
proof of principle of a system that can scale to several neurally controlled compliant …

From image recognition to automated driving, machine learning nowadays is all around us
and impacts various aspects of our daily lives. This disruptive technology is rapidly evolving …

Models and algorithms developed in the computational neuroscience or machine learning
domain are able to solve more and more complex tasks. At the same time there is an …

In this article, we present our initial work on sequence prediction of a visual target by
implementing a cortically inspired method, namely Hierarchical Temporal Memory (HTM). As …

The possibility of simulating in detail in-vivo experiments could be highly beneficial to the
neuroscientific community. It could easily allow for preliminary testing of different …