The design of robots that interact autonomously with the environment and exhibit complex
behaviours is an open challenge that can benefit from understanding what makes living …

Robotics and neuroscience are sister disciplines that both aim to understand how agile,
efficient, and robust locomotion can be achieved in autonomous agents. Robotics has …

Deep artificial neural networks apply principles of the brain's information processing that led
to breakthroughs in machine learning spanning many problem domains. Neuromorphic …

Biological computing (or biocomputing) offers potential advantages over silicon-based
computing in terms of faster decision-making, continuous learning during tasks, and greater …

Addressing the multiscale organization of the brain, which is fundamental to the dynamic
repertoire of the organ, remains challenging. In principle, it should be possible to model …

Biological intelligence processes information using impulses or spikes, which makes those
living creatures able to perceive and act in the real world exceptionally well and outperform …

In this paper we demonstrate how the Nengo neural modeling and simulation libraries
enable users to quickly develop robotic perception and action neural networks for simulation …

Our knowledge of the brain has evolved over millennia in philosophical, experimental and
theoretical phases. We suggest that the next phase is simulation neuroscience. The main …

Understanding the human brain is a “Grand Challenge” for 21st century research.
Computational approaches enable large and complex datasets to be addressed efficiently …

Animals have evolved mechanisms to travel safely and efficiently within different habitats.
On a journey in dense terrains animals avoid collisions and cross narrow passages while …