Neuromorphic computing technologies will be important for the future of computing, but
much of the work in neuromorphic computing has focused on hardware development. Here …

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 …

In recent years, deep learning has revolutionized the field of machine learning, for computer
vision in particular. In this approach, a deep (multilayer) artificial neural network (ANN) is …

What mechanisms underlie flexible inter-areal communication in the cortex? We consider
four mechanisms for temporal coordination and their contributions to communication:(1) …

From bacteria following simple chemical gradients to the brain distinguishing complex odour
information, the ability to recognize molecular patterns is essential for biological organisms …

Active inference is a normative principle underwriting perception, action, planning, decision-
making and learning in biological or artificial agents. From its inception, its associated …

In recent years, deep artificial neural networks (including recurrent ones) have won
numerous contests in pattern recognition and machine learning. This historical survey …

A striking difference between brain-inspired neuromorphic processors and current von
Neumann processor architectures is the way in which memory and processing is organized …

Neuromorphic computing is henceforth a major research field for both academic and
industrial actors. As opposed to Von Neumann machines, brain-inspired processors aim at …

In recent years, there has been remarkable progress in the understanding and practical use
of transcranial electrical stimulation (tES) techniques. Nevertheless, to date, this …