Multichannel recording technologies have revealed travelling waves of neural activity in
multiple sensory, motor and cognitive systems. These waves can be spontaneously …

Brain-inspired computing (BIC) is an emerging research field that aims to build fundamental
theories, models, hardware architectures, and application systems toward more general …

State-of-the-art software tools for neuronal network simulations scale to the largest
computing systems available today and enable investigations of large-scale networks of up …

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

We present results from a new approach to learning and plasticity in neuromorphic
hardware systems: to enable flexibility in implementable learning mechanisms while …

Brain-scale networks exhibit a breathtaking heterogeneity in the dynamical properties and
parameters of their constituents. At cellular resolution, the entities of theory are neurons and …

This paper presents an extension of the BrainScaleS accelerated analog neuromorphic
hardware model. The scalable neuromorphic architecture is extended by the support for …

With rapidly advancing multi-electrode recording technology, the local field potential (LFP)
has again become a popular measure of neuronal activity in both research and clinical …

Here we present the Digital Brain (DB)—a platform for simulating spiking neuronal networks
at the large neuron scale of the human brain on the basis of personalized magnetic …

In this work, we present a computing platform named digital twin brain (DTB) that can
simulate spiking neuronal networks of the whole human brain scale and more importantly, a …