The past decade has witnessed the great success of deep neural networks in various
domains. However, deep neural networks are very resource-intensive in terms of energy …

Artificial neural networks (ANNs) inspired by biology are beginning to be widely used to
model behavioural and neural data, an approach we call 'neuroconnectionism'. ANNs have …

Spiking neural networks (SNNs) aim to realize brain-inspired intelligence on neuromorphic
chips with high energy efficiency by introducing neural dynamics and spike properties. As …

Exploiting the excellent electronic properties of two-dimensional (2D) materials to fabricate
advanced electronic circuits is a major goal for the semiconductor industry,. However, most …

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

As a key building block of biological cortex, neurons are powerful information processing
units and can achieve highly complex nonlinear computations even in individual cells …

Extended wakefulness is associated with reduced performance and the build-up of sleep
pressure. In the cortex, this manifests as changes in network activity. These changes show …

Artificial Intelligence (AI) is currently experiencing a bloom driven by deep learning (DL)
techniques, which rely on networks of connected simple computing units operating in …

Throughout development, the brain transits from early highly synchronous activity patterns to
a mature state with sparse and decorrelated neural activity, yet the mechanisms underlying …

Episodic memory involves learning and recalling associations between items and their
spatiotemporal context. Those memories can be further used to generate internal models of …