Abstract Systems neuroscience seeks explanations for how the brain implements a wide
variety of perceptual, cognitive and motor tasks. Conversely, artificial intelligence attempts to …

Neuroscience has long been an essential driver of progress in artificial intelligence (AI). We
propose that to accelerate progress in AI, we must invest in fundamental research in NeuroAI…

The ability to learn tasks in a sequential fashion is crucial to the development of artificial
intelligence. Until now neural networks have not been capable of this and it has been widely …

Neuronal networks with strong recurrent connectivity provide the brain with a powerful
means to perform complex computational tasks. However, high-gain excitatory networks are …

Electrophysiological connectivity patterns in cortex often have a few strong connections,
which are sometimes bidirectional, among a lot of weak connections. To explain these …

Advances in machine learning (ML) and artificial intelligence (AI) present an opportunity to
build better tools and solutions to help address some of the world’s most pressing challenges, …

The brain extracts behaviourally relevant sensory input to produce appropriate motor output.
On the one hand, our constantly changing environment requires this transformation to be …

Cortical neurons receive balanced excitatory and inhibitory synaptic currents. Such a balance
could be established and maintained in an experience-dependent manner by synaptic …

For simulations of large spiking neuron networks, an accurate, simple and versatile single-neuron
modeling framework is required. Here we explore the versatility of a simple two-…

Sensory processing occurs in neocortical microcircuits in which synaptic connectivity is
highly structured 1 , 2 , 3 , 4 and excitatory neurons form subnetworks that process related …