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 …

Neuroscience research is undergoing a minor revolution. Recent advances in machine
learning and artificial intelligence research have opened up new ways of thinking about …

Convolutional neural networks (CNNs) have so far been the de-facto model for visual data.
Recent work has shown that (Vision) Transformer models (ViT) can achieve comparable or …

Whether current or near-term AI systems could be conscious is a topic of scientific interest
and increasing public concern. This report argues for, and exemplifies, a rigorous and …

Attention is the important ability to flexibly control limited computational resources. It has
been studied in conjunction with many other topics in neuroscience and psychology …

Deep neural network models of sensory systems are often proposed to learn
representational transformations with invariances like those in the brain. To reveal these …

Functional magnetic resonance imaging (fMRI) enables non-invasive access to the awake,
behaving human brain. By tracking whole-brain signals across a diverse range of cognitive …

Does the human mind resemble the machines that can behave like it? Biologically inspired
machine-learning systems approach “human-level” accuracy in an astounding variety of …

Objects are the core meaningful elements in our visual environment. Classic theories of
object vision focus upon object recognition and are elegant and simple. Some of their …

Background: Heart rate–corrected QT interval (QTc) prolongation, whether secondary to
drugs, genetics including congenital long QT syndrome, and/or systemic diseases including …