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 …

Efforts to design devices emulating complex cognitive abilities and response processes of
biological systems have long been a coveted goal. Recent advancements in flexible …

The fruit fly Drosophila melanogaster has emerged as a key model organism in
neuroscience, in large part due to the concentration of collaboratively generated molecular …

Flexible behaviors over long timescales are thought to engage recurrent neural networks in
deep brain regions, which are experimentally challenging to study. In insects, recurrent …

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 …

The leading approaches in Machine Learning are notoriously data-hungry. Unfortunately,
many application domains do not have access to big data because acquiring data involves a …

Deep neural networks (DNNs) have had extraordinary successes in classifying
photographic images of objects and are often described as the best models of biological …

Deep neural networks currently provide the best quantitative models of the response
patterns of neurons throughout the primate ventral visual stream. However, such networks …

Cognition can be defined as computation over meaningful representations in the brain to
produce adaptive behaviour. There are two views on the relationship between cognition and …

Health care is evolving and with it the need to reform medical education. As the practice of
medicine enters the age of artificial intelligence (AI), the use of data to improve clinical …