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 connection patterns of neural circuits form a complex network. How signaling in these
circuits manifests as complex cognition and adaptive behaviour remains the central question …

Brains can gracefully weed out irrelevant stimuli to guide behavior. This feat is believed to
rely on a progressive selection of task-relevant stimuli across the cortical hierarchy, but the …

The strategies found by animals facing a new task are determined both by individual
experience and by structural priors evolved to leverage the statistics of natural …

Striking progress has been made in understanding cognition by analyzing how the brain is
engaged in different modes of information processing. For instance, so-called synergistic …

In recent years, deep learning has revolutionized machine learning and its applications,
producing results comparable to human experts in several domains, including …

In addition to long-timescale rewiring, synapses in the brain are subject to significant
modulation that occurs at faster timescales that endow the brain with additional means of …

Cognitive flexibility is a fundamental ability that enables humans and animals to exhibit
appropriate behaviors in various contexts. The thalamocortical interactions between the …

Recurrent neural networks (RNNs) are often used to model circuits in the brain and can
solve a variety of difficult computational problems requiring memory, error correction, or …

The connection patterns of neural circuits form a complex network. How signaling in these
circuits manifests as complex cognition and adaptive behaviour remains the central question …