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

10.7554/eLife.22901.001 Deep learning has led to significant advances in artificial intelligence,
in part, by adopting strategies motivated by neurophysiology. However, it is unclear …

The predominant focus in the neurobiological study of memory has been on remembering (persistence).
However, recent studies have considered the neurobiology of forgetting (…

Throughout life, new neurons are continuously added to the dentate gyrus. As this continuous
addition remodels hippocampal circuits, computational models predict that neurogenesis …

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…

Synaptic plasticity is believed to be a key physiological mechanism for learning. It is well
established that it depends on pre- and postsynaptic activity. However, models that rely solely …

The present investigation sought to identify which brain regions distinguish pedophilic from
nonpedophilic men, using unbiased, automated analyses of the whole brain. T1-weighted …

The backpropagation of error algorithm (BP) is impossible to implement in a real brain. The
recent success of deep networks in machine learning and AI, however, has inspired …

The connection patterns of neural circuits in the brain form a complex network. Collective
signalling within the network manifests as patterned neural activity and is thought to support …

Memories are not static but continue to be processed after encoding. This is thought to allow
the integration of related episodes via the identification of patterns. Although this idea lies at …