To cope with real-world dynamics, an intelligent system needs to incrementally acquire,
update, accumulate, and exploit knowledge throughout its lifetime. This ability, known as …

This review focuses on neuropeptides and peptide hormones, the largest and most diverse
class of neuroactive substances, known in Drosophila and other animals to play roles in …

Brains contain networks of interconnected neurons and so knowing the network architecture
is essential for understanding brain function. We therefore mapped the synaptic-resolution …

Continual learning aims to empower artificial intelligence with strong adaptability to the real
world. For this purpose, a desirable solution should properly balance memory stability with …

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 …

Making inferences about the computations performed by neuronal circuits from synapse-
level connectivity maps is an emerging opportunity in neuroscience. The mushroom body …

Neuroscience has focused on the detailed implementation of computation, studying neural
codes, dynamics and circuits. In machine learning, however, artificial neural networks tend …

Associating stimuli with positive or negative reinforcement is essential for survival, but a
complete wiring diagram of a higher-order circuit supporting associative memory has not …

We identified the neurons comprising the Drosophila mushroom body (MB), an associative
center in invertebrate brains, and provide a comprehensive map describing their potential …

Understanding memory formation, storage and retrieval requires knowledge of the
underlying neuronal circuits. In Drosophila, the mushroom body (MB) is the major site of …