Analysis of neuronal circuit architecture provides mechanistic insights into what an adult fly can learn, remember, and use to guide its behavior.

A stochastic model of locomotory control in C. elegans based on an extensive new set of tracking data can explain and predict effects of ablations and mutations on behavior.

Fixed, intact animals of C. elegans can be physically expanded with high isotropy, to enable super-resolved imaging of general proteins and nucleic acids throughout the organism, on conventional microscopes.

3D atlas of the macaque frontal lobe, based on the novel quantitative parcellation, integrates anatomical, neurochemical, and functional connectivity data.

Synaptic resolution analysis of a full olfactory connectome reveals lateralised circuits, convergence of innate and learned pathways, and shows that homologous neurons are highly stereotyped within and across brains.

Small gated recurrent neural networks can dynamically adapt to inferred changes in the environment, represent and use the precision of their estimate to weight their updates, and leverage the environment's latent hierarchical structure, like the Bayesian agent and the brain.

Enhanced Gq-signaling-mediated activation of forebrain excitatory neurons in postnatal life programs enhanced anxiety-, despair- and schizophrenia-like behavior, recapitulating key aspects of the behavioral consequences of early life adversity.

Selective synapse formation in a retinal motion-sensitive circuit is orchestrated by starburst amacrine cells, which use homotypic interactions to initiate formation of a dendritic scaffold that recruits projections from circuit partners.