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An analysis of the Drosophila connectome yields all cell types intrinsic to the optic lobe, and their rules of connectivity.

A consensus cell type atlas for the fly brain provides both an intellectual framework and open-source toolchains for brain-scale comparative connectomics.

This study maps the connections of layer 5 pyramidal neurons in the mouse cortex, revealing distinct local and intercortical wiring patterns, and provides an open framework for exploring the connectivity of cell types.

The authors use Patch-seq and electron microscopy datasets to relate synaptic connectivity to the transcriptomic cell type of different types of inhibitory neuron.

The Connectome Annotation Versioning Engine (CAVE) is a platform for proofreading, annotating and analyzing datasets reaching the petascale. Currently, CAVE is used for electron microscopy datasets, but it can potentially be used for other large-scale datasets.

Neural Decomposition (NEURD) is a software package that decomposes neuronal data from high-resolution electron microscopy volumes into feature-rich graph representations to facilitate analysis for neuroscience research.

Three electron microscopy datasets are combined to provide a complete connectomic description of the neural circuitry that makes up the neck connective in Drosophila, including the descending neurons, ascending neurons and sensory ascending neurons.

FlyWire presents a neuronal wiring diagram of the whole fly brain with annotations for cell types, classes, nerves, hemilineages and predicted neurotransmitters, with data products and an open ecosystem to facilitate exploration and browsing.

We create a computational model of the adult Drosophila brain that accurately describes circuit responses upon activation of different gustatory and mechanosensory subtypes and generates experimentally testable hypotheses to describe complete sensorimotor transformations.

Excitatory neurons in the neocortex exhibit considerable morphological diversity, yet their organizational principles remain a subject of ongoing research. Here, the authors use unsupervised learning to show that most excitatory neuron morphologies in the mouse visual cortex form a continuum, with notable exceptions in deeper layers.

An analysis demonstrates that quantitative measurements of perisomatic ultrastructure features of neurons can be used to categorize them into cell types.

The MICrONS mouse visual cortex dataset shows that neurons with similar response properties preferentially connect, a pattern that emerges within and across brain areas and layers, and independently emerges in artificial neural networks where these ‘like-to-like’ connections prove important for task performance.

Analysis of the whole-brain fly connectome reveals high-dimensional dynamics supported by many small independent circuits, motivating a proposal for optogenetic perturbation to efficiently learn a whole-brain causal neural dynamics model.

The network of the fly brain is highly recurrent and displays rich-club organization, with a large population (30%) of preferentially connected neurons.

FlyWire is an online community and a platform for proofreading electron microscopy-based connectome data of the Drosophila brain.

Dense calcium imaging combined with co-registered high-resolution electron microscopy reconstruction of the brain of the same mouse provide a functional connectomics map of tens of thousands of neurons of a region of the primary cortex and higher visual areas.