Neuronal "parts list" and wiring diagram for a visual system.

A catalog of neuronal cell types has often been called a "parts list" of the brain, and regarded as a prerequisite for understanding brain function. In the optic lobe of Drosophila, rules of connectivity between cell types have already proven essential for understanding fly vision. Here we analyze the fly connectome to complete the list of cell types intrinsic to the optic lobe, as well as the rules governing their connectivity. We more than double the list of known types. Most new cell types contain between 10 and 100 cells, and integrate information over medium distances in the visual field. Some existing type families (transmedullary, lobula intrinsic, and lobula plate intrinsic) at least double in number of types, with implications for perception of color, motion, and form. We introduce a new family, serpentine medulla intrinsic, which has more types than any other, and three new families of types that span multiple neuropils. We demonstrate self-consistency of our cell types through automatic assignment of cells by distance in high-dimensional feature space, and provide further validation by selection of small subsets of discriminative features. Our work showcases the advantages of connectomic cell typing: complete and unbiased sampling, a rich array of features based on connectivity, and reduction of the connectome to a drastically simpler wiring diagram of cell types, with immediate relevance for brain function and development.

FlyWire: online community for whole-brain connectomics.

Due to advances in automated image acquisition and analysis, whole-brain connectomes with 100,000 or more neurons are on the horizon. Proofreading of whole-brain automated reconstructions will require many person-years of effort, due to the huge volumes of data involved. Here we present FlyWire, an online community for proofreading neural circuits in a Drosophila melanogaster brain and explain how its computational and social structures are organized to scale up to whole-brain connectomics. Browser-based three-dimensional interactive segmentation by collaborative editing of a spatially chunked supervoxel graph makes it possible to distribute proofreading to individuals located virtually anywhere in the world. Information in the edit history is programmatically accessible for a variety of uses such as estimating proofreading accuracy or building incentive systems. An open community accelerates proofreading by recruiting more participants and accelerates scientific discovery by requiring information sharing. We demonstrate how FlyWire enables circuit analysis by reconstructing and analyzing the connectome of mechanosensory neurons.

The neural basis for a persistent internal state in Drosophila females.

Sustained changes in mood or action require persistent changes in neural activity, but it has been difficult to identify the neural circuit mechanisms that underlie persistent activity and contribute to long-lasting changes in behavior. Here, we show that a subset of Doublesex+ pC1 neurons in the Drosophila female brain, called pC1d/e, can drive minutes-long changes in female behavior in the presence of males. Using automated reconstruction of a volume electron microscopic (EM) image of the female brain, we map all inputs and outputs to both pC1d and pC1e. This reveals strong recurrent connectivity between, in particular, pC1d/e neurons and a specific subset of Fruitless+ neurons called aIPg. We additionally find that pC1d/e activation drives long-lasting persistent neural activity in brain areas and cells overlapping with the pC1d/e neural network, including both Doublesex+ and Fruitless+ neurons. Our work thus links minutes-long persistent changes in behavior with persistent neural activity and recurrent circuit architecture in the female brain.

Long-term mental states such as arousal and mood variations rely on persistent changes in the activity of certain neural circuits which have been difficult to identify. For instance, in male fruit flies, the activation of a particular circuit containing 'P1 neurons' can escalate aggressive and mating behaviors. However, less is known about the neural networks that underlie arousal in female flies. A group of female-specific, 'pC1 neurons' similar to P1 neurons could play this role, but it was unclear whether it could drive lasting changes in female fly behavior. To investigate this question, Deutsch et al. stimulated or shut down pC1 circuits in female flies, and then recorded the insects' interactions with male flies. Stimulation was accomplished using optogenetics, a technique which allows researchers to precisely control the activity of specially modified light-sensitive neurons. Silencing pC1 neurons in female flies diminished their interest in male partners and their suitor's courtship songs. Activating these neural circuits made the females more receptive to males; it also triggered long-lasting aggressive behaviors not typically observed in virgin females, such as shoving and chasing. Deutsch et al. then identified the brain cells that pC1 neurons connect to, discovering that these neurons are part of an interconnected circuit also formed of aIPg neurons ­ a population of fly brain cells that shows sex differences and is linked to female aggression. The brains of females were then imaged as pC1 neurons were switched on, revealing a persistent activity which outlasted the activation in circuits containing both pC1 and aIPg neurons. Thus, these results link neural circuit architecture to long lasting changes in neural activity, and ultimately, in behavior. Future experiments can build on these results to determine how this circuit is activated during natural social interactions.