The reward system is a collection of circuits that reinforce behaviors necessary for survival [1, 2]. Given the importance of reproduction for survival, actions that promote successful mating induce pleasurable feeling and are positively reinforced [3, 4]. This principle is conserved in Drosophila, where successful copulation is naturally rewarding to male flies, induces long-term appetitive memories [5], increases brain levels of neuropeptide F (NPF, the fly homolog of neuropeptide Y), and prevents ethanol, known otherwise as rewarding to flies [6, 7], from being rewarding [5]. It is not clear which of the multiple sensory and motor responses performed during mating induces perception of reward. Sexual interactions with female flies that do not reach copulation are not sufficient to reduce ethanol consumption [5], suggesting that only successful mating encounters are rewarding. Here, we uncoupled the initial steps of mating from its final steps and tested the ability of ejaculation to mimic the rewarding value of full copulation. We induced ejaculation by activating neurons that express the neuropeptide corazonin (CRZ) [8] and subsequently measured different aspects of reward. We show that activating Crz-expressing neurons is rewarding to male flies, as they choose to reside in a zone that triggers optogenetic stimulation of Crz neurons and display conditioned preference for an odor paired with the activation. Reminiscent of successful mating, repeated activation of Crz neurons increases npf levels and reduces ethanol consumption. Our results demonstrate that ejaculation stimulated by Crz/Crz-receptor signaling serves as an essential part of the mating reward mechanism in Drosophila. VIDEO ABSTRACT.

Neural circuit reconstruction at single synapse resolution is increasingly recognized as crucially important to decipher the function of biological nervous systems. Volume electron microscopy in serial transmission or scanning mode has been demonstrated to provide the necessary resolution to segment or trace all neurites and to annotate all synaptic connections. 
Automatic annotation of synaptic connections has been done successfully in near isotropic electron microscopy of vertebrate model organisms. Results on non-isotropic data in insect models, however, are not yet on par with human annotation. 
We designed a new 3D-U-Net architecture to optimally represent isotropic fields of view in non-isotropic data. We used regression on a signed distance transform of manually annotated synaptic clefts of the CREMI challenge dataset to train this model and observed significant improvement over the state of the art. 
We developed open source software for optimized parallel prediction on very large volumetric datasets and applied our model to predict synaptic clefts in a 50 tera-voxels dataset of the complete Drosophila brain. Our model generalizes well to areas far away from where training data was available.

Neural circuits, governed by a complex interplay between excitatory and inhibitory neurons, are the substrate for information processing, and the organization of synaptic connectivity in neural network is an important determinant of circuit function. Here, we analyzed the fine structure of connectivity in hippocampal CA1 excitatory and inhibitory neurons innervated by Schaffer collaterals (SCs) using mGRASP in male mice. Our previous study revealed spatially structured synaptic connectivity between CA3-CA1 pyramidal cells (PCs). Surprisingly, parvalbumin-positive interneurons (PVs) showed a significantly more random pattern spatial structure. Notably, application of Peters' Rule for synapse prediction by random overlap between axons and dendrites enhanced structured connectivity in PCs, but, by contrast, made the connectivity pattern in PVs more random. In addition, PCs in a deep sublayer of striatum pyramidale appeared more highly structured than PCs in superficial layers, and little or no sublayer specificity was found in PVs. Our results show that CA1 excitatory PCs and inhibitory PVs innervated by the same SC inputs follow different connectivity rules. The different organizations of fine scale structured connectivity in hippocampal excitatory and inhibitory neurons provide important insights into the development and functions of neural networks.Understanding how neural circuits generate behavior is one of the central goals of neuroscience. An important component of this endeavor is the mapping of fine-scale connection patterns that underlie, and help us infer, signal processing in the brain. Here, using our recently developed synapse detection technology (mGRASP and neuTube), we provide detailed profiles of synaptic connectivity in excitatory (CA1 pyramidal) and inhibitory (CA1 parvalbumin-positive) neurons innervated by the same presynaptic inputs (CA3 Schaffer collaterals). Our results reveal that these two types of CA1 neurons follow different connectivity patterns. Our new evidence for differently structured connectivity at a fine scale in hippocampal excitatory and inhibitory neurons provides a better understanding of hippocampal networks and will guide theoretical and experimental studies.

The advent of direct electron detectors has enabled the routine use of single-particle cryo-electron microscopy (EM) approaches to determine structures of a variety of protein complexes at near-atomic resolution. Here, we report the development of methods to account for local variations in defocus and beam-induced drift, and the implementation of a data-driven dose compensation scheme that significantly improves the extraction of high-resolution information recorded during exposure of the specimen to the electron beam. These advances enable determination of a cryo-EM density map for β-galactosidase bound to the inhibitor phenylethyl β-D-thiogalactopyranoside where the ordered regions are resolved at a level of detail seen in X-ray maps at ∼ 1.5 Å resolution. Using this density map in conjunction with constrained molecular dynamics simulations provides a measure of the local flexibility of the non-covalently bound inhibitor and offers further opportunities for structure-guided inhibitor design.

The mammalian hippocampus, comprised of serially connected subfields, participates in diverse behavioral and cognitive functions. It has been postulated that parallel circuitry embedded within hippocampal subfields may underlie such functional diversity. We sought to identify, delineate, and manipulate this putatively parallel architecture in the dorsal subiculum, the primary output subfield of the dorsal hippocampus. Population and single-cell RNA-seq revealed that the subiculum can be divided into two spatially adjacent subregions associated with prominent differences in pyramidal cell gene expression. Pyramidal cells occupying these two regions differed in their long-range inputs, local wiring, projection targets, and electrophysiological properties. Leveraging gene-expression differences across these regions, we use genetically restricted neuronal silencing to show that these regions differentially contribute to spatial working memory. This work provides a coherent molecular-, cellular-, circuit-, and behavioral-level demonstration that the hippocampus embeds structurally and functionally dissociable streams within its serial architecture.

Intracellular recording allows measurement and perturbation of the membrane potential of identified neurons with sub-millisecond and sub-millivolt precision. This gives intracellular recordings a unique capacity to provide rich information about individual cells (e.g., high-resolution characterization of inputs, outputs, excitability, and structure). Hence, such recordings can elucidate the mechanisms that underlie fundamental phenomena, such as brain state, sparse coding, gating, gain modulation, and learning. Technical developments have increased the range of behaviors during which intracellular recording methods can be employed, such as in freely moving animals and head-fixed animals actively performing tasks, including in virtual environments. Such advances, and the combination of intracellular recordings with genetic and imaging techniques, have enabled investigation of the mechanisms that underlie neural computations during natural and trained behaviors.

Large electron microscopy image datasets for connectomics are typically composed of thousands to millions of partially overlapping two-dimensional images (tiles), which must be registered into a coherent volume prior to further analysis. A common registration strategy is to find matching features between neighboring and overlapping image pairs, followed by a numerical estimation of optimal image deformation using a so-called solver program. 
Existing solvers are inadequate for large data volumes, and inefficient for small-scale image registration. 
In this work, an efficient and accurate matrix-based solver method is presented. A linear system is constructed that combines minimization of feature-pair square distances with explicit constraints in a regularization term. In absence of reliable priors for regularization, we show how to construct a rigid-model approximation to use as prior. The linear system is solved using available computer programs, whose performance on typical registration tasks we briefly compare, and to which future scale-up is delegated. Our method is applied to the joint alignment of 2.67 million images, with more than 200 million point-pairs and has been used for successfully aligning the first full adult fruit fly brain.

Zika virus (ZIKV) is an emerging flavivirus that caused thousands of human infections in recent years. Compared to other human flaviviruses, ZIKV replication is not well understood. Using fluorescent, transmission electron, and focused ion beam-scanning electron microscopy, we examined ZIKV replication dynamics in Vero 76 cells and in the brains of infected laboratory mice. We observed the progressive development of a perinuclear flaviviral replication factory both in vitro and in vivo. In vitro, we illustrated the ZIKV lifecycle from particle cell entry to egress. ZIKV particles assembled and aggregated in an induced convoluted membrane structure and ZIKV strain-specific membranous vesicles. While most mature virus particles egressed via membrane budding, some particles also likely trafficked through late endosomes and egressed through membrane abscission. Interestingly, we consistently observed a novel sheet-like virus particle array consisting of a single layer of ZIKV particles. Our study further defines ZIKV replication and identifies a novel hallmark of ZIKV infection.

Sensory cortices are active in the absence of external sensory stimuli. To understand the nature of this ongoing activity, we used two-photon calcium imaging to record from over 10,000 neurons in the visual cortex of mice awake in darkness while monitoring their behavior videographically. Ongoing population activity was multidimensional, exhibiting at least 100 significant dimensions, some of which were related to the spontaneous behaviors of the mice. The largest single dimension was correlated with the running speed and pupil area, while a 16-dimensional summary of orofacial behaviors could predict ~45% of the explainable neural variance. Electrophysiological recordings with 8 simultaneous Neuropixels probes revealed a similar encoding of high-dimensional orofacial behaviors across multiple forebrain regions. Representation of motor variables continued uninterrupted during visual stimulus presentation, occupying dimensions nearly orthogonal to the stimulus responses. Our results show that a multidimensional representation of motor state is encoded across the forebrain, and is integrated with visual input by neuronal populations in primary visual cortex.

True physiological imaging of subcellular dynamics requires studying cells within their parent organisms, where all the environmental cues that drive gene expression, and hence the phenotypes that we actually observe, are present. A complete understanding also requires volumetric imaging of the cell and its surroundings at high spatiotemporal resolution, without inducing undue stress on either. We combined lattice light-sheet microscopy with adaptive optics to achieve, across large multicellular volumes, noninvasive aberration-free imaging of subcellular processes, including endocytosis, organelle remodeling during mitosis, and the migration of axons, immune cells, and metastatic cancer cells in vivo. The technology reveals the phenotypic diversity within cells across different organisms and developmental stages and may offer insights into how cells harness their intrinsic variability to adapt to different physiological environments.