Painful events establish opponent memories: cues that precede pain are remembered negatively, whereas cues that follow pain, thus coinciding with relief are recalled positively. How do individual reinforcement-signaling neurons contribute to this "timing-dependent valence-reversal?" We addressed this question using an optogenetic approach in the fruit fly. Two types of fly dopaminergic neuron, each comprising just one paired cell, indeed established learned avoidance of odors that preceded their photostimulation during training, and learned approach to odors that followed the photostimulation. This is in striking parallel to punishment versus relief memories reinforced by a real noxious event. For only one of these neuron types, both effects were strong enough for further analyses. Notably, interfering with dopamine biosynthesis in these neurons partially impaired the punishing effect, but not the relieving after-effect of their photostimulation. We discuss how this finding constraints existing computational models of punishment versus relief memories and introduce a new model, which also incorporates findings from mammals. Furthermore, whether using dopaminergic neuron photostimulation or a real noxious event, more prolonged punishment led to stronger relief. This parametric feature of relief may also apply to other animals and may explain particular aspects of related behavioral dysfunction in humans.

Human immunodeficiency virus type 1 (HIV-1) assembly occurs on the inner leaflet of the host cell plasma membrane, incorporating the essential viral envelope glycoprotein (Env) within a budding lattice of HIV-1 Gag structural proteins. The mechanism by which Env incorporates into viral particles remains poorly understood. To determine the mechanism of recruitment of Env to assembly sites, we interrogate the subviral angular distribution of Env on cell-associated virus using multicolor, three-dimensional (3D) superresolution microscopy. We demonstrate that, in a manner dependent on cell type and on the long cytoplasmic tail of Env, the distribution of Env is biased toward the necks of cell-associated particles. We postulate that this neck-biased distribution is regulated by vesicular retention and steric complementarity of Env during independent Gag lattice formation.

The GAL4-UAS system has proven its versatility in studying the function and expression patterns of neurons the Drosophila central nervous system. Although the GAL4 system has been used for 25 years, recent genetic intersectional tools have enabled genetic targeting of very small numbers of neurons aiding in the understanding of their function. This split-GAL4 system is extremely powerful for studying neuronal morphology and the neural basis of animal behavior. However, choosing lines to intersect that have overlapping patterns restricted to one to a few neurons has been cumbersome. This challenge is now growing as the collections of GAL4 driver lines has increased. Here we present a new method and software plug-in for Fiji to dramatically improve the speed of querying large databases of potential lines to intersect and aid in the split-GAL4 creation. We also provide pre-computed datasets for the Janelia GAL4 (5,738 lines) and VT GAL4 (7,429 lines) of the Drosophila central nervous system (CNS). The tool reduced our split-GAL4 creation effort dramatically.

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.

Sodium (Na) is a ubiquitous and important inorganic salt mediating many critical biological processes such as neuronal excitation, signaling, and facilitation of various transporters. The hydration states of Na are proposed to play critical roles in determining the conductance and the selectivity of Na channels, yet they are rarely captured by conventional structural biology means. Here we use the emerging cryo-electron microscopy (cryoEM) method micro-electron diffraction (MicroED) to study the structure of a prototypical tetrameric Na-conducting channel, NaK, to 2.5 Å resolution from nano-crystals. Two new conformations at the external site of NaK are identified, allowing us to visualize a partially hydrated Na ion at the entrance of the channel pore. A process of dilation coupled with Na movement is identified leading to valuable insights into the mechanism of ion conduction and gating. This study lays the ground work for future studies using MicroED in membrane protein biophysics.

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.