How the brain perceives sensory information and generates meaningful behavior depends critically on its underlying circuitry. The protocerebral bridge (PB) is a major part of the insect central complex (CX), a premotor center that may be analogous to the human basal ganglia. Here, by deconstructing hundreds of PB single neurons and reconstructing them into a common three-dimensional framework, we have constructed a comprehensive map of PB circuits with labeled polarity and predicted directions of information flow. Our analysis reveals a highly ordered information processing system that involves directed information flow among CX subunits through 194 distinct PB neuron types. Circuitry properties such as mirroring, convergence, divergence, tiling, reverberation, and parallel signal propagation were observed; their functional and evolutional significance is discussed. This layout of PB neuronal circuitry may provide guidelines for further investigations on transformation of sensory (e.g., visual) input into locomotor commands in fly brains.

The gills of most teleost fishes are covered by plate-like structures, the secondary lamellae, that provide the bulk of the respiratory surface area. Water passing over the secondary lamellae exchanges gases with blood passing through the secondary lamellae, forming a system that has served as a classic model of counter-current exchange. In this study, a computational model of flow around the secondary lamellae is used to examine the hydrodynamic consequences of changes to the lamellar morphology. Consistent with previous studies, the interlamellar distance is found to strongly affect the hydrodynamic resistance of the gills. However, the presence of a small gap between the tips of the secondary lamellae is found to have a similarly strong effect on the hydrodynamic resistance and flow patterns within the gills. The results from this model have been generally formulated, allowing the calculation of the hydrodynamic resistance for measured morphometric parameters. These results provide a new basis for comparing theoretical predictions of the gill resistance with measured values, and provide a general model for examining the diversity gill morphologies observed in teleost fishes.

A crucial issue in studies of morphogen gradients relates to their range: the distance over which they can act as direct regulators of cell signaling, gene expression and cell differentiation. To address this, we present a straightforward statistical framework that can be used in multiple developmental systems. We illustrate the developed approach by providing a point estimate and confidence interval for the spatial range of the graded distribution of nuclear Dorsal, a transcription factor that controls the dorsoventral pattern of the Drosophila embryo.

Double-stranded DNA (dsDNA) viruses such as herpesviruses and bacteriophages infect by delivering their genetic material into cells, a task mediated by a DNA channel called "portal protein." We have used electron cryomicroscopy to determine the structure of bacteriophage P22 portal protein in both the procapsid and mature capsid conformations. We find that, just as the viral capsid undergoes major conformational changes during virus maturation, the portal protein switches conformation from a procapsid to a mature phage state upon binding of gp4, the factor that initiates tail assembly. This dramatic conformational change traverses the entire length of the DNA channel, from the outside of the virus to the inner shell, and erects a large dome domain directly above the DNA channel that binds dsDNA inside the capsid. We hypothesize that this conformational change primes dsDNA for injection and directly couples completion of virus morphogenesis to a new cycle of infection.

The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly . Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly's brain.

What can we learn from a connectome? We constructed a simplified model of the first two stages of the fly visual system, the lamina and medulla. The resulting hexagonal lattice convolutional network was trained using backpropagation through time to perform object tracking in natural scene videos. Networks initialized with weights from connectome reconstructions automatically discovered well-known orientation and direction selectivity properties in T4 neurons and their inputs, while networks initialized at random did not. Our work is the first demonstration, that knowledge of the connectome can enable in silico predictions of the functional properties of individual neurons in a circuit, leading to an understanding of circuit function from structure alone.

Understanding the structure and operation of any nervous system has been a subject of research for well over a century. A near-term opportunity in this quest is to understand the brain of a model species, the fruit fly Drosophila melanogaster. This is an enticing target given its relatively small size (roughly 200,000 neurons), coupled with the behavioral richness that this brain supports, and the wide variety of techniques now available to study both brain and behavior. It is clear that within a few years we will possess a connectome for D. melanogaster: an electron-microscopy-level description of all neurons and their chemical synaptic connections. Given what we will soon have, what we already know and the research that is currently underway, what more do we need to know to enable us to understand the fly's brain? Here, we itemize the data we will need to obtain, collate and organize in order to build an integrated model of the brain of D. melanogaster.

Understanding memory formation, storage and retrieval requires knowledge of the underlying neuronal circuits. In Drosophila, the mushroom body (MB) is the major site of associative learning. We reconstructed the morphologies and synaptic connections of all 983 neurons within the three functional units, or compartments, that compose the adult MB’s α lobe, using a dataset of isotropic 8-nm voxels collected by focused ion-beam milling scanning electron microscopy. We found that Kenyon cells (KCs), whose sparse activity encodes sensory information, each make multiple en passant synapses to MB output neurons (MBONs) in each compartment. Some MBONs have inputs from all KCs, while others differentially sample sensory modalities. Only six percent of KC>MBON synapses receive a direct synapse from a dopaminergic neuron (DAN). We identified two unanticipated classes of synapses, KC>DAN and DAN>MBON. DAN activation produces a slow depolarization of the MBON in these DAN>MBON synapses and can weaken memory recall.

Flexible behaviors over long timescales are thought to engage recurrent neural networks in deep brain regions, which are experimentally challenging to study. In insects, recurrent circuit dynamics in a brain region called the central complex (CX) enable directed locomotion, sleep, and context- and experience-dependent spatial navigation. We describe the first complete electron-microscopy-based connectome of the CX, including all its neurons and circuits at synaptic resolution. We identified new CX neuron types, novel sensory and motor pathways, and network motifs that likely enable the CX to extract the fly's head-direction, maintain it with attractor dynamics, and combine it with other sensorimotor information to perform vector-based navigational computations. We also identified numerous pathways that may facilitate the selection of CX-driven behavioral patterns by context and internal state. The CX connectome provides a comprehensive blueprint necessary for a detailed understanding of network dynamics underlying sleep, flexible navigation, and state-dependent action selection.

Animal behavior is principally expressed through neural control of muscles. Therefore understanding how the brain controls behavior requires mapping neuronal circuits all the way to motor neurons. We have previously established technology to collect large-volume electron microscopy data sets of neural tissue and fully reconstruct the morphology of the neurons and their chemical synaptic connections throughout the volume. Using these tools we generated a dense wiring diagram, or connectome, for a large portion of the Drosophila central brain. However, in most animals, including the fly, the majority of motor neurons are located outside the brain in a neural center closer to the body, i.e. the mammalian spinal cord or insect ventral nerve cord (VNC). In this paper, we extend our effort to map full neural circuits for behavior by generating a connectome of the VNC of a male fly.