Navigating animals continuously integrate velocity signals to update internal representations of their directional heading and spatial location in the environment. How neural circuits combine sensory and motor information to construct these velocity estimates and how these self-motion signals, in turn, update internal representations that support navigational computations are not well understood. Recent work in Drosophila has identified a neural circuit that performs angular path integration to compute the fly's head direction, but the nature of the velocity signal is unknown. Here we identify a pair of neurons necessary for angular path integration that encode the fly's rotational velocity with high accuracy using both visual optic flow and motor information. This estimate of rotational velocity does not rely on a moment-to-moment integration of sensory and motor information. Rather, when visual and motor signals are congruent, these neurons prioritize motor information over visual information, and when the two signals are in conflict, reciprocal inhibition selects either the motor or visual signal. Together, our results suggest that flies update their head direction representation by constructing an estimate of rotational velocity that relies primarily on motor information and only incorporates optic flow signals in specific sensorimotor contexts, such as when the motor signal is absent.

Serial-section electronmicroscopy (ssEM) is themethod of choice for studyingmacroscopic biological samples at extremely high resolution in three dimensions. In the nervous system, nanometer-scale images are necessary to reconstruct dense neural wiring diagrams in the brain, so called connectomes. In order to use this data, consisting of up to 10 individual EM images, it must be assembled into a volume, requiring seamless 2D stitching from each physical section followed by 3D alignment of the stitched sections. The high throughput of ssEM necessitates 2D stitching to be done at the pace of imaging, which currently produces tens of terabytes per day. To achieve this, we present a modular volume assembly software pipeline ASAP (Assembly Stitching and Alignment Pipeline) that is scalable to datasets containing petabytes of data and parallelized to work in a distributed computational environment. The pipeline is built on top of the Render (27) services used in the volume assembly of the brain of adult Drosophilamelanogaster (30). It achieves high throughput by operating on themeta-data and transformations of each image stored in a database, thus eliminating the need to render intermediate output. ASAP ismodular, allowing for easy incorporation of new algorithms without significant changes in the workflow. The entire software pipeline includes a complete set of tools for stitching, automated quality control, 3D section alignment, and final rendering of the assembled volume to disk. ASAP has been deployed for continuous stitching of several large-scale datasets of the mouse visual cortex and human brain samples including one cubic millimeter of mouse visual cortex (28; 8) at speeds that exceed imaging. The pipeline also has multi-channel processing capabilities and can be applied to fluorescence and multi-modal datasets like array tomography.

Training spiking recurrent neural networks on neuronal recordings or behavioral tasks has become a prominent tool to study computations in the brain. With an increasing size and complexity of neural recordings, there is a need for fast algorithms that can scale to large datasets. We present optimized CPU and GPU implementations of the recursive least-squares algorithm in spiking neural networks. The GPU implementation allows training networks to reproduce neural activity of an order of millions neurons at order of magnitude times faster than the CPU implementation. We demonstrate this by applying our algorithm to reproduce the activity of > 66, 000 recorded neurons of a mouse performing a decision-making task. The fast implementation enables efficient training of large-scale spiking models, thus allowing for in-silico study of the dynamics and connectivity underlying multi-area computations.

Morphogen gradients are used in developing embryos, where they subdivide a field of cells into territories characterized by distinct cell fate potentials. Such systems require both a spatially-graded distribution of the morphogen, and an ability to encode different responses at different target genes. However, the potential for different temporal responses is also present because morphogen gradients typically provide temporal cues, which may be a potential source of conflict. Thus, a low threshold response adapted for an early temporal onset may be inappropriate when the desired spatial response is a spatially-limited, high-threshold expression pattern. Here, we identify such a case with the Drosophila vnd locus, which is a target of the dorsal (dl) nuclear concentration gradient that patterns the dorsal/ventral (D/V) axis of the embryo. The vnd gene plays a critical role in the "ventral dominance" hierarchy of vnd, ind, and msh, which individually specify distinct D/V neural columnar fates in increasingly dorsal ectodermal compartments. The role of vnd in this regulatory hierarchy requires early temporal expression, which is characteristic of low-threshold responses, but its specification of ventral neurogenic ectoderm demands a relatively high-threshold response to dl. We show that the Neurogenic Ectoderm Enhancer (NEE) at vnd takes additional input from the complementary Dpp gradient via a conserved Schnurri/Mad/Medea silencer element (SSE) unlike NEEs at brk, sog, rho, and vn. These results show how requirements for conflicting temporal and spatial responses to the same gradient can be solved by additional inputs from complementary gradients.

Climbing over chasms larger than step size is vital to fruit flies, since foraging and mating are achieved while walking. Flies avoid futile climbing attempts by processing parallax-motion vision to estimate gap width. To identify neuronal substrates of climbing control, we screened a large collection of fly lines with temporarily inactivated neuronal populations in a novel high-throughput assay described here. The observed climbing phenotypes were classified; lines in each group are reported. Selected lines were further analysed by high-resolution video cinematography. One striking class of flies attempts to climb chasms of unsurmountable width; expression analysis guided us to C2 optic-lobe interneurons. Inactivation of C2 or the closely related C3 neurons with highly specific intersectional driver lines consistently reproduced hyperactive climbing whereas strong or weak artificial depolarization of C2/C3 neurons strongly or mildly decreased climbing frequency. Contrast-manipulation experiments support our conclusion that C2/C3 neurons are part of the distance-evaluation system.

ro(Dom) is a dominant allele of rough (ro) that results in reduced eye size due to premature arrest in morphogenetic furrow (MF) progression. We found that the ro(Dom) stop-furrow phenotype was sensitive to the dosage of genes known to affect retinal differentiation, in particular members of the hedgehog (hh) signaling cascade. We demonstrate that ro(Dom) interferes with Hh's ability to induce the retina-specific proneural gene atonal (ato) in the MF and that normal eye size can be restored by providing excess Ato protein. We used ro(Dom) as a sensitive genetic background in which to identify mutations that affect hh signal transduction or regulation of ato expression. In addition to mutations in several unknown loci, we recovered multiple alleles of groucho (gro) and Hairless (H). Analysis of their phenotypes in somatic clones suggests that both normally act to restrict neuronal cell fate in the retina, although they control different aspects of ato's complex expression pattern.

Precise, repeatable genetic access to specific neurons via GAL4/UAS and related methods is a key advantage of Drosophila neuroscience. Neuronal targeting is typically documented using light microscopy of full GAL4 expression patterns, which generally lack the single-cell resolution required for reliable cell type identification. Here we use stochastic GAL4 labeling with the MultiColor FlpOut approach to generate cellular resolution confocal images at large scale. We are releasing aligned images of 74,000 such adult central nervous systems. An anticipated use of this resource is to bridge the gap between neurons identified by electron or light microscopy. Identifying individual neurons that make up each GAL4 expression pattern improves the prediction of split-GAL4 combinations targeting particular neurons. To this end we have made the images searchable on the NeuronBridge website. We demonstrate the potential of NeuronBridge to rapidly and effectively identify neuron matches based on morphology across imaging modalities and datasets.

Controlling the propagation of electromagnetic waves is important to a broad range of applications. Recent advances in controlling wave propagation in random scattering media have enabled optical focusing and imaging inside random scattering media. In this work, we propose and demonstrate a new method to deliver optical power more efficiently through scattering media. Drastically different from the random matrix characterization approach, our method can rapidly establish high efficiency communication channels using just a few measurements, regardless of the number of optical modes, and provides a practical and robust solution to boost the signal levels in optical or short wave communications. We experimentally demonstrated analog and digital signal transmission through highly scattering media with greatly improved performance. Besides scattering, our method can also reduce the loss of signal due to absorption. Experimentally, we observed that our method forced light to go around absorbers, leading to even higher signal improvement than in the case of purely scattering media. Interestingly, the resulting signal improvement is highly directional, which provides a new means against eavesdropping.

C. elegans is the premier system for the systematic analysis of cell fate specification and morphogenetic events during embryonic development. One challenge is that embryogenesis dynamically unfolds over a period of about 13 h; this half day-long timescale has constrained the scope of experiments by limiting the number of embryos that can be imaged. Here, we describe a semi-high-throughput protocol that allows for the simultaneous 3D time-lapse imaging of development in 80–100 embryos at moderate time resolution, from up to 14 different conditions, in a single overnight run. The protocol is straightforward and can be implemented by any laboratory with access to a microscope with point visiting capacity. The utility of this protocol is demonstrated by using it to image two custom-built strains expressing fluorescent markers optimized to visualize key aspects of germ-layer specification and morphogenesis. To analyze the data, a custom program that crops individual embryos out of a broader field of view in all channels, z-steps, and timepoints and saves the sequences for each embryo into a separate tiff stack was built. The program, which includes a user-friendly graphical user interface (GUI), streamlines data processing by isolating, pre-processing, and uniformly orienting individual embryos in preparation for visualization or automated analysis. Also supplied is an ImageJ macro that compiles individual embryo data into a multi-panel file that displays maximum intensity fluorescence projection and brightfield images for each embryo at each time point. The protocols and tools described herein were validated by using them to characterize embryonic development following knock-down of 40 previously described developmental genes; this analysis visualized previously annotated developmental phenotypes and revealed new ones. In summary, this work details a semi-high-throughput imaging method coupled with a cropping program and ImageJ visualization tool that, when combined with strains expressing informative fluorescent markers, greatly accelerates experiments to analyze embryonic development.

Enzyme kinetics measurements are a standard component of undergraduate biochemistry laboratories. The combination of serine hydrolases and fluorogenic enzyme substrates provides a rapid, sensitive, and general method for measuring enzyme kinetics in an undergraduate biochemistry laboratory. In this method, the kinetic activity of multiple protein variants is determined in parallel using a microplate reader, multichannel pipets, serial dilutions, and fluorogenic ester substrates. The utility of this methodology is illustrated by the measurement of differential enzyme activity in microplate volumes in triplicate with small protein samples and low activity enzyme variants. Enzyme kinetic measurements using fluorogenic substrates are, thus, adaptable for use with student-purified enzyme variants and for comparative enzyme kinetics studies. The rapid setup and analysis of these kinetic experiments not only provides advanced undergraduates with experience in a fundamental biochemical technique, but also provides the adaptability for use in inquiry-based laboratories.