A visual motion detection circuit suggested by Drosophila connectomics

In vivo Evaluation of a Newly Synthesized Acetylcholinesterase Inhibitor in a Transgenic Drosophila Model of Alzheimer's Disease

Alzheimer's disease is a neurodegenerative disease characterized by disrupted memory, learning functions, reduced life expectancy, and locomotor dysfunction, as a result of the accumulation and aggregation of amyloid peptides that cause neuronal damage in neuronal circuits. In the current study, we exploited a transgenic Drosophila melanogaster line, expressing amyloid-β peptides to investigate the efficacy of a newly synthesized acetylcholinesterase inhibitor, named XJP-1, as a potential AD therapy. Behavioral assays and confocal microscopy were used to characterize the drug effect on AD symptomatology and amyloid peptide deposition. The symptomatology induced in this particular transgenic model recapitulates the scenario observed in human AD patients, showing a shortened lifespan and reduced locomotor functions, along with a significant accumulation of amyloid plaques in the brain. XJP-1 treatment resulted in a significant improvement of AD symptoms and a reduction of amyloid plaques by diminishing the amyloid aggregation rate. In comparison with clinically effective AD drugs, our results demonstrated that XJP-1 has similar effects on AD symptomatology, but at 10 times lower drug concentration than donepezil. It also showed an earlier beneficial effect on the reduction of amyloid plaques at 10 days after drug treatment, as observed for donepezil at 20 days, while the other drugs tested have no such effect. As a novel and potent AChE inhibitor, our study demonstrates that inhibition of the enzyme AChE by XJP-1 treatment improves the amyloid-induced symptomatology in Drosophila, by reducing the number of amyloid plaques within the fruit fly CNS. Thus, compound XJP-1 has the therapeutic potential to be further investigated for the treatment of AD.

Neural specification, targeting, and circuit formation during visual system assembly

Like other sensory systems, the visual system is topographically organized: Its sensory neurons, the photoreceptors, and their targets maintain point-to-point correspondence in physical space, forming a retinotopic map. The iterative wiring of circuits in the visual system conveniently facilitates the study of its development. Over the past few decades, experiments in Drosophila have shed light on the principles that guide the specification and connectivity of visual system neurons. In this review, we describe the main findings unearthed by the study of the Drosophila visual system and compare them with similar events in mammals. We focus on how temporal and spatial patterning generates diverse cell types, how guidance molecules distribute the axons and dendrites of neurons within the correct target regions, how vertebrates and invertebrates generate their retinotopic map, and the molecules and mechanisms required for neuronal migration. We suggest that basic principles used to wire the fly visual system are broadly applicable to other systems and highlight its importance as a model to study nervous system development.

Single-Cell RNA Sequencing Analysis of the Drosophila Larval Ventral Cord

Drosophila provides a powerful genetic system and an excellent model to study the development and function of the nervous system. The fly's small brain and complex behavior has been instrumental in mapping neuronal circuits and elucidating the neural basis of behavior. The fast pace of fly development and the wealth of genetic tools has enabled systematic studies on cell differentiation and fate specification, and has uncovered strategies for axon guidance and targeting. The accessibility of neuronal structures and the ability to edit and manipulate gene expression in selective cells and/or synaptic compartments has revealed mechanisms for synapse assembly and neuronal connectivity. Recent advances in single-cell RNA sequencing (scRNA-seq) have further enhanced our appreciation and understanding of neuronal diversity in a fly brain. However, due to the small size of the fly brain and its constituent cells, scRNA-seq methodologies require a few adaptations. Here, we describe a set of protocols optimized for scRNA-seq analysis of the Drosophila larval ventral nerve cord, starting from tissue dissection and cell dissociation to cDNA library preparation, sequencing, and data analysis. We apply this workflow to three separate samples and detail the technical challenges associated with successful application of scRNA-seq to studies on neuronal diversity. An accompanying article (Vicidomini, Nguyen, Choudhury, Brody, & Serpe, 2021) presents a custom multistage analysis pipeline that integrates modules contained in different R packages to ensure high-flexibility, high-quality RNA-seq data analysis. These protocols are developed for Drosophila larval ventral nerve cord, but could easily be adapted to other tissues and model organisms. © 2021 U.S. Government. Basic Protocol 1: Dissection of larval ventral nerve cords and preparation of single-cell suspensions Basic Protocol 2: Preparation and sequencing of single-cell transcriptome libraries Basic Protocol 3: Alignment of raw sequencing data to indexed genome and generation of count matrices.

Energy constraints on brain network formation

Energy constraints are a fundamental limitation of the brain, which is physically embedded in a restricted space. The collective dynamics of neurons through connections enable the brain to achieve rich functionality, but building connections and maintaining activity come at a high cost. The effects of reducing these costs can be found in the characteristic structures of the brain network. Nevertheless, the mechanism by which energy constraints affect the organization and formation of the neuronal network in the brain is unclear. Here, it is shown that a simple model based on cost minimization can reproduce structures characteristic of the brain network. With reference to the behavior of neurons in real brains, the cost function was introduced in an activity-dependent form correlating the activity cost and the wiring cost as a simple ratio. Cost reduction of this ratio resulted in strengthening connections, especially at highly activated nodes, and induced the formation of large clusters. Regarding these network features, statistical similarity was confirmed by comparison to connectome datasets from various real brains. The findings indicate that these networks share an efficient structure maintained with low costs, both for activity and for wiring. These results imply the crucial role of energy constraints in regulating the network activity and structure of the brain.

R7 photoreceptor axon targeting depends on the relative levels of lost and found expression in R7 and its synaptic partners

As neural circuits form, growing processes select the correct synaptic partners through interactions between cell surface proteins. The presence of such proteins on two neuronal processes may lead to either adhesion or repulsion; however, the consequences of mismatched expression have rarely been explored. Here, we show that the Drosophila CUB-LDL protein Lost and found (Loaf) is required in the UV-sensitive R7 photoreceptor for normal axon targeting only when Loaf is also present in its synaptic partners. Although targeting occurs normally in loaf mutant animals, removing loaf from photoreceptors or expressing it in their postsynaptic neurons Tm5a/b or Dm9 in a loaf mutant causes mistargeting of R7 axons. Loaf localizes primarily to intracellular vesicles including endosomes. We propose that Loaf regulates the trafficking or function of one or more cell surface proteins, and an excess of these proteins on the synaptic partners of R7 prevents the formation of stable connections.

Cellular connectomes as arbiters of local circuit models in the cerebral cortex

With the availability of cellular-resolution connectivity maps, connectomes, from the mammalian nervous system, it is in question how informative such massive connectomic data can be for the distinction of local circuit models in the mammalian cerebral cortex. Here, we investigated whether cellular-resolution connectomic data can in principle allow model discrimination for local circuit modules in layer 4 of mouse primary somatosensory cortex. We used approximate Bayesian model selection based on a set of simple connectome statistics to compute the posterior probability over proposed models given a to-be-measured connectome. We find that the distinction of the investigated local cortical models is faithfully possible based on purely structural connectomic data with an accuracy of more than 90%, and that such distinction is stable against substantial errors in the connectome measurement. Furthermore, mapping a fraction of only 10% of the local connectome is sufficient for connectome-based model distinction under realistic experimental constraints. Together, these results show for a concrete local circuit example that connectomic data allows model selection in the cerebral cortex and define the experimental strategy for obtaining such connectomic data.

Building a circuit through correlated spontaneous neuronal activity in the developing vertebrate and invertebrate visual systems

During the development of the vertebrate nervous systems, genetic programs assemble an immature circuit that is subsequently refined by neuronal activity evoked by external stimuli. However, prior to sensory experience, the intrinsic property of the developing nervous system also triggers correlated network-level neuronal activity, with retinal waves in the developing vertebrate retina being the best documented example. Spontaneous activity has also been found in the visual system of Drosophila Here, we compare the spontaneous activity of the developing visual system between mammalian and Drosophila and suggest that Drosophila is an emerging model for mechanistic and functional studies of correlated spontaneous activity.

Inhibitory Interactions and Columnar Inputs to an Object Motion Detector in Drosophila

The direction-selective T4/T5 cells innervate optic-flow processing projection neurons in the lobula plate of the fly that mediate the visual control of locomotion. In the lobula, visual projection neurons coordinate complex behavioral responses to visual features, however, the input circuitry and computations that bestow their feature-detecting properties are less clear. Here, we study a highly specialized small object motion detector, LC11, and demonstrate that its responses are suppressed by local background motion. We show that LC11 expresses GABA-A receptors that serve to sculpt responses to small objects but are not responsible for the rejection of background motion. Instead, LC11 is innervated by columnar T2 and T3 neurons that are themselves highly sensitive to small static or moving objects, insensitive to wide-field motion and, unlike T4/T5, respond to both ON and OFF luminance steps.

The development and function of neuronal subtypes processing color and skylight polarization in the optic lobes of Drosophila melanogaster

The retinal mosaics of many insects contain different ommatidial subtypes harboring photoreceptors that are both molecularly and morphologically specialized for comparing between different wavelengths versus detecting the orientation of skylight polarization. The neural circuits underlying these different inputs and the characterization of their specific cellular elements are the subject of intense research. Here we review recent progress on the description of both assembly and function of color and skylight polarization circuitry, by focusing on two cell types located in the distal portion of the medulla neuropil of the fruit fly Drosophila melanogaster's optic lobes, called Dm8 and Dm9. In the main part of the retina, Dm8 cells fall into two molecularly distinct subtypes whose center becomes specifically connected to either one of randomly distributed 'pale' or 'yellow' R7 photoreceptor fates during development. Only in the 'dorsal rim area' (DRA), both polarization-sensitive R7 and R8 photoreceptors are connected to different Dm8-like cell types, called Dm-DRA1 and Dm-DRA2, respectively. An additional layer of interommatidial integration is introduced by Dm9 cells, which receive input from multiple neighboring R7 and R8 cells, as well as providing feedback synapses back into these photoreceptors. As a result, the response properties of color-sensitive photoreceptor terminals are sculpted towards being both maximally decorrelated, as well as harboring several levels of opponency (both columnar as well as intercolumnar). In the DRA, individual Dm9 cells appear to mix both polarization and color signals, thereby potentially serving as the first level of integration of different celestial stimuli. The molecular mechanisms underlying the establishment of these synaptic connections are beginning to be revealed, by using a combination of live imaging, developmental genetic studies, and cell type-specific transcriptomics.

On the structural connectivity of large-scale models of brain networks at cellular level

The brain’s structural connectivity plays a fundamental role in determining how neuron networks generate, process, and transfer information within and between brain regions. The underlying mechanisms are extremely difficult to study experimentally and, in many cases, large-scale model networks are of great help. However, the implementation of these models relies on experimental findings that are often sparse and limited. Their predicting power ultimately depends on how closely a model’s connectivity represents the real system. Here we argue that the data-driven probabilistic rules, widely used to build neuronal network models, may not be appropriate to represent the dynamics of the corresponding biological system. To solve this problem, we propose to use a new mathematical framework able to use sparse and limited experimental data to quantitatively reproduce the structural connectivity of biological brain networks at cellular level.

Reconstruction of motor control circuits in adult Drosophila using automated transmission electron microscopy

To investigate circuit mechanisms underlying locomotor behavior, we used serial-section electron microscopy (EM) to acquire a synapse-resolution dataset containing the ventral nerve cord (VNC) of an adult female Drosophila melanogaster. To generate this dataset, we developed GridTape, a technology that combines automated serial-section collection with automated high-throughput transmission EM. Using this dataset, we studied neuronal networks that control leg and wing movements by reconstructing all 507 motor neurons that control the limbs. We show that a specific class of leg sensory neurons synapses directly onto motor neurons with the largest-caliber axons on both sides of the body, representing a unique pathway for fast limb control. We provide open access to the dataset and reconstructions registered to a standard atlas to permit matching of cells between EM and light microscopy data. We also provide GridTape instrumentation designs and software to make large-scale EM more accessible and affordable to the scientific community.

Optimal Local Estimates of Visual Motion in a Natural Environment

Many organisms use visual signals to estimate motion, and these estimates typically are biased. Here, we ask whether these biases may reflect physical rather than biological limitations. Using a camera-gyroscope system, we sample the joint distribution of images and rotational motions in a natural environment, and from this distribution we construct the optimal estimator of velocity based on local image intensities. Over most of the natural dynamic range, this estimator exhibits the biases observed in neural and behavioral responses. Thus, imputed errors in sensory processing may represent an optimal response to the physical signals sampled from the environment.

Toward a scalable framework for reproducible processing of volumetric, nanoscale neuroimaging datasets

BACKGROUND

Emerging neuroimaging datasets (collected with imaging techniques such as electron microscopy, optical microscopy, or X-ray microtomography) describe the location and properties of neurons and their connections at unprecedented scale, promising new ways of understanding the brain. These modern imaging techniques used to interrogate the brain can quickly accumulate gigabytes to petabytes of structural brain imaging data. Unfortunately, many neuroscience laboratories lack the computational resources to work with datasets of this size: computer vision tools are often not portable or scalable, and there is considerable difficulty in reproducing results or extending methods.

RESULTS

We developed an ecosystem of neuroimaging data analysis pipelines that use open-source algorithms to create standardized modules and end-to-end optimized approaches. As exemplars we apply our tools to estimate synapse-level connectomes from electron microscopy data and cell distributions from X-ray microtomography data. To facilitate scientific discovery, we propose a generalized processing framework, which connects and extends existing open-source projects to provide large-scale data storage, reproducible algorithms, and workflow execution engines.

CONCLUSIONS

Our accessible methods and pipelines demonstrate that approaches across multiple neuroimaging experiments can be standardized and applied to diverse datasets. The techniques developed are demonstrated on neuroimaging datasets but may be applied to similar problems in other domains.

Comprehensive map of visual projection neurons for processing ultraviolet information in the Drosophila brain

The brain perceives visual information and controls behavior depending on its underlying neural circuits. How UV information is represented and processed in the brain remains poorly understood. In Drosophila melanogaster, UV light is detected by the R7 photoreceptor that projects exclusively into the medulla layer 6 (M₆ ). Herein, we imaged 28,768 single neurons and identified 238 visual projection neurons linking M₆ to the central brain. Based on morphology and connectivity, these visual projection neurons were systematically classified into 94 cell types belonging to 12 families. Three tracts connected M₆ in each optic lobe to the central brain: One dorsal tract linking to the ipsilateral lateral anterior optic tubercle (L-AOTU) and two medial tracts linking to the ipsilateral ventral medial protocerebrum (VMP) and the contralateral VMP. The M₆ information was primarily represented in the L-AOTU. Each L-AOTU consisted of four columns that each contained three glomeruli. Each L-AOTU glomerulus received inputs from M₆ subdomains and gave outputs to a glomerulus within the ellipsoid body dendritic region, suggesting specific processing of spatial information through the dorsal pathway. Furthermore, the middle columns of the L-AOTUs of both hemispheres were connected via the intertubercle tract, suggesting information integration between the two eyes. In contrast, an ascending neuron linked each VMP to all glomeruli in the bulb and the L-AOTU, bilaterally, suggesting general processing of information through the ventral pathway. Altogether, these diverse morphologies of the visual projection neurons suggested multi-dimensional processing of UV information through parallel and bilateral circuits in the Drosophila brain.

Transcriptional Programs of Circuit Assembly in the Drosophila Visual System

Precise patterns of synaptic connections between neurons are encoded in their genetic programs. Here, we use single-cell RNA sequencing to profile neuronal transcriptomes at multiple stages in the developing Drosophila visual system. We devise an efficient strategy for profiling neurons at multiple time points in a single pool, thereby minimizing batch effects and maximizing the reliability of time-course data. A transcriptional atlas spanning multiple stages is generated, including more than 150 distinct neuronal populations; of these, 88 are followed through synaptogenesis. This analysis reveals a common (pan-neuronal) program unfolding in highly coordinated fashion in all neurons, including genes encoding proteins comprising the core synaptic machinery and membrane excitability. This program is overlaid by cell-type-specific programs with diverse cell recognition molecules expressed in different combinations and at different times. We propose that a pan-neuronal program endows neurons with the competence to form synapses and that cell-type-specific programs control synaptic specificity.

Comparative Connectomics Reveals How Partner Identity, Location, and Activity Specify Synaptic Connectivity in Drosophila

The mechanisms by which synaptic partners recognize each other and establish appropriate numbers of connections during embryonic development to form functional neural circuits are poorly understood. We combined electron microscopy reconstruction, functional imaging of neural activity, and behavioral experiments to elucidate the roles of (1) partner identity, (2) location, and (3) activity in circuit assembly in the embryonic nerve cord of Drosophila. We found that postsynaptic partners are able to find and connect to their presynaptic partners even when these have been shifted to ectopic locations or silenced. However, orderly positioning of axon terminals by positional cues and synaptic activity is required for appropriate numbers of connections between specific partners, for appropriate balance between excitatory and inhibitory connections, and for appropriate functional connectivity and behavior. Our study reveals with unprecedented resolution the fine connectivity effects of multiple factors that work together to control the assembly of neural circuits.

Whole-brain estimates of directed connectivity for human connectomics

Connectomics is essential for understanding large-scale brain networks but requires that individual connection estimates are neurobiologically interpretable. In particular, a principle of brain organization is that reciprocal connections between cortical areas are functionally asymmetric. This is a challenge for fMRI-based connectomics in humans where only undirected functional connectivity estimates are routinely available. By contrast, whole-brain estimates of effective (directed) connectivity are computationally challenging, and emerging methods require empirical validation. Here, using a motor task at 7T, we demonstrate that a novel generative model can infer known connectivity features in a whole-brain network (>200 regions, >40,000 connections) highly efficiently. Furthermore, graph-theoretical analyses of directed connectivity estimates identify functional roles of motor areas more accurately than undirected functional connectivity estimates. These results, which can be achieved in an entirely unsupervised manner, demonstrate the feasibility of inferring directed connections in whole-brain networks and open new avenues for human connectomics.

A petascale automated imaging pipeline for mapping neuronal circuits with high-throughput transmission electron microscopy

Electron microscopy (EM) is widely used for studying cellular structure and network connectivity in the brain. We have built a parallel imaging pipeline using transmission electron microscopes that scales this technology, implements 24/7 continuous autonomous imaging, and enables the acquisition of petascale datasets. The suitability of this architecture for large-scale imaging was demonstrated by acquiring a volume of more than 1 mm3 of mouse neocortex, spanning four different visual areas at synaptic resolution, in less than 6 months. Over 26,500 ultrathin tissue sections from the same block were imaged, yielding a dataset of more than 2 petabytes. The combined burst acquisition rate of the pipeline is 3 Gpixel per sec and the net rate is 600 Mpixel per sec with six microscopes running in parallel. This work demonstrates the feasibility of acquiring EM datasets at the scale of cortical microcircuits in multiple brain regions and species.

DWnt4 and DWnt10 Regulate Morphogenesis and Arrangement of Columnar Units via Fz2/PCP Signaling in the Drosophila Brain

Columns are structural and functional units of the brain. However, the mechanism of column formation remains unclear. The medulla of the fly visual center shares features with the mammalian cerebral cortex, such as columnar and layered structures, and provides a good opportunity to study the mechanisms of column formation. Column formation is initiated by three core neurons in the medulla, namely, Mi1, R8, and R7. The proper orientation of neurons is required for the orientation and arrangement of multiple columns. Their orientations may be under the control of planar cell polarity (PCP) signaling, because it is known to regulate the orientation of cells in two-dimensional tissue structures. In this study, we demonstrate that the ligands DWnt4 and DWnt10 expressed specifically in the ventral medulla and dorsal medulla, respectively, globally regulate the columnar arrangement and orientation of Mi1 and R8 terminals through Fz2/PCP signaling in a three-dimensional space.

A novel setup for simultaneous two-photon functional imaging and precise spectral and spatial visual stimulation in Drosophila

Motion vision has been extensively characterised in Drosophila melanogaster, but substantially less is known about how flies process colour, or how spectral information affects other visual modalities. To accurately dissect the components of the early visual system responsible for processing colour, we developed a versatile visual stimulation setup to probe combined spatial, temporal and spectral response properties. Using flies expressing neural activity indicators, we tracked visual responses in the medulla, the second visual neuropil, to a projected colour stimulus. The introduction of custom bandpass optical filters enables simultaneous two-photon imaging and visual stimulation over a large range of wavelengths without compromising the temporal stimulation rate. With monochromator-produced light, any spectral bandwidth and centre wavelength from 390 to 730 nm can be selected to produce a narrow spectral hue. A specialised screen material scatters each band of light across the visible spectrum equally at all locations of the screen, thus enabling presentation of spatially structured stimuli. We show layer-specific shifts of spectral response properties in the medulla correlating with projection regions of photoreceptor terminals.

A connectome and analysis of the adult Drosophila central brain

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 Drosophila melanogaster. 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.

A minimal synaptic model for direction selective neurons in Drosophila

Visual motion estimation is a canonical neural computation. In Drosophila, recent advances have identified anatomic and functional circuitry underlying direction-selective computations. Models with varying levels of abstraction have been proposed to explain specific experimental results but have rarely been compared across experiments. Here we use the wealth of available anatomical and physiological data to construct a minimal, biophysically inspired synaptic model for Drosophila’s first-order direction-selective T4 cells. We show how this model relates mathematically to classical models of motion detection, including the Hassenstein-Reichardt correlator model. We used numerical simulation to test how well this synaptic model could reproduce measurements of T4 cells across many datasets and stimulus modalities. These comparisons include responses to sinusoid gratings, to apparent motion stimuli, to stochastic stimuli, and to natural scenes. Without fine-tuning this model, it sufficed to reproduce many, but not all, response properties of T4 cells. Since this model is flexible and based on straightforward biophysical properties, it provides an extensible framework for developing a mechanistic understanding of T4 neural response properties. Moreover, it can be used to assess the sufficiency of simple biophysical mechanisms to describe features of the direction-selective computation and identify where our understanding must be improved.

Serotonergic modulation of visual neurons in Drosophila melanogaster

Sensory systems rely on neuromodulators, such as serotonin, to provide flexibility for information processing as stimuli vary, such as light intensity throughout the day. Serotonergic neurons broadly innervate the optic ganglia of Drosophila melanogaster, a widely used model for studying vision. It remains unclear whether serotonin modulates the physiology of interneurons in the optic ganglia. To address this question, we first mapped the expression patterns of serotonin receptors in the visual system, focusing on a subset of cells with processes in the first optic ganglion, the lamina. Serotonin receptor expression was found in several types of columnar cells in the lamina including 5-HT2B in lamina monopolar cell L2, required for spatiotemporal luminance contrast, and both 5-HT1A and 5-HT1B in T1 cells, whose function is unknown. Subcellular mapping with GFP-tagged 5-HT2B and 5-HT1A constructs indicated that these receptors localize to layer M2 of the medulla, proximal to serotonergic boutons, suggesting that the medulla neuropil is the primary site of serotonergic regulation for these neurons. Exogenous serotonin increased basal intracellular calcium in L2 terminals in layer M2 and modestly decreased the duration of visually induced calcium transients in L2 neurons following repeated dark flashes, but otherwise did not alter the calcium transients. Flies without functional 5-HT2B failed to show an increase in basal calcium in response to serotonin. 5-HT2B mutants also failed to show a change in amplitude in their response to repeated light flashes but other calcium transient parameters were relatively unaffected. While we did not detect serotonin receptor expression in L1 neurons, they, like L2, underwent serotonin-induced changes in basal calcium, presumably via interactions with other cells. These data demonstrate that serotonin modulates the physiology of interneurons involved in early visual processing in Drosophila.

Serotonergic neurons innervate the Drosophila melanogaster eye, but it was not known whether serotonin signaling could induce acute physiological responses in visual interneurons. We found serotonin receptors expressed in all neuropils of the optic lobe and identified specific neurons involved in visual information processing that express serotonin receptors. Activation of these receptors increased intracellular calcium in first order interneurons L1 and L2 and may enhance visually induced calcium transients in L2 neurons. These data support a role for the serotonergic neuromodulation of interneurons in the Drosophila visual system.

An optimized approach using cryofixation for high-resolution 3D analysis by FIB-SEM

Compared with conventional two-dimensional transmission electron microscopy (TEM), focused ion beam scanning electron microscopy (FIB-SEM) can provide more comprehensive 3D information on cell substructures at the nanometer scale. Biological samples prepared by cryofixation using high-pressure freezing demonstrate optimal preservation of the morphology of cellular structures, as these are arrested instantly in their near-native states. However, samples from cryofixation often show a weak back-scatter electron signal and bad image contrast in FIB-SEM imaging. In addition, it is impossible to do large amounts of heavy metal staining. This is commonly achieved via established osmium impregnation (OTO) en bloc staining protocols. Here, we compared the FIB-SEM image quality of brain tissues prepared using several common freeze-substitution media, and we developed an approach that overcomes these limitations through a combination of osmium tetroxide, uranyl acetate, tannic acid, and potassium permanganate at proper concentrations, respectively. Using this optimized sample preparation protocol for high-pressure freezing and freeze-substitution, perfect smooth membrane morphology, even of the lipid bilayers of the cell membrane, was readily obtained using FIB-SEM. In addition, our protocol is broadly applicable and we demonstrated successful application to brain tissues, plant tissues, Caenorhabditis elegans, Candida albicans, and chlorella. This approach combines the potential of cryofixation for 3D large volume analysis of subcellular structures with the high-resolution capabilities of FIB-SEM.

BRICseq Bridges Brain-wide Interregional Connectivity to Neural Activity and Gene Expression in Single Animals

Comprehensive analysis of neuronal networks requires brain-wide measurement of connectivity, activity, and gene expression. Although high-throughput methods are available for mapping brain-wide activity and transcriptomes, comparable methods for mapping region-to-region connectivity remain slow and expensive because they require averaging across hundreds of brains. Here we describe BRICseq (brain-wide individual animal connectome sequencing), which leverages DNA barcoding and sequencing to map connectivity from single individuals in a few weeks and at low cost. Applying BRICseq to the mouse neocortex, we find that region-to-region connectivity provides a simple bridge relating transcriptome to activity: the spatial expression patterns of a few genes predict region-to-region connectivity, and connectivity predicts activity correlations. We also exploited BRICseq to map the mutant BTBR mouse brain, which lacks a corpus callosum, and recapitulated its known connectopathies. BRICseq allows individual laboratories to compare how age, sex, environment, genetics, and species affect neuronal wiring and to integrate these with functional activity and gene expression.

Lamina feedback neurons regulate the bandpass property of the flicker-induced orientation response in Drosophila

Natural scenes contain complex visual cues with specific features, including color, motion, flicker, and position. It is critical to understand how different visual features are processed at the early stages of visual perception to elicit appropriate cellular responses, and even behavioral output. Here, we studied the visual orientation response induced by flickering stripes in a novel behavioral paradigm in Drosophila melanogaster. We found that free walking flies exhibited bandpass orientation response to flickering stripes of different frequencies. The most sensitive frequency spectrum was confined to low frequencies of 2-4 Hz. Through genetic silencing, we showed that lamina L1 and L2 neurons, which receive visual inputs from R1 to R6 neurons, were the main components in mediating flicker-induced orientation behavior. Moreover, specific blocking of different types of lamina feedback neurons Lawf1, Lawf2, C2, C3, and T1 modulated orientation responses to flickering stripes of particular frequencies, suggesting that bandpass orientation response was generated through cooperative modulation of lamina feedback neurons. Furthermore, we found that lamina feedback neurons Lawf1 were glutamatergic. Thermal activation of Lawf1 neurons could suppress neural activities in L1 and L2 neurons, which could be blocked by the glutamate-gated chloride channel inhibitor picrotoxin (PTX). In summary, lamina monopolar neurons L1 and L2 are the primary components in mediating flicker-induced orientation response. Meanwhile, lamina feedback neurons cooperatively modulate the orientation response in a frequency-dependent way, which might be achieved through modulating neural activities of L1 and L2 neurons.

State-of-the-Art Technology of Model Organisms for Current Human Medicine

Since the 1980s, molecular biology has been used to investigate medical field mechanisms that still require the use of crude biological materials in order to achieve their necessary goals. Transcription factor-induced pluripotent stem cells are used in regenerative medicine to screen drugs and to support lost tissues. However, these cells insufficiently reconstruct whole organs and require various intact cells, such as damaged livers and diabetic pancreases. For efficient gene transfer in medical use, virally mediated gene transfers are used, although immunogenic issues are investigated. To obtain efficient detective and diagnostic power in intractable diseases, biological tools such as roundworms and zebrafish have been found to be useful for high-throughput screening (HST) and diagnosis. Taken together, this biological approach will help to fill the gaps between medical needs and novel innovations in the field of medicine.

A combinatorial code of transcription factors specifies subtypes of visual motion-sensing neurons in Drosophila

Direction-selective T4/T5 neurons exist in four subtypes, each tuned to visual motion along one of the four cardinal directions. Along with their directional tuning, neurons of each T4/T5 subtype orient their dendrites and project their axons in a subtype-specific manner. Directional tuning, thus, appears strictly linked to morphology in T4/T5 neurons. How the four T4/T5 subtypes acquire their distinct morphologies during development remains largely unknown. Here, we investigated when and how the dendrites of the four T4/T5 subtypes acquire their specific orientations, and profiled the transcriptomes of all T4/T5 neurons during this process. This revealed a simple and stable combinatorial code of transcription factors defining the four T4/T5 subtypes during their development. Changing the combination of transcription factors of specific T4/T5 subtypes resulted in predictable and complete conversions of subtype-specific properties, i.e. dendrite orientation and matching axon projection pattern. Therefore, a combinatorial code of transcription factors coordinates the development of dendrite and axon morphologies to generate anatomical specializations that differentiate subtypes of T4/T5 motion-sensing neurons.

Summary: Morphological and transcriptomic analyses allowed the identification of a combinatorial code of transcription factors that controls the development of subtype-specific morphologies in motion-detecting neurons of the Drosophila visual system.

Precision as a measure of predictability of missing links in real networks

Predicting missing links in real networks is an important open problem in network science to which considerable efforts have been devoted, giving as a result a vast plethora of link prediction methods in the literature. In this work, we take a different point of view on the problem and focus on predictability instead of prediction. By considering ensembles defined by well-known network models, we prove analytically that even the best possible link prediction method, given by the ensemble connection probabilities, yields a limited precision that depends quantitatively on the topological properties-such as degree heterogeneity, clustering, and community structure-of the ensemble. This suggests an absolute limitation to the predictability of missing links in real networks, due to the irreducible uncertainty arising from the random nature of link formation processes. We show that a predictability limit can be estimated in real networks, and we propose a method to approximate such a bound from real-world networks with missing links. The predictability limit gives a benchmark to gauge the quality of link prediction methods in real networks.

The natverse, a versatile toolbox for combining and analysing neuroanatomical data

To analyse neuron data at scale, neuroscientists expend substantial effort reading documentation, installing dependencies and moving between analysis and visualisation environments. To facilitate this, we have developed a suite of interoperable open-source R packages called the natverse. The natverse allows users to read local and remote data, perform popular analyses including visualisation and clustering and graph-theoretic analysis of neuronal branching. Unlike most tools, the natverse enables comparison across many neurons of morphology and connectivity after imaging or co-registration within a common template space. The natverse also enables transformations between different template spaces and imaging modalities. We demonstrate tools that integrate the vast majority of Drosophila neuroanatomical light microscopy and electron microscopy connectomic datasets. The natverse is an easy-to-use environment for neuroscientists to solve complex, large-scale analysis challenges as well as an open platform to create new code and packages to share with the community.

Gene regulatory networks during the development of the Drosophila visual system

The Drosophila visual system integrates input from 800 ommatidia and extracts different features in stereotypically connected optic ganglia. The development of the Drosophila visual system is controlled by gene regulatory networks that control the number of precursor cells, generate neuronal diversity by integrating spatial and temporal information, coordinate the timing of retinal and optic lobe cell differentiation, and determine distinct synaptic targets of each cell type. In this chapter, we describe the known gene regulatory networks involved in the development of the different parts of the visual system and explore general components in these gene networks. Finally, we discuss the advantages of the fly visual system as a model for gene regulatory network discovery in the era of single-cell transcriptomics.

Hawkmoth lamina monopolar cells act as dynamic spatial filters to optimize vision at different light levels

How neural form and function are connected is a central question of neuroscience. One prominent functional hypothesis, from the beginnings of neuroanatomical study, states that laterally extending dendrites of insect lamina monopolar cells (LMCs) spatially integrate visual information. We provide the first direct functional evidence for this hypothesis using intracellular recordings from type II LMCs in the hawkmoth Macroglossum stellatarum. We show that their spatial receptive fields broaden with decreasing light intensities, thus trading spatial resolution for higher sensitivity. These dynamic changes in LMC spatial properties can be explained by the density and lateral extent of their dendritic arborizations. Our results thus provide the first physiological evidence for a century-old hypothesis, directly correlating physiological response properties with distinctive dendritic morphology.

Antagonistic regulation by insulin-like peptide and activin ensures the elaboration of appropriate dendritic field sizes of amacrine neurons

Establishing appropriate sizes and shapes of dendritic arbors is critical for proper wiring of the central nervous system. Here we report that Insulin-like Peptide 2 (DILP2) locally activates transiently expressed insulin receptors in the central dendrites of Drosophila Dm8 amacrine neurons to positively regulate dendritic field elaboration. We found DILP2 was expressed in L5 lamina neurons, which have axonal terminals abutting Dm8 dendrites. Proper Dm8 dendrite morphogenesis and synapse formation required insulin signaling through TOR (target of rapamycin) and SREBP (sterol regulatory element-binding protein), acting in parallel with previously identified negative regulation by Activin signaling to provide robust control of Dm8 dendrite elaboration. A simulation of dendritic growth revealed trade-offs between dendritic field size and robustness when branching and terminating kinetic parameters were constant, but dynamic modulation of the parameters could mitigate these trade-offs. We suggest that antagonistic DILP2 and Activin signals from different afferents appropriately size Dm8 dendritic fields.

Autophagy-dependent filopodial kinetics restrict synaptic partner choice during Drosophila brain wiring

Brain wiring is remarkably precise, yet most neurons readily form synapses with incorrect partners when given the opportunity. Dynamic axon-dendritic positioning can restrict synaptogenic encounters, but the spatiotemporal interaction kinetics and their regulation remain essentially unknown inside developing brains. Here we show that the kinetics of axonal filopodia restrict synapse formation and partner choice for neurons that are not otherwise prevented from making incorrect synapses. Using 4D imaging in developing Drosophila brains, we show that filopodial kinetics are regulated by autophagy, a prevalent degradation mechanism whose role in brain development remains poorly understood. With surprising specificity, autophagosomes form in synaptogenic filopodia, followed by filopodial collapse. Altered autophagic degradation of synaptic building material quantitatively regulates synapse formation as shown by computational modeling and genetic experiments. Increased filopodial stability enables incorrect synaptic partnerships. Hence, filopodial autophagy restricts inappropriate partner choice through a process of kinetic exclusion that critically contributes to wiring specificity.

A Robust Visual System for Small Target Motion Detection Against Cluttered Moving Backgrounds

Monitoring small objects against cluttered moving backgrounds is a huge challenge to future robotic vision systems. As a source of inspiration, insects are quite apt at searching for mates and tracking prey, which always appear as small dim speckles in the visual field. The exquisite sensitivity of insects for small target motion, as revealed recently, is coming from a class of specific neurons called small target motion detectors (STMDs). Although a few STMD-based models have been proposed, these existing models only use motion information for small target detection and cannot discriminate small targets from small-target-like background features (named fake features). To address this problem, this paper proposes a novel visual system model (STMD+) for small target motion detection, which is composed of four subsystems-ommatidia, motion pathway, contrast pathway, and mushroom body. Compared with the existing STMD-based models, the additional contrast pathway extracts directional contrast from luminance signals to eliminate false positive background motion. The directional contrast and the extracted motion information by the motion pathway are integrated into the mushroom body for small target discrimination. Extensive experiments showed the significant and consistent improvements of the proposed visual system model over the existing STMD-based models against fake features.

A network approach to analyze neuronal lineage and layer innervation in the Drosophila optic lobes

The optic lobes of the fruit fly Drosophila melanogaster form a highly wired neural network composed of roughly 130.000 neurons of more than 80 different types. How neuronal diversity arises from very few cell progenitors is a central question in developmental neurobiology. We use the optic lobe of the fruit fly as a paradigm to understand how neuroblasts, the neural stem cells, generate multiple neuron types. Although the development of the fly brain has been the subject of extensive research, very little is known about the lineage relationships of the cell types forming the adult optic lobes. Here we perform a large-scale lineage bioinformatics analysis using the graph theory. We generated a large collection of cell clones that genetically label the progeny of neuroblasts and built a database to draw graphs showing the lineage relationships between cell types. By establishing biological criteria that measures the strength of the neuronal relationships and applying community detection tools we have identified eight clusters of neurons. Each cluster contains different cell types that we pose are the product of eight distinct classes of neuroblasts. Three of these clusters match the available lineage data, supporting the predictive value of the analysis. Finally, we show that the neuronal progeny of a neuroblast do not have preferential innervation patterns, but instead become part of different layers and neuropils. Here we establish a new methodology that helps understanding the logic of Drosophila brain development and can be applied to the more complex vertebrate brains.

Color vision in insects: insights from Drosophila

Color vision is an important sensory capability that enhances the detection of contrast in retinal images. Monochromatic animals exclusively detect temporal and spatial changes in luminance, whereas two or more types of photoreceptors and neuronal circuitries for the comparison of their responses enable animals to differentiate spectral information independent of intensity. Much of what we know about the cellular and physiological mechanisms underlying color vision comes from research on vertebrates including primates. In insects, many important discoveries have been made, but direct insights into the physiology and circuit implementation of color vision are still limited. Recent advances in Drosophila systems neuroscience suggest that a complete insect color vision circuitry, from photoreceptors to behavior, including all elements and computations, can be revealed in future. Here, we review fundamental concepts in color vision alongside our current understanding of the neuronal basis of color vision in Drosophila, including side views to selected other insects.

Navigable maps of structural brain networks across species

Connectomes are spatially embedded networks whose architecture has been shaped by physical constraints and communication needs throughout evolution. Using a decentralized navigation protocol, we investigate the relationship between the structure of the connectomes of different species and their spatial layout. As a navigation strategy, we use greedy routing where nearest neighbors, in terms of geometric distance, are visited. We measure the fraction of successful greedy paths and their length as compared to shortest paths in the topology of connectomes. In Euclidean space, we find a striking difference between the navigability properties of mammalian and non-mammalian species, which implies the inability of Euclidean distances to fully explain the structural organization of their connectomes. In contrast, we find that hyperbolic space, the effective geometry of complex networks, provides almost perfectly navigable maps of connectomes for all species, meaning that hyperbolic distances are exceptionally congruent with the structure of connectomes. Hyperbolic maps therefore offer a quantitative meaningful representation of connectomes that suggests a new cartography of the brain based on the combination of its connectivity with its effective geometry rather than on its anatomy only. Hyperbolic maps also provide a universal framework to study decentralized communication processes in connectomes of different species and at different scales on an equal footing.

Luminance Information Is Required for the Accurate Estimation of Contrast in Rapidly Changing Visual Contexts

Visual perception scales with changes in the visual stimulus, or contrast, irrespective of background illumination. However, visual perception is challenged when adaptation is not fast enough to deal with sudden declines in overall illumination, for example, when gaze follows a moving object from bright sunlight into a shaded area. Here, we show that the visual system of the fly employs a solution by propagating a corrective luminance-sensitive signal. We use in vivo 2-photon imaging and behavioral analyses to demonstrate that distinct OFF-pathway inputs encode contrast and luminance. Predictions of contrast-sensitive neuronal responses show that contrast information alone cannot explain behavioral responses in sudden dim light. The luminance-sensitive pathway via the L3 neuron is required for visual processing in such rapidly changing light conditions, ensuring contrast constancy when pure contrast sensitivity underestimates a stimulus. Thus, retaining a peripheral feature, luminance, in visual processing is required for robust behavioral responses.

Heterogeneous Temporal Contrast Adaptation in Drosophila Direction-Selective Circuits

In visual systems, neurons adapt both to the mean light level and to the range of light levels, or the contrast. Contrast adaptation has been studied extensively, but it remains unclear how it is distributed among neurons in connected circuits, and how early adaptation affects subsequent computations. Here, we investigated temporal contrast adaptation in neurons across Drosophila's visual motion circuitry. Several ON-pathway neurons showed strong adaptation to changes in contrast over time. One of these neurons, Mi1, showed almost complete adaptation on fast timescales, and experiments ruled out several potential mechanisms for its adaptive properties. When contrast adaptation reduced the gain in ON-pathway cells, it was accompanied by decreased motion responses in downstream direction-selective cells. Simulations show that contrast adaptation can substantially improve motion estimates in natural scenes. The benefits are larger for ON-pathway adaptation, which helps explain the heterogeneous distribution of contrast adaptation in these circuits.

A genetic, genomic, and computational resource for exploring neural circuit function

The anatomy of many neural circuits is being characterized with increasing resolution, but their molecular properties remain mostly unknown. Here, we characterize gene expression patterns in distinct neural cell types of the Drosophila visual system using genetic lines to access individual cell types, the TAPIN-seq method to measure their transcriptomes, and a probabilistic method to interpret these measurements. We used these tools to build a resource of high-resolution transcriptomes for 100 driver lines covering 67 cell types, available at http://www.opticlobe.com. Combining these transcriptomes with recently reported connectomes helps characterize how information is transmitted and processed across a range of scales, from individual synapses to circuit pathways. We describe examples that include identifying neurotransmitters, including cases of apparent co-release, generating functional hypotheses based on receptor expression, as well as identifying strong commonalities between different cell types.

Circuit Mechanisms Underlying Chromatic Encoding in Drosophila Photoreceptors

Spectral information is commonly processed in the brain through generation of antagonistic responses to different wavelengths. In many species, these color opponent signals arise as early as photoreceptor terminals. Here, we measure the spectral tuning of photoreceptors in Drosophila. In addition to a previously described pathway comparing wavelengths at each point in space, we find a horizontal-cell-mediated pathway similar to that found in mammals. This pathway enables additional spectral comparisons through lateral inhibition, expanding the range of chromatic encoding in the fly. Together, these two pathways enable efficient decorrelation and dimensionality reduction of photoreceptor signals while retaining maximal chromatic information. A biologically constrained model accounts for our findings and predicts a spatio-chromatic receptive field for fly photoreceptor outputs, with a color opponent center and broadband surround. This dual mechanism combines motifs of both an insect-specific visual circuit and an evolutionarily convergent circuit architecture, endowing flies with the ability to extract chromatic information at distinct spatial resolutions.

A multilayer circuit architecture for the generation of distinct locomotor behaviors in Drosophila

Animals generate diverse motor behaviors, yet how the same motor neurons (MNs) generate two distinct or antagonistic behaviors remains an open question. Here, we characterize Drosophila larval muscle activity patterns and premotor/motor circuits to understand how they generate forward and backward locomotion. We show that all body wall MNs are activated during both behaviors, but a subset of MNs change recruitment timing for each behavior. We used TEM to reconstruct a full segment of all 60 MNs and 236 premotor neurons (PMNs), including differentially-recruited MNs. Analysis of this comprehensive connectome identified PMN-MN 'labeled line' connectivity; PMN-MN combinatorial connectivity; asymmetric neuronal morphology; and PMN-MN circuit motifs that could all contribute to generating distinct behaviors. We generated a recurrent network model that reproduced the observed behaviors, and used functional optogenetics to validate selected model predictions. This PMN-MN connectome will provide a foundation for analyzing the full suite of larval behaviors.

Distinct expression of potassium channels regulates visual response properties of lamina neurons in Drosophila melanogaster

The computational organization of sensory systems depends on the diversification of individual cell types with distinct signal-processing capabilities. The Drosophila visual system, for instance, splits information into channels with different temporal properties directly downstream of photoreceptors in the first-order interneurons of the OFF pathway, L2 and L3. However, the biophysical mechanisms that determine this specialization are largely unknown. Here, we show that the voltage-gated K_a channels Shaker and Shal contribute to the response properties of the major OFF pathway input L2. L3 calcium response kinetics postsynaptic to photoreceptors resemble the sustained calcium signals of photoreceptors, whereas L2 neurons decay transiently. Based on a cell-type-specific RNA-seq data set and endogenous protein tagging, we identified Shaker and Shal as the primary candidates to shape L2 responses. Using in vivo two-photon imaging of L2 calcium signals in combination with pharmacological and genetic perturbations of these K_a channels, we show that the wild-type Shaker and Shal function is to enhance L2 responses and cell-autonomously sharpen L2 kinetics. Our results reveal a role for K_a channels in determining the signal-processing characteristics of a specific cell type in the visual system.

The computation of directional selectivity in the Drosophila OFF motion pathway

In flies, the direction of moving ON and OFF features is computed separately. T4 (ON) and T5 (OFF) are the first neurons in their respective pathways to extract a directionally selective response from their non-selective inputs. Our recent study of T4 found that the integration of offset depolarizing and hyperpolarizing inputs is critical for the generation of directional selectivity. However, T5s lack small-field inhibitory inputs, suggesting they may use a different mechanism. Here we used whole-cell recordings of T5 neurons and found a similar receptive field structure: fast depolarization and persistent, spatially offset hyperpolarization. By assaying pairwise interactions of local stimulation across the receptive field, we found no amplifying responses, only suppressive responses to the non-preferred motion direction. We then evaluated passive, biophysical models and found that a model using direct inhibition, but not the removal of excitation, can accurately predict T5 responses to a range of moving stimuli.