Comprehensive maps of Drosophila higher olfactory centers: spatially segregated fruit and pheromone representation

Complete Connectomic Reconstruction of Olfactory Projection Neurons in the Fly Brain

Nervous systems contain sensory neurons, local neurons, projection neurons, and motor neurons. To understand how these building blocks form whole circuits, we must distil these broad classes into neuronal cell types and describe their network connectivity. Using an electron micrograph dataset for an entire Drosophila melanogaster brain, we reconstruct the first complete inventory of olfactory projections connecting the antennal lobe, the insect analog of the mammalian olfactory bulb, to higher-order brain regions in an adult animal brain. We then connect this inventory to extant data in the literature, providing synaptic-resolution "holotypes" both for heavily investigated and previously unknown cell types. Projection neurons are approximately twice as numerous as reported by light level studies; cell types are stereotyped, but not identical, in cell and synapse numbers between brain hemispheres. The lateral horn, the insect analog of the mammalian cortical amygdala, is the main target for this olfactory information and has been shown to guide innate behavior. Here, we find new connectivity motifs, including axo-axonic connectivity between projection neurons, feedback, and lateral inhibition of these axons by a large population of neurons, and the convergence of different inputs, including non-olfactory inputs and memory-related feedback onto third-order olfactory neurons. These features are less prominent in the mushroom body calyx, the insect analog of the mammalian piriform cortex and a center for associative memory. Our work provides a complete neuroanatomical platform for future studies of the adult Drosophila olfactory system.

Extrinsic activin signaling cooperates with an intrinsic temporal program to increase mushroom body neuronal diversity

Temporal patterning of neural progenitors leads to the sequential production of diverse neurons. To understand how extrinsic cues influence intrinsic temporal programs, we studied Drosophila mushroom body progenitors (neuroblasts) that sequentially produce only three neuronal types: γ, then α’β’, followed by αβ. Opposing gradients of two RNA-binding proteins Imp and Syp comprise the intrinsic temporal program. Extrinsic activin signaling regulates the production of α’β’ neurons but whether it affects the intrinsic temporal program was not known. We show that the activin ligand Myoglianin from glia regulates the temporal factor Imp in mushroom body neuroblasts. Neuroblasts missing the activin receptor Baboon have a delayed intrinsic program as Imp is higher than normal during the α’β’ temporal window, causing the loss of α’β’ neurons, a decrease in αβ neurons, and a likely increase in γ neurons, without affecting the overall number of neurons produced. Our results illustrate that an extrinsic cue modifies an intrinsic temporal program to increase neuronal diversity.

Density Visualization Pipeline: A Tool for Cellular and Network Density Visualization and Analysis

Neuron classification is an important component in analyzing network structure and quantifying the effect of neuron topology on signal processing. Current quantification and classification approaches rely on morphology projection onto lower-dimensional spaces. In this paper a 3D visualization and quantification tool is presented. The Density Visualization Pipeline (DVP) computes, visualizes and quantifies the density distribution, i.e., the "mass" of interneurons. We use the DVP to characterize and classify a set of GABAergic interneurons. Classification of GABAergic interneurons is of crucial importance to understand on the one hand their various functions and on the other hand their ubiquitous appearance in the neocortex. 3D density map visualization and projection to the one-dimensional x, y, z subspaces show a clear distinction between the studied cells, based on these metrics. The DVP can be coupled to computational studies of the behavior of neurons and networks, in which network topology information is derived from DVP information. The DVP reads common neuromorphological file formats, e.g., Neurolucida XML files, NeuroMorpho.org SWC files and plain ASCII files. Full 3D visualization and projections of the density to 1D and 2D manifolds are supported by the DVP. All routines are embedded within the visual programming IDE VRL-Studio for Java which allows the definition and rapid modification of analysis workflows.

Controlling motor neurons of every muscle for fly proboscis reaching

We describe the anatomy of all the primary motor neurons in the fly proboscis and characterize their contributions to its diverse reaching movements. Pairing this behavior with the wealth of Drosophila's genetic tools offers the possibility to study motor control at single-neuron resolution, and soon throughout entire circuits. As an entry to these circuits, we provide detailed anatomy of proboscis motor neurons, muscles, and joints. We create a collection of fly strains to individually manipulate every proboscis muscle through control of its motor neurons, the first such collection for an appendage. We generate a model of the action of each proboscis joint, and find that only a small number of motor neurons are needed to produce proboscis reaching. Comprehensive control of each motor element in this numerically simple system paves the way for future study of both reflexive and flexible movements of this appendage.

Evolution of olfactory circuits in insects

Recent years have seen an explosion of interest in the evolution of neural circuits. Comparison of animals from different families, orders, and phyla reveals fascinating variation in brain morphology, circuit structure, and neural cell types. However, it can be difficult to connect the complex changes that occur across long evolutionary distances to behavior. Luckily, these changes accumulate through processes that should also be observable in recent time, making more tractable comparisons of closely related species relevant and complementary. Here, we review several decades of research on the evolution of insect olfactory circuits across short evolutionary time scales. We describe two well-studied systems, Drosophila sechellia flies and Heliothis moths, in detailed case studies. We then move through key types of circuit evolution, cataloging examples from other insects and looking for general patterns. The literature is dominated by changes in sensory neuron number and tuning at the periphery-often enhancing neural response to odorants with new ecological or social relevance. However, changes in the way olfactory information is processed by central circuits is clearly important in a few cases, and we suspect the development of genetic tools in non-model species will reveal a broad role for central circuit evolution. Moving forward, such tools should also be used to rigorously test causal links between brain evolution and behavior.

A neuropeptide regulates fighting behavior in Drosophila melanogaster

Aggressive behavior is regulated by various neuromodulators such as neuropeptides and biogenic amines. Here we found that the neuropeptide Drosulfakinin (Dsk) modulates aggression in Drosophila melanogaster. Knock-out of Dsk or Dsk receptor CCKLR-17D1 reduced aggression. Activation and inactivation of Dsk-expressing neurons increased and decreased male aggressive behavior, respectively. Moreover, data from transsynaptic tracing, electrophysiology and behavioral epistasis reveal that Dsk-expressing neurons function downstream of a subset of P1 neurons (P1^a-splitGAL4) to control fighting behavior. In addition, winners show increased calcium activity in Dsk-expressing neurons. Conditional overexpression of Dsk promotes social dominance, suggesting a positive correlation between Dsk signaling and winning effects. The mammalian ortholog CCK has been implicated in mammal aggression, thus our work suggests a conserved neuromodulatory system for the modulation of aggressive behavior.

Layered roles of fruitless isoforms in specification and function of male aggression-promoting neurons in Drosophila

Inter-male aggressive behavior is a prominent sexually dimorphic behavior. Neural circuits that underlie aggressive behavior are therefore likely under the control of sex-determining genes. However, the neurogenetic mechanism that generates sex-specific aggressive behavior remains largely unknown. Here, we found that a neuronal class specified by one of the Drosophila sex determining genes, fruitless (fru), belongs to the neural circuit that generates male-type aggressive behavior. This neuronal class can promote aggressive behavior independent of another sex determining gene, doublesex (dsx), although dsx is involved in ensuring that aggressive behavior is performed only toward males. We also found that three fru isoforms with different DNA binding domains show a division of labor on male aggressive behaviors. A dominant role of fru in specifying sex-specific aggressive behavior may underscore a genetic mechanism that allows male-type aggressive behavior to evolve at least partially independently from courtship behavior, which is under different selective pressures.

Sex-determining genes distinctly regulate courtship capability and target preference via sexually dimorphic neurons

For successful mating, a male animal must execute effective courtship behaviors toward a receptive target sex, which is female. Whether the courtship execution capability and upregulation of courtship toward females are specified through separable sex-determining genetic pathways remains uncharacterized. Here, we found that one of the two Drosophila sex-determining genes, doublesex (dsx), specifies a male-specific neuronal component that serves as an execution mechanism for courtship behavior, whereas fruitless (fru) is required for enhancement of courtship behavior toward females. The dsx-dependent courtship execution mechanism includes a specific subclass within a neuronal cluster that co-express dsx and fru. This cluster contains at least another subclass that is specified cooperatively by both dsx and fru. Although these neuronal populations can also promote aggressive behavior toward male flies, this capacity requires fru-dependent mechanisms. Our results uncover how sex-determining genes specify execution capability and female-specific enhancement of courtship behavior through separable yet cooperative neurogenetic mechanisms.

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.

Behavioral and Transcriptional Response to Selection for Olfactory Behavior in Drosophila

The detection, discrimination, and behavioral responses to chemical cues in the environment can have marked effects on organismal survival and reproduction, eliciting attractive or aversive behavior. To gain insight into mechanisms mediating this hedonic valence, we applied thirty generations of divergent artificial selection for Drosophila melanogaster olfactory behavior. We independently selected for positive and negative behavioral responses to two ecologically relevant chemical compounds: 2,3-butanedione and cyclohexanone. We also tested the correlated responses to selection by testing behavioral responses to other odorants and life history traits. Measurements of behavioral responses of the selected lines and unselected controls to additional odorants showed that the mechanisms underlying responses to these odorants are, in some cases, differentially affected by selection regime and generalization of the response to other odorants was only detected in the 2,3-butanedione selection lines. Food consumption and lifespan varied with selection regime and, at times, sex. An analysis of gene expression of both selection regimes identified multiple differentially expressed genes. New genes and genes previously identified in mediating olfactory behavior were identified. In particular, we found functional enrichment of several gene ontology terms, including cell-cell adhesion and sulfur compound metabolic process, the latter including genes belonging to the glutathione S-transferase family. These findings highlight a potential role for glutathione S-transferases in the evolution of hedonic valence to ecologically relevant volatile compounds and set the stage for a detailed investigation into mechanisms by which these genes mediate attraction and aversion.

A Smart Region-Growing Algorithm for Single-Neuron Segmentation From Confocal and 2-Photon Datasets

Accurately digitizing the brain at the micro-scale is crucial for investigating brain structure-function relationships and documenting morphological alterations due to neuropathies. Here we present a new Smart Region Growing algorithm (SmRG) for the segmentation of single neurons in their intricate 3D arrangement within the brain. Its Region Growing procedure is based on a homogeneity predicate determined by describing the pixel intensity statistics of confocal acquisitions with a mixture model, enabling an accurate reconstruction of complex 3D cellular structures from high-resolution images of neural tissue. The algorithm's outcome is a 3D matrix of logical values identifying the voxels belonging to the segmented structure, thus providing additional useful volumetric information on neurons. To highlight the algorithm's full potential, we compared its performance in terms of accuracy, reproducibility, precision and robustness of 3D neuron reconstructions based on microscopic data from different brain locations and imaging protocols against both manual and state-of-the-art reconstruction tools.

The self-organized learning of noisy environmental stimuli requires distinct phases of plasticity

Along sensory pathways, representations of environmental stimuli become increasingly sparse and expanded. If additionally the feed-forward synaptic weights are structured according to the inherent organization of stimuli, the increase in sparseness and expansion leads to a reduction of sensory noise. However, it is unknown how the synapses in the brain form the required structure, especially given the omnipresent noise of environmental stimuli. Here, we employ a combination of synaptic plasticity and intrinsic plasticity—adapting the excitability of each neuron individually—and present stimuli with an inherent organization to a feed-forward network. We observe that intrinsic plasticity maintains the sparseness of the neural code and thereby allows synaptic plasticity to learn the organization of stimuli in low-noise environments. Nevertheless, even high levels of noise can be handled after a subsequent phase of readaptation of the neuronal excitabilities by intrinsic plasticity. Interestingly, during this phase the synaptic structure has to be maintained. These results demonstrate that learning and recalling in the presence of noise requires the coordinated interplay between plasticity mechanisms adapting different properties of the neuronal circuit.

Everyday life requires living beings to continuously recognize and categorize perceived stimuli from the environment. To master this task, the representations of these stimuli become increasingly sparse and expanded along the sensory pathways of the brain. In addition, the underlying neuronal network has to be structured according to the inherent organization of the environmental stimuli. However, how the neuronal network learns the required structure even in the presence of noise remains unknown. In this theoretical study, we show that the interplay between synaptic plasticity—controlling the synaptic efficacies—and intrinsic plasticity—adapting the neuronal excitabilities—enables the network to encode the organization of environmental stimuli. It thereby structures the network to correctly categorize stimuli even in the presence of noise. After having encoded the stimuli’s organization, consolidating the synaptic structure while keeping the neuronal excitabilities dynamic enables the neuronal system to readapt to arbitrary levels of noise resulting in a near-optimal classification performance for all noise levels. These results provide new insights into the interplay between different plasticity mechanisms and how this interplay enables sensory systems to reliably learn and categorize stimuli from the surrounding environment.

Olfactory receptor and circuit evolution promote host specialization

The evolution of animal behaviour is poorly understood^1,2. Despite numerous correlations between interspecific divergence in behaviour and nervous system structure and function, demonstrations of the genetic basis of these behavioural differences remain rare^3-5. Here we develop a neurogenetic model, Drosophila sechellia, a species that displays marked differences in behaviour compared to its close cousin Drosophila melanogaster^6,7, which are linked to its extreme specialization on noni fruit (Morinda citrifolia)^8-16. Using calcium imaging, we identify olfactory pathways in D. sechellia that detect volatiles emitted by the noni host. Our mutational analysis indicates roles for different olfactory receptors in long- and short-range attraction to noni, and our cross-species allele-transfer experiments demonstrate that the tuning of one of these receptors is important for species-specific host-seeking. We identify the molecular determinants of this functional change, and characterize their evolutionary origin and behavioural importance. We perform circuit tracing in the D. sechellia brain, and find that receptor adaptations are accompanied by increased sensory pooling onto interneurons as well as species-specific central projection patterns. This work reveals an accumulation of molecular, physiological and anatomical traits that are linked to behavioural divergence between species, and defines a model for investigating speciation and the evolution of the nervous system.

Olfactory receptor and circuit evolution promote host specialization

The evolution of animal behaviour is poorly understood^1,2. Despite numerous correlations of behavioural and nervous system divergence, demonstration of the genetic basis of interspecific behavioural differences remains rare^3–5. Here, we develop a novel neurogenetic model, Drosophila sechellia, a close cousin of D. melanogaster^6,7 that displays profound behavioural changes linked to its extreme specialisation on noni fruit^8–16. Using calcium imaging, we identify D. sechellia olfactory pathways detecting host volatiles. Mutational analysis indicates roles for different olfactory receptors in long- and short-range attraction to noni. Cross-species allele transfer demonstrates that tuning of one of these receptors is important for species-specific host-seeking. We identify the molecular determinants of this functional change, and characterise their evolutionary origin and behavioural significance. Through circuit tracing in the D. sechellia brain, we find that receptor adaptations are accompanied by increased sensory pooling onto interneurons and novel central projection patterns. This work reveals the accumulation of molecular, physiological and anatomical traits linked to behavioural divergence, and defines a powerful model for investigating nervous system evolution and speciation.

Multiple network properties overcome random connectivity to enable stereotypic sensory responses

Connections between neuronal populations may be genetically hardwired or random. In the insect olfactory system, projection neurons of the antennal lobe connect randomly to Kenyon cells of the mushroom body. Consequently, while the odor responses of the projection neurons are stereotyped across individuals, the responses of the Kenyon cells are variable. Surprisingly, downstream of Kenyon cells, mushroom body output neurons show stereotypy in their responses. We found that the stereotypy is enabled by the convergence of inputs from many Kenyon cells onto an output neuron, and does not require learning. The stereotypy emerges in the total response of the Kenyon cell population using multiple odor-specific features of the projection neuron responses, benefits from the nonlinearity in the transfer function, depends on the convergence:randomness ratio, and is constrained by sparseness. Together, our results reveal the fundamental mechanisms and constraints with which convergence enables stereotypy in sensory responses despite random connectivity.

Wiring patterns from auditory sensory neurons to the escape and song-relay pathways in fruit flies

Many animals rely on acoustic cues to decide what action to take next. Unraveling the wiring patterns of the auditory neural pathways is prerequisite for understanding such information processing. Here, we reconstructed the first step of the auditory neural pathway in the fruit fly brain, from primary to secondary auditory neurons, at the resolution of transmission electron microscopy. By tracing axons of two major subgroups of auditory sensory neurons in fruit flies, low-frequency tuned Johnston's organ (JO)-B neurons and high-frequency tuned JO-A neurons, we observed extensive connections from JO-B neurons to the main second-order neurons in both the song-relay and escape pathways. In contrast, JO-A neurons connected strongly to a neuron in the escape pathway. Our findings suggest that heterogeneous JO neuronal populations could be recruited to modify escape behavior whereas only specific JO neurons contribute to courtship behavior. We also found that all JO neurons have postsynaptic sites at their axons. Presynaptic modulation at the output sites of JO neurons could affect information processing of the auditory neural pathway in flies.

Stochastic and Arbitrarily Generated Input Patterns to the Mushroom Bodies Can Serve as Conditioned Stimuli in Drosophila

Single neurons in the brains of insects often have individual genetic identities and can be unambiguously identified between animals. The overall neuronal connectivity is also genetically determined and hard-wired to a large degree. Experience-dependent structural and functional plasticity is believed to be superimposed onto this more-or-less fixed connectome. However, in Drosophila melanogaster, it has been shown that the connectivity between the olfactory projection neurons (OPNs) and Kenyon cells, the intrinsic neurons of the mushroom body, is highly stochastic and idiosyncratic between individuals. Ensembles of distinctly and sparsely activated Kenyon cells represent information about the identity of the olfactory input, and behavioral relevance can be assigned to this representation in the course of associative olfactory learning. Previously, we showed that in the absence of any direct sensory input, artificially and stochastically activated groups of Kenyon cells could be trained to encode aversive cues when their activation coincided with aversive stimuli. Here, we have tested the hypothesis that the mushroom body can learn any stochastic neuronal input pattern as behaviorally relevant, independent of its exact origin. We show that fruit flies can learn thermogenetically generated, stochastic activity patterns of OPNs as conditioned stimuli, irrespective of glomerular identity, the innate valence that the projection neurons carry, or inter-hemispheric symmetry.

The brain of a nocturnal migratory insect, the Australian Bogong moth

Every year, millions of Australian Bogong moths (Agrotis infusa) complete an astonishing journey: In Spring, they migrate over 1,000 km from their breeding grounds to the alpine regions of the Snowy Mountains, where they endure the hot summer in the cool climate of alpine caves. In autumn, the moths return to their breeding grounds, where they mate, lay eggs and die. These moths can use visual cues in combination with the geomagnetic field to guide their flight, but how these cues are processed and integrated into the brain to drive migratory behavior is unknown. To generate an access point for functional studies, we provide a detailed description of the Bogong moth's brain. Based on immunohistochemical stainings against synapsin and serotonin (5HT), we describe the overall layout as well as the fine structure of all major neuropils, including the regions that have previously been implicated in compass-based navigation. The resulting average brain atlas consists of 3D reconstructions of 25 separate neuropils, comprising the most detailed account of a moth brain to date. Our results show that the Bogong moth brain follows the typical lepidopteran ground pattern, with no major specializations that can be attributed to their spectacular migratory lifestyle. These findings suggest that migratory behavior does not require widespread modifications of brain structure, but might be achievable via small adjustments of neural circuitry in key brain areas. Locating these subtle changes will be a challenging task for the future, for which our study provides an essential anatomical framework.

Olfactory Neurons and Brain Centers Directing Oviposition Decisions in Drosophila

The sense of smell influences many behaviors, yet how odors are represented in the brain remains unclear. A major challenge to studying olfaction is the lack of methods allowing activation of specific types of olfactory neurons in an ethologically relevant setting. To address this, we developed a genetic method in Drosophila called olfactogenetics in which a narrowly tuned odorant receptor, Or56a, is ectopically expressed in different olfactory neuron types. Stimulation with geosmin (the only known Or56a ligand) in an Or56a mutant background leads to specific activation of only target olfactory neuron types. We used this approach to identify olfactory sensory neurons (OSNs) that directly guide oviposition decisions. We identify 5 OSN-types (Or71a, Or47b, Or49a, Or67b, and Or7a) that, when activated alone, suppress oviposition. Projection neurons partnering with these OSNs share a region of innervation in the lateral horn, suggesting that oviposition site selection might be encoded in this brain region.

Structural Neural Connectivity Analysis in Zebrafish With Restricted Anterograde Transneuronal Viral Labeling and Quantitative Brain Mapping

The unique combination of small size, translucency, and powerful genetic tools makes larval zebrafish a uniquely useful vertebrate system to investigate normal and pathological brain structure and function. While functional connectivity can now be assessed by optical imaging (via fluorescent calcium or voltage reporters) at the whole-brain scale, it remains challenging to systematically determine structural connections and identify connectivity changes during development or disease. To address this, we developed Tracer with Restricted Anterograde Spread (TRAS), a novel vesicular stomatitis virus (VSV)-based neural circuit labeling approach. TRAS makes use of replication-incompetent VSV (VSVΔG) and a helper virus (lentivirus) to enable anterograde transneuronal spread between efferent axons and their direct postsynaptic targets but restricts further spread to downstream areas. We integrated TRAS with the Z-Brain zebrafish 3D atlas for quantitative connectivity analysis and identified targets of the retinal and habenular efferent projections, in patterns consistent with previous reports. We compared retinofugal connectivity patterns between wild-type and down syndrome cell adhesion molecule-like 1 (dscaml1) mutant zebrafish and revealed differences in topographical distribution. These results demonstrate the utility of TRAS for quantitative structural connectivity analysis that would be valuable for detecting novel efferent targets and mapping connectivity changes underlying neurological or behavioral deficits.

Adult neurogenesis in the mushroom bodies of red flour beetles (Tribolium castaneum, HERBST) is influenced by the olfactory environment

Several studies showed adult persisting neurogenesis in insects, including the red flour beetle Tribolium castaneum, while it is absent in honeybees, carpenter ants, and vinegar flies. In our study, we focus on cell proliferation in the adult mushroom bodies of T. castaneum. We reliably labelled the progenies of the adult persisting mushroom body neuroblasts and determined the proliferation rate under several olfactory conditions within the first week after adult eclosion. We found at least two phases of Kenyon cell proliferation in the early adult beetle. Our results suggest that the generation of Kenyon cells during the first three days after adult eclosion is mainly genetically predetermined and a continuation of the developmental processes (nature), whereas from day four on proliferation seems to be mainly dependent on the odour environment (nurture). Considering that the mushroom bodies are linked to learning and memory, neurogenesis in the mushroom bodies is part of the remodelling of neuronal circuits leading to the adaption to the environment and optimization of behaviour.

Presynaptic developmental plasticity allows robust sparse wiring of the Drosophila mushroom body

In order to represent complex stimuli, principle neurons of associative learning regions receive combinatorial sensory inputs. Density of combinatorial innervation is theorized to determine the number of distinct stimuli that can be represented and distinguished from one another, with sparse innervation thought to optimize the complexity of representations in networks of limited size. How the convergence of combinatorial inputs to principle neurons of associative brain regions is established during development is unknown. Here, we explore the developmental patterning of sparse olfactory inputs to Kenyon cells of the Drosophila melanogaster mushroom body. By manipulating the ratio between pre- and post-synaptic cells, we find that postsynaptic Kenyon cells set convergence ratio: Kenyon cells produce fixed distributions of dendritic claws while presynaptic processes are plastic. Moreover, we show that sparse odor responses are preserved in mushroom bodies with reduced cellular repertoires, suggesting that developmental specification of convergence ratio allows functional robustness.

A Feedforward Circuit Regulates Action Selection of Pre-mating Courtship Behavior in Female Drosophila

In the early phase of courtship, female fruit flies exhibit an acute rejection response to avoid unfavorable mating. This pre-mating rejection response is evolutionarily paralleled across species, but the molecular and neuronal basis of that behavior is unclear. Here, we show that a putative incoherent feedforward circuit comprising ellipsoid body neurons, cholinergic R4d, and its repressor GABAergic R2/R4m neurons regulates the pre-mating rejection response in the virgin female Drosophila melanogaster. Both R4d and R2/R4m are positively regulated, via specific dopamine receptors, by a subset of neurons in the dopaminergic PPM3 cluster. Genetic deprivation of GABAergic signal via GABA_A receptor RNA interference in this circuit induces a massive rejection response, whereas activation of GABAergic R2/R4m or suppression of cholinergic R4d increases receptivity. Moreover, glutamatergic signaling via N-methyl-d-aspartate receptors induces NO-mediated retrograde regulation potentially from R4d to R2/R4m, likely providing flexible control of the behavioral switching from rejection to acceptance. Our study elucidates the molecular and neural mechanisms regulating the behavioral selection process of the pre-mating female.

Neurons that Function within an Integrator to Promote a Persistent Behavioral State in Drosophila

Innate behaviors involve both reflexive motor programs and enduring internal states, but how these responses are coordinated by the brain is not clear. In Drosophila, male-specific P1 interneurons promote courtship song, as well as a persistent internal state that prolongs courtship and enhances aggressiveness. However, P1 neurons themselves are not persistently active. Here, we identify pCd neurons as persistently active, indirect P1 targets that are required for P1-evoked persistent courtship and aggression. Acute activation of pCd neurons alone is inefficacious but enhances and prolongs courtship or aggression promoted by female cues. Brief female exposure induces a persistent increase in male aggressiveness, an effect abrogated by interruption of pCd activity. pCd activity is not sufficient but necessary for persistent physiological activity, implying an essential role in a persistence network. Thus, P1 neurons coordinate both command-like control of courtship song and a persistent internal state of social arousal mediated by pCd neurons.

Neuronal mechanisms underlying innate and learned olfactory processing in Drosophila

Olfaction allows animals to adapt their behavior in response to different chemical cues in their environment. How does the brain efficiently discriminate different odors to drive appropriate behavior, and how does it flexibly assign value to odors to adjust behavior according to experience? This review traces neuronal mechanisms underlying these processes in adult Drosophila melanogaster from olfactory receptors to higher brain centers. We highlight neural circuit principles such as lateral inhibition, segregation and integration of olfactory channels, temporal accumulation of sensory evidence, and compartmentalized synaptic plasticity underlying associative memory.

Scaling the interactive effects of attractive and repellent odours for insect search behaviour

Insects searching for resources are exposed to a complexity of mixed odours, often involving both attractant and repellent substances. Understanding how insects respond to this complexity of cues is crucial for understanding consumer-resource interactions, but also to develop novel tools to control harmful pests. To advance our understanding of insect responses to combinations of attractive and repellent odours, we formulated three qualitative hypotheses; the response-ratio hypothesis, the repellent-threshold hypothesis and the odour-modulation hypothesis. The hypotheses were tested by exposing Drosophila melanogaster in a wind tunnel to combinations of vinegar as attractant and four known repellents; benzaldehyde, 1-octen-3-ol, geosmin and phenol. The responses to benzaldehyde, 1-octen-3-ol and geosmin provided support for the response-ratio hypothesis, which assumes that the behavioural response depends on the ratio between attractants and repellents. The response to phenol, rather supported the repellent-threshold hypothesis, where aversion only occurs above a threshold concentration of the repellent due to overshadowing of the attractant. We hypothesize that the different responses may be connected to the localization of receptors, as receptors detecting phenol are located on the maxillary palps whereas receptors detecting the other odorants are located on the antennae.

A subset of brain neurons controls regurgitation in adult Drosophila melanogaster

Taste is essential for animals to evaluate food quality and make important decisions about food choice and intake. How complex brains process sensory information to produce behavior is an essential question in the field of sensory neurobiology. Currently, little is known about higher-order taste circuits in the brain as compared with those of other sensory systems. Here, we used the common vinegar fly, Drosophila melanogaster, to screen for candidate neurons labeled by different transgenic GAL4 lines in controlling feeding behaviors. We found that activation of one line (VT041723-GAL4) produces 'proboscis holding' behavior (extrusion of the mouthpart without withdrawal). Further analysis showed that the proboscis holding phenotype indicates an aversive response, as flies pre-fed with either sucrose or water prior to neuronal activation exhibited regurgitation. Anatomical characterization of VT041723-GAL4-labeled neurons suggests that they receive sensory input from peripheral taste neurons. Overall, our study identifies a subset of brain neurons labeled by VT041723-GAL4 that may be involved in a taste circuit that controls regurgitation.

Cellular Mechanism Underlying rTMS Treatment for the Neural Plasticity of Nervous System in Drosophila Brain

Repetitive transcranial magnetic stimulation (rTMS) is used as a research tool and clinical treatment for the non-clinical and clinical populations, to modulate brain plasticity. In the case of neurologic and psychiatric disease, there is significant evidence to suggest that rTMS plays an important role in the functional recovery after neurological dysfunction. However, the causal role for rTMS in the recovery of nervous dysfunction remains unclear. The purpose of the present study is to detect the regulation of rTMS on the excitatory neuronal transmission and specify the mode of action of rTMS on the neural plasticity using Drosophila whole brain. Therefore, we identified the effects of rTMS on the neural plasticity of central neural system (CNS) by detecting the electrophysiology properties of projection neurons (PNs) from adult Drosophila brain after rTMS. Using patch clamp recordings, we recorded the mini excitatory postsynaptic current (mEPSC) of PNs after rTMS at varying frequencies (1 Hz and 100 Hz) and intensities (1%, 10%, 50%, and 100%). Then, the chronic electrophysiology recordings, including mEPSC, spontaneous action potential (sAP), and calcium channel currents from PNs after rTMS at low frequency (1 Hz), with low intensity (1%) were detected and the properties of the recordings were analyzed. Finally, the frequency and decay time of mEPSC, the resting potential and frequency of sAP, and the current density and rise time of calcium channel currents were significantly changed by rTMS. Our work reveals that rTMS can be used as a tool to regulate the presynaptic function of neural circuit, by modulating the calcium channel in a frequency-, intensity- and time-dependent manner.

Layer 4 of mouse neocortex differs in cell types and circuit organization between sensory areas

Layer 4 (L4) of mammalian neocortex plays a crucial role in cortical information processing, yet a complete census of its cell types and connectivity remains elusive. Using whole-cell recordings with morphological recovery, we identified one major excitatory and seven inhibitory types of neurons in L4 of adult mouse visual cortex (V1). Nearly all excitatory neurons were pyramidal and all somatostatin-positive (SOM+) non-fast-spiking interneurons were Martinotti cells. In contrast, in somatosensory cortex (S1), excitatory neurons were mostly stellate and SOM+ interneurons were non-Martinotti. These morphologically distinct SOM+ interneurons corresponded to different transcriptomic cell types and were differentially integrated into the local circuit with only S1 neurons receiving local excitatory input. We propose that cell type specific circuit motifs, such as the Martinotti/pyramidal and non-Martinotti/stellate pairs, are used across the cortex as building blocks to assemble cortical circuits.

Insect brain plasticity: effects of olfactory input on neuropil size

Insect brains are known to express a high degree of experience-dependent structural plasticity. One brain structure in particular, the mushroom body (MB), has been attended to in numerous studies as it is implicated in complex cognitive processes such as olfactory learning and memory. It is, however, poorly understood to what extent sensory input per se affects the plasticity of the mushroom bodies. By performing unilateral blocking of olfactory input on immobilized butterflies, we were able to measure the effect of passive sensory input on the volumes of antennal lobes (ALs) and MB calyces. We showed that the primary and secondary olfactory neuropils respond in different ways to olfactory input. ALs show absolute experience-dependency and increase in volume only if receiving direct olfactory input from ipsilateral antennae, while MB calyx volumes were unaffected by the treatment and instead show absolute age-dependency in this regard. We therefore propose that cognitive processes related to behavioural expressions are needed in order for the calyx to show experience-dependent volumetric expansions. Our results indicate that such experience-dependent volumetric expansions of calyces observed in other studies may have been caused by cognitive processes rather than by sensory input, bringing some causative clarity to a complex neural phenomenon.

Segregation of Unknown Odors From Mixtures Based on Stimulus Onset Asynchrony in Honey Bees

Animals use olfaction to search for distant objects. Unlike vision, where objects are spaced out, olfactory information mixes when it reaches olfactory organs. Therefore, efficient olfactory search requires segregating odors that are mixed with background odors. Animals can segregate known odors by detecting short differences in the arrival of mixed odorants (stimulus onset asynchrony). However, it is unclear whether animals can also use stimulus onset asynchrony to segregate odorants that they had no previous experience with and which have no innate or learned relevance (unknown odorants). Using behavioral experiments in honey bees, we here show that stimulus onset asynchrony also improves segregation of those unknown odorants. The stimulus onset asynchrony necessary to segregate unknown odorants is in the range of seconds, which is two orders of magnitude larger than the previously reported stimulus asynchrony sufficient for segregating known odorants. We propose that for unknown odorants, segregating odorant A from a mixture with B requires sensory adaptation to B.

Third-Order Neurons in the Lateral Horn Enhance Bilateral Contrast of Odor Inputs Through Contralateral Inhibition in Drosophila

The survival and reproduction of Drosophila melanogaster depends heavily on its ability to determine the location of an odor source and either to move toward or away from it. Despite the very small spatial separation between the two antennae and the redundancy in sensory neuron projection to both sides of the brain, Drosophila can resolve the concentration gradient by comparing the signal strength between the two antennae. When an odor stimulates the antennae asymmetrically, ipsilateral projection neurons from the first olfactory center are more strongly excited compared to the contralateral ones. However, it remains elusive how higher-order neurons process such asymmetric or lateralized odor inputs. Here, we monitored and analyzed for the first time the activity patterns of a small cluster of third-order neurons (so-called ventrolateral protocerebrum neurons) to asymmetric olfactory stimulation using two-photon calcium imaging. Our data demonstrate that lateralized odors evoke distinct activation of these neurons in the left and right brain hemisphere as a result of contralateral inhibition. Moreover, using laser transection experiments we show that this contralateral inhibition is mediated by presynaptic neurons most likely located in the lateral horn. Finally, we propose that this inhibitory interaction between higher-order neurons facilitates odor lateralization and plays a crucial role in olfactory navigation behavior of Drosophila, a theory that needs to be experimentally addressed in future studies.

Local synaptic inputs support opposing, network-specific odor representations in a widely projecting modulatory neuron

Serotonin plays different roles across networks within the same sensory modality. Previously, we used whole-cell electrophysiology in Drosophila to show that serotonergic neurons innervating the first olfactory relay are inhibited by odorants (Zhang and Gaudry, 2016). Here we show that network-spanning serotonergic neurons segregate information about stimulus features, odor intensity and identity, by using opposing coding schemes in different olfactory neuropil. A pair of serotonergic neurons (the CSDns) innervate the antennal lobe and lateral horn, which are first and second order neuropils. CSDn processes in the antennal lobe are inhibited by odors in an identity independent manner. In the lateral horn, CSDn processes are excited in an odor identity dependent manner. Using functional imaging, modeling, and EM reconstruction, we demonstrate that antennal lobe derived inhibition arises from local GABAergic inputs and acts as a means of gain control on branch-specific inputs that the CSDns receive within the lateral horn.

Food-derived volatiles enhance consumption in Drosophila melanogaster

Insects use multiple sensory modalities when searching for and accepting a food source, in particular odor and taste cues. Food-derived odorants are generally involved in mediating long- and short-range attraction. Taste cues, in contrast, act directly by contact with the food source, promoting the ingestion of nutritious food and the avoidance of toxic substances. It is possible, however, that insects integrate information from these sensory modalities during the process of feeding itself. Here, using a simple feeding assay, we investigated whether odors modulate food consumption in the fruit fly Drosophila melanogaster We found that the presence of both single food-derived odorants and complex odor mixtures enhanced consumption of an appetitive food. Feeding enhancement depended on the concentration and the chemical identity of the odorant. Volatile cues alone were sufficient to mediate this effect, as feeding was also increased when animals were prevented from contacting the odor source. Both males and females, including virgin females, increased ingestion in the presence of food-derived volatiles. Moreover, the presence of food-derived odorants significantly increased the consumption of food mixtures containing aversive bitter compounds, suggesting that flies integrate diverse olfactory and gustatory cues to guide feeding decisions, including situations in which animals are confronted with stimuli of opposite valence. Overall, these results show that food-derived olfactory cues directly modulate feeding in D. melanogaster, enhancing ingestion.

Neurogenetic dissection of the Drosophila lateral horn reveals major outputs, diverse behavioural functions, and interactions with the mushroom body

Animals exhibit innate behaviours to a variety of sensory stimuli including olfactory cues. In Drosophila, one higher olfactory centre, the lateral horn (LH), is implicated in innate behaviour. However, our structural and functional understanding of the LH is scant, in large part due to a lack of sparse neurogenetic tools for this region. We generate a collection of split-GAL4 driver lines providing genetic access to 82 LH cell types. We use these to create an anatomical and neurotransmitter map of the LH and link this to EM connectomics data. We find ~30% of LH projections converge with outputs from the mushroom body, site of olfactory learning and memory. Using optogenetic activation, we identify LH cell types that drive changes in valence behavior or specific locomotor programs. In summary, we have generated a resource for manipulating and mapping LH neurons, providing new insights into the circuit basis of innate and learned olfactory behavior.

Functional and anatomical specificity in a higher olfactory centre

Most sensory systems are organized into parallel neuronal pathways that process distinct aspects of incoming stimuli. In the insect olfactory system, second order projection neurons target both the mushroom body, required for learning, and the lateral horn (LH), proposed to mediate innate olfactory behavior. Mushroom body neurons form a sparse olfactory population code, which is not stereotyped across animals. In contrast, odor coding in the LH remains poorly understood. We combine genetic driver lines, anatomical and functional criteria to show that the Drosophila LH has ~1400 neurons and >165 cell types. Genetically labeled LHNs have stereotyped odor responses across animals and on average respond to three times more odors than single projection neurons. LHNs are better odor categorizers than projection neurons, likely due to stereotyped pooling of related inputs. Our results reveal some of the principles by which a higher processing area can extract innate behavioral significance from sensory stimuli.

Developmental organization of central neurons in the adult Drosophila ventral nervous system

We have used MARCM to reveal the adult morphology of the post embryonically produced neurons in the thoracic neuromeres of the Drosophila VNS. The work builds on previous studies of the origins of the adult VNS neurons to describe the clonal organization of the adult VNS. We present data for 58 of 66 postembryonic thoracic lineages, excluding the motor neuron producing lineages (15 and 24) which have been described elsewhere. MARCM labels entire lineages but where both A and B hemilineages survive (e.g., lineages 19, 12, 13, 6, 1, 3, 8, and 11), the two hemilineages can be discriminated and we have described each hemilineage separately. Hemilineage morphology is described in relation to the known functional domains of the VNS neuropil and based on the anatomy we are able to assign broad functional roles for each hemilineage. The data show that in a thoracic hemineuromere, 16 hemilineages are primarily involved in controlling leg movements and walking, 9 are involved in the control of wing movements, and 10 interface between both leg and wing control. The data provide a baseline of understanding of the functional organization of the adult Drosophila VNS. By understanding the morphological organization of these neurons, we can begin to define and test the rules by which neuronal circuits are assembled during development and understand the functional logic and evolution of neuronal networks.

Phenotypic Landscape of Schizophrenia-Associated Genes Defines Candidates and Their Shared Functions

Genomic studies have identified hundreds of candidate genes near loci associated with risk for schizophrenia. To define candidates and their functions, we mutated zebrafish orthologs of 132 human schizophrenia-associated genes. We created a phenotype atlas consisting of whole-brain activity maps, brain structural differences, and profiles of behavioral abnormalities. Phenotypes were diverse but specific, including altered forebrain development and decreased prepulse inhibition. Exploration of these datasets identified promising candidates in more than 10 gene-rich regions, including the magnesium transporter cnnm2 and the translational repressor gigyf2, and revealed shared anatomical sites of activity differences, including the pallium, hypothalamus, and tectum. Single-cell RNA sequencing uncovered an essential role for the understudied transcription factor znf536 in the development of forebrain neurons implicated in social behavior and stress. This phenotypic landscape of schizophrenia-associated genes prioritizes more than 30 candidates for further study and provides hypotheses to bridge the divide between genetic association and biological mechanism.

Artificial neural network filters for enhancing 3D optical microscopy images of neurites

The ability to extract accurate morphology of labeled neurons from microscopy images is crucial for mapping brain connectivity and for understanding changes in connectivity that underlie learning and neurological disorders. There are, however, two problems, specific to optical microscopy imaging of neurons, which make accurate neuron tracing exceedingly challenging: (i) neurites can appear broken due to inhomogeneous labeling and (ii) neurites can appear fused in 3D due to limited resolution. Here, we propose and evaluate several artificial neural network (ANN) architectures and conventional image enhancement filters with the aim of alleviating both problems. We developed four image quality metrics to evaluate the effects of the proposed filters: normalized intensity in the cross-over regions between neurites, effective radius of neurites, coefficient of variation of intensity along neurites, and local background to neurite intensity ratio. Our results show that ANN-based filters, trained on optimized semi-manual traces of neurites, can significantly outperform conventional filters. In particular, U-Net based filtering can virtually eliminate background intensity, while also reducing the effective radius of neurites to nearly 1 voxel. In addition, this filter significantly decreases intensity in the cross-over regions between neurites and reduces fluctuations of intensity on neurites' centerlines. These results suggest that including an ANN-based filtering step, which does not require substantial extra time or computing power, can be beneficial for automated neuron tracing projects.

Neural Evolution of Context-Dependent Fly Song

It is unclear where in the nervous system evolutionary changes tend to occur. To localize the source of neural evolution that has generated divergent behaviors, we developed a new approach to label and functionally manipulate homologous neurons across Drosophila species. We examined homologous descending neurons that drive courtship song in two species that sing divergent song types and localized relevant evolutionary changes in circuit function downstream of the intrinsic physiology of these descending neurons. This evolutionary change causes different species to produce divergent motor patterns in similar social contexts. Artificial stimulation of these descending neurons drives multiple song types, suggesting that multifunctional properties of song circuits may facilitate rapid evolution of song types.

Mechanisms of Sensory Discrimination: Insights from Drosophila Olfaction

All an animal can do to infer the state of its environment is to observe the sensory-evoked activity of its own neurons. These inferences about the presence, quality, or similarity of objects are probabilistic and inform behavioral decisions that are often made in close to real time. Neural systems employ several strategies to facilitate sensory discrimination: Biophysical mechanisms separate the neuronal response distributions in coding space, compress their variances, and combine information from sequential observations. We review how these strategies are implemented in the olfactory system of the fruit fly. The emerging principles of odor discrimination likely apply to other neural circuits of similar architecture.

Olfactory Object Recognition Based on Fine-Scale Stimulus Timing in Drosophila

Odorants of behaviorally relevant objects (e.g., food sources) intermingle with those from other sources. Therefore to determine whether an odor source is good or bad—without actually visiting it—animals first need to segregate the odorants from different sources. To do so, animals could use temporal stimulus cues, because odorants from one source exhibit correlated fluctuations, whereas odorants from different sources are less correlated. However, the behaviorally relevant timescales of temporal stimulus cues for odor source segregation remain unclear. Using behavioral experiments with free-flying flies, we show that (1) odorant onset asynchrony increases flies' attraction to a mixture of two odorants with opposing innate or learned valence and (2) attraction does not increase when the attractive odorant arrives first. These data suggest that flies can use stimulus onset asynchrony for odor source segregation and imply temporally precise neural mechanisms for encoding odors and for segregating them into distinct objects.

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Flies can detect whether two mixed odorants arrive synchronously or asynchronously

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This temporal sensitivity occurs for odorants with innate and learned valences

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Flies' behavior suggests use of odor onset asynchrony for odor source segregation

Sensory neuron lineage mapping and manipulation in the Drosophila olfactory system

Nervous systems exhibit myriad cell types, but understanding how this diversity arises is hampered by the difficulty to visualize and genetically-probe specific lineages, especially at early developmental stages prior to expression of unique molecular markers. Here, we use a genetic immortalization method to analyze the development of sensory neuron lineages in the Drosophila olfactory system, from their origin to terminal differentiation. We apply this approach to define a fate map of nearly all olfactory lineages and refine the model of temporal patterns of lineage divisions. Taking advantage of a selective marker for the lineage that gives rise to Or67d pheromone-sensing neurons and a genome-wide transcription factor RNAi screen, we identify the spatial and temporal requirements for Pointed, an ETS family member, in this developmental pathway. Transcriptomic analysis of wild-type and Pointed-depleted olfactory tissue reveals a universal requirement for this factor as a switch-like determinant of fates in these sensory lineages.

Few tools exist to study molecular diversity during neurodevelopment. Here the authors apply a genetic immortalization method in Drosophila to generate a fate map of olfactory sensory lineages, examine the relationships of this map and the neuroanatomical, molecular and evolutionary properties of the mature circuits, and identify a novel factor controlling lineage development.

Neuronal cell types in the fly: single-cell anatomy meets single-cell genomics

At around 150 000 neurons, the adult Drosophila melanogaster central nervous system is one of the largest species, for which a complete cellular catalogue is imminent. While numerically much simpler than mammalian brains, its complexity is still difficult to parse without grouping neurons into consistent types, which can number 1-1000 cells per hemisphere. We review how neuroanatomical and gene expression data are being used to discover neuronal types at scale. The correlation among multiple co-varying neuronal properties, including lineage, gene expression, morphology, connectivity, response properties and shared behavioral significance is essential to the definition of neuronal cell type. Initial studies comparing morphological and transcriptomic definitions of neuronal type suggest that these are highly consistent, but there is much to do to match these approaches brain-wide. Matched single-cell transcriptomic and morphological data provide an effective reference point to integrate other data types, including connectomics data. This will significantly enhance our ability to make functional predictions from brain wiring diagrams as well facilitating molecular genetic manipulation of neuronal types.

Threshold-Based Ordering of Sequential Actions during Drosophila Courtship

Goal-directed animal behaviors are typically composed of sequences of motor actions whose order and timing are critical for a successful outcome. Although numerous theoretical models for sequential action generation have been proposed, few have been supported by the identification of control neurons sufficient to elicit a sequence. Here, we identify a pair of descending neurons that coordinate a stereotyped sequence of engagement actions during Drosophila melanogaster male courtship behavior. These actions are initiated sequentially but persist cumulatively, a feature not explained by existing models of sequential behaviors. We find evidence consistent with a ramp-to-threshold mechanism, in which increasing neuronal activity elicits each action independently at successively higher activity thresholds.

Biological Mechanisms for Learning: A Computational Model of Olfactory Learning in the Manduca sexta Moth, With Applications to Neural Nets

The insect olfactory system, which includes the antennal lobe (AL), mushroom body (MB), and ancillary structures, is a relatively simple neural system capable of learning. Its structural features, which are widespread in biological neural systems, process olfactory stimuli through a cascade of networks where large dimension shifts occur from stage to stage and where sparsity and randomness play a critical role in coding. Learning is partly enabled by a neuromodulatory reward mechanism of octopamine stimulation of the AL, whose increased activity induces synaptic weight updates in the MB through Hebbian plasticity. Enforced sparsity in the MB focuses Hebbian growth on neurons that are the most important for the representation of the learned odor. Based upon current biophysical knowledge, we have constructed an end-to-end computational firing-rate model of the Manduca sexta moth olfactory system which includes the interaction of the AL and MB under octopamine stimulation. Our model is able to robustly learn new odors, and neural firing rates in our simulations match the statistical features of in vivo firing rate data. From a biological perspective, the model provides a valuable tool for examining the role of neuromodulators, like octopamine, in learning, and gives insight into critical interactions between sparsity, Hebbian growth, and stimulation during learning. Our simulations also inform predictions about structural details of the olfactory system that are not currently well-characterized. From a machine learning perspective, the model yields bio-inspired mechanisms that are potentially useful in constructing neural nets for rapid learning from very few samples. These mechanisms include high-noise layers, sparse layers as noise filters, and a biologically-plausible optimization method to train the network based on octopamine stimulation, sparse layers, and Hebbian growth.

Pheromone-Induced Accuracy of Nestmate Recognition in Carpenter Ants: Simultaneous Decrease in Type I and Type II Errors

The ecological and evolutionary success of social insects relies on their ability to efficiently discriminate between group members and aliens. Nestmate recognition occurs by phenotype matching, the comparison of the referent (colony) phenotype to the one of an encountered individual. Based on the level of dissimilarity between the two, the discriminator accepts or rejects the target. The tolerated degree of mismatch is predicted by the acceptance threshold model, which assumes adaptive threshold shifts depending on the costs of discrimination errors. Inherent in the model is that rejection (type I) and acceptance (type II) errors are reciprocally related: if one type decreases, the other increases. We studied whether alarm pheromones modulate the acceptance threshold. We exposed Camponotus aethiops ants to formic acid and subsequently measured aggression toward nestmates and nonnestmates. Formic acid induced both more nonnestmate rejection and more nestmate acceptance than a control treatment, thus uncovering an unexpected effect of an alarm pheromone on responses to nestmates. Nestmate discrimination accuracy was improved via a decrease in both types of errors, a result that cannot be explained by a shift in the acceptance threshold. We propose that formic acid increases the amount of information available to the ants, thus decreasing the perceived phenotypic overlap between nestmate and nonnestmate recognition cues. This mechanism for improved discrimination reveals a novel function of alarm pheromones in recognition processes and may have far-reaching implications in our understanding of the modus operandi of recognition systems in general.

Mapping Histological Slice Sequences to the Allen Mouse Brain Atlas Without 3D Reconstruction

Histological brain slices are widely used in neuroscience to study the anatomical organization of neural circuits. Systematic and accurate comparisons of anatomical data from multiple brains, especially from different studies, can benefit tremendously from registering histological slices onto a common reference atlas. Most existing methods rely on an initial reconstruction of the volume before registering it to a reference atlas. Because these slices are prone to distortions during the sectioning process and often sectioned with non-standard angles, reconstruction is challenging and often inaccurate. Here we describe a framework that maps each slice to its corresponding plane in the Allen Mouse Brain Atlas (2015) to build a plane-wise mapping and then perform 2D nonrigid registration to build a pixel-wise mapping. We use the L2 norm of the histogram of oriented gradients difference of two patches as the similarity metric for both steps and a Markov random field formulation that incorporates tissue coherency to compute the nonrigid registration. To fix significantly distorted regions that are misshaped or much smaller than the control grids, we train a context-aggregation network to segment and warp them to their corresponding regions with thin plate spline. We have shown that our method generates results comparable to an expert neuroscientist and is significantly better than reconstruction-first approaches. Code and sample dataset are available at sites.google.com/view/brain-mapping.

Prenatal Neuropathologies in Autism Spectrum Disorder and Intellectual Disability: The Gestation of a Comprehensive Zebrafish Model

Autism spectrum disorder (ASD) and intellectual disability (ID) are neurodevelopmental disorders with overlapping diagnostic behaviors and risk factors. These include embryonic exposure to teratogens and mutations in genes that have important functions prenatally. Animal models, including rodents and zebrafish, have been essential in delineating mechanisms of neuropathology and identifying developmental critical periods, when those mechanisms are most sensitive to disruption. This review focuses on how the developmentally accessible zebrafish is contributing to our understanding of prenatal pathologies that set the stage for later ASD-ID behavioral deficits. We discuss the known factors that contribute prenatally to ASD-ID and the recent use of zebrafish to model deficits in brain morphogenesis and circuit development. We conclude by suggesting that a future challenge in zebrafish ASD-ID modeling will be to bridge prenatal anatomical and physiological pathologies to behavioral deficits later in life.