Neuromodulatory Control of Long-Term Behavioral Patterns and Individuality across Development

Segmentation-free measurement of locomotor frequency in Caenorhabditis elegans using image invariants

An animal's locomotor rate is an important indicator of its motility. In studies of the nematode Caenorhabditis elegans (C. elegans), assays of the frequency of body bending waves have often been used to discern the effects of mutations, drugs, or aging. Traditional manual methods for measuring locomotor frequency are low in throughput and subject to human error. Most current automated methods depend on image segmentation, which requires high image quality and is prone to errors. Here, we describe an algorithm for automated estimation of C. elegans locomotor frequency using image invariants, i.e. shape-based parameters that are independent of object translation, rotation, and scaling. For each video frame, the method calculates a combination of 8 Hu's moment invariants and a set of maximally stable extremal regions (MSER) invariants. The algorithm then calculates the locomotor frequency by computing the autocorrelation of the time sequence of the invariant ensemble. Results of our method show excellent agreement with manual or segmentation-based results over a wide range of frequencies. We show that compared to a segmentation-based method that analyzes a worm's shape and a method based on video covariance, our technique is more robust to low image quality and background noise. We demonstrate the system's capabilities by testing the effects of serotonin and serotonin pathway mutations on C. elegans locomotor frequency.

Mapping the developmental structure of stereotyped and individual-unique behavioral spaces in C. elegans

Developmental patterns of behavior are variably organized in time and among different individuals. However, long-term behavioral diversity was previously studied using pre-defined behavioral parameters, representing a limited fraction of the full individuality structure. Here, we continuously extract ∼1.2 billion body postures of ∼2,200 single C. elegans individuals throughout their full development time to create a complete developmental atlas of stereotyped and individual-unique behavioral spaces. Unsupervised inference of low-dimensional movement modes of each single individual identifies a dynamic developmental trajectory of stereotyped behavioral spaces and exposes unique behavioral trajectories of individuals that deviate from the stereotyped patterns. Moreover, classification of behavioral spaces within tens of neuromodulatory and environmentally perturbed populations shows plasticity in the temporal structures of stereotyped behavior and individuality. These results present a comprehensive atlas of continuous behavioral dynamics across development time and a general framework for unsupervised dissection of shared and unique developmental signatures of behavior.

Drift in Individual Behavioral Phenotype as a Strategy for Unpredictable Worlds

Individuals, even with matched genetics and environment, show substantial phenotypic variability. This variability may be part of a bet-hedging strategy, where populations express a range of phenotypes to ensure survival in unpredictable environments. In addition phenotypic variability between individuals ("bet-hedging"), individuals also show variability in their phenotype across time, even absent external cues. There are few evolutionary theories that explain random shifts in phenotype across an animals life, which we term drift in individual phenotype. We use individuality in locomotor handedness in Drosophila melanogaster to characterize both bet-hedging and drift. We use a continuous circling assay to show that handedness spontaneously changes over timescales ranging from seconds to the lifespan of a fly. We compare the amount of drift and bet-hedging across a number of different fly strains and show independent strain specific differences in bet-hedging and drift. We show manipulation of serotonin changes the rate of drift, indicating a potential circuit substrate controlling drift. We then develop a theoretical framework for assessing the adaptive value of drift, demonstrating that drift may be adaptive for populations subject to selection pressures that fluctuate on timescales similar to the lifespan of an animal. We apply our model to real world environmental signals and find patterns of fluctuations that favor random drift in behavioral phenotype, suggesting that drift may be adaptive under some real world conditions. These results demonstrate that drift plays a role in driving variability in a population and may serve an adaptive role distinct from population level bet-hedging.

Significance Statement

Why do individuals animals spontaneously change their preferences over time? While stable idiosyncratic behavioral preferences have been proposed to help species survive unpredictable environments as part of a bet-hedging strategy, the role of intraindividual shifts in preferences is unclear. Using Drosophila melanogaster , we show the stability of individual preferences is influenced by genetic background and neuromodulation, and is therefore a regulated phenomenon. We use theoretical modeling to show that shifts in preferences may be adaptive to environments that change within an individual's lifespan, including many real world patterns of environmental fluctuations. Together, this work suggests that the stability of individual preferences may affect the survival of species in unpredictable worlds - understanding that may be increasingly important in the face of anthropogenic change.

Automated multimodal imaging of Caenorhabditis elegans behavior in multi-well plates

Assays of behavior in model organisms play an important role in genetic screens, drug testing, and the elucidation of gene-behavior relationships. We have developed an automated, high-throughput imaging and analysis method for assaying behaviors of the nematode C. elegans . We use high-resolution optical imaging to longitudinally record the behaviors of 96 animals at a time in multi-well plates, and computer vision software to quantify the animals' locomotor activity, behavioral states, and egg laying events. To demonstrate the capabilities of our system we used it to examine the role of serotonin in C. elegans behavior. We found that egg-laying events are preceded by a period of reduced locomotion, and that this decline in movement requires serotonin signaling. In addition, we identified novel roles of serotonin receptors SER-1 and SER-7 in regulating the effects of serotonin on egg laying across roaming, dwelling, and quiescent locomotor states. Our system will be useful for performing genetic or chemical screens for modulators of behavior.

Lysergic acid diethylamide induces behavioral changes in Caenorhabditis elegans

Lysergic acid diethylamide (LSD) is a synthetic psychedelic compound with potential therapeutic value for psychiatric disorders. This study aims to establish Caenorhabditis elegans as an in vivo model for examining LSD's effects on locomotor behavior. Our results demonstrate that LSD is absorbed by C. elegans and that the acute treatment reduces animal speed, similar to the role of endogenous serotonin. This response is mediated in part by the serotonergic receptors SER-1 and SER-4. Our findings highlight the potential of this nematode as a new experimental model in psychedelic research.

Accelerated hermaphrodite maturation on male pheromones suggests a general principle of coordination between larval behavior and development

Environment in general and social signals in particular could alter development. In Caenorhabditis elegans, male pheromones hasten development of hermaphrodite larvae. We show that this involves acceleration of growth and both somatic and germline development during the last larval stage (L4). Larvae exposed to male pheromones spend more time in L3 and less in the quiescent period between L3 and L4. This behavioral alteration improves provision in early L4, likely allowing for faster development. Larvae must be exposed to male pheromones in late L3 for behavioral and developmental effects to occur. Latter portions of other larval stages also contain periods of heightened sensitivity to environmental signals. Behavior during the early part of the larval stages is biased toward exploration, whereas later the emphasis shifts to food consumption. We argue that this organization allows assessment of the environment to identify the most suitable patch of resources, followed by acquisition of sufficient nutrition and salient information for the developmental events in the next larval stage. Evidence from other species indicates that such coordination of behavior and development may be a general feature of larval development.

Segmentation-free measurement of locomotor frequency in Caenorhabditis elegans using image invariants

An animal's locomotor rate is an important indicator of its motility. In studies of the nematode C. elegans, assays of the frequency of body bending waves have often been used to discern the effects of mutations, drugs, or aging. Traditional manual methods for measuring locomotor frequency are low in throughput and subject to human error. Most current automated methods depend on image segmentation, which requires high image quality and is prone to errors. Here, we describe an algorithm for automated estimation of C. elegans locomotor frequency using image invariants, i.e., shape-based parameters that are independent of object translation, rotation, and scaling. For each video frame, the method calculates a combination of 8 Hu's moment invariants and a set of Maximally Stable Extremal Regions (MSER) invariants. The algorithm then calculates the locomotor frequency by computing the autocorrelation of the time sequence of the invariant ensemble. Results of our method show excellent agreement with manual or segmentation-based results over a wide range of frequencies. We show that compared to a segmentation-based method that analyzes a worm's shape and a method based on video covariance, our technique is more robust to low image quality and background noise. We demonstrate the system's capabilities by testing the effects of serotonin and serotonin pathway mutations on C. elegans locomotor frequency.

Expansion of learning capacity elicited by interspecific hybridization

Learned behavior, a fundamental adaptive trait in fluctuating environments, is shaped by species-specific constraints. This phenomenon is evident in songbirds, which acquire their species-specific songs through vocal learning. To explore the neurogenetic mechanisms underlying species-specific song learning, we generated F1 hybrid songbirds by crossing Taeniopygia guttata with Aidemosyne modesta. These F1 hybrids demonstrate expanded learning capacities, adeptly mimicking songs from both parental species and other heterospecific songs more extensively than their parental counterparts. Despite the conserved size of brain regions and neuron numbers in the neural circuits for song learning and production, single-cell transcriptomics reveals distinctive transcriptional characteristics in the F1 hybrids, especially in vocal-motor projection neurons. These neurons exhibit enrichment for nonadditively expressed genes, particularly those related to ion channel activity and cell adhesion, which are associated with the degree of song learning among F1 individuals. Our findings provide insights into the emergence of altered learning capabilities through hybridization, linked to cell type-specific transcriptional changes.

Genetic variants that modify neuroendocrine gene expression and foraging behavior of C. elegans

The molecular mechanisms underlying diversity in animal behavior are not well understood. A major experimental challenge is determining the contribution of genetic variants that affect neuronal gene expression to differences in behavioral traits. In Caenorhabditis elegans, the neuroendocrine transforming growth factor-β ligand, DAF-7, regulates diverse behavioral responses to bacterial food and pathogens. The dynamic neuron-specific expression of daf-7 is modulated by environmental and endogenous bacteria-derived cues. Here, we investigated natural variation in the expression of daf-7 from the ASJ pair of chemosensory neurons. We identified common genetic variants in gap-2, encoding a Ras guanosine triphosphatase (GTPase)-activating protein homologous to mammalian synaptic Ras GTPase-activating protein, which modify daf-7 expression cell nonautonomously and promote exploratory foraging behavior in a partially DAF-7-dependent manner. Our data connect natural variation in neuron-specific gene expression to differences in behavior and suggest that genetic variation in neuroendocrine signaling pathways mediating host-microbe interactions may give rise to diversity in animal behavior.

C. elegans foraging as a model for understanding the neuronal basis of decision-making

Animals have evolved to seek, select, and exploit food sources in their environment. Collectively termed foraging, these ubiquitous behaviors are necessary for animal survival. As a foundation for understanding foraging, behavioral ecologists established early theoretical and mathematical frameworks which have been subsequently refined and supported by field and laboratory studies of foraging animals. These simple models sought to explain how animals decide which strategies to employ when locating food, what food items to consume, and when to explore the environment for new food sources. These foraging decisions involve integration of prior experience with multimodal sensory information about the animal's current environment and internal state. We suggest that the nematode Caenorhabditis elegans is well-suited for a high-resolution analysis of complex goal-oriented behaviors such as foraging. We focus our discussion on behavioral studies highlighting C. elegans foraging on bacteria and summarize what is known about the underlying neuronal and molecular pathways. Broadly, we suggest that this simple model system can provide a mechanistic understanding of decision-making and present additional avenues for advancing our understanding of complex behavioral processes.

Ethological computational psychiatry: Challenges and opportunities

Studying the intricacies of individual subjects' moods and cognitive processing over extended periods of time presents a formidable challenge in medicine. While much of systems neuroscience appropriately focuses on the link between neural circuit functions and well-constrained behaviors over short timescales (e.g., trials, hours), many mental health conditions involve complex interactions of mood and cognition that are non-stationary across behavioral contexts and evolve over extended timescales. Here, we discuss opportunities, challenges, and possible future directions in computational psychiatry to quantify non-stationary continuously monitored behaviors. We suggest that this exploratory effort may contribute to a more precision-based approach to treating mental disorders and facilitate a more robust reverse translation across animal species. We conclude with ethical considerations for any field that aims to bridge artificial intelligence and patient monitoring.

Mesolimbic Neural Response Dynamics Predict Future Individual Alcohol Drinking in Mice

BACKGROUND

Individual variability in response to rewarding stimuli is a striking but understudied phenomenon. The mesolimbic dopamine system is critical in encoding the reinforcing properties of both natural reward and alcohol; however, how innate or baseline differences in the response dynamics of this circuit define individual behavior and shape future vulnerability to alcohol remain unknown.

METHODS

Using naturalistic behavioral assays, a voluntary alcohol drinking paradigm, in vivo fiber photometry, in vivo electrophysiology, and chemogenetics, we investigated how differences in mesolimbic neural circuit activity contribute to the individual variability seen in reward processing and, by proxy, alcohol drinking.

RESULTS

We first characterized heterogeneous behavioral and neural responses to natural reward and defined how these baseline responses predicted future individual alcohol-drinking phenotypes in male mice. We then determined spontaneous ventral tegmental area dopamine neuron firing profiles associated with responses to natural reward that predicted alcohol drinking. Using a dual chemogenetic approach, we mimicked specific mesolimbic dopamine neuron firing activity before or during voluntary alcohol drinking to link unique neurophysiological profiles to individual phenotype. We show that hyperdopaminergic individuals exhibit a lower neuronal response to both natural reward and alcohol that predicts lower levels of alcohol consumption in the future.

CONCLUSIONS

These findings reveal unique, circuit-specific neural signatures that predict future individual vulnerability or resistance to alcohol and expand the current knowledge base on how some individuals are able to titrate their alcohol consumption whereas others go on to engage in unhealthy alcohol-drinking behaviors.

A molecular atlas of adult C. elegans motor neurons reveals ancient diversity delineated by conserved transcription factor codes

Motor neurons (MNs) constitute an ancient cell type targeted by multiple adult-onset diseases. It is therefore important to define the molecular makeup of adult MNs in animal models and extract organizing principles. Here, we generate a comprehensive molecular atlas of adult Caenorhabditis elegans MNs and a searchable database. Single-cell RNA sequencing of 13,200 cells reveals that ventral nerve cord MNs cluster into 29 molecularly distinct subclasses. Extending C. elegans Neuronal Gene Expression Map and Network (CeNGEN) findings, all MN subclasses are delineated by distinct expression codes of either neuropeptide or transcription factor gene families. Strikingly, combinatorial codes of homeodomain transcription factor genes succinctly delineate adult MN diversity in both C. elegans and mice. Further, molecularly defined MN subclasses in C. elegans display distinct patterns of connectivity. Hence, our study couples the connectivity map of the C. elegans motor circuit with a molecular atlas of its constituent MNs and uncovers organizing principles and conserved molecular codes of adult MN diversity.

Sperm function is required for suppressing locomotor activity of C. elegans hermaphrodites

Sex differences in sex-shared behavior are common across various species. During mating, males transfer sperm and seminal fluid to females, which can affect female behavior. Sperm can be stored in the female reproductive tract for extended periods of time and used to fertilize eggs. However, the role of either sperm or embryo production in regulating female behavior is poorly understood. In the androdioecious nematode C. elegans, hermaphrodites produce both oocytes and sperm, enabling them to self-fertilize or mate with males. Hermaphrodites exhibit less locomotor activity compared to males, indicating sex difference in behavioral regulation. In this study, mutants defective in the sperm production and function were examined to investigate the role of sperm function in the regulation of locomotor behavior. Infertile hermaphrodites exhibited increased locomotor activity, which was suppressed after mating with fertile males. The results suggest that sperm, seminal fluid, or the presence of embryos are detected by hermaphrodites, leading to a reduction in locomotor activity. Additionally, females of closely related gonochoristic species, C. remanei and C. brenneri, exhibited reduced locomotor activity after mating. The regulation of locomotion by sperm function may be an adaptive mechanism that enables hermaphrodites lacking sperm or embryo to search for mates and allow females to cease their search for mates after mating.

A predisposed motor bias shapes individuality in vocal learning

The development of individuality during learned behavior is a common trait observed across animal species; however, the underlying biological mechanisms remain understood. Similar to human speech, songbirds develop individually unique songs with species-specific traits through vocal learning. In this study, we investigate the developmental and molecular mechanisms underlying individuality in vocal learning by utilizing F1 hybrid songbirds (Taeniopygia guttata cross with Taeniopygia bichenovii), taking an integrating approach combining experimentally controlled systematic song tutoring, unbiased discriminant analysis of song features, and single-cell transcriptomics. When tutoring with songs from both parental species, F1 hybrid individuals exhibit evident diversity in their acquired songs. Approximately 30% of F1 hybrids selectively learn either song of the two parental species, while others develop merged songs that combine traits from both species. Vocal acoustic biases during vocal babbling initially appear as individual differences in songs among F1 juveniles and are maintained through the sensitive period of song vocal learning. These vocal acoustic biases emerge independently of the initial auditory experience of hearing the biological father's and passive tutored songs. We identify individual differences in transcriptional signatures in a subset of cell types, including the glutamatergic neurons projecting from the cortical vocal output nucleus to the hypoglossal nuclei, which are associated with variations of vocal acoustic features. These findings suggest that a genetically predisposed vocal motor bias serves as the initial origin of individual variation in vocal learning, influencing learning constraints and preferences.

Sensory neurons couple arousal and foraging decisions in Caenorhabditis elegans

Foraging animals optimize feeding decisions by adjusting both common and rare behavioral patterns. Here, we characterize the relationship between an animal's arousal state and a rare decision to leave a patch of bacterial food. Using long-term tracking and behavioral state classification, we find that food leaving decisions in Caenorhabditis elegans are coupled to arousal states across multiple timescales. Leaving emerges probabilistically over minutes from the high arousal roaming state, but is suppressed during the low arousal dwelling state. Immediately before leaving, animals have a brief acceleration in speed that appears as a characteristic signature of this behavioral motif. Neuromodulatory mutants and optogenetic manipulations that increase roaming have a coupled increase in leaving rates, and similarly acute manipulations that inhibit feeding induce both roaming and leaving. By contrast, inactivating a set of chemosensory neurons that depend on the cGMP-gated transduction channel TAX-4 uncouples roaming and leaving dynamics. In addition, tax-4-expressing sensory neurons promote lawn-leaving behaviors that are elicited by feeding inhibition. Our results indicate that sensory neurons responsive to both internal and external cues play an integrative role in arousal and foraging decisions.

Distinct neurexin isoforms cooperate to initiate and maintain foraging activity

Neurexins are synaptic adhesion molecules that play diverse roles in synaptic development, function, maintenance, and plasticity. Neurexin genes have been associated with changes in human behavior, where variants in NRXN1 are associated with autism, schizophrenia, and Tourette syndrome. While NRXN1, NRXN2, and NRXN3 all encode major α and β isoforms, NRXN1 uniquely encodes a γ isoform, for which mechanistic roles in behavior have yet to be defined. Here, we show that both α and γ isoforms of neurexin/nrx-1 are required for the C. elegans behavioral response to food deprivation, a sustained period of hyperactivity upon food loss. We find that the γ isoform regulates initiation and the α isoform regulates maintenance of the behavioral response to food deprivation, demonstrating cooperative function of multiple nrx-1 isoforms in regulating a sustained behavior. The γ isoform alters monoamine signaling via octopamine, relies on specific expression of NRX-1 isoforms throughout the relevant circuit, and is independent of neuroligin/nlg-1, the canonical trans-synaptic partner of nrx-1. The α isoform regulates the pre-synaptic structure of the octopamine producing RIC neuron and its maintenance role is conditional on neuroligin/nlg-1. Collectively, these results demonstrate that neurexin isoforms can have separate behavioral roles and act cooperatively across neuronal circuits to modify behavior, highlighting the need to directly analyze and consider all isoforms when defining the contribution of neurexins to behavior.

Neural signal propagation atlas of Caenorhabditis elegans

Establishing how neural function emerges from network properties is a fundamental problem in neuroscience1. Here, to better understand the relationship between the structure and the function of a nervous system, we systematically measure signal propagation in 23,433 pairs of neurons across the head of the nematode Caenorhabditis elegans by direct optogenetic activation and simultaneous whole-brain calcium imaging. We measure the sign (excitatory or inhibitory), strength, temporal properties and causal direction of signal propagation between these neurons to create a functional atlas. We find that signal propagation differs from model predictions that are based on anatomy. Using mutants, we show that extrasynaptic signalling not visible from anatomy contributes to this difference. We identify many instances of dense-core-vesicle-dependent signalling, including on timescales of less than a second, that evoke acute calcium transients-often where no direct wired connection exists but where relevant neuropeptides and receptors are expressed. We propose that, in such cases, extrasynaptically released neuropeptides serve a similar function to that of classical neurotransmitters. Finally, our measured signal propagation atlas better predicts the neural dynamics of spontaneous activity than do models based on anatomy. We conclude that both synaptic and extrasynaptic signalling drive neural dynamics on short timescales, and that measurements of evoked signal propagation are crucial for interpreting neural function.

Chemical cognition: chemoconnectomics and convergent evolution of integrative systems in animals

Neurons underpin cognition in animals. However, the roots of animal cognition are elusive from both mechanistic and evolutionary standpoints. Two conceptual frameworks both highlight and promise to address these challenges. First, we discuss evidence that animal neural and other integrative systems evolved more than once (convergent evolution) within basal metazoan lineages, giving us unique experiments by Nature for future studies. The most remarkable examples are neural systems in ctenophores and neuroid-like systems in placozoans and sponges. Second, in addition to classical synaptic wiring, a chemical connectome mediated by hundreds of signal molecules operates in tandem with neurons and is the most information-rich source of emerging properties and adaptability. The major gap-dynamic, multifunctional chemical micro-environments in nervous systems-is not understood well. Thus, novel tools and information are needed to establish mechanistic links between orchestrated, yet cell-specific, volume transmission and behaviors. Uniting what we call chemoconnectomics and analyses of the cellular bases of behavior in basal metazoan lineages arguably would form the foundation for deciphering the origins and early evolution of elementary cognition and intelligence.

Anatomical restructuring of a lateralized neural circuit during associative learning by asymmetric insulin signaling

Studies of neuronal connectivity in model organisms, i.e., of their connectomes, have been instrumental in dissecting the structure-function relationship of nervous systems. However, the limited sample size of these studies has impeded analyses into how variation of connectivity across populations may influence circuit architecture and behavior. Moreover, little is known about how experiences induce changes in circuit architecture. Here, we show that an asymmetric salt-sensing circuit in the nematode Caenorhabditis elegans exhibits variation that predicts the animals' salt preferences and undergoes restructuring during salt associative learning. Naive worms memorize and prefer the salt concentration they experience in the presence of food through a left-biased neural network architecture. However, animals conditioned at elevated salt concentrations change this left-biased network to a right-biased network. This change in circuit architecture occurs through the addition of new synapses in response to asymmetric, paracrine insulin signaling. Therefore, experience-dependent changes in an animal's neural connectome are induced by insulin signaling and are fundamental to learning and behavior.

Heterogeneous receptor expression underlies non-uniform peptidergic modulation of olfaction in Drosophila

Sensory systems are dynamically adjusted according to the animal's ongoing needs by neuromodulators, such as neuropeptides. Neuropeptides are often widely-distributed throughout sensory networks, but it is unclear whether such neuropeptides uniformly modulate network activity. Here, we leverage the Drosophila antennal lobe (AL) to resolve whether myoinhibitory peptide (MIP) uniformly modulates AL processing. Despite being uniformly distributed across the AL, MIP decreases olfactory input to some glomeruli, while increasing olfactory input to other glomeruli. We reveal that a heterogeneous ensemble of local interneurons (LNs) are the sole source of AL MIP, and show that differential expression of the inhibitory MIP receptor across glomeruli allows MIP to act on distinct intraglomerular substrates. Our findings demonstrate how even a seemingly simple case of modulation can have complex consequences on network processing by acting non-uniformly within different components of the overall network.

Periods of environmental sensitivity couple larval behavior and development

The typical life cycle in most animal phyla includes a larval period that bridges embryogenesis and adulthood1. Despite the great diversity of larval forms, all larvae grow, acquire adult morphology and function, while navigating their habitats to obtain resources necessary for development. How larval development is coordinated with behavior remains substantially unclear. Here, we describe features of the iterative organization of larval stages that serve to assess the environment and procure resources prior to costly developmental commitments. We found that male-excreted pheromones accelerate2-4 the onset of adulthood in C. elegans hermaphrodites by coordinately advancing multiple developmental events and growth during the last larval stage. The larvae are sensitive to the accelerating male pheromones only at the end of the penultimate larval stage, just before the acceleration begins. Other larval stages also contain windows of sensitivity to environmental inputs. Importantly, behaviors associated with search and consumption of food are distinct between early and late portions of larval stages. We infer that each larval stage in C. elegans is subdivided into two epochs: A) global assessment of the environment to identify the most suitable patch and B) consumption of sufficient food and acquisition of salient information for developmental events in the next stage. We predict that in larvae of other species behavior is also divided into distinct epochs optimized either for assessing the habitat or obtaining the resources. Thus, a major role of larval behavior is to coordinate the orderly progression of development in variable environments.

A molecular atlas of adult C. elegans motor neurons reveals ancient diversity delineated by conserved transcription factor codes

Motor neurons (MNs) constitute an ancient cell type targeted by multiple adult-onset diseases. It is therefore important to define the molecular makeup of adult MNs in animal models and extract organizing principles. Here, we generated a comprehensive molecular atlas of adult Caenorhabditis elegans MNs and a searchable database (http://celegans.spinalcordatlas.org). Single-cell RNA-sequencing of 13,200 cells revealed that ventral nerve cord MNs cluster into 29 molecularly distinct subclasses. All subclasses are delineated by unique expression codes of either neuropeptide or transcription factor gene families. Strikingly, we found that combinatorial codes of homeodomain transcription factor genes define adult MN diversity both in C. elegans and mice. Further, molecularly defined MN subclasses in C. elegans display distinct patterns of connectivity. Hence, our study couples the connectivity map of the C. elegans motor circuit with a molecular atlas of its constituent MNs, and uncovers organizing principles and conserved molecular codes of adult MN diversity.

Continuous, long-term crawling behavior characterized by a robotic transport system

Detailed descriptions of behavior provide critical insight into the structure and function of nervous systems. In Drosophila larvae and many other systems, short behavioral experiments have been successful in characterizing rapid responses to a range of stimuli at the population level. However, the lack of long-term continuous observation makes it difficult to dissect comprehensive behavioral dynamics of individual animals and how behavior (and therefore the nervous system) develops over time. To allow for long-term continuous observations in individual fly larvae, we have engineered a robotic instrument that automatically tracks and transports larvae throughout an arena. The flexibility and reliability of its design enables controlled stimulus delivery and continuous measurement over developmental time scales, yielding an unprecedented level of detailed locomotion data. We utilize the new system's capabilities to perform continuous observation of exploratory search behavior over a duration of 6 hr with and without a thermal gradient present, and in a single larva for over 30 hr. Long-term free-roaming behavior and analogous short-term experiments show similar dynamics that take place at the beginning of each experiment. Finally, characterization of larval thermotaxis in individuals reveals a bimodal distribution in navigation efficiency, identifying distinct phenotypes that are obfuscated when only analyzing population averages.

Study of Alerting, Orienting, and Executive Control Attentional Networks in Bilingual and Monolingual Primary School Children: The Role of Socioeconomic Status

For decades, researchers have suggested the existence of a bilingual cognitive advantage, especially in tasks involving executive functions such as inhibition, shifting, and updating. Recently, an increasing number of studies have questioned whether bilingualism results in a change in executive functions, highlighting conflicting data published in the literature. The present study compared the performance of third-, fourth-, and fifth-grade bilingual and monolingual children on attentional and cognitive tasks. The participants were 61 monolingual and 74 bilingual children (M = 114.6 months; SD = 8.48 months) who were tested on two versions of the attention network task (ANT), with and without social stimuli, as well as tests investigating working memory, short-term memory, narrative memory, and receptive vocabulary. Data on families' socioeconomic status and children's reasoning abilities were also collected. The results showed that bilingualism and socioeconomic status affected attentional networks in tasks involving social stimuli. In tasks involving non-social stimuli, socioeconomic status only affected the alerting and executive conflict networks. Consistent with the literature, a positive relationship emerged between socioeconomic status and executive control in the context of social stimuli, and a negative relationship emerged between socioeconomic status and the alerting network in the context of non-social stimuli. Interestingly, neither socioeconomic status nor social attentional networks correlated with working memory. Therefore, although more investigations are required, the results suggest that differences in social contexts mainly affect attentional functions.

Multisite regulation integrates multimodal context in sensory circuits to control persistent behavioral states in C. elegans

Maintaining or shifting between behavioral states according to context is essential for animals to implement fitness-promoting strategies. How the integration of internal state, past experience and sensory inputs orchestrates persistent multidimensional behavioral changes remains poorly understood. Here, we show that C. elegans integrates environmental temperature and food availability over different timescales to engage in persistent dwelling, scanning, global or glocal search strategies matching thermoregulatory and feeding needs. Transition between states, in each case, involves regulating multiple processes including AFD or FLP tonic sensory neurons activity, neuropeptide expression and downstream circuit responsiveness. State-specific FLP-6 or FLP-5 neuropeptide signaling acts on a distributed set of inhibitory GPCR(s) to promote scanning or glocal search, respectively, bypassing dopamine and glutamate-dependent behavioral state control. Integration of multimodal context via multisite regulation in sensory circuits might represent a conserved regulatory logic for a flexible prioritization on the valence of multiple inputs when operating persistent behavioral state transitions.

Development under predation risk increases serotonin-signaling, variability of turning behavior and survival in adult fruit flies Drosophila melanogaster

The development of high-throughput behavioral assays, where numerous individual animals can be analyzed in various experimental conditions, has facilitated the study of animal personality. Previous research showed that isogenic Drosophila melanogaster flies exhibit striking individual non-heritable locomotor handedness. The variability of this trait, i.e., the predictability of left-right turn biases, varies across genotypes and under the influence of neural activity in specific circuits. This suggests that the brain can dynamically regulate the extent of animal personality. It has been recently shown that predators can induce changes in prey phenotypes via lethal or non-lethal effects affecting the serotonergic signaling system. In this study, we tested whether fruit flies grown with predators exhibit higher variability/lower predictability in their turning behavior and higher survival than those grown with no predators in their environment. We confirmed these predictions and found that both effects were blocked when flies were fed an inhibitor (αMW) of serotonin synthesis. The results of this study demonstrate a negative association between the unpredictability of turning behavior of fruit flies and the hunting success of their predators. We also show that the neurotransmitter serotonin controls predator-induced changes in the turning variability of fruit flies, regulating the dynamic control of behavioral predictability.

Tonic activity in lateral habenula neurons acts as a neutral valence brake on reward-seeking behavior

Survival requires both the ability to persistently pursue goals and the ability to determine when it is time to stop, an adaptive balance of perseverance and disengagement. Neural activity in the lateral habenula (LHb) has been linked to negative valence, but its role in regulating the balance between engaged reward seeking and disengaged behavioral states remains unclear. Here, we show that LHb neural activity is tonically elevated during minutes-long periods of disengagement from reward-seeking behavior, both when due to repeated reward omission (negative valence) and when sufficient reward has been consumed (positive valence). Furthermore, we show that LHb inhibition extends ongoing reward-seeking behavioral states but does not prompt task re-engagement. We find no evidence for similar tonic activity changes in ventral tegmental area dopamine neurons. Our findings support a framework in which tonic activity in LHb neurons suppresses engagement in reward-seeking behavior in response to both negatively and positively valenced factors.

Multisensory Integration in Caenorhabditis elegans in Comparison to Mammals

Multisensory integration refers to sensory inputs from different sensory modalities being processed simultaneously to produce a unitary output. Surrounded by stimuli from multiple modalities, animals utilize multisensory integration to form a coherent and robust representation of the complex environment. Even though multisensory integration is fundamentally essential for animal life, our understanding of the underlying mechanisms, especially at the molecular, synaptic and circuit levels, remains poorly understood. The study of sensory perception in Caenorhabditis elegans has begun to fill this gap. We have gained a considerable amount of insight into the general principles of sensory neurobiology owing to C. elegans’ highly sensitive perceptions, relatively simple nervous system, ample genetic tools and completely mapped neural connectome. Many interesting paradigms of multisensory integration have been characterized in C. elegans, for which input convergence occurs at the sensory neuron or the interneuron level. In this narrative review, we describe some representative cases of multisensory integration in C. elegans, summarize the underlying mechanisms and compare them with those in mammalian systems. Despite the differences, we believe C. elegans is able to provide unique insights into how processing and integrating multisensory inputs can generate flexible and adaptive behaviors. With the emergence of whole brain imaging, the ability of C. elegans to monitor nearly the entire nervous system may be crucial for understanding the function of the brain as a whole.

A negative feedback loop in the GPCR pathway underlies efficient coding of external stimuli

Efficient navigation based on chemical cues is an essential feature shared by all animals. These cues may be encountered in complex spatiotemporal patterns and with orders of magnitude varying intensities. Nevertheless, sensory neurons accurately extract the relevant information from such perplexing signals. Here, we show how a single sensory neuron in Caenorhabditis elegans animals can cell-autonomously encode complex stimulus patterns composed of instantaneous sharp changes and of slowly changing continuous gradients. This encoding relies on a simple negative feedback in the G-protein-coupled receptor (GPCR) signaling pathway in which TAX-6/Calcineurin plays a key role in mediating the feedback inhibition. This negative feedback supports several important coding features that underlie an efficient navigation strategy, including exact adaptation and adaptation to the magnitude of the gradient's first derivative. A simple mathematical model explains the fine neural dynamics of both wild-type and tax-6 mutant animals, further highlighting how the calcium-dependent activity of TAX-6/Calcineurin dictates GPCR inhibition and response dynamics. As GPCRs are ubiquitously expressed in all sensory neurons, this mechanism may be a general solution for efficient cell-autonomous coding of external stimuli.

The emergence and influence of internal states

Animal behavior is shaped by a variety of "internal states"-partially hidden variables that profoundly shape perception, cognition, and action. The neural basis of internal states, such as fear, arousal, hunger, motivation, aggression, and many others, is a prominent focus of research efforts across animal phyla. Internal states can be inferred from changes in behavior, physiology, and neural dynamics and are characterized by properties such as pleiotropy, persistence, scalability, generalizability, and valence. To date, it remains unclear how internal states and their properties are generated by nervous systems. Here, we review recent progress, which has been driven by advances in behavioral quantification, cellular manipulations, and neural population recordings. We synthesize research implicating defined subsets of state-inducing cell types, widespread changes in neural activity, and neuromodulation in the formation and updating of internal states. In addition to highlighting the significance of these findings, our review advocates for new approaches to clarify the underpinnings of internal brain states across the animal kingdom.

New insights from small rhythmic circuits

Small rhythmic circuits, such as those found in invertebrates, have provided fundamental insights into how circuit dynamics depend on individual neuronal and synaptic properties. Degenerate circuits are those with different network parameters and similar behavior. New work on degenerate circuits and their modulation illustrates some of the rules that help maintain stable and robust circuit function despite environmental perturbations. Advances in neuropeptide isolation and identification provide enhanced understanding of the neuromodulation of circuits for behavior. The advent of molecular studies of mRNA expression provides new insight into animal-to-animal variability and the homeostatic regulation of excitability in neurons and networks.

Stereotyped behavioral maturation and rhythmic quiescence in C.elegans embryos

Systematic analysis of rich behavioral recordings is being used to uncover how circuits encode complex behaviors. Here, we apply this approach to embryos. What are the first embryonic behaviors and how do they evolve as early neurodevelopment ensues? To address these questions, we present a systematic description of behavioral maturation for Caenorhabditis elegans embryos. Posture libraries were built using a genetically encoded motion capture suit imaged with light-sheet microscopy and annotated using custom tracking software. Analysis of cell trajectories, postures, and behavioral motifs revealed a stereotyped developmental progression. Early movement is dominated by flipping between dorsal and ventral coiling, which gradually slows into a period of reduced motility. Late-stage embryos exhibit sinusoidal waves of dorsoventral bends, prolonged bouts of directed motion, and a rhythmic pattern of pausing, which we designate slow wave twitch (SWT). Synaptic transmission is required for late-stage motion but not for early flipping nor the intervening inactive phase. A high-throughput behavioral assay and calcium imaging revealed that SWT is elicited by the rhythmic activity of a quiescence-promoting neuron (RIS). Similar periodic quiescent states are seen prenatally in diverse animals and may play an important role in promoting normal developmental outcomes.

Precise Quantification of Behavioral Individuality From 80 Million Decisions Across 183,000 Flies

Individual animals behave differently from each other. This variability is a component of personality and arises even when genetics and environment are held constant. Discovering the biological mechanisms underlying behavioral variability depends on efficiently measuring individual behavioral bias, a requirement that is facilitated by automated, high-throughput experiments. We compiled a large data set of individual locomotor behavior measures, acquired from over 183,000 fruit flies walking in Y-shaped mazes. With this data set we first conducted a "computational ethology natural history" study to quantify the distribution of individual behavioral biases with unprecedented precision and examine correlations between behavioral measures with high power. We discovered a slight, but highly significant, left-bias in spontaneous locomotor decision-making. We then used the data to evaluate standing hypotheses about biological mechanisms affecting behavioral variability, specifically: the neuromodulator serotonin and its precursor transporter, heterogametic sex, and temperature. We found a variety of significant effects associated with each of these mechanisms that were behavior-dependent. This indicates that the relationship between biological mechanisms and behavioral variability may be highly context dependent. Going forward, automation of behavioral experiments will likely be essential in teasing out the complex causality of individuality.

Dynamic functional connectivity in the static connectome of Caenorhabditis elegans

A hallmark of adaptive behavior is the ability to flexibly respond to sensory cues. To understand how neural circuits implement this flexibility, it is critical to resolve how a static anatomical connectome can be modulated such that functional connectivity in the network can be dynamically regulated. Here, we review recent work in the roundworm Caenorhabditis elegans on this topic. EM studies have mapped anatomical connectomes of many C. elegans animals, highlighting the level of stereotypy in the anatomical network. Brain-wide calcium imaging and studies of specified neural circuits have uncovered striking flexibility in the functional coupling of neurons. The coupling between neurons is controlled by neuromodulators that act over long timescales. This gives rise to persistent behavioral states that animals switch between, allowing them to generate adaptive behavioral responses across environmental conditions. Thus, the dynamic coupling of neurons enables multiple behavioral states to be encoded in a physically stereotyped connectome.

Deep learning for robust and flexible tracking in behavioral studies for C. elegans

Robust and accurate behavioral tracking is essential for ethological studies. Common methods for tracking and extracting behavior rely on user adjusted heuristics that can significantly vary across different individuals, environments, and experimental conditions. As a result, they are difficult to implement in large-scale behavioral studies with complex, heterogenous environmental conditions. Recently developed deep-learning methods for object recognition such as Faster R-CNN have advantages in their speed, accuracy, and robustness. Here, we show that Faster R-CNN can be employed for identification and detection of Caenorhabditis elegans in a variety of life stages in complex environments. We applied the algorithm to track animal speeds during development, fecundity rates and spatial distribution in reproductive adults, and behavioral decline in aging populations. By doing so, we demonstrate the flexibility, speed, and scalability of Faster R-CNN across a variety of experimental conditions, illustrating its generalized use for future large-scale behavioral studies.

Behavioral Neuroscience in the Era of Genomics: Tools and Lessons for Analyzing High-Dimensional Datasets

Behavioral neuroscience underwent a technology-driven revolution with the emergence of machine-vision and machine-learning technologies. These technological advances facilitated the generation of high-resolution, high-throughput capture and analysis of complex behaviors. Therefore, behavioral neuroscience is becoming a data-rich field. While behavioral researchers use advanced computational tools to analyze the resulting datasets, the search for robust and standardized analysis tools is still ongoing. At the same time, the field of genomics exploded with a plethora of technologies which enabled the generation of massive datasets. This growth of genomics data drove the emergence of powerful computational approaches to analyze these data. Here, we discuss the composition of a large behavioral dataset, and the differences and similarities between behavioral and genomics data. We then give examples of genomics-related tools that might be of use for behavioral analysis and discuss concepts that might emerge when considering the two fields together.

Megapixel camera arrays enable high-resolution animal tracking in multiwell plates

Tracking small laboratory animals such as flies, fish, and worms is used for phenotyping in neuroscience, genetics, disease modelling, and drug discovery. An imaging system with sufficient throughput and spatiotemporal resolution would be capable of imaging a large number of animals, estimating their pose, and quantifying detailed behavioural differences at a scale where hundreds of treatments could be tested simultaneously. Here we report an array of six 12-megapixel cameras that record all the wells of a 96-well plate with sufficient resolution to estimate the pose of C. elegans worms and to extract high-dimensional phenotypic fingerprints. We use the system to study behavioural variability across wild isolates, the sensitisation of worms to repeated blue light stimulation, the phenotypes of worm disease models, and worms' behavioural responses to drug treatment. Because the system is compatible with standard multiwell plates, it makes computational ethological approaches accessible in existing high-throughput pipelines.

Social Determinants of Inter-Individual Variability and Vulnerability: The Role of Dopamine

Individuals differ in their traits and preferences, which shape their interactions, their prospects for survival and their susceptibility to diseases. These correlations are well documented, yet the neurophysiological mechanisms underlying the emergence of distinct personalities and their relation to vulnerability to diseases are poorly understood. Social ties, in particular, are thought to be major modulators of personality traits and psychiatric vulnerability, yet the majority of neuroscience studies are performed on rodents in socially impoverished conditions. Rodent micro-society paradigms are therefore key experimental paradigms to understand how social life generates diversity by shaping individual traits. Dopamine circuitry is implicated at the interface between social life experiences, the expression of essential traits, and the emergence of pathologies, thus proving a possible mechanism to link these three concepts at a neuromodulatory level. Evaluating inter-individual variability in automated social testing environments shows great promise for improving our understanding of the link between social life, personality, and precision psychiatry – as well as elucidating the underlying neurophysiological mechanisms.

High temporal resolution measurements of movement reveal novel early-life physiological decline in C. elegans

Age-related physiological changes are most notable and best-studied late in life, while the nature of aging in early- or middle-aged individuals has not been explored as thoroughly. In C. elegans, many studies of movement vs. age generally focus on three distinct phases: sustained, youthful movement; onset of rapidly progressing impairment; and gross immobility. We investigated whether this first period of early-life adult movement is a sustained “healthy” level of high function followed by a discrete “movement catastrophe”—or whether there are early-life changes in movement that precede future physiological declines. To determine how movement varies during early adult life, we followed isolated individuals throughout life with a previously unachieved combination of duration and temporal resolution. By tracking individuals across the first six days of adulthood, we observed declines in movement starting as early as the first two days of adult life, as well as high interindividual variability in total daily movement. These findings suggest that movement is a highly dynamic behavior early in life, and that factors driving movement decline may begin acting as early as the first day of adulthood. Using simulation studies based on acquired data, we suggest that too-infrequent sampling in common movement assays limits observation of early-adult changes in motility, and we propose feasible strategies and a framework for designing assays with increased sensitivity for early movement declines.

Behavior Individuality: A Focus on Drosophila melanogaster

Among individuals, behavioral differences result from the well-known interplay of nature and nurture. Minute differences in the genetic code can lead to differential gene expression and function, dramatically affecting developmental processes and adult behavior. Environmental factors, epigenetic modifications, and gene expression and function are responsible for generating stochastic behaviors. In the last decade, the advent of high-throughput sequencing has facilitated studying the genetic basis of behavior and individuality. We can now study the genomes of multiple individuals and infer which genetic variations might be responsible for the observed behavior. In addition, the development of high-throughput behavioral paradigms, where multiple isogenic animals can be analyzed in various environmental conditions, has again facilitated the study of the influence of genetic and environmental variations in animal personality. Mainly, Drosophila melanogaster has been the focus of a great effort to understand how inter-individual behavioral differences emerge. The possibility of using large numbers of animals, isogenic populations, and the possibility of modifying neuronal function has made it an ideal model to search for the origins of individuality. In the present review, we will focus on the recent findings that try to shed light on the emergence of individuality with a particular interest in D. melanogaster.

A Brief History of Wires in the Brain

Metaphors have formed a significant part of the development of neuroscience, often linked with technology. A metaphor that has been widely used for the past two centuries is that of the nervous system being like wires, either as a telegraph system or telephone exchange, or, more recently, in the more abstract metaphor of a wiring diagram. The entry of these terms into scientific writing is traced, together with the insights provided by these metaphors, in particular in relation to recent developments in the study of connectomes. Finally, the place of the wiring diagram as a modern version of Leibniz’s “mill” argument is described, as a way of exploring the limits of what insight the metaphor can provide

Neuromodulation and Individuality

Within populations, individuals show a variety of behavioral preferences, even in the absence of genetic or environmental variability. Neuromodulators affect these idiosyncratic preferences in a wide range of systems, however, the mechanism(s) by which they do so is unclear. I review the evidence supporting three broad mechanisms by which neuromodulators might affect variability in idiosyncratic behavioral preference: by being a source of variability directly upstream of behavior, by affecting the behavioral output of a circuit in a way that masks or accentuates underlying variability in that circuit, and by driving plasticity in circuits leading to either homeostatic convergence toward a given behavior or divergence from a developmental setpoint. I find evidence for each of these mechanisms and propose future directions to further understand the complex interplay between individual variability and neuromodulators.

Environmental and Molecular Modulation of Motor Individuality in Larval Zebrafish

Innate behavioral biases such as human handedness are a ubiquitous form of inter-individual variation that are not strictly hardwired into the genome and are influenced by diverse internal and external cues. Yet, genetic and environmental factors modulating behavioral variation remain poorly understood, especially in vertebrates. To identify genetic and environmental factors that influence behavioral variation, we take advantage of larval zebrafish light-search behavior. During light-search, individuals preferentially turn in leftward or rightward loops, in which directional bias is sustained and non-heritable. Our previous work has shown that bias is maintained by a habenula-rostral PT circuit and genes associated with Notch signaling. Here we use a medium-throughput recording strategy and unbiased analysis to show that significant individual to individual variation exists in wildtype larval zebrafish turning preference. We classify stable left, right, and unbiased turning types, with most individuals exhibiting a directional preference. We show unbiased behavior is not due to a loss of photo-responsiveness but reduced persistence in same-direction turning. Raising larvae at elevated temperature selectively reduces the leftward turning type and impacts rostral PT neurons, specifically. Exposure to conspecifics, variable salinity, environmental enrichment, and physical disturbance does not significantly impact inter-individual turning bias. Pharmacological manipulation of Notch signaling disrupts habenula development and turn bias individuality in a dose dependent manner, establishing a direct role of Notch signaling. Last, a mutant allele of a known Notch pathway affecter gene, gsx2, disrupts turn bias individuality, implicating that brain regions independent of the previously established habenula-rostral PT likely contribute to inter-individual variation. These results establish that larval zebrafish is a powerful vertebrate model for inter-individual variation with established neural targets showing sensitivity to specific environmental and gene signaling disruptions. Our results provide new insight into how variation is generated in the vertebrate nervous system.

Early childhood attachment stability and change: a meta-analysis

Examining degrees of stability in attachment throughout early childhood is important for understanding developmental pathways and for informing intervention. Updating and building upon all prior meta-analyses, this study aimed to determine levels of stability in all forms of attachment classifications across early childhood. Attachment stability was assessed between three developmental epochs within early childhood: infancy, toddlerhood, and preschool/early school. To ensure data homogeneity, only studies that assessed attachment with methods based on the strange situation procedure were included. Results indicate moderate levels of stability at both the four-way (secure, avoidant, resistant, and disorganised; κ = 0.23) and secure/insecure (r = 0.28) levels of assessment. Meta-regression analysis indicated security to be the most stable attachment organisation. This study also found evidence for publication bias, highlighting a preference for the publication of significant findings.

Chronic nicotine increases midbrain dopamine neuron activity and biases individual strategies towards reduced exploration in mice

Long-term exposure to nicotine alters brain circuits and induces profound changes in decision-making strategies, affecting behaviors both related and unrelated to drug seeking and consumption. Using an intracranial self-stimulation reward-based foraging task, we investigated in mice the impact of chronic nicotine on midbrain dopamine neuron activity and its consequence on the trade-off between exploitation and exploration. Model-based and archetypal analysis revealed substantial inter-individual variability in decision-making strategies, with mice passively exposed to nicotine shifting toward a more exploitative profile compared to non-exposed animals. We then mimicked the effect of chronic nicotine on the tonic activity of dopamine neurons using optogenetics, and found that photo-stimulated mice adopted a behavioral phenotype similar to that of mice exposed to chronic nicotine. Our results reveal a key role of tonic midbrain dopamine in the exploration/exploitation trade-off and highlight a potential mechanism by which nicotine affects the exploration/exploitation balance and decision-making.

The structure of behavioral variation within a genotype

Individual animals vary in their behaviors. This is true even when they share the same genotype and were reared in the same environment. Clusters of covarying behaviors constitute behavioral syndromes, and an individual’s position along such axes of covariation is a representation of their personality. Despite these conceptual frameworks, the structure of behavioral covariation within a genotype is essentially uncharacterized and its mechanistic origins unknown. Passing hundreds of inbred Drosophila individuals through an experimental pipeline that captured hundreds of behavioral measures, we found sparse but significant correlations among small sets of behaviors. Thus, the space of behavioral variation has many independent dimensions. Manipulating the physiology of the brain, and specific neural populations, altered specific correlations. We also observed that variation in gene expression can predict an individual’s position on some behavioral axes. This work represents the first steps in understanding the biological mechanisms determining the structure of behavioral variation within a genotype.

Single pixel imaging at megahertz switching rates via cyclic Hadamard masks

Optical imaging is commonly performed with either a camera and wide-field illumination or with a single detector and a scanning collimated beam; unfortunately, these options do not exist at all wavelengths. Single-pixel imaging offers an alternative that can be performed with a single detector and wide-field illumination, potentially enabling imaging applications in which the detection and illumination technologies are immature. However, single-pixel imaging currently suffers from low imaging rates owing to its reliance on configurable spatial light modulators, generally limited to 22 kHz rates. We develop an approach for rapid single-pixel imaging which relies on cyclic patterns coded onto a spinning mask and demonstrate it for in vivo imaging of C. elegans worms. Spatial modulation rates of up to 2.4 MHz, imaging rates of up to 72 fps, and image-reconstruction times of down to 1.5 ms are reported, enabling real-time visualization of dynamic objects.

Inferring temporal organization of postembryonic development from high-content behavioral tracking

Understanding temporal regulation of development remains an important challenge. Whereas average, species-typical timing of many developmental processes has been established, less is known about inter-individual variability and correlations in timing of specific events. We addressed these questions in the context of postembryonic development in Caenorhabditis elegans. Based on patterns of locomotor activity of freely moving animals, we inferred durations of four larval stages (L1-L4) in over 100 individuals. Analysis of these data supports several conclusions. Individuals have consistently faster or slower rates of development because durations of L1 through L3 stages are positively correlated. The last larval stage, the L4, is less variable than the earlier stages and its duration is largely independent of the rate of early larval development, implying existence of two distinct larval epochs. We describe characteristic patterns of variation and correlation, as well as the fact that stage durations tend to scale relative to total developmental time. This scaling relationship suggests that each larval stage is not limited by an absolute duration, but is instead terminated when a subset of events that must occur prior to adulthood have been completed. The approach described here offers a scalable platform that will facilitate the study of temporal regulation of postembryonic development.