Beyond the connectome: how neuromodulators shape neural circuits

Comparative Perspectives on Neuropeptide Function and Social Isolation

Chronic social isolation alters behavior across animal species. Genetic model organisms such as mice and flies provide crucial insight into the molecular and physiological effects of social isolation on brain cells and circuits. Here, we comparatively review recent findings regarding the function of conserved neuropeptides in social isolation in mice and flies. Analogous functions of 3 classes of neuropeptides-tachykinins, cholecystokinins, and neuropeptide Y/F-in the two model organisms suggest that these molecules may be involved in modulating behavioral changes induced by social isolation across a wider range of species, including humans. Comparative approaches armed with tools to dissect neuropeptidergic function can lead to an integrated understanding of the impacts of social isolation on brain circuits and behavior.

Convergent effects of peptides on the initiation of feeding motor programs in the mollusk Aplysia

Neuropeptides configure the feeding network of Aplysia. For example, egestive activity is promoted by small cardioactive peptide (SCP), and ingestive activity is promoted by a combination of feeding circuit activating peptide (FCAP) and cerebral peptide 2 (CP-2). In addition, SCP and FCAP/CP-2 have a common network effect that does not contribute to motor program specification. They increase the excitability of an interneuron, B63. In this report, we further characterized the effects of peptides on B63. We performed voltage-clamp experiments and used a step protocol to look at steady-state currents. We found that SCP and FCAP/CP-2 both induced an inward current that was virtually absent in low-sodium saline. Previous work has established that B63 is unusual in the feeding circuit in that subthreshold depolarizations are autonomously generated that can trigger motor programs. Here, we show that this autonomous activity is more frequent in the presence of peptides. Previous studies have also shown that activity of the feeding central pattern generator (CPG) can be initiated by neurons that excite B63, e.g., by cerebral buccal interneuron 2 (CBI-2), a projection neuron that triggers biting-like motor programs. Here, we show that the latency of CBI-2-induced activity is decreased by stimulation of the esophageal nerve (EN) (which releases endogenous SCP). These results, taken together with previous results, indicate that peptides that act divergently to configure network activity additionally act convergently to promote motor program induction. We present data that suggest that this arrangement facilitates brief switches between ingestive and egestive motor activity.NEW & NOTEWORTHY The activity of most networks is affected by multiple neuromodulators. Studies that have sought to determine why this is the case have focused on how the effects of one modulator differ from those of another (how modulators uniquely determine motor output). This study differs in that we ask why a convergent (common) network modification is important. We show that it can promote program induction and present data that suggest this may have consequences for task switching.

Rhythmic circuit function is more robust to changes in synaptic than intrinsic conductances

Circuit function results from both intrinsic conductances of network neurons and the synaptic conductances that connect them. In models of neural circuits, different combinations of maximal conductances can give rise to similar activity. We compared the robustness of a neural circuit to changes in their intrinsic versus synaptic conductances. To address this, we performed a sensitivity analysis on a population of conductance-based models of the pyloric network from the crustacean stomatogastric ganglion (STG). The model network consists of three neurons with nine currents: a sodium current (Na), three potassium currents (Kd, KCa, KA), two calcium currents (CaS and CaT), a hyperpolarization-activated current (H), a non-voltage-gated leak current (leak), and a neuromodulatory current (MI). The model cells are connected by seven synapses of two types, glutamatergic and cholinergic. We produced one hundred models of the pyloric network that displayed similar activities with values of maximal conductances distributed over wide ranges. We evaluated the robustness of each model to changes in their maximal conductances. We found that individual models have different sensitivities to changes in their maximal conductances, both in their intrinsic and synaptic conductances. As expected, the models become less robust as the extent of the changes increases. Despite quantitative differences in their robustness, we found that in all cases, the model networks are more sensitive to the perturbation of their intrinsic conductances than their synaptic conductances.

Mapping and decoding neuropeptide signaling networks in nervous system function

Neuropeptides are widespread signaling molecules that are central to brain function in all animals. Recent advances in profiling their expression across neural circuits, in conjunction with detailed biochemical characterization of their interactions with receptors, have made it feasible to build brain-wide maps of neuropeptide signaling. Here, we discuss how recent reconstructions of neuropeptide signaling networks, from mammalian brain regions to nervous system-wide maps in C. elegans, reveal conserved organizational features of neuropeptidergic networks. Furthermore, we review recent technical breakthroughs in in vivo sensors for peptide release, receptor binding, and intracellular signaling that bring a mechanistic understanding of neuropeptide networks within experimental reach. Finally, we describe how the architecture of neuropeptide signaling networks can change throughout evolution or even the lifetime of individuals, which highlights the complexities that must be considered to understand how these molecules modulate circuit activity and behavior across different contexts.

What Drosophila can tell us about state-dependent peptidergic signaling in insects

Plasticity in animal behavior and physiology is largely due to modulatory and regulatory signaling with neuropeptides and peptide hormones (collectively abbreviated NPHs). The NPHs constitute a very large and versatile group of signaling substances that partake at different regulatory levels in most daily activities of an organism. This review summarizes key principles in NPH actions in the brain and in interorgan signaling, with focus on Drosophila. NPHs are produced by neurons, neurosecretory cells (NSCs) and other endocrine cells in NPH-specific and stereotypic patterns. Most of the NPHs have multiple (pleiotropic) functions and target several different neuronal circuits and/or peripheral tissues. Such divergent NPH signaling ensures orchestration of behavior and physiology in state-dependent manners. Conversely, many neurons, circuits, NSCs, or other cells, are targeted by multiple NPHs. This convergent signaling commonly conveys various signals reporting changes in the external and internal environment to central neurons/circuits. As an example of wider functional convergence, 26 different Drosophila NPHs act at many different levels to regulate food search and feeding. Convergence is also seen in hormonal regulation of peripheral functions. For instance, multiple NPHs target renal tubules to ensure osmotic homeostasis. Interestingly, several of the same osmoregulatory NPHs also regulate feeding, metabolism and stress. However, for some NPHs the cellular distribution and functions suggests multiple unrelated functions that are restricted to specific circuits. Thus, NPH signaling follows distinct patterns for each specific NPH, but taken together they form overlapping networks that modulate behavior and physiology.

Neuroendocrine Control of Synaptic Transmission by PHAC-1 in C. elegans

A dynamic interplay between fast synaptic signals and slower neuromodulatory signals controls the excitatory/inhibitory (E/I) balance within neuronal circuits. The mechanisms by which neuropeptide signaling is regulated to maintain E/I balance remain uncertain. We designed a genetic screen to isolate genes involved in the peptidergic maintenance of the E/I balance in the C. elegans motor circuit. This screen identified the C. elegans orthologs of the presynaptic phosphoprotein synapsin (snn-1) and the protein phosphatase 1 (PP1) regulatory subunit PHACTR1 (phac-1). We demonstrate that both phac-1 and snn-1 alter the motor behavior of C. elegans, and genetic interactions suggest that SNN-1 contributes to PP1-PHAC-1 holoenzyme signaling. De novo variants of human PHACTR1, associated with early-onset epilepsies [developmental and epileptic encephalopathy 70 (DEE70)], when expressed in C. elegans resulted in constitutive PP1-PHAC-1 holoenzyme activity. Unregulated PP1-PHAC-1 signaling alters the synapsin and actin cytoskeleton and increases neuropeptide release by cholinergic motor neurons, which secondarily affects the presynaptic vesicle cycle. Together, these results clarify the dominant mechanisms of action of the DEE70 alleles and suggest that altered neuropeptide release may alter E/I balance in DEE70.

Neuropeptides: The Evergreen Jack-of-All-Trades in Neuronal Circuit Development and Regulation

Neuropeptides are key modulators of adult neurocircuits, balancing their sensitivity to both excitation and inhibition, and fine-tuning fast neurotransmitter action under physiological conditions. Here, we reason that transient increases in neuropeptide availability and action exist during brain development for synapse maturation, selection, and maintenance. We discuss fundamental concepts of neuropeptide signaling at G protein-coupled receptors (GPCRs), with a particular focus on how signaling at neuropeptide GPCRs could underpin neuronal morphogenesis. We use galanin, a 29/30 amino acid-long neuropeptide, as an example for its retrograde release from the dendrites of thalamic neurons to impact the selection and wiring of sensory afferents originating at the trigeminal nucleus through galanin receptor 1 (GalR1) engagement. Thus, we suggest novel roles for neuropeptides, expressed transiently or permanently during both pre- and postnatal neuronal circuit development, with potentially life-long effects on circuit layout and ensuing behavioral operations.

Augmenting flexibility: mutual inhibition between inhibitory neurons expands functional diversity

Recent advances in microcircuit analysis of nervous systems have revealed a plethora of mutual connections between inhibitory interneurons across many different species and brain regions. The abundance of these mutual connections has not been fully explained. Strikingly, we show that neural circuits with mutually inhibitory connections are able to rapidly and flexibly switch between distinct functions. That is, multiple functions coexist for a single set of synaptic weights. Here, we develop a theoretical framework to explain how inhibitory recurrent circuits give rise to this flexibility and show that mutual inhibition doubles the number of cusp bifurcations in small neural circuits. As a concrete example, we study a class of functional motifs we call coupled recurrent inhibitory and recurrent excitatory loops (CRIRELs). These CRIRELs have the advantage of being both multi-functional and controllable, performing a plethora of functions, including decisions, memory, toggle, and so forth. Finally, we demonstrate how mutual inhibition maximizes storage capacity for larger networks.

Rhythmic circuit function is more robust to changes in synaptic than intrinsic conductances

Circuit function results from both intrinsic conductances of network neurons and the synaptic conductances that connect them. In models of neural circuits, different combinations of maximal conductances can give rise to similar activity. We compared the robustness of a neural circuit to changes in their intrinsic versus synaptic conductances. To address this, we performed a sensitivity analysis on a population of conductance-based models of the pyloric network from the crustacean stomatogastric ganglion (STG). The model network consists of three neurons with nine currents: a sodium current (Na), three potassium currents (Kd, KCa, A-type), two calcium currents (CaS and CaT), a hyperpolarization-activated current (H), a non-voltage-gated leak current (leak), and a neuromodulatory current (MI). The model cells are connected by seven synapses of two types, glutamatergic and cholinergic. We produced one hundred models of the pyloric network that displayed similar activities with values of maximal conductances distributed over wide ranges. We evaluated the robustness of each model to changes in their maximal conductances. We found that individual models have different sensitivities to changes in their maximal conductances, both in their intrinsic and synaptic conductances. As expected the models become less robust as the extent of the changes increase. Despite quantitative differences in their robustness, we found that in all cases, the model networks are more sensitive to the perturbation of their intrinsic conductances than their synaptic conductances.

A brief history of insect neuropeptide and peptide hormone research

This review briefly summarizes 50 years of research on insect neuropeptide and peptide hormone (collectively abbreviated NPH) signaling, starting with the sequencing of proctolin in 1975. The first 25 years, before the sequencing of the Drosophila genome, were characterized by efforts to identify novel NPHs by biochemical means, mapping of their distribution in neurons, neurosecretory cells, and endocrine cells of the intestine. Functional studies of NPHs were predominantly dealing with hormonal aspects of peptides and many employed ex vivo assays. With the annotation of the Drosophila genome, and more specifically of the NPHs and their receptors in Drosophila and other insects, a new era followed. This started with matching of NPH ligands to orphan receptors, and studies to localize NPHs with improved detection methods. Important advances were made with introduction of a rich repertoire of innovative molecular genetic approaches to localize and interfere with expression or function of NPHs and their receptors. These methods enabled cell- or circuit-specific interference with NPH signaling for in vivo assays to determine roles in behavior and physiology, imaging of neuronal activity, and analysis of connectivity in peptidergic circuits. Recent years have seen a dramatic increase in reports on the multiple functions of NPHs in development, physiology and behavior. Importantly, we can now appreciate the pleiotropic functions of NPHs, as well as the functional peptidergic "networks" where state dependent NPH signaling ensures behavioral plasticity and systemic homeostasis.

Temperature-dependent lifespan extension is achieved in miR-80-deleted Caenorhabditis elegans by NLP-45 to modulate endoplasmic reticulum unfolded protein responses

MicroRNA plays a crucial role in post-transcriptional gene regulation and has recently emerged as a factor linked to aging, but the underlying regulatory mechanisms remain incompletely understood. In this study, we observed lifespan-extending effects in miR-80-deficient Caenorhabditis elegans at 20°C but not 25°C. At 20°C, miR-80 deletion leads to NLP-45 upregulation, which positively correlates to increased abu transcripts and extended lifespan. Supportively, we identified miR-80 binding regions in the 5' and 3' UTR of nlp-45. As the temperature rises to 25°C, wildtype increases miR-80 levels, but removal of miR-80 is accompanied by decreased nlp-45 expression, suggesting intervention from other temperature-sensitive mechanisms. These findings support the concept that microRNAs and neuropeptide-like proteins can form molecular regulatory networks involving downstream molecules to regulate lifespan, and such regulatory effects vary on environmental conditions. This study unveils the role of an axis of miR-80/NLP-45/UPRER components in regulating longevity, offering new insights on strategies of aging attenuation and health span prolongation.

Degenerate neuronal and circuit mechanisms important for generating rhythmic motor patterns

In 1996, we published a review article (Marder E, Calabrese RL. Physiol Rev 76: 687-717, 1996) describing the state of knowledge about the structure and function of the central pattern-generating circuits important for producing rhythmic behaviors. Although many of the core questions persist, much has changed since 1996. Here, we focus on newer studies that reveal ambiguities that complicate understanding circuit dynamics, despite the enormous technical advances of the recent past. In particular, we highlight recent studies of animal-to-animal variability and our understanding that circuit rhythmicity may be supported by multiple state-dependent mechanisms within the same animal and that robustness and resilience in the face of perturbation may depend critically on the presence of modulators and degenerate circuit mechanisms. Additionally, we highlight the use of computational models to ask whether there are generalizable principles about circuit motifs that can be found across rhythmic motor systems in different animal species.

Uncovering multiscale structure in the variability of larval zebrafish navigation

Animals chain movements into long-lived motor strategies, exhibiting variability across scales that reflects the interplay between internal states and environmental cues. To reveal structure in such variability, we build Markov models of movement sequences that bridge across timescales and enable a quantitative comparison of behavioral phenotypes among individuals. Applied to larval zebrafish responding to diverse sensory cues, we uncover a hierarchy of long-lived motor strategies, dominated by changes in orientation distinguishing cruising versus wandering strategies. Environmental cues induce preferences along these modes at the population level: while fish cruise in the light, they wander in response to aversive stimuli, or in search for appetitive prey. As our method encodes the behavioral dynamics of each individual fish in the transitions among coarse-grained motor strategies, we use it to uncover a hierarchical structure in the phenotypic variability that reflects exploration-exploitation trade-offs. Across a wide range of sensory cues, a major source of variation among fish is driven by prior and/or immediate exposure to prey that induces exploitation phenotypes. A large degree of variability that is not explained by environmental cues unravels hidden states that override the sensory context to induce contrasting exploration-exploitation phenotypes. Altogether, by extracting the timescales of motor strategies deployed during navigation, our approach exposes structure among individuals and reveals internal states tuned by prior experience.

Dopamine neurons that inform Drosophila olfactory memory have distinct, acute functions driving attraction and aversion

The brain must guide immediate responses to beneficial and harmful stimuli while simultaneously writing memories for future reference. While both immediate actions and reinforcement learning are instructed by dopamine, how dopaminergic systems maintain coherence between these 2 reward functions is unknown. Through optogenetic activation experiments, we showed that the dopamine neurons that inform olfactory memory in Drosophila have a distinct, parallel function driving attraction and aversion (valence). Sensory neurons required for olfactory memory were dispensable to dopaminergic valence. A broadly projecting set of dopaminergic cells had valence that was dependent on dopamine, glutamate, and octopamine. Similarly, a more restricted dopaminergic cluster with attractive valence was reliant on dopamine and glutamate; flies avoided opto-inhibition of this narrow subset, indicating the role of this cluster in controlling ongoing behavior. Dopamine valence was distinct from output-neuron opto-valence in locomotor pattern, strength, and polarity. Overall, our data suggest that dopamine's acute effect on valence provides a mechanism by which a dopaminergic system can coherently write memories to influence future responses while guiding immediate attraction and aversion.

Neuropeptide signaling network of Caenorhabditis elegans: from structure to behavior

Neuropeptides are abundant signaling molecules that control neuronal activity and behavior in all animals. Owing in part to its well-defined and compact nervous system, Caenorhabditis elegans has been one of the primary model organisms used to investigate how neuropeptide signaling networks are organized and how these neurochemicals regulate behavior. We here review recent work that has expanded our understanding of the neuropeptidergic signaling network in C. elegans by mapping the evolutionary conservation, the molecular expression, the receptor-ligand interactions, and the system-wide organization of neuropeptide pathways in the C. elegans nervous system. We also describe general insights into neuropeptidergic circuit motifs and the spatiotemporal range of peptidergic transmission that have emerged from in vivo studies on neuropeptide signaling. With efforts ongoing to chart peptide signaling networks in other organisms, the C. elegans neuropeptidergic connectome can serve as a prototype to further understand the organization and the signaling dynamics of these networks at organismal level.

Cell non-autonomous signaling through the conserved C. elegans glycoprotein hormone receptor FSHR-1 regulates cholinergic neurotransmission

Modulation of neurotransmission is key for organismal responses to varying physiological contexts such as during infection, injury, or other stresses, as well as in learning and memory and for sensory adaptation. Roles for cell autonomous neuromodulatory mechanisms in these processes have been well described. The importance of cell non-autonomous pathways for inter-tissue signaling, such as gut-to-brain or glia-to-neuron, has emerged more recently, but the cellular mechanisms mediating such regulation remain comparatively unexplored. Glycoproteins and their G protein-coupled receptors (GPCRs) are well-established orchestrators of multi-tissue signaling events that govern diverse physiological processes through both cell-autonomous and cell non-autonomous regulation. Here, we show that follicle stimulating hormone receptor, FSHR-1, the sole Caenorhabditis elegans ortholog of mammalian glycoprotein hormone GPCRs, is important for cell non-autonomous modulation of synaptic transmission. Inhibition of fshr-1 expression reduces muscle contraction and leads to synaptic vesicle accumulation in cholinergic motor neurons. The neuromuscular and locomotor defects in fshr-1 loss-of-function mutants are associated with an underlying accumulation of synaptic vesicles, build-up of the synaptic vesicle priming factor UNC-10/RIM, and decreased synaptic vesicle release from cholinergic motor neurons. Restoration of FSHR-1 to the intestine is sufficient to restore neuromuscular activity and synaptic vesicle localization to fshr-1-deficient animals. Intestine-specific knockdown of FSHR-1 reduces neuromuscular function, indicating FSHR-1 is both necessary and sufficient in the intestine for its neuromuscular effects. Re-expression of FSHR-1 in other sites of endogenous expression, including glial cells and neurons, also restored some neuromuscular deficits, indicating potential cross-tissue regulation from these tissues as well. Genetic interaction studies provide evidence that downstream effectors gsa-1/GαS, acy-1/adenylyl cyclase and sphk-1/sphingosine kinase and glycoprotein hormone subunit orthologs, GPLA-1/GPA2 and GPLB-1/GPB5, are important for intestinal FSHR-1 modulation of the NMJ. Together, our results demonstrate that FSHR-1 modulation directs inter-tissue signaling systems, which promote synaptic vesicle release at neuromuscular synapses.

Understanding the neurobiology of social behavior through exploring brain-wide dynamics of neural activity

Social behavior is highly complex and adaptable. It can be divided into multiple temporal stages: detection, approach, and consummatory behavior. Each stage can be further divided into several cognitive and behavioral processes, such as perceiving social cues, evaluating the social and non-social contexts, and recognizing the internal/emotional state of others. Recent studies have identified numerous brain-wide circuits implicated in social behavior and suggested the existence of partially overlapping functional brain networks underlying various types of social and non-social behavior. However, understanding the brain-wide dynamics underlying social behavior remains challenging, and several brain-scale dynamics (macro-, meso-, and micro-scale levels) need to be integrated. Here, we suggest leveraging new tools and concepts to explore social brain networks and integrate those different levels. These include studying the expression of immediate-early genes throughout the entire brain to impartially define the structure of the neuronal networks involved in a given social behavior. Then, network dynamics could be investigated using electrode arrays or multi-channel fiber photometry. Finally, tools like high-density silicon probes and miniscopes can probe neural activity in specific areas and across neuronal populations at the single-cell level.

Dynamics of neural activity in early nervous system evolution

New techniques for largescale neural recordings from diverse animals are reshaping comparative systems neuroscience. This growth necessitates fresh conceptual paradigms for comparing neural circuits and activity patterns. Here, we take a systems neuroscience approach to early neural evolution, emphasizing the importance of considering nervous systems as multiply modulated, continuous dynamical systems. We argue that endogenous neural activity likely arose early in evolution to organize behaviors and internal states at the organismal level. This connects to a rich literature on the physiology of endogenous activity in small neural circuits: a field that has built links between data and dynamical systems models. Such models offer mechanistic insight and have robust predictive power. Using these tools, we suggest that the emergence of intrinsically active neurons and periodic dynamics played a critical role in the ascendancy of nervous systems, and that dynamical systems presents an appealing framework for comparing across species.

A Drosophila computational brain model reveals sensorimotor processing

The recent assembly of the adult Drosophila melanogaster central brain connectome, containing more than 125,000 neurons and 50 million synaptic connections, provides a template for examining sensory processing throughout the brain1,2. Here we create a leaky integrate-and-fire computational model of the entire Drosophila brain, on the basis of neural connectivity and neurotransmitter identity3, to study circuit properties of feeding and grooming behaviours. We show that activation of sugar-sensing or water-sensing gustatory neurons in the computational model accurately predicts neurons that respond to tastes and are required for feeding initiation4. In addition, using the model to activate neurons in the feeding region of the Drosophila brain predicts those that elicit motor neuron firing5-a testable hypothesis that we validate by optogenetic activation and behavioural studies. Activating different classes of gustatory neurons in the model makes accurate predictions of how several taste modalities interact, providing circuit-level insight into aversive and appetitive taste processing. Additionally, we applied this model to mechanosensory circuits and found that computational activation of mechanosensory neurons predicts activation of a small set of neurons comprising the antennal grooming circuit, and accurately describes the circuit response upon activation of different mechanosensory subtypes6-10. Our results demonstrate that modelling brain circuits using only synapse-level connectivity and predicted neurotransmitter identity generates experimentally testable hypotheses and can describe complete sensorimotor transformations.

Neuroscience: A big step forward for motor control in Drosophila

Connectomics approaches are fundamentally changing the way scientists investigate the brain. Recently published connectomes have enabled dissection of the intricate motor circuits in the fly's version of the spinal cord on a synaptic level. This has allowed reconstruction of complete sensorimotor pathways in Drosophila.

Uncovering the determinants of brain functioning, behavior and their interplay in the light of context

Notwithstanding the huge progress in molecular and cellular neuroscience, our ability to understand the brain and develop effective treatments promoting mental health is still limited. This can be partially ascribed to the reductionist, deterministic and mechanistic approaches in neuroscience that struggle with the complexity of the central nervous system. Here, I introduce the Context theory of constrained systems proposing a novel role of contextual factors and genetic, molecular and neural substrates in determining brain functioning and behavior. This theory entails key conceptual implications. First, context is the main driver of behavior and mental states. Second, substrates, from genes to brain areas, have no direct causal link to complex behavioral responses as they can be combined in multiple ways to produce the same response and different responses can impinge on the same substrates. Third, context and biological substrates play distinct roles in determining behavior: context drives behavior, substrates constrain the behavioral repertoire that can be implemented. Fourth, since behavior is the interface between the central nervous system and the environment, it is a privileged level of control and orchestration of brain functioning. Such implications are illustrated through the Kitchen metaphor of the brain. This theoretical framework calls for the revision of key concepts in neuroscience and psychiatry, including causality, specificity and individuality. Moreover, at the clinical level, it proposes treatments inducing behavioral changes through contextual interventions as having the highest impact to reorganize the complexity of the human mind and to achieve a long-lasting improvement in mental health.

Emotional vocalizations alter behaviors and neurochemical release into the amygdala

The basolateral amygdala (BLA), a brain center of emotional expression, contributes to acoustic communication by first interpreting the meaning of social sounds in the context of the listener's internal state, then organizing the appropriate behavioral responses. We propose that modulatory neurochemicals such as acetylcholine (ACh) and dopamine (DA) provide internal-state signals to the BLA while an animal listens to social vocalizations. We tested this in a vocal playback experiment utilizing highly affective vocal sequences associated with either mating or restraint, then sampled and analyzed fluids within the BLA for a broad range of neurochemicals and observed behavioral responses of adult male and female mice. In male mice, playback of restraint vocalizations increased ACh release and usually decreased DA release, while playback of mating sequences evoked the opposite neurochemical release patterns. In non-estrus female mice, patterns of ACh and DA release with mating playback were similar to males. Estrus females, however, showed increased ACh, associated with vigilance, as well as increased DA, associated with reward-seeking. Experimental groups that showed increased ACh release also showed the largest increases in an aversive behavior. These neurochemical release patterns and several behavioral responses depended on a single prior experience with the mating and restraint behaviors. Our results support a model in which ACh and DA provide contextual information to sound analyzing BLA neurons that modulate their output to downstream brain regions controlling behavioral responses to social vocalizations.

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.

Automated dual olfactory device for studying head/tail chemosensation in Caenorhabditis elegans

The correct interpretation of threat and reward is important for animal survival. Often, the decisions underlying these behavioral programs are mediated by volatile compounds in the animal's environment, which they detect and discriminate with specialized olfactory neurons along their body. Caenorhabditis (C.) elegans senses chemical stimuli with neurons located in the head and the tail of the animal, which mediate either attractive or aversive behaviors. How conflicting stimuli are processed in animals navigating different chemical gradients is poorly understood. Here, we conceived, created, and capitalized on a novel microfluidic device to enable automated and precise stimulation of head and tail neurons, either simultaneously or sequentially, while reading out neuronal activity in sensory and interneurons using genetically encoded calcium indicators. We achieve robust and programmable chemical pulses through the modulation of inlet pressures. To evaluate the device performance, we synchronized the flow control with microscopy data acquisition and characterized the flow properties in the fabricated devices. Together, our design has the potential to provide insight into the neural circuits and behavior of C. elegans simulating the experience of natural environments.

Uncovering multiscale structure in the variability of larval zebrafish navigation

Animals chain movements into long-lived motor strategies, resulting in variability that ultimately reflects the interplay between internal states and environmental cues. To reveal structure in such variability, we build models that bridges across time scales that enable a quantitative comparison of behavioral phenotypes among individuals. Applied to larval zebrafish exposed to diverse sensory cues, we uncover a hierarchy of long-lived motor strategies, dominated by changes in orientation distinguishing cruising and wandering strategies. Environmental cues induce preferences along these modes at the population level: while fish cruise in the light, they wander in response to aversive (dark) stimuli or in search for prey. Our method enables us to encode the behavioral dynamics of each individual fish in the transitions among coarse-grained motor strategies. By doing so, we uncover a hierarchical structure to the phenotypic variability that corresponds to exploration-exploitation trade-offs. Within a wide range of sensory cues, a major source of variation among fish is driven by prior and immediate exposure to prey that induces exploitation phenotypes. However, a large degree of variability is unexplained by environmental cues, pointing to hidden states that override the sensory context to induce contrasting exploration-exploitation phenotypes. Altogether, our approach extracts the timescales of motor strategies deployed during navigation, exposing undiscovered structure among individuals and pointing to internal states tuned by prior experience.

Zebrafish and nematodes as whole organism models to measure developmental neurotoxicity

Despite the growing epidemiological evidence of an association between toxin exposure and developmental neurotoxicity (DNT), systematic testing of DNT is not mandatory in international regulations for admission of pharmaceuticals or industrial chemicals. However, to date around 200 compounds, ranging from pesticides, pharmaceuticals and industrial chemicals, have been tested for DNT in the current OECD test guidelines (TG-443 or TG-426). There are calls for the development of new approach methodologies (NAMs) for DNT, which has resulted in a DNT testing battery using in vitro human cell-based assays. These assays provide a means to elucidate the molecular mechanisms of toxicity in humans which is lacking in animal-based toxicity tests. However, cell-based assays do not represent all steps of the complex process leading to DNT. Validated models with a multi-organ network of pathways that interact at the molecular, cellular and tissue level at very specific timepoints in a life cycle are currently missing. Consequently, whole model organisms are being developed to screen for, and causally link, new molecular targets of DNT compounds and how they affect whole brain development and neurobehavioral endpoints. Given the practical and ethical restraints associated with vertebrate testing, lower animal models that qualify as 3 R (reduce, refine and replace) models, including the nematode (Caenorhabditis elegans) and the zebrafish (Danio rerio) will prove particularly valuable for unravelling toxicity pathways leading to DNT. Although not as complex as the human brain, these 3 R-models develop a complete functioning brain with numerous neurodevelopmental processes overlapping with human brain development. Importantly, the main signalling pathways relating to (neuro)development, metabolism and growth are highly conserved in these models. We propose the use of whole model organisms specifically zebrafish and C. elegans for DNT relevant endpoints.

C. elegans: a prominent platform for modeling and drug screening in neurological disorders

INTRODUCTION

Human neurodevelopmental and neurodegenerative diseases (NDevDs and NDegDs, respectively) encompass a broad spectrum of disorders affecting the nervous system with an increasing incidence. In this context, the nematode C. elegans, has emerged as a benchmark model for biological research, especially in the field of neuroscience.

AREAS COVERED

The authors highlight the numerous advantages of this tiny worm as a model for exploring nervous system pathologies and as a platform for drug discovery. There is a particular focus given to describing the existing models of C. elegans for the study of NDevDs and NDegDs. Specifically, the authors underscore their strong applicability in preclinical drug development. Furthermore, they place particular emphasis on detailing the common techniques employed to explore the nervous system in both healthy and diseased states.

EXPERT OPINION

Drug discovery constitutes a long and expensive process. The incorporation of invertebrate models, such as C. elegans, stands as an exemplary strategy for mitigating costs and expediting timelines. The utilization of C. elegans as a platform to replicate nervous system pathologies and conduct high-throughput automated assays in the initial phases of drug discovery is pivotal for rendering therapeutic options more attainable and cost-effective.

How neurobehavior and brain development in alternative whole-organism models can contribute to prediction of developmental neurotoxicity

Developmental neurotoxicity (DNT) is not routinely evaluated in chemical risk assessment because current test paradigms for DNT require the use of mammalian models which are ethically controversial, expensive, and resource demanding. Consequently, efforts have focused on revolutionizing DNT testing through affordable novel alternative methods for risk assessment. The goal is to develop a DNT in vitro test battery amenable to high-throughput screening (HTS). Currently, the DNT in vitro test battery consists primarily of human cell-based assays because of their immediate relevance to human health. However, such cell-based assays alone are unable to capture the complexity of a developing nervous system. Whole organismal systems that qualify as 3 R (Replace, Reduce and Refine) models are urgently needed to complement cell-based DNT testing. These models can provide the necessary organismal context and be used to explore the impact of chemicals on brain function by linking molecular and/or cellular changes to behavioural readouts. The nematode Caenorhabditis elegans, the planarian Dugesia japonica, and embryos of the zebrafish Danio rerio are all suited to low-cost HTS and each has unique strengths for DNT testing. Here, we review the strengths and the complementarity of these organisms in a novel, integrative context and highlight how they can augment current cell-based assays for more comprehensive and robust DNT screening of chemicals. Considering the limitations of all in vitro test systems, we discuss how a smart combinatory use of these systems will contribute to a better human relevant risk assessment of chemicals that considers the complexity of the developing brain.

Evolution of neural circuitry and cognition

Neural circuits govern the interface between the external environment, internal cues and outwardly directed behaviours. To process multiple environmental stimuli and integrate these with internal state requires considerable neural computation. Expansion in neural network size, most readily represented by whole brain size, has historically been linked to behavioural complexity, or the predominance of cognitive behaviours. Yet, it is largely unclear which aspects of circuit variation impact variation in performance. A key question in the field of evolutionary neurobiology is therefore how neural circuits evolve to allow improved behavioural performance or innovation. We discuss this question by first exploring how volumetric changes in brain areas reflect actual neural circuit change. We explore three major axes of neural circuit evolution-replication, restructuring and reconditioning of cells and circuits-and discuss how these could relate to broader phenotypes and behavioural variation. This discussion touches on the relevant uses and limitations of volumetrics, while advocating a more circuit-based view of cognition. We then use this framework to showcase an example from the insect brain, the multi-sensory integration and internal processing that is shared between the mushroom bodies and central complex. We end by identifying future trends in this research area, which promise to advance the field of evolutionary neurobiology.

Protein-Based Tools for Studying Neuromodulation

Neuromodulators play crucial roles in regulating neuronal activity and affecting various aspects of brain functions, including learning, memory, cognitive functions, emotional states, and pain modulation. In this Account, we describe our group's efforts in designing sensors and tools for studying neuromodulation. Our lab focuses on developing new classes of integrators that can detect neuromodulators across the whole brain while leaving a mark for further imaging analysis at high spatial resolution. Our lab also designed chemical- and light-dependent protein switches for controlling peptide activity to potentially modulate the endogenous receptors of the neuromodulatory system in order to study the causal effects of selective neuronal pathways.

A tonically active master neuron modulates mutually exclusive motor states at two timescales

Continuity of behaviors requires animals to make smooth transitions between mutually exclusive behavioral states. Neural principles that govern these transitions are not well understood. Caenorhabditis elegans spontaneously switch between two opposite motor states, forward and backward movement, a phenomenon thought to reflect the reciprocal inhibition between interneurons AVB and AVA. Here, we report that spontaneous locomotion and their corresponding motor circuits are not separately controlled. AVA and AVB are neither functionally equivalent nor strictly reciprocally inhibitory. AVA, but not AVB, maintains a depolarized membrane potential. While AVA phasically inhibits the forward promoting interneuron AVB at a fast timescale, it maintains a tonic, extrasynaptic excitation on AVB over the longer timescale. We propose that AVA, with tonic and phasic activity of opposite polarities on different timescales, acts as a master neuron to break the symmetry between the underlying forward and backward motor circuits. This master neuron model offers a parsimonious solution for sustained locomotion consisted of mutually exclusive motor states.

Beyond hippocampus: Thalamic and prefrontal contributions to an evolving memory

The hippocampus has long been at the center of memory research, and rightfully so. However, with emerging technological capabilities, we can increasingly appreciate memory as a more dynamic and brain-wide process. In this perspective, our goal is to begin developing models to understand the gradual evolution, reorganization, and stabilization of memories across the brain after their initial formation in the hippocampus. By synthesizing studies across the rodent and human literature, we suggest that as memory representations initially form in hippocampus, parallel traces emerge in frontal cortex that cue memory recall, and as they mature, with sustained support initially from limbic then diencephalic then cortical circuits, they become progressively independent of hippocampus and dependent on a mature cortical representation. A key feature of this model is that, as time progresses, memory representations are passed on to distinct circuits with progressively longer time constants, providing the opportunity to filter, forget, update, or reorganize memories in the process of committing to long-term storage.

Neuronal mechanisms regulating locomotion in adult Drosophila

The coordinated action of multiple leg joints and muscles is required even for the simplest movements. Understanding the neuronal circuits and mechanisms that generate precise movements is essential for comprehending the neuronal basis of the locomotion and to infer the neuronal mechanisms underlying several locomotor-related diseases. Drosophila melanogaster provides an excellent model system for investigating the neuronal circuits underlying motor behaviors due to its simple nervous system and genetic accessibility. This review discusses current genetic methods for studying locomotor circuits and their function in adult Drosophila. We highlight recently identified neuronal pathways that modulate distinct forward and backward locomotion and describe the underlying neuronal control of leg swing and stance phases in freely moving flies. We also report various automated leg tracking methods to measure leg motion parameters and define inter-leg coordination, gait and locomotor speed of freely moving adult flies. Finally, we emphasize the role of leg proprioceptive signals to central motor circuits in leg coordination. Together, this review highlights the utility of adult Drosophila as a model to uncover underlying motor circuitry and the functional organization of the leg motor system that governs correct movement.

Neurobiological Causal Models of Language Processing

The language faculty is physically realized in the neurobiological infrastructure of the human brain. Despite significant efforts, an integrated understanding of this system remains a formidable challenge. What is missing from most theoretical accounts is a specification of the neural mechanisms that implement language function. Computational models that have been put forward generally lack an explicit neurobiological foundation. We propose a neurobiologically informed causal modeling approach which offers a framework for how to bridge this gap. A neurobiological causal model is a mechanistic description of language processing that is grounded in, and constrained by, the characteristics of the neurobiological substrate. It intends to model the generators of language behavior at the level of implementational causality. We describe key features and neurobiological component parts from which causal models can be built and provide guidelines on how to implement them in model simulations. Then we outline how this approach can shed new light on the core computational machinery for language, the long-term storage of words in the mental lexicon and combinatorial processing in sentence comprehension. In contrast to cognitive theories of behavior, causal models are formulated in the "machine language" of neurobiology which is universal to human cognition. We argue that neurobiological causal modeling should be pursued in addition to existing approaches. Eventually, this approach will allow us to develop an explicit computational neurobiology of language.

Serotonergic modulation of vigilance states in zebrafish and mice

Vigilance refers to being alertly watchful or paying sustained attention to avoid potential threats. Animals in vigilance states reduce locomotion and have an enhanced sensitivity to aversive stimuli so as to react quickly to dangers. Here we report that an unconventional 5-HT driven mechanism operating at neural circuit level which shapes the internal state underlying vigilance behavior in zebrafish and male mice. The neural signature of internal vigilance state was characterized by persistent low-frequency high-amplitude neuronal synchrony in zebrafish dorsal pallium and mice prefrontal cortex. The neuronal synchronization underlying vigilance was dependent on intense release of 5-HT induced by persistent activation of either DRN 5-HT neuron or local 5-HT axon terminals in related brain regions via activation of 5-HTR7. Thus, we identify a mechanism of vigilance behavior across species that illustrates the interplay between neuromodulators and neural circuits necessary to shape behavior states.

Neuromodulation and the toolkit for behavioural evolution: can ecdysis shed light on an old problem?

The geneticist Thomas Dobzhansky famously declared: 'Nothing in biology makes sense except in the light of evolution'. A key evolutionary adaptation of Metazoa is directed movement, which has been elaborated into a spectacularly varied number of behaviours in animal clades. The mechanisms by which animal behaviours have evolved, however, remain unresolved. This is due, in part, to the indirect control of behaviour by the genome, which provides the components for both building and operating the brain circuits that generate behaviour. These brain circuits are adapted to respond flexibly to environmental contingencies and physiological needs and can change as a function of experience. The resulting plasticity of behavioural expression makes it difficult to characterize homologous elements of behaviour and to track their evolution. Here, we evaluate progress in identifying the genetic substrates of behavioural evolution and suggest that examining adaptive changes in neuromodulatory signalling may be a particularly productive focus for future studies. We propose that the behavioural sequences used by ecdysozoans to moult are an attractive model for studying the role of neuromodulation in behavioural evolution.

Cell non-autonomous signaling through the conserved C. elegans glycopeptide hormone receptor FSHR-1 regulates cholinergic neurotransmission

Modulation of neurotransmission is key for organismal responses to varying physiological contexts such as during infection, injury, or other stresses, as well as in learning and memory and for sensory adaptation. Roles for cell autonomous neuromodulatory mechanisms in these processes have been well described. The importance of cell non-autonomous pathways for inter-tissue signaling, such as gut-to-brain or glia-to-neuron, has emerged more recently, but the cellular mechanisms mediating such regulation remain comparatively unexplored. Glycoproteins and their G protein-coupled receptors (GPCRs) are well-established orchestrators of multi-tissue signaling events that govern diverse physiological processes through both cell-autonomous and cell non-autonomous regulation. Here, we show that follicle stimulating hormone receptor, FSHR-1, the sole Caenorhabditis elegans ortholog of mammalian glycoprotein hormone GPCRs, is important for cell non-autonomous modulation of synaptic transmission. Inhibition of fshr-1 expression reduces muscle contraction and leads to synaptic vesicle accumulation in cholinergic motor neurons. The neuromuscular and locomotor defects in fshr-1 loss-of-function mutants are associated with an underlying accumulation of synaptic vesicles, build-up of the synaptic vesicle priming factor UNC-10/RIM, and decreased synaptic vesicle release from cholinergic motor neurons. Restoration of FSHR-1 to the intestine is sufficient to restore neuromuscular activity and synaptic vesicle localization to fshr-1- deficient animals. Intestine-specific knockdown of FSHR-1 reduces neuromuscular function, indicating FSHR-1 is both necessary and sufficient in the intestine for its neuromuscular effects. Re-expression of FSHR-1 in other sites of endogenous expression, including glial cells and neurons, also restored some neuromuscular deficits, indicating potential cross-tissue regulation from these tissues as well. Genetic interaction studies provide evidence that downstream effectors gsa-1 / Gα S , acy-1 /adenylyl cyclase and sphk-1/ sphingosine kinase and glycoprotein hormone subunit orthologs, GPLA-1/GPA2 and GPLB-1/GPB5, are important for FSHR-1 modulation of the NMJ. Together, our results demonstrate that FSHR-1 modulation directs inter-tissue signaling systems, which promote synaptic vesicle release at neuromuscular synapses.

Understanding neural circuit function through synaptic engineering

Synapses are a key component of neural circuits, facilitating rapid and specific signalling between neurons. Synaptic engineering - the synthetic insertion of new synaptic connections into in vivo neural circuits - is an emerging approach for neural circuit interrogation. This approach is especially powerful for establishing causality in neural circuit structure-function relationships, for emulating synaptic plasticity and for exploring novel patterns of circuit connectivity. Contrary to other approaches for neural circuit manipulation, synaptic engineering targets specific connections between neurons and functions autonomously with no user-controlled external activation. Synaptic engineering has been successfully implemented in several systems and in different forms, including electrical synapses constructed from ectopically expressed connexin gap junction proteins, synthetic optical synapses composed of presynaptic photon-emitting luciferase coupled with postsynaptic light-gated channels, and artificial neuropeptide signalling pathways. This Perspective describes these different methods and how they have been applied, and examines how the field may advance.

Neuroendocrine gene expression coupling of interoceptive bacterial food cues to foraging behavior of C. elegans

Animal internal state is modulated by nutrient intake, resulting in behavioral responses to changing food conditions. The neural mechanisms by which internal states are generated and maintained are not well understood. Here, we show that in the nematode Caenorhabditis elegans, distinct cues from bacterial food - interoceptive signals from the ingestion of bacteria and gustatory molecules sensed from nearby bacteria - act antagonistically on the expression of the neuroendocrine TGF-beta ligand DAF-7 from the ASJ pair of sensory neurons to modulate foraging behavior. A positive-feedback loop dependent on the expression of daf-7 from the ASJ neurons acts to promote transitions between roaming and dwelling foraging states and influence the persistence of roaming states. SCD-2, the C. elegans ortholog of mammalian anaplastic lymphoma kinase (ALK), which has been implicated in the central control of metabolism of mammals, functions in the AIA interneurons to regulate foraging behavior and cell-non-autonomously control the expression of DAF-7 from the ASJ neurons. Our data establish how a dynamic neuroendocrine daf-7 expression feedback loop regulated by SCD-2 functions to couple sensing and ingestion of bacterial food to foraging behavior. We further suggest that this neuroendocrine feedback loop underlies previously characterized exploratory behaviors in C. elegans. Our data suggest that the expression of daf-7 from the ASJ neurons contributes to and is correlated with an internal state of 'unmet need' that regulates exploratory foraging behavior in response to bacterial cues in diverse physiological contexts.

Modulation by Neuropeptides with Overlapping Targets Results in Functional Overlap in Oscillatory Circuit Activation

Neuromodulation lends flexibility to neural circuit operation but the general notion that different neuromodulators sculpt neural circuit activity into distinct and characteristic patterns is complicated by interindividual variability. In addition, some neuromodulators converge onto the same signaling pathways, with similar effects on neurons and synapses. We compared the effects of three neuropeptides on the rhythmic pyloric circuit in the stomatogastric ganglion of male crabs, Cancer borealis Proctolin (PROC), crustacean cardioactive peptide (CCAP), and red pigment concentrating hormone (RPCH) activate the same modulatory inward current, I MI, and have convergent actions on synapses. However, while PROC targets all four neuron types in the core pyloric circuit, CCAP and RPCH target the same subset of only two neurons. After removal of spontaneous neuromodulator release, none of the neuropeptides restored the control cycle frequency, but all restored the relative timing between neuron types. Consequently, differences between neuropeptide effects were mainly found in the spiking activity of different neuron types. We performed statistical comparisons using the Euclidean distance in the multidimensional space of normalized output attributes to obtain a single measure of difference between modulatory states. Across preparations, the circuit output in PROC was distinguishable from CCAP and RPCH, but CCAP and RPCH were not distinguishable from each other. However, we argue that even between PROC and the other two neuropeptides, population data overlapped enough to prevent reliable identification of individual output patterns as characteristic for a specific neuropeptide. We confirmed this notion by showing that blind classifications by machine learning algorithms were only moderately successful.Significance Statement It is commonly assumed that distinct behaviors or circuit activities can be elicited by different neuromodulators. Yet it is unknown to what extent these characteristic actions remain distinct across individuals. We use a well-studied circuit model of neuromodulation to examine the effects of three neuropeptides, each known to produce a distinct activity pattern in controlled studies. We find that, when compared across individuals, the three peptides elicit activity patterns that are either statistically indistinguishable or show too much overlap to be labeled characteristic. We ascribe this to interindividual variability and overlapping subcellular actions of the modulators. Because both factors are common in all neural circuits, these findings have broad significance for understanding chemical neuromodulatory actions while considering interindividual variability.

Optimized design and in vivo application of optogenetically functionalized Drosophila dopamine receptors

Neuromodulatory signaling via G protein-coupled receptors (GPCRs) plays a pivotal role in regulating neural network function and animal behavior. The recent development of optogenetic tools to induce G protein-mediated signaling provides the promise of acute and cell type-specific manipulation of neuromodulatory signals. However, designing and deploying optogenetically functionalized GPCRs (optoXRs) with accurate specificity and activity to mimic endogenous signaling in vivo remains challenging. Here we optimize the design of optoXRs by considering evolutionary conserved GPCR-G protein interactions and demonstrate the feasibility of this approach using two Drosophila Dopamine receptors (optoDopRs). These optoDopRs exhibit high signaling specificity and light sensitivity in vitro. In vivo, we show receptor and cell type-specific effects of dopaminergic signaling in various behaviors, including the ability of optoDopRs to rescue the loss of the endogenous receptors. This work demonstrates that optoXRs can enable optical control of neuromodulatory receptor-specific signaling in functional and behavioral studies.

The neuropeptidergic connectome of C. elegans

Efforts are ongoing to map synaptic wiring diagrams, or connectomes, to understand the neural basis of brain function. However, chemical synapses represent only one type of functionally important neuronal connection; in particular, extrasynaptic, "wireless" signaling by neuropeptides is widespread and plays essential roles in all nervous systems. By integrating single-cell anatomical and gene-expression datasets with biochemical analysis of receptor-ligand interactions, we have generated a draft connectome of neuropeptide signaling in the C. elegans nervous system. This network is characterized by high connection density, extended signaling cascades, autocrine foci, and a decentralized topology, with a large, highly interconnected core containing three constituent communities sharing similar patterns of input connectivity. Intriguingly, several key network hubs are little-studied neurons that appear specialized for peptidergic neuromodulation. We anticipate that the C. elegans neuropeptidergic connectome will serve as a prototype to understand how networks of neuromodulatory signaling are organized.

Neuroendocrine Gene Expression Coupling of Interoceptive Bacterial Food Cues to Foraging Behavior of C. elegans

Animal internal state is modulated by nutrient intake, resulting in behavioral responses to changing food conditions. The neural mechanisms by which internal states are generated and maintained are not well understood. Here, we show that in the nematode Caenorhabditis elegans, distinct cues from bacterial food - interoceptive signals from the ingestion of bacteria and gustatory molecules sensed from nearby bacteria - act antagonistically on the expression of the neuroendocrine TGF-beta ligand DAF-7 from the ASJ pair of sensory neurons to modulate foraging behavior. A positive-feedback loop dependent on the expression of daf-7 from the ASJ neurons acts to promote transitions between roaming and dwelling foraging states and influence the persistence of roaming states. SCD-2, the C. elegans ortholog of mammalian Anaplastic Lymphoma Kinase (ALK), which has been implicated in the central control of metabolism of mammals, functions in the AIA interneurons to regulate foraging behavior and cell-non-autonomously control the expression of DAF-7 from the ASJ neurons. Our data establish how a dynamic neuroendocrine daf-7 expression feedback loop regulated by SCD-2 functions to couple sensing and ingestion of bacterial food to foraging behavior. We further suggest that this neuroendocrine feedback loop underlies previously characterized exploratory behaviors in C. elegans. Our data suggest that the expression of daf-7 from the ASJ neurons contributes to and is correlated with an internal state of "unmet need" that regulates exploratory foraging behavior in response to bacterial cues in diverse physiological contexts.

Semantic representation of neural circuit knowledge in Caenorhabditis elegans

In modern biology, new knowledge is generated quickly, making it challenging for researchers to efficiently acquire and synthesise new information from the large volume of primary publications. To address this problem, computational approaches that generate machine-readable representations of scientific findings in the form of knowledge graphs have been developed. These representations can integrate different types of experimental data from multiple papers and biological knowledge bases in a unifying data model, providing a complementary method to manual review for interacting with published knowledge. The Gene Ontology Consortium (GOC) has created a semantic modelling framework that extends individual functional gene annotations to structured descriptions of causal networks representing biological processes (Gene Ontology-Causal Activity Modelling, or GO-CAM). In this study, we explored whether the GO-CAM framework could represent knowledge of the causal relationships between environmental inputs, neural circuits and behavior in the model nematode C. elegans [C. elegans Neural-Circuit Causal Activity Modelling (CeN-CAM)]. We found that, given extensions to several relevant ontologies, a wide variety of author statements from the literature about the neural circuit basis of egg-laying and carbon dioxide (CO2) avoidance behaviors could be faithfully represented with CeN-CAM. Through this process, we were able to generate generic data models for several categories of experimental results. We also discuss how semantic modelling may be used to functionally annotate the C. elegans connectome. Thus, Gene Ontology-based semantic modelling has the potential to support various machine-readable representations of neurobiological knowledge.

Why an animal needs a brain

In Principles of Neural Design (2015, MIT Press), inspired by Charles Darwin, Sterling and Laughlin undertook the unfashionable task of distilling principles from facts in the technique-driven, data-saturated domain of neuroscience. Their starting point for deriving the organizing principles of brains are two brainless single-celled organisms, Escherichia coli and Paramecium, and the 302-neuron brain of the nematode Caenorhabditis elegans. The book is an exemplar in how to connect the dots between simpler and (much) more complex organisms in a particular area. Here, they have generously agreed to republish an abridged version of Chapter 2 (Why an Animal Needs a Brain), in which many of their principles are first described.

Fluctuating landscapes and heavy tails in animal behavior

Animal behavior is shaped by a myriad of mechanisms acting on a wide range of scales. This immense variability hampers quantitative reasoning and renders the identification of universal principles elusive. Through data analysis and theory, we here show that slow non-ergodic drives generally give rise to heavy-tailed statistics in behaving animals. We leverage high-resolution recordings of C. elegans locomotion to extract a self-consistent reduced order model for an inferred reaction coordinate, bridging from sub-second chaotic dynamics to long-lived stochastic transitions among metastable states. The slow mode dynamics exhibits heavy-tailed first passage time distributions and correlation functions, and we show that such heavy tails can be explained by dynamics on a time-dependent potential landscape. Inspired by these results, we introduce a generic model in which we separate faster mixing modes that evolve on a quasi-stationary potential, from slower non-ergodic modes that drive the potential landscape, and reflect slowly varying internal states. We show that, even for simple potential landscapes, heavy tails emerge when barrier heights fluctuate slowly and strongly enough. In particular, the distribution of first passage times and the correlation function can asymptote to a power law, with related exponents that depend on the strength and nature of the fluctuations. We support our theoretical findings through direct numerical simulations.

Using neurons to maintain autonomy: Learning from C. elegans

Understanding how biological organisms are autonomous-maintain themselves far from equilibrium through their own activities-requires understanding how they regulate those activities. In multicellular animals, such control can be exercised either via endocrine signaling through the vasculature or via neurons. In C. elegans this control is exercised by a well-delineated relatively small but distributed nervous system that relies on both chemical and electric transmission of signals. This system provides resources to integrate information from multiple sources as needed to maintain the organism. Especially important for the exercise of neural control are neuromodulators, which we present as setting agendas for control through more traditional electrical signaling. To illustrate how the C. elegans nervous system integrates multiple sources of information in controlling activities important for autonomy, we focus on feeding behavior and responses to adverse conditions. We conclude by considering how a distributed nervous system without a centralized controller is nonetheless adequate for autonomy.

Semantic Representation of Neural Circuit Knowledge in Caenorhabditis elegans

In modern biology, new knowledge is generated quickly, making it challenging for researchers to efficiently acquire and synthesise new information from the large volume of primary publications. To address this problem, computational approaches that generate machine-readable representations of scientific findings in the form of knowledge graphs have been developed. These representations can integrate different types of experimental data from multiple papers and biological knowledge bases in a unifying data model, providing a complementary method to manual review for interacting with published knowledge. The Gene Ontology Consortium (GOC) has created a semantic modelling framework that extends individual functional gene annotations to structured descriptions of causal networks representing biological processes (Gene Ontology Causal Activity Modelling, or GO-CAM). In this study, we explored whether the GO-CAM framework could represent knowledge of the causal relationships between environmental inputs, neural circuits and behavior in the model nematode C. elegans (C. elegans Neural Circuit Causal Activity Modelling (CeN-CAM)). We found that, given extensions to several relevant ontologies, a wide variety of author statements from the literature about the neural circuit basis of egg-laying and carbon dioxide (CO2) avoidance behaviors could be faithfully represented with CeN-CAM. Through this process, we were able to generate generic data models for several categories of experimental results. We also discuss how semantic modelling may be used to functionally annotate the C. elegans connectome. Thus, Gene Ontology-based semantic modelling has the potential to support various machine-readable representations of neurobiological knowledge.

System-wide mapping of peptide-GPCR interactions in C. elegans

Neuropeptides and peptide hormones are ancient, widespread signaling molecules that underpin almost all brain functions. They constitute a broad ligand-receptor network, mainly by binding to G protein-coupled receptors (GPCRs). However, the organization of the peptidergic network and roles of many peptides remain elusive, as our insight into peptide-receptor interactions is limited and many peptide GPCRs are still orphan receptors. Here we report a genome-wide peptide-GPCR interaction map in Caenorhabditis elegans. By reverse pharmacology screening of over 55,384 possible interactions, we identify 461 cognate peptide-GPCR couples that uncover a broad signaling network with specific and complex combinatorial interactions encoded across and within single peptidergic genes. These interactions provide insights into peptide functions and evolution. Combining our dataset with phylogenetic analysis supports peptide-receptor co-evolution and conservation of at least 14 bilaterian peptidergic systems in C. elegans. This resource lays a foundation for system-wide analysis of the peptidergic network.