Invertebrate central pattern generation moves along

Entrainment by transcranial alternating current stimulation: Insights from models of cortical oscillations and dynamical systems theory

Signature of neuronal oscillations can be found in nearly every brain function. However, abnormal oscillatory activity is linked with several brain disorders. Transcranial alternating current stimulation (tACS) is a non-invasive brain stimulation technique that can potentially modulate neuronal oscillations and influence behavior both in health and disease. Yet, a complete understanding of how interacting networks of neurons are affected by tACS remains elusive. Entrainment effects by which tACS synchronizes neuronal oscillations is one of the main hypothesized mechanisms, as evidenced in animals and humans. Computational models of cortical oscillations may shed light on the entrainment effects of tACS, but current modeling studies lack specific guidelines to inform experimental investigations. This study addresses the existing gap in understanding the mechanisms of tACS effects on rhythmogenesis within the brain by providing a comprehensive overview of both theoretical and experimental perspectives. We explore the intricate interactions between oscillators and periodic stimulation through the lens of dynamical systems theory. Subsequently, we present a synthesis of experimental findings that demonstrate the effects of tACS on both individual neurons and collective oscillatory patterns in animal models and humans. Our review extends to computational investigations that elucidate the interplay between tACS and neuronal dynamics across diverse cortical network models. To illustrate these concepts, we conclude with a simple oscillatory neuron model, showcasing how fundamental theories of oscillatory behavior derived from dynamical systems, such as phase response of neurons to external perturbation, can account for the entrainment effects observed with tACS. Studies reviewed here render the necessity of integrated experimental and computational approaches for effective neuromodulation by tACS in health and disease.

Volonté Y, Menezes J, Prüger K, Ibarra J, Arana M, Pérez MS, Veenstra JA, Wegener C, Gontijo AM, Garelli A. Triggering and modulation of a complex behavior by a single peptidergic command neuron in Drosophila

At the end of their growth phase, Drosophila larvae remodel their bodies, glue themselves to a substrate, and harden their cuticle in preparation for metamorphosis. This process-termed pupariation-is triggered by a surge in the hormone ecdysone. Substrate attachment is achieved by a pupariation subprogram called glue expulsion and spreading behavior (GSB). An epidermis-to-CNS Dilp8-Lgr3 relaxin signaling event that occurs downstream of ecdysone is critical for unlocking progression of the pupariation motor program toward GSB, but the factors and circuits acting downstream of Lgr3 signaling remain unknown. Here, using cell-type-specific RNA interference and behavioral monitoring, we identify Myoinhibiting peptide (Mip) as a neuromodulator of multiple GSB action components, such as tetanic contraction, peristaltic contraction alternation, and head-waving. Mip is required in a pair of brain descending neurons, which act temporally downstream of Dilp8-Lgr3 signaling. Mip modulates GSB via ventral nerve cord neurons expressing its conserved receptor, sex peptide receptor (SPR). Silencing of Mip descending neurons by hyperpolarization completely abrogates GSB, while their optogenetic activation at a restricted competence time window triggers GSB-like behavior. Hence, Mip descending neurons have at least two functions: to act as GSB command neurons and to secrete Mip to modulate GSB action components. Our results provide insight into conserved aspects of Mip-SPR signaling in animals, reveal the complexity of GSB control, and contribute to the understanding of how multistep innate behaviors are coordinated in time and with other developmental processes through command neurons and neuropeptidergic signaling.

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.

Analysis methods for large-scale neuronal recordings

Simultaneous recordings from hundreds or thousands of neurons are becoming routine because of innovations in instrumentation, molecular tools, and data processing software. Such recordings can be analyzed with data science methods, but it is not immediately clear what methods to use or how to adapt them for neuroscience applications. We review, categorize, and illustrate diverse analysis methods for neural population recordings and describe how these methods have been used to make progress on longstanding questions in neuroscience. We review a variety of approaches, ranging from the mathematically simple to the complex, from exploratory to hypothesis-driven, and from recently developed to more established methods. We also illustrate some of the common statistical pitfalls in analyzing large-scale neural data.

Milking a spherical cow: Toy models in neuroscience

There are many different kinds of models, and they play many different roles in the scientific endeavour. Neuroscience, and biology more generally, has understandably tended to emphasise empirical models that are grounded in data and make specific, experimentally testable predictions. Meanwhile, strongly idealised or 'toy' models have played a central role in the theoretical development of other sciences such as physics. In this paper, we examine the nature of toy models and their prospects in neuroscience.

Excitation of the abdominal ganglion affects the electrophysiological activity of indirect flight muscles of the honeybee Apis mellifera

Our understanding of the nervous tissues that affect the wing flapping of insects mainly focuses on the brain, but wing flapping is a rhythmic movement related to the central pattern generator in the ventral nerve cord. To verify whether the neural activity of the abdominal ganglion of the honeybee (Apis mellifera) affects the flapping-wing flight, we profiled the response characteristics of indirect flight muscles to abdominal ganglion excitation. Strikingly, a change in the neural activity of ganglion 3 or ganglion 4 has a stronger effect on the electrophysiological activity of indirect flight muscles than that of ganglion 5. The electrophysiological activity of vertical indirect flight muscles is affected more by the change in neural activity of the abdominal ganglion than that of lateral indirect flight muscles. Moreover, the change in neural activity of the abdominal ganglion mainly causes the change in the muscular activity of indirect wing muscles, but the activity patterns change relatively little and there is little change in the complicated details. This work improves our understanding of the neuroregulatory mechanisms associated with the flapping-wing flight of honeybees.

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.

Investigating postsynaptic effects of a Drosophila neuropeptide on muscle contraction

The Drosophila neuropeptide, DPKQDFMRFamide, was previously shown to enhance excitatory junctional potentials (EJPs) and muscle contraction by both presynaptic and postsynaptic actions. Since the peptide acts on both sides of the synaptic cleft, it has been difficult to examine postsynaptic modulatory mechanisms, particularly when contractions are elicited by nerve stimulation. Here, postsynaptic actions are examined in 3rd instar larvae by applying peptide and the excitatory neurotransmitter, l-glutamate, in the bathing solution to elicit contractions after silencing motor output by removing the central nervous system (CNS). DPKQDFMRFamide enhanced glutamate-evoked contractions at low concentrations (EC50 1.3 nM), consistent with its role as a neurohormone, and the combined effect of both substances was supra-additive. Glutamate-evoked contractions were also enhanced when transmitter release was blocked in temperature-sensitive (Shibire) mutants, confirming the peptide's postsynaptic action. The peptide increased membrane depolarization in muscle when co-applied with glutamate, and its effects were blocked by nifedipine, an L-type channel blocker, indicating effects at the plasma membrane involving calcium influx. DPKQDFMRFamide also enhanced contractions induced by caffeine in the absence of extracellular calcium, suggesting increased calcium release from the sarcoplasmic reticulum (SR) or effects downstream of calcium release from the SR. The peptide's effects do not appear to involve calcium/calmodulin-dependent protein kinase II (CaMKII), previously shown to mediate presynaptic effects. The approach used here might be useful for examining postsynaptic effects of neurohormones and cotransmitters in other systems.NEW & NOTEWORTHY Distinguishing presynaptic and postsynaptic effects of neurohormones is a long-standing challenge in many model organisms. Here, postsynaptic actions of DPKQDFMRFamide are demonstrated by assessing its ability to potentiate contractions elicited by direct application of the neurotransmitter, glutamate, when axons are silent and when transmitter release is blocked. The peptide acts at multiple sites to increase contraction, increasing glutamate-induced depolarization at the cell membrane, acting on L-type channels, and acting downstream of calcium release from the sarcoplasmic reticulum.

Switching neuron contributions to second network activity

Network flexibility is important for adaptable behaviors. This includes neuronal switching, where neurons alter their network participation, including changing from single- to dual-network activity. Understanding the implications of neuronal switching requires determining how a switching neuron interacts with each of its networks. Here, we tested 1) whether "home" and second networks, operating via divergent rhythm generation mechanisms, regulate a switching neuron and 2) if a switching neuron, recruited via modulation of intrinsic properties, contributes to rhythm or pattern generation in a new network. Small, well-characterized feeding-related networks (pyloric, ∼1 Hz; gastric mill, ∼0.1 Hz) and identified modulatory inputs make the isolated crab (Cancer borealis) stomatogastric nervous system (STNS) a useful model to study neuronal switching. In particular, the neuropeptide Gly1-SIFamide switches the lateral posterior gastric (LPG) neuron (2 copies) from pyloric-only to dual-frequency pyloric/gastric mill (fast/slow) activity via modulation of LPG-intrinsic properties. Using current injections to manipulate neuronal activity, we found that gastric mill, but not pyloric, network neurons regulated the intrinsically generated LPG slow bursting. Conversely, selective elimination of LPG from both networks using photoinactivation revealed that LPG regulated gastric mill neuron-firing frequencies but was not necessary for gastric mill rhythm generation or coordination. However, LPG alone was sufficient to produce a distinct pattern of network coordination. Thus, modulated intrinsic properties underlying dual-network participation may constrain which networks can regulate switching neuron activity. Furthermore, recruitment via intrinsic properties may occur in modulatory states where it is important for the switching neuron to actively contribute to network output.NEW & NOTEWORTHY We used small, well-characterized networks to investigate interactions between rhythmic networks and neurons that switch their network participation. For a neuron switching into dual-network activity, only the second network regulated its activity in that network. In addition, the switching neuron was sufficient but not necessary to coordinate second network neurons and regulated their activity levels. Thus, regulation of switching neurons may be selective, and a switching neuron is not necessarily simply a follower in additional networks.

Quantitative trait loci underlying a speciation phenotype

Sexual signalling traits and their associated genetic components play a crucial role in the speciation process, as divergence in these traits can contribute to sexual isolation. Despite their importance, our understanding of the genetic basis of variable sexual signalling traits linked to speciation remains limited. In this study, we present new genetic evidence of Quantitative Trait Loci (QTL) underlying divergent sexual signalling behaviour, specifically pulse rate, in the Hawaiian cricket Laupala. By performing RNA sequencing on the brain and central nervous system of the parental species, we annotate these QTL regions and identify candidate genes associated with pulse rate. Our findings provide insights into the genetic processes driving reproductive isolation during speciation, with implications for understanding the mechanisms underlying species diversity.

Interdependence of cellular and network properties in respiratory rhythmogenesis

How breathing is generated by the preBötzinger Complex (preBötC) remains divided between two ideological frameworks, and the persistent sodium current (INaP) lies at the heart of this debate. Although INaP is widely expressed, the pacemaker hypothesis considers it essential because it endows a small subset of neurons with intrinsic bursting or "pacemaker" activity. In contrast, burstlet theory considers INaP dispensable because rhythm emerges from "pre-inspiratory" spiking activity driven by feed-forward network interactions. Using computational modeling, we discover that changes in spike shape can dissociate INaP from intrinsic bursting. Consistent with many experimental benchmarks, conditional effects on spike shape during simulated changes in oxygenation, development, extracellular potassium, and temperature alter the prevalence of intrinsic bursting and pre-inspiratory spiking without altering the role of INaP. Our results support a unifying hypothesis where INaP and excitatory network interactions, but not intrinsic bursting or pre-inspiratory spiking, are critical interdependent features of preBötC rhythmogenesis.

Bridging two insect flight modes in evolution, physiology and robophysics

Since taking flight, insects have undergone repeated evolutionary transitions between two seemingly distinct flight modes1-3. Some insects neurally activate their muscles synchronously with each wingstroke. However, many insects have achieved wingbeat frequencies beyond the speed limit of typical neuromuscular systems by evolving flight muscles that are asynchronous with neural activation and activate in response to mechanical stretch2-8. These modes reflect the two fundamental ways of generating rhythmic movement: time-periodic forcing versus emergent oscillations from self-excitation8-10. How repeated evolutionary transitions have occurred and what governs the switching between these distinct modes remain unknown. Here we find that, despite widespread asynchronous actuation in insects across the phylogeny3,6, asynchrony probably evolved only once at the order level, with many reversions to the ancestral, synchronous mode. A synchronous moth species, evolved from an asynchronous ancestor, still preserves the stretch-activated muscle physiology. Numerical and robophysical analyses of a unified biophysical framework reveal that rather than a dichotomy, these two modes are two regimes of the same dynamics. Insects can transition between flight modes across a bridge in physiological parameter space. Finally, we integrate these two actuation modes into an insect-scale robot11-13 that enables transitions between modes and unlocks a new self-excited wingstroke strategy for engineered flight. Together, this framework accounts for repeated transitions in insect flight evolution and shows how flight modes can flip with changes in physiological parameters.

Predicting the Behavior of Sparsely-Sampled Systems Across Neurobiology and Epidemiology

Inference is a term that encompasses many techniques including statistical data assimilation (SDA). Unlike machine learning, which is designed to harness predictive power from extremely large data sets, SDA is designed for sparsely-sampled systems. This is the realm of study of nonlinear dynamical systems in nature. Formulated as an optimization procedure, SDA can be considered a path-integral approach to state and parameter estimation. Within this formulation, we can use the physical principle of least action to identify optimal solutions: solutions that are consistent with both measurements and a dynamical model assumed to give rise to those measurements. I review examples from neurobiology and an epidemiological model tailored to the coronavirus SARS-CoV-2, to demonstrate the versatility of SDA across the sciences, and how these distinct applications possess commonalities that can inform one another.

Locomotor pattern generation and descending control: a historical perspective

The ability to generate and control locomotor movements depends on complex interactions between many areas of the nervous system, the musculoskeletal system, and the environment. How the nervous system manages to accomplish this task has been the subject of investigation for more than a century. In vertebrates, locomotion is generated by neural networks located in the spinal cord referred to as central pattern generators. Descending inputs from the brain stem initiate, maintain, and stop locomotion as well as control speed and direction. Sensory inputs adapt locomotor programs to the environmental conditions. This review presents a comparative and historical overview of some of the neural mechanisms underlying the control of locomotion in vertebrates. We have put an emphasis on spinal mechanisms and descending control.

Flexible neural control of transition points within the egg-laying behavioral sequence in Drosophila

Innate behaviors are frequently comprised of ordered sequences of component actions that progress to satisfy essential drives. Progression is governed by specialized sensory cues that induce transitions between components within the appropriate context. Here we have characterized the structure of the egg-laying behavioral sequence in Drosophila and found significant variability in the transitions between component actions that affords the organism an adaptive flexibility. We identified distinct classes of interoceptive and exteroceptive sensory neurons that control the timing and direction of transitions between the terminal components of the sequence. We also identified a pair of motor neurons that enact the final transition to egg expulsion. These results provide a logic for the organization of innate behavior in which sensory information processed at critical junctures allows for flexible adjustments in component actions to satisfy drives across varied internal and external environments.

Mechanosensory signal transmission in the arms and the nerve ring, an interarm connective, of Octopus bimaculoides

Octopuses coordinate their arms in a range of complex behaviors. In addition to brain-based sensorimotor integration and control, interarm coordination also occurs through a nerve ring at the arms' base. Here, we examine responses to mechanosensory stimulation of the arms by recording neural activity in the stimulated arm, the nerve ring, and other arms in a preparation of only the ring and arms. Arm axial nerve cords show graded responses to mechanosensory input and activity is transmitted proximally and distally in the arm. Mechanostimulation of one arm generates spiking in the nerve ring and in other arms. Activity in the nerve ring decreases with distance from the stimulated arm. Spontaneous activity with a range of spiking patterns occurs in the axial nerve cords and the nerve ring. These data show rich interarm signaling that supports arm control and coordination occurring outside of the brain.

Dynamic models for musical rhythm perception and coordination

Rhythmicity permeates large parts of human experience. Humans generate various motor and brain rhythms spanning a range of frequencies. We also experience and synchronize to externally imposed rhythmicity, for example from music and song or from the 24-h light-dark cycles of the sun. In the context of music, humans have the ability to perceive, generate, and anticipate rhythmic structures, for example, "the beat." Experimental and behavioral studies offer clues about the biophysical and neural mechanisms that underlie our rhythmic abilities, and about different brain areas that are involved but many open questions remain. In this paper, we review several theoretical and computational approaches, each centered at different levels of description, that address specific aspects of musical rhythmic generation, perception, attention, perception-action coordination, and learning. We survey methods and results from applications of dynamical systems theory, neuro-mechanistic modeling, and Bayesian inference. Some frameworks rely on synchronization of intrinsic brain rhythms that span the relevant frequency range; some formulations involve real-time adaptation schemes for error-correction to align the phase and frequency of a dedicated circuit; others involve learning and dynamically adjusting expectations to make rhythm tracking predictions. Each of the approaches, while initially designed to answer specific questions, offers the possibility of being integrated into a larger framework that provides insights into our ability to perceive and generate rhythmic patterns.

Disexcitation in the ASH/RIM/ADL negative feedback circuit fine-tunes hyperosmotic sensation and avoidance in Caenorhabditis elegans

Sensations, especially nociception, are tightly controlled and regulated by the central and peripheral nervous systems. Osmotic sensation and related physiological and behavioral reactions are essential for animal well-being and survival. In this study, we find that interaction between secondary nociceptive ADL and primary nociceptive ASH neurons upregulates Caenorhabditis elegans avoidance of the mild and medium hyperosmolality of 0.41 and 0.88 Osm but does not affect avoidance of high osmolality of 1.37 and 2.29 Osm. The interaction between ASH and ADL is actualized through a negative feedback circuit consisting of ASH, ADL, and RIM interneurons. In this circuit, hyperosmolality-sensitive ADL augments the ASH hyperosmotic response and animal hyperosmotic avoidance; RIM inhibits ADL and is excited by ASH; thus, ASH exciting RIM reduces ADL augmenting ASH. The neuronal signal integration modality in the circuit is disexcitation. In addition, ASH promotes hyperosmotic avoidance through ASH/RIC/AIY feedforward circuit. Finally, we find that in addition to ASH and ADL, multiple sensory neurons are involved in hyperosmotic sensation and avoidance behavior.

Molecular characterization and functional roles for Vibrio alginolyticus resistance of an octopamine/tyramine receptor of the white shrimp, Litopenaeus vannamei

Octopamine and Tyramine are biogenic amines that have been demonstrated to play an important immunological role in white shrimp, Litopenaeus vannamei. G protein-coupled receptors, known as seven-transmembrane domain receptors, are a variety of neurotransmitter receptors which are sensitive to biogenic amines for initiating the cell signaling pathway. In present study, we cloned and characterized an octopamine/tyramine receptor (LvOA/TA-R) from the hemocytes of L. vannamei, with a 1194 b.p. open reading frame that encodes 398 amino acids. Several bioinformatics analyses indicated that LvOA/TA-R had seven conserved hydrophobic transmembrane domains. The phylogenetic analysis and multiple sequence alignment indicated that LvOA/TA-R was orthologous to the OA/TA receptor of tiger shrimp, P. monodon. LvOA/TA-R was expressed in hemocytes and nervous tissue including circumoesphageal connective tissue and the thoracic and abdominal ganglia. Significant increases in LvOA/TA-R occurred in hemocytes of L. vannamei under Vibrio alginolyticus infection within 30-60 min of infection. Here, we demonstrated that LvOA/TA-R expression is upregulated in response to Vibrio alginolyticus infection and appears to be functionally responsible for the observed immune response. These results suggest that LvOA/TA-R mediates regulation of immunity, which promotes the resistance of L. vannamei to V. alginolyticus.

---Connectomic analysis of the Drosophila lateral neuron clock cells reveals the synaptic basis of functional pacemaker classes

The circadian clock orchestrates daily changes in physiology and behavior to ensure internal temporal order and optimal timing across the day. In animals, a central brain clock coordinates circadian rhythms throughout the body and is characterized by a remarkable robustness that depends on synaptic connections between constituent neurons. The clock neuron network of Drosophila, which shares network motifs with clock networks in the mammalian brain yet is built of many fewer neurons, offers a powerful model for understanding the network properties of circadian timekeeping. Here, we report an assessment of synaptic connectivity within a clock network, focusing on the critical lateral neuron (LN) clock neuron classes within the Janelia hemibrain dataset. Our results reveal that previously identified anatomical and functional subclasses of LNs represent distinct connectomic types. Moreover, we identify a small number of non-clock cell subtypes representing highly synaptically coupled nodes within the clock neuron network. This suggests that neurons lacking molecular timekeeping likely play integral roles within the circadian timekeeping network. To our knowledge, this represents the first comprehensive connectomic analysis of a circadian neuronal network.

Most organisms on Earth possess an internal timekeeping system which ensures that bodily processes such as sleep, wakefulness or digestion take place at the right time. These precise daily rhythms are kept in check by a master clock in the brain. There, thousands of neurons – some of which carrying an internal ‘molecular clock’ – connect to each other through structures known as synapses. Exactly how the resulting network is organised to support circadian timekeeping remains unclear.

To explore this question, Shafer, Gutierrez et al. focused on fruit flies, as recent efforts have systematically mapped every neuron and synaptic connection in the brain of this model organism. Analysing available data from the hemibrain connectome project at Janelia revealed that that the neurons with the most important timekeeping roles were in fact forming the fewest synapses within the network. In addition, neurons without internal molecular clocks mediated strong synaptic connections between those that did, suggesting that ‘clockless’ cells still play an integral role in circadian timekeeping.

With this research, Shafer, Gutierrez et al. provide unexpected insights into the organisation of the master body clock. Better understanding the networks that underpin circadian rhythms will help to grasp how and why these are disrupted in obesity, depression and Alzheimer’s disease.

Cholecystokinin/sulfakinin peptide signaling: conserved roles at the intersection between feeding, mating and aggression

Neuropeptides are the most diverse messenger molecules in metazoans and are involved in regulation of daily physiology and a wide array of behaviors. Some neuropeptides and their cognate receptors are structurally and functionally well conserved over evolution in bilaterian animals. Among these are peptides related to gastrin and cholecystokinin (CCK). In mammals, CCK is produced by intestinal endocrine cells and brain neurons, and regulates gall bladder contractions, pancreatic enzyme secretion, gut functions, satiety and food intake. Additionally, CCK plays important roles in neuromodulation in several brain circuits that regulate reward, anxiety, aggression and sexual behavior. In invertebrates, CCK-type peptides (sulfakinins, SKs) are, with a few exceptions, produced by brain neurons only. Common among invertebrates is that SKs mediate satiety and regulate food ingestion by a variety of mechanisms. Also regulation of secretion of digestive enzymes has been reported. Studies of the genetically tractable fly Drosophila have advanced our understanding of SK signaling mechanisms in regulation of satiety and feeding, but also in gustatory sensitivity, locomotor activity, aggression and reproductive behavior. A set of eight SK-expressing brain neurons plays important roles in regulation of these competing behaviors. In males, they integrate internal state and external stimuli to diminish sex drive and increase aggression. The same neurons also diminish sugar gustation, induce satiety and reduce feeding. Although several functional roles of CCK/SK signaling appear conserved between Drosophila and mammals, available data suggest that the underlying mechanisms differ.

Connexins evolved after early chordates lost innexin diversity

Gap junction channels are formed by two unrelated protein families. Non-chordates use the primordial innexins, while chordates use connexins that superseded the gap junction function of innexins. Chordates retained innexin-homologs, but N-glycosylation prevents them from forming gap junctions. It is puzzling why chordates seem to exclusively use the new gap junction protein and why no chordates should exist that use non-glycosylated innexins to form gap junctions. Here, we identified glycosylation sites of 2388 innexins from 174 non-chordate and 276 chordate species. Among all chordates, we found not a single innexin without glycosylation sites. Surprisingly, the glycosylation motif is also widespread among non-chordate innexins indicating that glycosylated innexins are not a novelty of chordates. In addition, we discovered a loss of innexin diversity during early chordate evolution. Most importantly, lancelets, which lack connexins, exclusively possess only one highly conserved innexin with one glycosylation site. A bottleneck effect might thus explain why connexins have become the only protein used to form chordate gap junctions.

Regulation of excitation-contraction coupling at the Drosophila neuromuscular junction

The Drosophila neuromuscular system is widely used to characterize synaptic development and function. However, little is known about how specific synaptic alterations effect neuromuscular transduction and muscle contractility, which ultimately dictate behavioural output. Here we develop and use a force transducer system to characterize excitation-contraction coupling at Drosophila larval neuromuscular junctions (NMJs), examining how specific neuronal and muscle manipulations disrupt muscle contractility. Muscle contraction force increased with motoneuron stimulation frequency and duration, showing considerable plasticity between 5 and 40 Hz and saturating above 50 Hz. Endogenous recordings of fictive contractions revealed average motoneuron burst frequencies of 20-30 Hz, consistent with the system operating within this plastic range of contractility. Temperature was also a key factor in muscle contractility, as force was enhanced at lower temperatures and dramatically reduced with increasing temperatures. Pharmacological and genetic manipulations of critical components of Ca2+ regulation in both pre- and postsynaptic compartments affected the strength and time course of muscle contractions. A screen for modulators of muscle contractility led to identification and characterization of the molecular and cellular pathway by which the FMRFa peptide, TPAEDFMRFa, increases muscle performance. These findings indicate Drosophila NMJs provide a robust system to correlate synaptic dysfunction, regulation and modulation to alterations in excitation-contraction coupling. KEY POINTS: Larval muscle contraction force increases with stimulation frequency and duration, revealing substantial plasticity between 5 and 40 Hz. Fictive contraction recordings demonstrate endogenous motoneuron burst frequencies consistent with the neuromuscular system operating within the range of greatest plasticity. Genetic and pharmacological manipulations of critical components of pre- and postsynaptic Ca2+ regulation significantly affect the strength and time course of muscle contractions. A screen for modulators of the excitation-contraction machinery identified a FMRFa peptide, TPAEDFMRFa and its associated signalling pathway, that dramatically increases muscle performance. Drosophila serves as an excellent model for dissecting components of the excitation-contraction coupling machinery.

An electrically coupled pioneer circuit enables motor development via proprioceptive feedback in Drosophila embryos

Precocious movements are widely seen in embryos of various animal species. Whether such movements via proprioceptive feedback play instructive roles in motor development or are a mere reflection of activities in immature motor circuits is a long-standing question. Here we image the emerging motor activities in Drosophila embryos that lack proprioceptive feedback and show that proprioceptive experience is essential for the development of locomotor central pattern generators (CPGs). Downstream of proprioceptive inputs, we identify a pioneer premotor circuit composed of two pairs of segmental interneurons, whose gap-junctional transmission requires proprioceptive experience and plays a crucial role in CPG formation. The circuit autonomously generates rhythmic plateau potentials via IP₃-mediated Ca²⁺ release from internal stores, which contribute to muscle contractions and hence produce proprioceptive feedback. Our findings demonstrate the importance of self-generated movements in instructing motor development and identify the cells, circuit, and physiology at the core of this proprioceptive feedback.

Investigating the role of low level reinforcement reflex loops in insect locomotion

Insects are highly capable walkers, but many questions remain regarding how the insect nervous system controls locomotion. One particular question is how information is communicated between the 'lower level' ventral nerve cord (VNC) and the 'higher level' head ganglia to facilitate control. In this work, we seek to explore this question by investigating how systems traditionally described as 'positive feedback' may initiate and maintain stepping in the VNC with limited information exchanged between lower and higher level centers. We focus on the 'reflex reversal' of the stick insect femur-tibia joint between a resistance reflex (RR) and an active reaction in response to joint flexion, as well as the activation of populations of descending dorsal median unpaired (desDUM) neurons from limb strain as our primary reflex loops. We present the development of a neuromechanical model of the stick insect (Carausius morosus) femur-tibia (FTi) and coxa-trochanter joint control networks 'in-the-loop' with a physical robotic limb. The control network generates motor commands for the robotic limb, whose motion and forces generate sensory feedback for the network. We based our network architecture on the anatomy of the non-spiking interneuron joint control network that controls the FTi joint, extrapolated network connectivity based on known muscle responses, and previously developed mechanisms to produce 'sideways stepping'. Previous studies hypothesized that RR is enacted by selective inhibition of sensory afferents from the femoral chordotonal organ, but no study has tested this hypothesis with a model of an intact limb. We found that inhibiting the network's flexion position and velocity afferents generated a reflex reversal in the robot limb's FTi joint. We also explored the intact network's ability to sustain steady locomotion on our test limb. Our results suggested that the reflex reversal and limb strain reinforcement mechanisms are both necessary but individually insufficient to produce and maintain rhythmic stepping in the limb, which can be initiated or halted by brief, transient descending signals. Removing portions of this feedback loop or creating a large enough disruption can halt stepping independent of the higher-level centers. We conclude by discussing why the nervous system might control motor output in this manner, as well as how to apply these findings to generalized nervous system understanding and improved robotic control.

Everything in modulation: neuromodulators as keys to understanding communication dynamics

Across the animal kingdom, the ability to produce communication signals appropriate to social encounters is essential, but how these behaviors are selected and adjusted in a context-dependent manner is poorly understood. This question can be addressed on many levels, including sensory processing by peripheral organs and the CNS, sensorimotor integration in decision-making brain regions, and motor circuit activation and modulation. Because neuromodulator systems act at each of these levels, they are a useful lens through which to explore the mechanisms underlying complex patterns of communication. It has been clear for decades that understanding the logic of input-output decision making by the nervous system requires far more than simply identifying the connections linking sensory organs to motor circuits; this is due in part to the fact that neuromodulators can promote distinct and temporally dynamic responses to similar signals. We focus on the vocal circuit dynamics of Xenopus frogs, and describe complementary examples from diverse vertebrate communication systems. While much remains to be discovered about how neuromodulators direct flexibility in communication behaviors, these examples illustrate that several neuromodulators can act upon the same circuit at multiple levels of control, and that the functional consequence of neuromodulation can depend on species-specific factors as well as dynamic organismal characteristics like internal state.

From Motor-Output to Connectivity: An In-Depth Study of in-vitro Rhythmic Patterns in the Cockroach Periplaneta americana

The cockroach is an established model in the study of locomotion control. While previous work has offered important insights into the interplay among brain commands, thoracic central pattern generators, and the sensory feedback that shapes their motor output, there remains a need for a detailed description of the central pattern generators' motor output and their underlying connectivity scheme. To this end, we monitored pilocarpine-induced activity of levator and depressor motoneurons in two types of novel in-vitro cockroach preparations: isolated thoracic ganglia and a whole-chain preparation comprising the thoracic ganglia and the subesophageal ganglion. Our data analyses focused on the motoneuron firing patterns and the coordination among motoneuron types in the network. The burstiness and rhythmicity of the motoneurons were monitored, and phase relations, coherence, coupling strength, and frequency-dependent variability were analyzed. These parameters were all measured and compared among network units both within each preparation and among the preparations. Here, we report differences among the isolated ganglia, including asymmetries in phase and coupling strength, which indicate that they are wired to serve different functions. We also describe the intrinsic default gait and a frequency-dependent coordination. The depressor motoneurons showed mostly similar characteristics throughout the network regardless of interganglia connectivity; whereas the characteristics of the levator motoneurons activity were mostly ganglion-dependent, and influenced by the presence of interganglia connectivity. Asymmetries were also found between the anterior and posterior homolog parts of the thoracic network, as well as between ascending and descending connections. Our analyses further discover a frequency-dependent inversion of the interganglia coordination from alternations between ipsilateral homolog oscillators to simultaneous activity. We present a detailed scheme of the network couplings, formulate coupling rules, and review a previously suggested model of connectivity in light of our new findings. Our data support the notion that the inter-hemiganglia coordination derives from the levator networks and their coupling with local depressor interneurons. Our findings also support a dominant role of the metathoracic ganglion and its ascending output in governing the anterior ganglia motor output during locomotion in the behaving animal.

Dopamine receptor DOP-1 engages a sleep pathway to modulate swimming in C. elegans

Animals require robust yet flexible programs to support locomotion. Here we report a pathway that connects the D1-like dopamine receptor DOP-1 with a sleep mechanism to modulate swimming in C. elegans. We show that DOP-1 plays a negative role in sustaining swimming behavior. By contrast, a pathway through the D2-like dopamine receptor DOP-3 negatively regulates the initiation of swimming, but its impact fades quickly over a few minutes. We find that DOP-1 and the GPCR kinase (G-protein-coupled receptor kinase-2) function in the sleep interneuron RIS, where DOP-1 modulates the secretion of a sleep neuropeptide FLP-11. We further show that DOP-1 and FLP-11 act in the same pathway to modulate swimming. Together, these results delineate a functional connection between a dopamine receptor and a sleep program to regulate swimming in C. elegans. The temporal transition between DOP-3 and DOP-1 pathways highlights the dynamic nature of neuromodulation for rhythmic movements that persist over time.

The Neurobiology of Ocean Change - insights from decapod crustaceans

The unprecedented rate of carbon dioxide accumulation in the atmosphere has led to increased warming, acidification and oxygen depletion in the world's oceans, with projected impacts also on ocean salinity. In this perspective article, we highlight potential impacts of these factors on neuronal responses in decapod crustaceans. Decapod crustaceans comprise more than 8,800 marine species which have colonized a wide range of habitats that are particularly affected by global ocean change, including estuarine, intertidal, and coastal areas. Many decapod species have large economic value and high ecological importance because of their global invasive potential and impact on local ecosystems. Global warming has already led to considerable changes in decapod species' behavior and habitat range. Relatively little is known about how the decapod nervous system, which is the ultimate driver of all behaviors, copes with environmental stressors. We use select examples to summarize current findings and evaluate the impact of current and expected environmental changes. While data indicate a surprising robustness against stressors like temperature and pH, we find that only a handful of species have been studied and long-term effects on neuronal activity remain mostly unknown. A further conclusion is that the combined effects of multiple stressors are understudied. We call for greater research efforts towards long-term effects on neuronal physiology and expansion of cross-species comparisons to address these issues.

A tale of two leeches: Toward the understanding of the evolution and development of behavioral neural circuits

In the animal kingdom, behavioral traits encompass a broad spectrum of biological phenotypes that have critical roles in adaptive evolution, but an EvoDevo approach has not been broadly used to study behavior evolution. Here, we propose that, by integrating two leech model systems, each of which has already attained some success in its respective field, it is possible to take on behavioral traits with an EvoDevo approach. We first identify the developmental changes that may theoretically lead to behavioral evolution and explain why an EvoDevo study of behavior is challenging. Next, we discuss the pros and cons of the two leech model species, Hirudo, a classic model for invertebrate neurobiology, and Helobdella, an emerging model for clitellate developmental biology, as models for behavioral EvoDevo research. Given the limitations of each leech system, neither is particularly strong for behavioral EvoDevo. However, the two leech systems are complementary in their technical accessibilities, and they do exhibit some behavioral similarities and differences. By studying them in parallel and together with additional leech species such as Haementeria, it is possible to explore the different levels of behavioral development and evolution.

Functional advantages of Lévy walks emerging near a critical point

A special class of random walks, so-called Lévy walks, has been observed in a variety of organisms ranging from cells, insects, fishes, and birds to mammals, including humans. Although their prevalence is considered to be a consequence of natural selection for higher search efficiency, some findings suggest that Lévy walks might also be epiphenomena that arise from interactions with the environment. Therefore, why they are common in biological movements remains an open question. Based on some evidence that Lévy walks are spontaneously generated in the brain and the fact that power-law distributions in Lévy walks can emerge at a critical point, we hypothesized that the advantages of Lévy walks might be enhanced by criticality. However, the functional advantages of Lévy walks are poorly understood. Here, we modeled nonlinear systems for the generation of locomotion and showed that Lévy walks emerging near a critical point had optimal dynamic ranges for coding information. This discovery suggested that Lévy walks could change movement trajectories based on the magnitude of environmental stimuli. We then showed that the high flexibility of Lévy walks enabled switching exploitation/exploration based on the nature of external cues. Finally, we analyzed the movement trajectories of freely moving Drosophila larvae and showed empirically that the Lévy walks may emerge near a critical point and have large dynamic range and high flexibility. Our results suggest that the commonly observed Lévy walks emerge near a critical point and could be explained on the basis of these functional advantages.

Proximate and ultimate causes of ritual behavior

Ritual behaviour, intended as a specific, repetitive and rigid form of action flow, appears both in social and non-social environmental contexts, representing an ubiquitous phenomenon in animal life including human individuals and cultures. The purpose of this contribution is to investigate an evolutionary continuum in proximate and ultimate causes of ritual behavior. A phylogenetic homology in proximal mechanisms can be found, based on the repetition of genetically programmed and/or epigenetically acquired action patterns of behavior. As far as its adaptive significance, ethological comparative studies show that the tendency to ritualization is driven by the unpredictability of social or ecological environmental stimuli. In this perspective, rituals may have a "homeostatic" function over unpredictable environments, as further highlighted by psychopathological compulsions. In humans, a circular loop may have occurred among ritual practices and symbolic activity to deal with a novel culturally-mediated world. However, we suggest that the compulsion to action patterns repetition, typical of all rituals, has a genetically inborn motor foundation, thus precognitive and pre-symbolic. Rooted in such phylogenetically conserved motor structure (proximate causes), the evolution of cognitive and symbolic capacities have generated the complexity of human rituals, though maintaining the original adaptive function (ultimate causes) to cope with unpredictable environments.

A Numerical Study of Metachronal Propulsion at Low to Intermediate Reynolds Numbers

Inspired by the forward swimming of long-tailed crustaceans, we study an underwater propulsion mechanism for a swimming body with multiple rigid paddles attached underneath undergoing cycles of power and return strokes with a constant phase-difference between neighboring paddles, a phenomenon known as metachronal propulsion. To study how inter-paddle phase-difference affects flux production, we develop a computational fluid dynamics model and a numerical algorithm based on the immersed boundary method, which allows us to simulate metachronal propulsion at Reynolds numbers (RE) ranging from close to 0 to about 100. Our main finding is that the highest average flux is generated when nearest-neighbor paddles maintain an approximate 20%–25% phase-difference with the more posterior paddle leading the cycle; this result is independent of stroke frequency across the full range of RE considered here. We also find that the optimal paddle spacing and the number of paddles depend on RE; we see a qualitative transition in the dynamics of flow generated by metachronal propulsion as RE rises above 80. Roughly speaking, in terms of average flux generation, a tight paddle spacing is preferred when RE is less than 10, but a wider spacing becomes clearly favored when RE is close to or above 100. In terms of efficiency of flux generation, at RE 0.1 the maximum efficiency occurs at two paddles, and the efficiency decreases as the number of paddles increases. At RE 100 the efficiency increases as the number of paddles increases, and it appears to saturate by eight paddles, whereas using four paddles is a good tradeoff for both low and intermediate RE.

On the Role of the Head Ganglia in Posture and Walking in Insects

In insects, locomotion is the result of rhythm generating thoracic circuits and their modulation by sensory reflexes and by inputs from the two head ganglia, the cerebral and the gnathal ganglia (GNG), which act as higher order neuronal centers playing different functions in the initiation, goal-direction, and maintenance of movement. Current knowledge on the various roles of major neuropiles of the cerebral ganglia (CRG), such as mushroom bodies (MB) and the central complex (CX), in particular, are discussed as well as the role of the GNG. Thoracic and head ganglia circuitries are connected by ascending and descending neurons. While less is known about the ascending neurons, recent studies in large insects and Drosophila have begun to unravel the identity of descending neurons and their appropriate roles in posture and locomotion. Descending inputs from the head ganglia are most important in initiating and modulating thoracic central pattern generating circuitries to achieve goal directed locomotion. In addition, the review will also deal with some known monoaminergic descending neurons which affect the motor circuits involved in posture and locomotion. In conclusion, we will present a few issues that have, until today, been little explored. For example, how and which descending neurons are selected to engage a specific motor behavior and how feedback from thoracic circuitry modulate the head ganglia circuitries. The review will discuss results from large insects, mainly locusts, crickets, and stick insects but will mostly focus on cockroaches and the fruit fly, Drosophila.

MicroRNAs Regulate Multiple Aspects of Locomotor Behavior in Drosophila

Locomotion is an ancient and fundamental output of the nervous system required for animals to perform many other complex behaviors. Although the formation of motor circuits is known to be under developmental control of transcriptional mechanisms that define the fates and connectivity of the many neurons, glia and muscle constituents of these circuits, relatively little is known about the role of post-transcriptional regulation of locomotor behavior. MicroRNAs have emerged as a potentially rich source of modulators for neural development and function. In order to define the microRNAs required for normal locomotion in Drosophila melanogaster, we utilized a set of transgenic Gal4-dependent competitive inhibitors (microRNA sponges, or miR-SPs) to functionally assess ca. 140 high-confidence Drosophila microRNAs using automated quantitative movement tracking systems followed by multiparametric analysis. Using ubiquitous expression of miR-SP constructs, we identified a large number of microRNAs that modulate aspects of normal baseline adult locomotion. Addition of temperature-dependent Gal80 to identify microRNAs that act during adulthood revealed that the majority of these microRNAs play developmental roles. Comparison of ubiquitous and neural-specific miR-SP expression suggests that most of these microRNAs function within the nervous system. Parallel analyses of spontaneous locomotion in adults and in larvae also reveal that very few of the microRNAs required in the adult overlap with those that control the behavior of larval motor circuits. These screens suggest that a rich regulatory landscape underlies the formation and function of motor circuits and that many of these mechanisms are stage and/or parameter-specific.

Statistical data assimilation for estimating electrophysiology simultaneously with connectivity within a biological neuronal network

A method of data assimilation (DA) is employed to estimate electrophysiological parameters of neurons simultaneously with their synaptic connectivity in a small model biological network. The DA procedure is cast as an optimization, with a cost function consisting of both a measurement error and a model error term. An iterative reweighting of these terms permits a systematic method to identify the lowest minimum, within a local region of state space, on the surface of a nonconvex cost function. In the model, two sets of parameter values are associated with two particular functional modes of network activity: simultaneous firing of all neurons and a pattern-generating mode wherein the neurons burst in sequence. The DA procedure is able to recover these modes if: (i) the stimulating electrical currents have chaotic waveforms and (ii) the measurements consist of the membrane voltages of all neurons in the circuit. Further, this method is able to prune a model of unnecessarily high dimensionality to a representation that contains the maximum dimensionality required to reproduce the provided measurements. This paper offers a proof-of-concept that DA has the potential to inform laboratory designs for estimating properties in small and isolatable functional circuits.

Optimal searching behaviour generated intrinsically by the central pattern generator for locomotion

Efficient searching for resources such as food by animals is key to their survival. It has been proposed that diverse animals from insects to sharks and humans adopt searching patterns that resemble a simple Lévy random walk, which is theoretically optimal for 'blind foragers' to locate sparse, patchy resources. To test if such patterns are generated intrinsically, or arise via environmental interactions, we tracked free-moving Drosophila larvae with (and without) blocked synaptic activity in the brain, suboesophageal ganglion (SOG) and sensory neurons. In brain-blocked larvae, we found that extended substrate exploration emerges as multi-scale movement paths similar to truncated Lévy walks. Strikingly, power-law exponents of brain/SOG/sensory-blocked larvae averaged 1.96, close to a theoretical optimum (µ ≅ 2.0) for locating sparse resources. Thus, efficient spatial exploration can emerge from autonomous patterns in neural activity. Our results provide the strongest evidence so far for the intrinsic generation of Lévy-like movement patterns.

Modelling the mechanics of exploration in larval Drosophila

The Drosophila larva executes a stereotypical exploratory routine that appears to consist of stochastic alternation between straight peristaltic crawling and reorientation events through lateral bending. We present a model of larval mechanics for axial and transverse motion over a planar substrate, and use it to develop a simple, reflexive neuromuscular model from physical principles. The mechanical model represents the midline of the larva as a set of point masses which interact with each other via damped translational and torsional springs, and with the environment via sliding friction forces. The neuromuscular model consists of: 1. segmentally localised reflexes that amplify axial compression in order to counteract frictive energy losses, and 2. long-range mutual inhibition between reflexes in distant segments, enabling overall motion of the model larva relative to its substrate. In the absence of damping and driving, the mechanical model produces axial travelling waves, lateral oscillations, and unpredictable, chaotic deformations. The neuromuscular model counteracts friction to recover these motion patterns, giving rise to forward and backward peristalsis in addition to turning. Our model produces spontaneous exploration, even though the nervous system has no intrinsic pattern generating or decision making ability, and neither senses nor drives bending motions. Ultimately, our model suggests a novel view of larval exploration as a deterministic superdiffusion process which is mechanistically grounded in the chaotic mechanics of the body. We discuss how this may provide new interpretations for existing observations at the level of tissue-scale activity patterns and neural circuitry, and provide some experimental predictions that would test the extent to which the mechanisms we present translate to the real larva.

We investigate the relationship between brain, body and environment in the exploratory behaviour of fruitfly larva. A larva crawls forward by propagating a wave of compression through its segmented body, and changes its crawling direction by bending to one side or the other. We show first that a purely mechanical model of the larva’s body can produce travelling compression waves, sideways bending, and unpredictable, chaotic motions. For this body to locomote through its environment, it is necessary to add a neuromuscular system to counteract the loss of energy due to friction, and to limit the simultaneous compression of segments. These simple additions allow our model larva to generate life-like forward and backward crawling as well as spontaneous turns, which occur without any direct sensing or control of reorientation. The unpredictability inherent in the larva’s physics causes the model to explore its environment, despite the lack of any neural mechanism for rhythm generation or for deciding when to switch from crawling to turning. Our model thus demonstrates how understanding body mechanics can generate and simplify neurobiological hypotheses as to how behaviour arises.

Neuromodulation of central pattern generators and its role in the functional recovery of central pattern generator activity

Neuromodulators play an important role in how the nervous system organizes activity that results in behavior. Disruption of the normal patterns of neuromodulatory release or production is known to be related to the onset of severe pathologies such as Parkinson's disease, Rett syndrome, Alzheimer's disease, and affective disorders. Some of these pathologies involve neuronal structures that are called central pattern generators (CPGs), which are involved in the production of rhythmic activities throughout the nervous system. Here I discuss the interplay between CPGs and neuromodulatory activity, with particular emphasis on the potential role of neuromodulators in the recovery of disrupted neuronal activity. I refer to invertebrate and vertebrate model systems and some of the lessons we have learned from research on these systems and propose a few avenues for future research. I make one suggestion that may guide future research in the field: neuromodulators restrict the parameter landscape in which CPG components operate, and the removal of neuromodulators may enable a perturbed CPG in finding a new set of parameter values that can allow it to regain normal function.

Neural Evolution: Homology in Neuronal Networks

Do behaviors and neuronal networks that control them evolve together in lockstep, or do separate selection processes lead to their evolution? New research, dissecting the swim motor networks in two related nudibranch species, seeks to answer this question.

Short-term synaptic dynamics control the activity phase of neurons in an oscillatory network

In oscillatory systems, neuronal activity phase is often independent of network frequency. Such phase maintenance requires adjustment of synaptic input with network frequency, a relationship that we explored using the crab, Cancer borealis, pyloric network. The burst phase of pyloric neurons is relatively constant despite a > two fold variation in network frequency. We used noise input to characterize how input shape influences burst delay of a pyloric neuron, and then used dynamic clamp to examine how burst phase depends on the period, amplitude, duration, and shape of rhythmic synaptic input. Phase constancy across a range of periods required a proportional increase of synaptic duration with period. However, phase maintenance was also promoted by an increase of amplitude and peak phase of synaptic input with period. Mathematical analysis shows how short-term synaptic plasticity can coordinately change amplitude and peak phase to maximize the range of periods over which phase constancy is achieved.

A short guide to insect oviposition: when, where and how to lay an egg

Egg-laying behavior is one of the most important aspects of female behavior, and has a profound impact on the fitness of a species. As such, it is controlled by several layers of regulation. Here, we review recent advances in our understanding of insect neural circuits that control when, where and how to lay an egg. We also outline outstanding open questions about the control of egg-laying decisions, and speculate on the possible neural underpinnings that can drive the diversification of oviposition behaviors through evolution.

The functional connectivity between the locust leg pattern generators and the subesophageal ganglion higher motor center

Higher motor centers and central pattern generators (CPGs) interact in the control of coordinated leg movements during locomotion throughout the animal kingdom. The subesophageal ganglion (SEG) is one of the insect head ganglia reported to have a role in the control of walking behavior. Here we explored the functional relations between the SEG and the thoracic leg CPGs in the desert locust. Backfill staining revealed about 300 SEG descending interneurons (DINs) altogether. Recordings from an in-vitro isolated chain of thoracic ganglia, with intact or severed connections to the SEG, during pharmacological activation were used to determine how the SEG affects the centrally generated motor output to the legs. The SEG was demonstrated to both activate leg CPGs and synchronize their bilateral activity. The role of the SEG in insect locomotion is discussed in light of these findings.

Functionally asymmetric motor neurons contribute to coordinating locomotion of Caenorhabditis elegans

Locomotion circuits developed in simple animals, and circuit motifs further evolved in higher animals. To understand locomotion circuit motifs, they must be characterized in many models. The nematode Caenorhabditis elegans possesses one of the best-studied circuits for undulatory movement. Yet, for 1/6^th of the cholinergic motor neurons (MNs), the AS MNs, functional information is unavailable. Ventral nerve cord (VNC) MNs coordinate undulations, in small circuits of complementary neurons innervating opposing muscles. AS MNs differ, as they innervate muscles and other MNs asymmetrically, without complementary partners. We characterized AS MNs by optogenetic, behavioral and imaging analyses. They generate asymmetric muscle activation, enabling navigation, and contribute to coordination of dorso-ventral undulation as well as anterio-posterior bending wave propagation. AS MN activity correlated with forward and backward locomotion, and they functionally connect to premotor interneurons (PINs) for both locomotion regimes. Electrical feedback from AS MNs via gap junctions may affect only backward PINs.

Neural mechanisms for sigh generation during prenatal development

The respiratory network of the preBötzinger complex (preBötC), which controls inspiratory behavior, can in normal conditions simultaneously produce two types of inspiration-related rhythmic activities: the eupneic rhythm composed of monophasic, low-amplitude, and relatively high-frequency bursts, interspersed with sigh rhythmic activity, composed of biphasic, high-amplitude, and lower frequency bursts. By combining electrophysiological recordings from transverse brainstem slices with computational modeling, new advances in the mechanisms underlying sigh production have been obtained during prenatal development. The present review summarizes recent findings that establish when sigh rhythmogenesis starts to be produced during embryonic development as well as the cellular, membrane, and synaptic properties required for its expression. Together, the results demonstrate that although generated by the same network, the eupnea and sigh rhythms have different developmental onset times and rely on distinct network properties. Because sighs (also known as augmented breaths) are important in maintaining lung function (by reopening collapsed alveoli), gaining insight into their underlying neural mechanisms at early developmental stages is likely to help in the treatment of prematurely born babies often suffering from breathing deficiencies.

Potential role of a ventral nerve cord central pattern generator in forward and backward locomotion in Caenorhabditis elegans

C. elegans locomotes in an undulatory fashion, generating thrust by propagating dorsoventral bends along its body. Although central pattern generators (CPGs) are typically involved in animal locomotion, their presence in C. elegans has been questioned, mainly because there has been no evident circuit that supports intrinsic network oscillations. With a fully reconstructed connectome, the question of whether it is possible to have a CPG in the ventral nerve cord (VNC) of C. elegans can be answered through computational models. We modeled a repeating neural unit based on segmentation analysis of the connectome. We then used an evolutionary algorithm to determine the unknown physiological parameters of each neuron so as to match the features of the neural traces of the worm during forward and backward locomotion. We performed 1,000 evolutionary runs and consistently found configurations of the neural circuit that produced oscillations matching the main characteristic observed in experimental recordings. In addition to providing an existence proof for the possibility of a CPG in the VNC, we suggest a series of testable hypotheses about its operation. More generally, we show the feasibility and fruitfulness of a methodology to study behavior based on a connectome, in the absence of complete neurophysiological details.