Stomatogastric Ganglion Research Articles

Frequency-Dependent Action of Neuromodulation.

In oscillatory circuits, some actions of neuromodulators depend on the oscillation frequency. However, the mechanisms are poorly understood. We explored this problem by characterizing neuromodulation of the lateral pyloric (LP) neuron of the crab stomatogastric ganglion (STG). Many peptide modulators, including proctolin, activate the same ionic current (IMI) in STG neurons. Because IMI is fast and non-inactivating, its peak level does not depend on the temporal properties of neuronal activity. We found, however, that the amplitude and peak time of the proctolin-activated current in LP is frequency dependent. Because frequency affects the rate of voltage change, we measured these currents with voltage ramps of different slopes and found that proctolin activated two kinetically distinct ionic currents: the known IMI, whose amplitude is independent of ramp slope or direction, and an inactivating current (IMI-T), which was only activated by positive ramps and whose amplitude increased with increasing ramp slope. Using a conductance-based model we found that IMI and IMI-T make distinct contributions to the bursting activity, with IMI increasing the excitability, and IMI-T regulating the burst onset by modifying the postinhibitory rebound in a frequency-dependent manner. The voltage dependence and partial calcium permeability of IMI-T is similar to other characterized neuromodulator-activated currents in this system, suggesting that these are isoforms of the same channel. Our computational model suggests that calcium permeability may allow this current to also activate the large calcium-dependent potassium current in LP, providing an additional mechanism to regulate burst termination. These results demonstrate a mechanism for frequency-dependent actions of neuromodulators.

Perturbation-specific responses by two neural circuits generating similar activity patterns

A fundamental question in neuroscience is whether neuronal circuits with variable circuit parameters that produce similar outputs respond comparably to equivalent perturbations.1-4 Work on the pyloric rhythm of the crustacean stomatogastric ganglion (STG) showed that highly variable sets of intrinsic and synaptic conductances can generate similar circuit activity patterns.5-9 Importantly, in response to physiologically relevant perturbations, these disparate circuit solutions can respond robustly and reliably,10-12 but when exposed to extreme perturbations the underlying circuit parameter differences produce diverse patterns of disrupted activity.7,12,13 In this example, the pyloric circuit is unchanged; only the conductance values vary. In contrast, the gastric mill rhythm in the STG can be generated by distinct circuits when activated by different modulatory neurons and/or neuropeptides.14-21 Generally, these distinct circuits produce different gastric mill rhythms. However, the rhythms driven by stimulating modulatory commissural neuron 1 (MCN1) and bath-applying CabPK (Cancer borealis pyrokinin) peptide generate comparable output patterns, despite having distinct circuits that use separate cellular and synaptic mechanisms.22-25 Here, we use these two gastric mill circuits to determine whether such circuits respond comparably when challenged with persisting (hormonal: CCAP) or acute (sensory: GPR neuron) metabotropic influences. Surprisingly, the hormone-mediated action separates these two rhythms despite activating the same ionic current in the same circuit neuron during both rhythms, whereas the sensory neuron evokes comparable responses despite acting via different synapses during each rhythm. These results highlight the need forcaution when inferring the circuit response to a perturbation when that circuit is not well defined physiologically.

Interrogating theoretical models of neural computation with emergent property inference.

A cornerstone of theoretical neuroscience is the circuit model: a system of equations that captures a hypothesized neural mechanism. Such models are valuable when they give rise to an experimentally observed phenomenon -- whether behavioral or a pattern of neural activity -- and thus can offer insights into neural computation. The operation of these circuits, like all models, critically depends on the choice of model parameters. A key step is then to identify the model parameters consistent with observed phenomena: to solve the inverse problem. In this work, we present a novel technique, emergent property inference (EPI), that brings the modern probabilistic modeling toolkit to theoretical neuroscience. When theorizing circuit models, theoreticians predominantly focus on reproducing computational properties rather than a particular dataset. Our method uses deep neural networks to learn parameter distributions with these computational properties. This methodology is introduced through a motivational example of parameter inference in the stomatogastric ganglion. EPI is then shown to allow precise control over the behavior of inferred parameters and to scale in parameter dimension better than alternative techniques. In the remainder of this work, we present novel theoretical findings in models of primary visual cortex and superior colliculus, which were gained through the examination of complex parametric structure captured by EPI. Beyond its scientific contribution, this work illustrates the variety of analyses possible once deep learning is harnessed towards solving theoretical inverse problems.

Mass spectrometry profiling and quantitation of changes in circulating hormones secreted over time in Cancer borealis hemolymph due to feeding behavior.

The crustacean stomatogastric ganglion (STG) is a valuable model for understanding circuit dynamics in neuroscience as it contains a small number of neurons, all easily distinguishable and most of which contribute to two complementary feeding-related neural circuits. These circuits are modulated by numerous neuropeptides, with many gaining access to the STG as hemolymph-transported hormones. Previous work characterized neuropeptides in the hemolymph of the crab Cancer borealis but was limited by low peptide abundance in the presence of a complex biological matrix and the propensity for rapid peptide degradation. To improve their detection, a data-independent acquisition (DIA) mass spectrometry (MS) method was implemented. This approach improved the number of neuropeptides detected by approximately twofold and showed greater reproducibility between experimental and biological replicates. This method was then used to profile neuropeptides at different stages of the feeding process, including hemolymph from crabs that were unfed, or 0min, 15min, 1h, and 2h post-feeding. The results show differences both in the presence and relative abundance of neuropeptides at the various time points. Additionally, 96 putative neuropeptide sequences were identified with de novo sequencing, indicating there may be more key modulators within this system than is currently known. These results suggest that a distinct cohort of neuropeptides provides modulation to the STG at different times in the feeding process, providing groundwork for targeted follow-up electrophysiological studies to better understand the functional role of circulating hormones in the neural basis of feeding behavior.

FMRF-related peptides in Aedes aegypti midgut: neuromuscular connections and enteric nervous system.

FMRFamide-related peptides (FaRPs) are a class of neuropeptides that participate in a variety of physiological processes in invertebrates. They occur in nerves of stomatogastric ganglia and enteroendocrine cells of the insect digestive tract, where they may control muscle functions. However, their direct involvement in muscle function has never been shown in situ. We studied the relationship between FaRPs and midgut muscle during larval-pupal transition of the mosquito Aedes aegypti. In late L4, FaRP-positive neuronal extensions attach to the bundles of the external circular muscle layer, and muscle stem cells start to undergo mitosis in the internal circular layer. Thereafter, the external muscle layer degenerates, disappearing during early pupal development, and is completely absent in the adult mosquito. Our results indicate that FaRP-based neural signals are involved in the reorganization of the muscle fibers of the mosquito midgut during the larval-pupal transition. In addition to confirming FaRP involvement in muscle function, we show that the mosquito midgut muscles are largely innervated, and that circular and longitudinal muscle have specific neuron bodies associated with them.

Estimating Transfer Entropy in Continuous Time Between Neural Spike Trains or Other Event-Based Data.

Transfer entropy (TE) is a widely used measure of directed information flows in a number of domains including neuroscience. Many real-world time series for which we are interested in information flows come in the form of (near) instantaneous events occurring over time. Examples include the spiking of biological neurons, trades on stock markets and posts to social media, amongst myriad other systems involving events in continuous time throughout the natural and social sciences. However, there exist severe limitations to the current approach to TE estimation on such event-based data via discretising the time series into time bins: it is not consistent, has high bias, converges slowly and cannot simultaneously capture relationships that occur with very fine time precision as well as those that occur over long time intervals. Building on recent work which derived a theoretical framework for TE in continuous time, we present an estimation framework for TE on event-based data and develop a k-nearest-neighbours estimator within this framework. This estimator is provably consistent, has favourable bias properties and converges orders of magnitude more quickly than the current state-of-the-art in discrete-time estimation on synthetic examples. We demonstrate failures of the traditionally-used source-time-shift method for null surrogate generation. In order to overcome these failures, we develop a local permutation scheme for generating surrogate time series conforming to the appropriate null hypothesis in order to test for the statistical significance of the TE and, as such, test for the conditional independence between the history of one point process and the updates of another. Our approach is shown to be capable of correctly rejecting or accepting the null hypothesis of conditional independence even in the presence of strong pairwise time-directed correlations. This capacity to accurately test for conditional independence is further demonstrated on models of a spiking neural circuit inspired by the pyloric circuit of the crustacean stomatogastric ganglion, succeeding where previous related estimators have failed.

Coupling between fast and slow oscillator circuits in Cancer borealis is temperature-compensated.

Coupled oscillatory circuits are ubiquitous in nervous systems. Given that most biological processes are temperature-sensitive, it is remarkable that the neuronal circuits of poikilothermic animals can maintain coupling across a wide range of temperatures. Within the stomatogastric ganglion (STG) of the crab, Cancer borealis, the fast pyloric rhythm (~1 Hz) and the slow gastric mill rhythm (~0.1 Hz) are precisely coordinated at ~11°C such that there is an integer number of pyloric cycles per gastric mill cycle (integer coupling). Upon increasing temperature from 7°C to 23°C, both oscillators showed similar temperature-dependent increases in cycle frequency, and integer coupling between the circuits was conserved. Thus, although both rhythms show temperature-dependent changes in rhythm frequency, the processes that couple these circuits maintain their coordination over a wide range of temperatures. Such robustness to temperature changes could be part of a toolbox of processes that enables neural circuits to maintain function despite global perturbations.

Training deep neural density estimators to identify mechanistic models of neural dynamics.

Mechanistic modeling in neuroscience aims to explain observed phenomena in terms of underlying causes. However, determining which model parameters agree with complex and stochastic neural data presents a significant challenge. We address this challenge with a machine learning tool which uses deep neural density estimators-trained using model simulations-to carry out Bayesian inference and retrieve the full space of parameters compatible with raw data or selected data features. Our method is scalable in parameters and data features and can rapidly analyze new data after initial training. We demonstrate the power and flexibility of our approach on receptive fields, ion channels, and Hodgkin-Huxley models. We also characterize the space of circuit configurations giving rise to rhythmic activity in the crustacean stomatogastric ganglion, and use these results to derive hypotheses for underlying compensation mechanisms. Our approach will help close the gap between data-driven and theory-driven models of neural dynamics.

Circuit dynamics in lobster stomatogastric ganglion based on winnerless competition network

The research of the circuit dynamics of the lobster stomatogastric ganglion (STG) inspires the understanding of the roles that regulates the rhythm of the lobster STG. In this paper, the lobster STG was analyzed by using Winnerless Competition (WLC) network. We got the rhythm of the gastric and pyloric circuits, which is similar to the experimental results, showing abundant firing modes especially the mixed-mode oscillations (MMOs). Firstly, we focused on the inhibitory loops in the STG which show the local dynamic properties of the system. The results show that the firing orders encode the information of these loops, and how the neurons’ spike numbers fluctuate with the change of an external stimulus acting on a neuron in the loops. Secondly, we researched the global dynamic properties of the STG. On the one hand, we discussed on the influence of the gap junction strength to firing results of the whole network. On the other hand, we showed that the WLC network of lobster STG has the potential to display chaos with a positive Lyapunov exponent.

Rapid adaptation to elevated extracellular potassium in the pyloric circuit of the crab, Cancer borealis.

Elevated potassium concentration ([K+]) is often used to alter excitability in neurons and networks by shifting the potassium equilibrium potential (EK) and, consequently, the resting membrane potential. We studied the effects of increased extracellular [K+] on the well-described pyloric circuit of the crab Cancer borealis. A 2.5-fold increase in extracellular [K+] (2.5×[K+]) depolarized pyloric dilator (PD) neurons and resulted in short-term loss of their normal bursting activity. This period of silence was followed within 5-10 min by the recovery of spiking and/or bursting activity during continued superfusion of 2.5×[K+] saline. In contrast, when PD neurons were pharmacologically isolated from pyloric presynaptic inputs, they exhibited no transient loss of spiking activity in 2.5×[K+], suggesting the presence of an acute inhibitory effect mediated by circuit interactions. Action potential threshold in PD neurons hyperpolarized during an hour-long exposure to 2.5×[K+] concurrent with the recovery of spiking and/or bursting activity. Thus the initial loss of activity appears to be mediated by synaptic interactions within the network, but the secondary adaptation depends on changes in the intrinsic excitability of the pacemaker neurons. The complex sequence of events in the responses of pyloric neurons to elevated [K+] demonstrates that electrophysiological recordings are necessary to determine both the transient and longer term effects of even modest alterations of K+ concentrations on neuronal activity.NEW & NOTEWORTHY Solutions with elevated extracellular potassium are commonly used as a depolarizing stimulus. We studied the effects of high potassium concentration ([K+]) on the pyloric circuit of the crab stomatogastric ganglion. A 2.5-fold increase in extracellular [K+] caused a transient loss of activity that was not due to depolarization block, followed by a rapid increase in excitability and recovery of spiking within minutes. This suggests that changing extracellular potassium can have complex and nonstationary effects on neuronal circuits.

Different microcircuit responses to comparable input from one versus both copies of an identified projection neuron.

Neuronal inputs to microcircuits are often present as multiple copies of apparently equivalent neurons. Thus far, however, little is known regarding the relative influence on microcircuit output of activating all or only some copies of such an input. We examine this issue in the crab (Cancer borealis) stomatogastric ganglion, where the gastric mill (chewing) microcircuit is activated by modulatory commissural neuron 1 (MCN1), a bilaterally paired modulatory projection neuron. Both MCN1s contain the same co-transmitters, influence the same gastric mill microcircuit neurons, can drive the biphasic gastric mill rhythm, and are co-activated by all identified MCN1-activating pathways. Here, we determine whether the gastric mill microcircuit response is equivalent when stimulating one or both MCN1s under conditions where the pair are matched to collectively fire at the same overall rate and pattern as single MCN1 stimulation. The dual MCN1 stimulations elicited more consistently coordinated rhythms, and these rhythms exhibited longer phases and cycle periods. These different outcomes from single and dual MCN1 stimulation may have resulted from the relatively modest, and equivalent, firing rate of the gastric mill neuron LG (lateral gastric) during each matched set of stimulations. The LG neuron-mediated, ionotropic inhibition of the MCN1 axon terminals is the trigger for the transition from the retraction to protraction phase. This LG neuron influence on MCN1 was more effective during the dual stimulations, where each MCN1 firing rate was half that occurring during the matched single stimulations. Thus, equivalent individual- and co-activation of a class of modulatory projection neurons does not necessarily drive equivalent microcircuit output.

Molecular profiling of single neurons of known identity in two ganglia from the crab Cancer borealis

Understanding circuit organization depends on identification of cell types. Recent advances in transcriptional profiling methods have enabled classification of cell types by their gene expression. While exceptionally powerful and high throughput, the ground-truth validation of these methods is difficult: If cell type is unknown, how does one assess whether a given analysis accurately captures neuronal identity? To shed light on the capabilities and limitations of solely using transcriptional profiling for cell-type classification, we performed 2 forms of transcriptional profiling-RNA-seq and quantitative RT-PCR, in single, unambiguously identified neurons from 2 small crustacean neuronal networks: The stomatogastric and cardiac ganglia. We then combined our knowledge of cell type with unbiased clustering analyses and supervised machine learning to determine how accurately functionally defined neuron types can be classified by expression profile alone. The results demonstrate that expression profile is able to capture neuronal identity most accurately when combined with multimodal information that allows for post hoc grouping, so analysis can proceed from a supervised perspective. Solely unsupervised clustering can lead to misidentification and an inability to distinguish between 2 or more cell types. Therefore, this study supports the general utility of cell identification by transcriptional profiling, but adds a caution: It is difficult or impossible to know under what conditions transcriptional profiling alone is capable of assigning cell identity. Only by combining multiple modalities of information such as physiology, morphology, or innervation target can neuronal identity be unambiguously determined.

Why is There No Successful Whole Brain Simulation (Yet)?

With the advent of powerful parallel computers, efforts have commenced to simulate complete mammalian brains. However, so far none of these efforts has produced outcomes close to explaining even the behavioral complexities of animals. In this article, we suggest four challenges that ground this shortcoming. First, we discuss the connection between hypothesis testing and simulations. Typically, efforts to simulate complete mammalian brains lack a clear hypothesis. Second, we treat complications related to a lack of parameter constraints for large-scale simulations. To demonstrate the severity of this issue, we review work on two small-scale neural systems, the crustacean stomatogastric ganglion and the Caenorhabditis elegans nervous system. Both of these small nervous systems are very thoroughly, but not completely understood, mainly due to issues with variable and plastic parameters. Third, we discuss the hierarchical structure of neural systems as a principled obstacle to whole-brain simulations. Different organizational levels imply qualitative differences not only in structure, but in choice and appropriateness of investigative technique and perspective. The challenge of reconciling different levels also undergirds the challenge of simulating and hypothesis testing, as modeling a system is not the same thing as simulating it. Fourth, we point out that animal brains are information processing systems tailored very specifically for the ecological niches the respective animals live in.

To what extent may peptide receptor gene diversity/complement contribute to functional flexibility in a simple pattern-generating neural network?

Peptides are known to contribute to central pattern generator (CPG) flexibility throughout the animal kingdom. However, the role played by receptor diversity/complement in determining this functional flexibility is not clear. The stomatogastric ganglion (STG) of the crab, Cancer borealis, contains CPGs that are models for investigating peptidergic control of rhythmic behavior. Although many Cancer peptides have been identified, their peptide receptors are largely unknown. Thus, the extent to which receptor diversity/complement contributes to modulatory flexibility in this system remains unresolved. Here, a Cancer mixed nervous system transcriptome was used to determine the peptide receptor complement for the crab nervous system as a whole. Receptors for 27 peptide families, including multiple receptors for some groups, were identified. To increase confidence in the predicted sequences, receptors for allatostatin-A, allatostatin-B, and allatostatin-C were cloned, sequenced, and expressed in an insect cell line; as expected, all three receptors trafficked to the cell membrane. RT-PCR was used to determine whether each receptor was expressed in the Cancer STG. Transcripts for 36 of the 46 identified receptors were amplified; these included at least one for each peptide family except RYamide. Finally, two peptides untested on the crab STG were assessed for their influence on its motor outputs. Myosuppressin, for which STG receptors were identified, exhibited clear modulatory effects on the motor patterns of the ganglion, while a native RYamide, for which no STG receptors were found, elicited no consistent modulatory effects. These data support receptor diversity/complement as a major contributor to the functional flexibility of CPGs.

Neuronal morphologies built for reliable physiology in a rhythmic motor circuit.

It is often assumed that highly-branched neuronal structures perform compartmentalized computations. However, previously we showed that the Gastric Mill (GM) neuron in the crustacean stomatogastric ganglion (STG) operates like a single electrotonic compartment, despite having thousands of branch points and total cable length >10 mm (Otopalik et al., 2017a; 2017b). Here we show that compact electrotonic architecture is generalizable to other STG neuron types, and that these neurons present direction-insensitive, linear voltage integration, suggesting they pool synaptic inputs across their neuronal structures. We also show, using simulations of 720 cable models spanning a broad range of geometries and passive properties, that compact electrotonus, linear integration, and directional insensitivity in STG neurons arise from their neurite geometries (diameters tapering from 10-20 µm to < 2 µm at their terminal tips). A broad parameter search reveals multiple morphological and biophysical solutions for achieving different degrees of passive electrotonic decrement and computational strategies in the absence of active properties.

Similarities and differences in circuit responses to applied Gly1-SIFamide and peptidergic (Gly1-SIFamide) neuron stimulation.

Microcircuit modulation by peptides is well established, but the cellular/synaptic mechanisms whereby identified neurons with identified peptide transmitters modulate microcircuits remain unknown for most systems. Here, we describe the distribution of GYRKPPFNGSIFamide (Gly1-SIFamide) immunoreactivity (Gly1-SIFamide-IR) in the stomatogastric nervous system (STNS) of the crab Cancer borealis and the Gly1-SIFamide actions on the two feeding-related circuits in the stomatogastric ganglion (STG). Gly1-SIFamide-IR localized to somata in the paired commissural ganglia (CoGs), two axons in the nerves connecting each CoG with the STG, and the CoG and STG neuropil. We identified one Gly1-SIFamide-IR projection neuron innervating the STG as the previously identified modulatory commissural neuron 5 (MCN5). Brief (~10 s) MCN5 stimulation excites some pyloric circuit neurons. We now find that bath applying Gly1-SIFamide to the isolated STG also enhanced pyloric rhythm activity and activated an imperfectly coordinated gastric mill rhythm that included unusually prolonged bursts in two circuit neurons [inferior cardiac (IC), lateral posterior gastric (LPG)]. Furthermore, longer duration (>30 s) MCN5 stimulation activated a Gly1-SIFamide-like gastric mill rhythm, including prolonged IC and LPG bursting. The prolonged LPG bursting decreased the coincidence of its activity with neurons to which it is electrically coupled. We also identified local circuit feedback onto the MCN5 axon terminals, which may contribute to some distinctions between the responses to MCN5 stimulation and Gly1-SIFamide application. Thus, MCN5 adds to the few identified projection neurons that modulate a well-defined circuit at least partly via an identified neuropeptide transmitter and provides an opportunity to study peptide regulation of electrical coupled neurons in a functional context. NEW & NOTEWORTHY Limited insight exists regarding how identified peptidergic neurons modulate microcircuits. We show that the modulatory projection neuron modulatory commissural neuron 5 (MCN5) is peptidergic, containing Gly1-SIFamide. MCN5 and Gly1-SIFamide elicit similar output from two well-defined motor circuits. Their distinct actions may result partly from circuit feedback onto the MCN5 axon terminals. Their similar actions include eliciting divergent activity patterns in normally coactive, electrically coupled neurons, providing an opportunity to examine peptide modulation of electrically coupled neurons in a functional context.

Two central pattern generators from the crab, Cancer borealis, respond robustly and differentially to extreme extracellular pH.

The activity of neuronal circuits depends on the properties of the constituent neurons and their underlying synaptic and intrinsic currents. We describe the effects of extreme changes in extracellular pH - from pH 5.5 to 10.4 - on two central pattern generating networks, the stomatogastric and cardiac ganglia of the crab, Cancer borealis. Given that the physiological properties of ion channels are known to be sensitive to pH within the range tested, it is surprising that these rhythms generally remained robust from pH 6.1 to pH 8.8. The pH sensitivity of these rhythms was highly variable between animals and, unexpectedly, between ganglia. Animal-to-animal variability was likely a consequence of similar network performance arising from variable sets of underlying conductances. Together, these results illustrate the potential difficulty in generalizing the effects of environmental perturbation across circuits, even within the same animal.

Graded Transmission without Action Potentials Sustains Rhythmic Activity in Some But Not All Modulators That Activate the Same Current

Neurons in the central pattern-generating circuits in the crustacean stomatogastric ganglion (STG) release neurotransmitter both as a graded function of presynaptic membrane potential that persists in TTX and in response to action potentials. In the STG of the male crab Cancer borealis, the modulators oxotremorine, C. borealis tachykinin-related peptide Ia (CabTRP1a), red pigment concentrating hormone (RPCH), proctolin, TNRNFLRFamide, and crustacean cardioactive peptide (CCAP) produce and sustain robust pyloric rhythms by activating the same modulatory current (I MI), albeit on different subsets of pyloric network targets. The muscarinic agonist oxotremorine, and the peptides CabTRP1a and RPCH elicited rhythmic triphasic intracellular alternating fluctuations of activity in the presence of TTX. Intracellular waveforms of pyloric neurons in oxotremorine and CabTRP1a in TTX were similar to those in the intact rhythm, and phase relationships among neurons were conserved. Although cycle frequency was conserved in oxotremorine and TTX, it was altered in CabTRP1a in the presence of TTX. Both rhythms were primarily driven by the pacemaker kernel consisting of the Anterior Burster and Pyloric Dilator neurons. In contrast, in TTX the circuit remained silent in proctolin, TNRNFLRFamide, and CCAP. These experiments show that graded synaptic transmission in the absence of voltage-gated Na+ current is sufficient to sustain rhythmic motor activity in some, but not other, modulatory conditions, even when each modulator activates the same ionic current. This further demonstrates that similar rhythmic motor patterns can be produced by qualitatively different mechanisms, one that depends on the activity of voltage-gated Na+ channels, and one that can persist in their absence.SIGNIFICANCE STATEMENT The pyloric rhythm of the crab stomatogastric ganglion depends both on spike-mediated and graded synaptic transmission. We activate the pyloric rhythm with a wide variety of different neuromodulators, all of which converge on the same voltage-dependent inward current. Interestingly, when action potentials and spike-mediated transmission are blocked using TTX, we find that the muscarinic agonist oxotremorine and the neuropeptide CabTRP1a sustain rhythmic alternations and appropriate phases of activity in the absence of action potentials. In contrast, TTX blocks rhythmic activity in the presence of other modulators. This demonstrates fundamental differences in the burst-generation mechanisms in different modulators that would not be suspected on the basis of their cellular actions at the level of the targeted current.

Distinct Co-Modulation Rules of Synapses and Voltage-Gated Currents Coordinate Interactions of Multiple Neuromodulators.

Multiple neuromodulators act in concert to shape the properties of neural circuits. Different neuromodulators usually activate distinct receptors but can have overlapping targets. Therefore, circuit output depends on neuromodulator interactions at shared targets, a poorly understood process. We explored quantitative rules of co-modulation of two principal targets of neuromodulation: synapses and voltage-gated ionic currents. In the stomatogastric ganglion of the male crab Cancer borealis, the neuropeptides proctolin (Proc) and the crustacean cardioactive peptide (CCAP) modulate synapses of the pyloric circuit and activate a voltage-gated current (IMI) in multiple neurons. We examined the validity of a simple dose-dependent quantitative rule, that co-modulation by Proc and CCAP is predicted by the linear sum of the individual effects of each modulator up to saturation. We found that this rule is valid for co-modulation of synapses, but not for the activation of IMI, in which co-modulation was sublinear. The predictions for the co-modulation of IMI activation were greatly improved if we assumed that the intracellular pathways activated by two peptide receptors inhibit one another. These findings suggest that the pathways activated by two neuromodulators could have distinct interactions, leading to distinct co-modulation rules for different targets even in the same neuron. Given the evolutionary conservation of neuromodulator receptors and signaling pathways, such distinct rules for co-modulation of different targets are likely to be common across neuronal circuits.SIGNIFICANCE STATEMENT We examine the quantitative rules of co-modulation at multiple shared targets, the first such characterization to our knowledge. Our results show that dose-dependent co-modulation of distinct targets in the same cells by the same two neuromodulators follows different rules: co-modulation of synaptic currents is linearly additive up to saturation, whereas co-modulation of the voltage-gated ionic current targeted in a single neuron is nonlinear, a mechanism that is likely generalizable. Given that all neural systems are multiply modulated and neuromodulators often act on shared targets, these findings and the methodology could guide studies to examine dynamic actions of neuromodulators at the biophysical and systems level in sensory and motor functions, sleep/wake regulation, and cognition.

Functional Identification and Characterization of the Diuretic Hormone 31 (DH31) Signaling System in the Green Shore Crab, Carcinus maenas.

The functional characterization of crustacean neuropeptides and their cognate receptors has not kept pace with the recent advances in sequence determination and, therefore, our understanding of the physiological roles of neuropeptides in this important arthropod sub-phylum is rather limited. We identified a candidate receptor-ligand pairing for diuretic hormone 31 (DH31) in a neural transcriptome of the crab, Carcinus maenas. In insects, DH31 plays species -specific but central roles in many facets of physiology, including fluid secretion, myoactivity, and gut peristalsis but little is known concerning its functions in crustaceans. The C. maenas DH31 transcript codes for a 147 amino acid prepropeptide, and a single receptor transcript translates to a secretin-like (Class B1) G protein-coupled receptor (GPCR). We used an in vitro aequorin luminescence Ca2+ mobilization assay to demonstrate that this candidate DH31R is activated byCarcinus and insect DH31s in a dose-dependent manner (EC50 15–30 nM). Whole mount immunohistochemical and in situ hybridization localization revealed extensive DH31 expressing neurons throughout the central nervous system, most notably in the abdominal ganglion where large, unpaired cells give rise to medial nerves, which terminate in extensive DH31 immunopositive dendritic fields intimately associated with oesophageal musculature. This system constitutes a large and hitherto undescribed neurohemal area adjacent to key muscle groups associated with the gastric system. DH31 expressing neurons were also seen in the cardiac, commissural, oesophageal, and stomatogastric ganglia and intense labeling was seen in dendrites innervating fore- and hindgut musculature but not with limb muscles. These labeling patterns, together with measurement of DH31R mRNA in the heart and hindgut, prompted us test the effects of DH31 on semi-isolated heart preparations. Cardiac superfusion with peptide evoked increased heart rates (10–100 nM). The neuroanatomical distribution of DH31 and its receptor transcripts, particularly that associated with gastric and cardiac musculature, coupled with the cardio- acceleratory effects of the peptide implicate this peptide in key myoactive roles, likely related to rhythmic coordination.