Rectifying electrical synapses can affect the influence of synaptic modulation on output pattern robustness

Neuropeptide modulation of bidirectional internetwork synapses

Oscillatory networks underlying rhythmic motor behaviors, and sensory and complex neural processing, are flexible, even in their neuronal composition. Neuromodulatory inputs enable neurons to switch participation between networks or participate in multiple networks simultaneously. Neuromodulation of internetwork synapses can both recruit and coordinate a switching neuron in a second network. We previously identified an example in which a neuron is recruited into dual-network activity via peptidergic modulation of intrinsic properties. We now ask whether the same neuropeptide also modulates internetwork synapses for internetwork coordination. The crab (Cancer borealis) stomatogastric nervous system contains two well-defined feeding-related networks (pyloric, food filtering, ∼1 Hz; gastric mill, food chewing, ∼0.1 Hz). The projection neuron MCN5 uses the neuropeptide Gly1-SIFamide to recruit the pyloric-only lateral posterior gastric (LPG) neuron into dual pyloric- plus gastric mill-timed bursting via modulation of LPG's intrinsic properties. Descending input is not required for a coordinated rhythm, thus intranetwork synapses between LPG and its second network must underlie coordination among these neurons. However, synapses between LPG and gastric mill neurons have not been documented. Using two-electrode voltage-clamp recordings, we found that graded synaptic currents between LPG and gastric mill neurons (lateral gastric, inferior cardiac, and dorsal gastric) were primarily negligible in saline, but were enhanced by Gly1-SIFamide. Furthermore, LPG and gastric mill neurons entrain each other during Gly1-SIFamide application, indicating bidirectional, functional connectivity. Thus, a neuropeptide mediates neuronal switching through parallel actions, modulating intrinsic properties for recruitment into a second network and as shown here, also modulating bidirectional internetwork synapses for coordination.NEW & NOTEWORTHY Neuromodulation can enable neurons to simultaneously coordinate with separate networks. Both recruitment into, and coordination with, a second network can occur via modulation of internetwork synapses. Alternatively, recruitment can occur via modulation of intrinsic ionic currents. We find that the same neuropeptide previously determined to modulate intrinsic currents also modulates bidirectional internetwork synapses that are typically ineffective. Thus, complementary modulatory peptide actions enable recruitment and coordination of a neuron into a second network.

Computational modeling predicts regulation of central pattern generator oscillations by size and density of the underlying heterogenous network

Central pattern generators are characterized by a heterogeneous cellular composition, with different cell types playing distinct roles in the production and transmission of rhythmic signals. However, little is known about the functional implications of individual variation in the relative distributions of cells and their connectivity patterns. Here, we addressed this question through a combination of morphological data analysis and computational modeling, using the pacemaker nucleus of the weakly electric fish Apteronotus leptorhynchus as case study. A neural network comprised of 60-110 interconnected pacemaker cells and 15-30 relay cells conveying its output to electromotoneurons in the spinal cord, this nucleus continuously generates neural signals at frequencies of up to 1 kHz with high temporal precision. We systematically explored the impact of network size and density on oscillation frequencies and their variation within and across cells. To accurately determine effect sizes, we minimized the likelihood of complex dynamics using a simplified setup precluding differential delays. To identify natural constraints, parameter ranges were extended beyond experimentally recorded numbers of cells and connections. Simulations revealed that pacemaker cells have higher frequencies and lower within-population variability than relay cells. Within-cell precision and between-cells frequency synchronization increased with the number of pacemaker cells and of connections of either type, and decreased with relay cell count in both populations. Network-level frequency-synchronized oscillations occurred in roughly half of simulations, with maximized likelihood and firing precision within biologically observed parameter ranges. These findings suggest the structure of the biological pacemaker nucleus is optimized for generating synchronized sustained oscillations.

Biological noise is a key determinant of the reproducibility and adaptability of cardiac pacemaking and EC coupling

Each heartbeat begins with the generation of an action potential in pacemaking cells in the sinoatrial node. This signal triggers contraction of cardiac muscle through a process termed excitation-contraction (EC) coupling. EC coupling is initiated in dyadic structures of cardiac myocytes, where ryanodine receptors in the junctional sarcoplasmic reticulum come into close apposition with clusters of CaV1.2 channels in invaginations of the sarcolemma. Cooperative activation of CaV1.2 channels within these clusters causes a local increase in intracellular Ca2+ that activates the juxtaposed ryanodine receptors. A salient feature of healthy cardiac function is the reliable and precise beat-to-beat pacemaking and amplitude of Ca2+ transients during EC coupling. In this review, we discuss recent discoveries suggesting that the exquisite reproducibility of this system emerges, paradoxically, from high variability at subcellular, cellular, and network levels. This variability is attributable to stochastic fluctuations in ion channel trafficking, clustering, and gating, as well as dyadic structure, which increase intracellular Ca2+ variance during EC coupling. Although the effects of these large, local fluctuations in function and organization are sometimes negligible at the macroscopic level owing to spatial-temporal summation within and across cells in the tissue, recent work suggests that the "noisiness" of these intracellular Ca2+ events may either enhance or counterintuitively reduce variability in a context-dependent manner. Indeed, these noisy events may represent distinct regulatory features in the tuning of cardiac contractility. Collectively, these observations support the importance of incorporating experimentally determined values of Ca2+ variance in all EC coupling models. The high reproducibility of cardiac contraction is a paradoxical outcome of high Ca2+ signaling variability at subcellular, cellular, and network levels caused by stochastic fluctuations in multiple processes in time and space. This underlying stochasticity, which counterintuitively manifests as reliable, consistent Ca2+ transients during EC coupling, also allows for rapid changes in cardiac rhythmicity and contractility in health and disease.

Intrinsic Sources and Functional Impacts of Asymmetry at Electrical Synapses

Electrical synapses couple inhibitory neurons across the brain, underlying a variety of functions that are modifiable by activity. Despite recent advances, many functions and contributions of electrical synapses within neural circuitry remain underappreciated. Among these are the sources and impacts of electrical synapse asymmetry. Using multi-compartmental models of neurons coupled through dendritic electrical synapses, we investigated intrinsic factors that contribute to effective synaptic asymmetry and that result in modulation of spike timing and synchrony between coupled cells. We show that electrical synapse location along a dendrite, input resistance, internal dendritic resistance, or directional conduction of the electrical synapse itself each alter asymmetry as measured by coupling between cell somas. Conversely, we note that asymmetrical gap junction (GJ) conductance can be masked by each of these properties. Furthermore, we show that asymmetry modulates spike timing and latency of coupled cells by up to tens of milliseconds, depending on direction of conduction or dendritic location of the electrical synapse. Coordination of rhythmic activity between two cells also depends on asymmetry. These simulations illustrate that causes of asymmetry are diverse, may not be apparent in somatic measurements of electrical coupling, influence dendritic processing, and produce a variety of outcomes on spiking and synchrony of coupled cells. Our findings highlight aspects of electrical synapses that should always be included in experimental demonstrations of coupling, and when assembling simulated networks containing electrical synapses.

Neuronal Switching between Single- and Dual-Network Activity via Modulation of Intrinsic Membrane Properties

Oscillatory networks underlie rhythmic behaviors (e.g., walking, chewing) and complex behaviors (e.g., memory formation, decision-making). Flexibility of oscillatory networks includes neurons switching between single- and dual-network participation, even generating oscillations at two distinct frequencies. Modulation of synaptic strength can underlie this neuronal switching. Here we ask whether switching into dual-frequency oscillations can also result from modulation of intrinsic neuronal properties. The isolated stomatogastric nervous system of male Cancer borealis crabs contains two well-characterized rhythmic feeding-related networks (pyloric, ∼1 Hz; gastric mill, ∼0.1 Hz). The identified modulatory projection neuron MCN5 causes the pyloric-only lateral posterior gastric (LPG) neuron to switch to dual pyloric/gastric mill bursting. Bath applying the MCN5 neuropeptide transmitter Gly¹-SIFamide only partly mimics the LPG switch to dual activity because of continued LP neuron inhibition of LPG. Here, we find that MCN5 uses a cotransmitter, glutamate, to inhibit LP, unlike Gly¹-SIFamide excitation of LP. Thus, we modeled the MCN5-elicited LPG switching with Gly¹-SIFamide application and LP photoinactivation. Using hyperpolarization of pyloric pacemaker neurons and gastric mill network neurons, we found that LPG pyloric-timed oscillations require rhythmic electrical synaptic input. However, LPG gastric mill-timed oscillations do not require any pyloric/gastric mill synaptic input and are voltage-dependent. Thus, we identify modulation of intrinsic properties as an additional mechanism for switching a neuron into dual-frequency activity. Instead of synaptic modulation switching a neuron into a second network as a passive follower, modulation of intrinsic properties could enable a switching neuron to become an active contributor to rhythm generation in the second network.SIGNIFICANCE STATEMENT Neuromodulation of oscillatory networks can enable network neurons to switch from single- to dual-network participation, even when two networks oscillate at distinct frequencies. We used small, well-characterized networks to determine whether modulation of synaptic strength, an identified mechanism for switching, is necessary for dual-network recruitment. We demonstrate that rhythmic electrical synaptic input is required for continued linkage with a "home" network, whereas modulation of intrinsic properties enables a neuron to generate oscillations at a second frequency. Neuromodulator-induced switches in neuronal participation between networks occur in motor, cognitive, and sensory networks. Our study highlights the importance of considering intrinsic properties as a pivotal target for enabling parallel participation of a neuron in two oscillatory networks.

Modeling of sustained spontaneous network oscillations of a sexually dimorphic brainstem nucleus: the role of potassium equilibrium potential

Intrinsic oscillators in the central nervous system play a preeminent role in the neural control of rhythmic behaviors, yet little is known about how the ionic milieu regulates their output patterns. A powerful system to address this question is the pacemaker nucleus of the weakly electric fish Apteronotus leptorhynchus. A neural network comprised of an average of 87 pacemaker cells and 20 relay cells produces tonic oscillations, with higher frequencies in males compared to females. Previous empirical studies have suggested that this sexual dimorphism develops and is maintained through modulation of buffering of extracellular K⁺ by a massive meshwork of astrocytes enveloping the pacemaker and relay cells. Here, we constructed a model of this neural network that can generate sustained spontaneous oscillations. Sensitivity analysis revealed the potassium equilibrium potential, E_K (as a proxy of extracellular K⁺ concentration), and corresponding somatic channel conductances as critical determinants of oscillation frequency and amplitude. In models of both the pacemaker nucleus network and isolated pacemaker and relay cells, the frequency increased almost linearly with E_K, whereas the amplitude decreased nonlinearly with increasing E_K. Our simulations predict that this frequency increase is largely caused by a shift in the minimum K⁺ conductance over one oscillation period. This minimum is close to zero at more negative E_K, converging to the corresponding maximum at less negative E_K. This brings the resting membrane potential closer to the threshold potential at which voltage-gated Na⁺ channels become active, increasing the excitability, and thus the frequency, of pacemaker and relay cells.

Molecular basis of junctional current rectification at an electrical synapse

Rectifying electrical synapses (RESs) exist across animal species, but their rectification mechanism is largely unknown. We investigated why RESs between AVA premotor interneurons and A-type cholinergic motoneurons (A-MNs) in Caenorhabditis elegans escape circuit conduct junctional currents (I j) only in the antidromic direction. These RESs consist of UNC-7 innexin in AVA and UNC-9 innexin in A-MNs. UNC-7 has multiple isoforms differing in the length and sequence of the amino terminus. In a heterologous expression system, only one UNC-7 isoform, UNC-7b, can form heterotypic gap junctions (GJs) with UNC-9 that strongly favor I j in the UNC-9 to UNC-7 direction. Knockout of unc-7b alone almost eliminated the I j, whereas AVA-specific expression of UNC-7b substantially rescued the coupling defect of unc-7 mutant. Neutralizing charged residues in UNC-7b amino terminus abolished the rectification property of UNC-7b/UNC-9 GJs. Our results suggest that the rectification property results from electrostatic interactions between charged residues in UNC-7b amino terminus.

Neuromorphic Dynamical Synapses With Reconfigurable Voltage-Gated Kinetics

OBJECTIVE

Although biological synapses express a large variety of receptors in neuronal membranes, the current hardware implementation of neuromorphic synapses often rely on simple models ignoring the heterogeneity of synaptic transmission. Our objective is to emulate different types of synapses with distinct properties.

METHODS

Conductance-based chemical and electrical synapses were implemented between silicon neurons on a fully programmable and reconfigurable, biophysically realistic neuromorphic VLSI chip. Different synaptic properties were achieved by configuring on-chip digital parameters for the conductances, reversal potentials, and voltage dependence of the channel kinetics. The measured I-V characteristics of the artificial synapses were compared with biological data.

RESULTS

We reproduced the response properties of five different types of chemical synapses, including both excitatory ( AMPA, NMDA) and inhibitory ( GABA_A, GABA_C, glycine) ionotropic receptors. In addition, electrical synapses were implemented in a small network of four silicon neurons.

CONCLUSION

Our work extends the repertoire of synapse types between silicon neurons, providing greater flexibility for the design and implementation of biologically realistic neural networks on neuromorphic chips.

SIGNIFICANCE

A higher synaptic heterogeneity in neuromorphic chips is relevant for the hardware implementation of energy-efficient population codes as well as for dynamic clamp applications where neural models are implemented in neuromorphic VLSI hardware.

Xolotl: An Intuitive and Approachable Neuron and Network Simulator for Research and Teaching

Conductance-based models of neurons are used extensively in computational neuroscience. Working with these models can be challenging due to their high dimensionality and large number of parameters. Here, we present a neuron and network simulator built on a novel automatic type system that binds object-oriented code written in C++ to objects in MATLAB. Our approach builds on the tradition of uniting the speed of languages like C++ with the ease-of-use and feature-set of scientific programming languages like MATLAB. Xolotl allows for the creation and manipulation of hierarchical models with components that are named and searchable, permitting intuitive high-level programmatic control over all parts of the model. The simulator's architecture allows for the interactive manipulation of any parameter in any model, and for visualizing the effects of changing that parameter immediately. Xolotl is fully featured with hundreds of ion channel models from the electrophysiological literature, and can be extended to include arbitrary conductances, synapses, and mechanisms. Several core features like bookmarking of parameters and automatic hashing of source code facilitate reproducible and auditable research. Its ease of use and rich visualization capabilities make it an attractive option in teaching environments. Finally, xolotl is written in a modular fashion, includes detailed tutorials and worked examples, and is freely available at https://github.com/sg-s/xolotl, enabling seamless integration into the workflows of other researchers.

Dopamine maintains network synchrony via direct modulation of gap junctions in the crustacean cardiac ganglion

The Large Cell (LC) motor neurons of the crab cardiac ganglion have variable membrane conductance magnitudes even within the same individual, yet produce identical synchronized activity in the intact network. In a previous study we blocked a subset of K+ conductances across LCs, resulting in loss of synchronous activity (Lane et al., 2016). In this study, we hypothesized that this same variability of conductances makes LCs vulnerable to desynchronization during neuromodulation. We exposed the LCs to serotonin (5HT) and dopamine (DA) while recording simultaneously from multiple LCs. Both amines had distinct excitatory effects on LC output, but only 5HT caused desynchronized output. We further determined that DA rapidly increased gap junctional conductance. Co-application of both amines induced 5HT-like output, but waveforms remained synchronized. Furthermore, DA prevented desynchronization induced by the K+ channel blocker tetraethylammonium (TEA), suggesting that dopaminergic modulation of electrical coupling plays a protective role in maintaining network synchrony.

Innexin expression in electrically coupled motor circuits

The many roles of innexins, the molecules that form gap junctions in invertebrates, have been explored in numerous species. Here, we present a summary of innexin expression and function in two small, central pattern generating circuits found in crustaceans: the stomatogastric ganglion and the cardiac ganglion. The two ganglia express multiple innexin genes, exhibit varying combinations of symmetrical and rectifying gap junctions, as well as gap junctions within and across different cell types. Past studies have revealed correlations in ion channel and innexin expression in coupled neurons, as well as intriguing functional relationships between ion channel conductances and electrical coupling. Together, these studies suggest a putative role for innexins in correlating activity between coupled neurons at the levels of gene expression and physiological activity during development and in the adult animal.

Gap junctional signaling in pattern regulation: Physiological network connectivity instructs growth and form

Gap junctions (GJs) are aqueous channels that allow cells to communicate via physiological signals directly. The role of gap junctional connectivity in determining single-cell functions has long been recognized. However, GJs have another important role: the regulation of large-scale anatomical pattern. GJs are not only versatile computational elements that allow cells to control which small molecule signals they receive and emit, but also establish connectivity patterns within large groups of cells. By dynamically regulating the topology of bioelectric networks in vivo, GJs underlie the ability of many tissues to implement complex morphogenesis. Here, a review of recent data on patterning roles of GJs in growth of the zebrafish fin, the establishment of left-right patterning, the developmental dysregulation known as cancer, and the control of large-scale head-tail polarity, and head shape in planarian regeneration has been reported. A perspective in which GJs are not only molecular features functioning in single cells, but also enable global neural-like dynamics in non-neural somatic tissues has been proposed. This view suggests a rich program of future work which capitalizes on the rapid advances in the biophysics of GJs to exploit GJ-mediated global dynamics for applications in birth defects, regenerative medicine, and morphogenetic bioengineering. © 2016 Wiley Periodicals, Inc. Develop Neurobiol 77: 643-673, 2017.

Functional asymmetry and plasticity of electrical synapses interconnecting neurons through a 36-state model of gap junction channel gating

We combined the Hodgkin–Huxley equations and a 36-state model of gap junction channel gating to simulate electrical signal transfer through electrical synapses. Differently from most previous studies, our model can account for dynamic modulation of junctional conductance during the spread of electrical signal between coupled neurons. The model of electrical synapse is based on electrical properties of the gap junction channel encompassing two fast and two slow gates triggered by the transjunctional voltage. We quantified the influence of a difference in input resistances of electrically coupled neurons and instantaneous conductance–voltage rectification of gap junctions on an asymmetry of cell-to-cell signaling. We demonstrated that such asymmetry strongly depends on junctional conductance and can lead to the unidirectional transfer of action potentials. The simulation results also revealed that voltage spikes, which develop between neighboring cells during the spread of action potentials, can induce a rapid decay of junctional conductance, thus demonstrating spiking activity-dependent short-term plasticity of electrical synapses. This conclusion was supported by experimental data obtained in HeLa cells transfected with connexin45, which is among connexin isoforms expressed in neurons. Moreover, the model allowed us to replicate the kinetics of junctional conductance under different levels of intracellular concentration of free magnesium ([Mg²⁺]_i), which was experimentally recorded in cells expressing connexin36, a major neuronal connexin. We demonstrated that such [Mg²⁺]_i-dependent long-term plasticity of the electrical synapse can be adequately reproduced through the changes of slow gate parameters of the 36-state model. This suggests that some types of chemical modulation of gap junctions can be executed through the underlying mechanisms of voltage gating. Overall, the developed model accounts for direction-dependent asymmetry, as well as for short- and long-term plasticity of electrical synapses. Our modeling results demonstrate that such complex behavior of the electrical synapse is important in shaping the response of coupled neurons.

In most computational models of neuronal networks, it is assumed that electrical synapses have a constant and ohmic conductance. However, numerous experimental studies demonstrate that connexin-based channels expressed in neuronal gap junctions can change their conductance in response to a transjunctional voltage or various chemical reagents. In addition, electrical synapses may exhibit direction-dependent asymmetry of signal transfer. To account for all these phenomena, we combined a 36-state model of gap junction channel gating with Hodgkin–Huxley equations, which describes neuronal excitability. The combined model (HH-36SM) allowed us to evaluate the kinetics of junctional conductance during the spread of electrical signal or in response to chemical factors. Our modeling results, which were based on experimental data, demonstrated that electrical synapses exhibit a complex behavior that can strongly affect the response of coupled neurons. We suggest that the proposed modeling approach is also applicable to describe the behavior of cardiac or other excitable cell networks interconnected through gap junction channels.

Gap Junction Blockers: An Overview of their Effects on Induced Seizures in Animal Models

BACKGROUND

Gap junctions are clusters of intercellular channels allowing the bidirectional pass of ions directly into the cytoplasm of adjacent cells. Electrical coupling mediated by gap junctions plays a role in the generation of highly synchronized electrical activity. The hypersynchronous neuronal activity is a distinctive characteristic of convulsive events. Therefore, it has been postulated that enhanced gap junctional communication is an underlying mechanism involved in the generation and maintenance of seizures. There are some chemical compounds characterized as gap junction blockers because of their ability to disrupt the gap junctional intercellular communication.

OBJECTIVE

Hence, the aim of this review is to analyze the available data concerning the effects of gap junction blockers specifically in seizure models.

RESULTS

Carbenoxolone, quinine, mefloquine, quinidine, anandamide, oleamide, heptanol, octanol, meclofenamic acid, niflumic acid, flufenamic acid, glycyrrhetinic acid and retinoic acid have all been evaluated on animal seizure models. In vitro, these compounds share anticonvulsant effects typically characterized by the reduction of both amplitude and frequency of the epileptiform activity induced in brain slices. In vivo, gap junction blockers modify the behavioral parameters related to seizures induced by 4-aminopyridine, pentylenetetrazole, pilocarpine, penicillin and maximal electroshock.

CONCLUSION

Although more studies are still required, these molecules could be a promising avenue in the search for new pharmaceutical alternatives for the treatment of epilepsy.

Functional contributions of electrical synapses in sensory and motor networks

Intercellular interactions in the nervous system are mediated by two types of dedicated structural arrangements: electrical and chemical synapses. Several characteristics distinguish these two mechanisms of communication, such as speed, reliability and the fact that electrical synapses are, potentially, bidirectional. Given these properties, electrical synapses can subserve, in addition to synchrony, three main interrelated network functions: signal amplification, noise reduction and/or coincidence detection. Specific network motifs in sensory and motor systems of invertebrates and vertebrates illustrate how signal transmission through electrical junctions contributes to a complex processing of information.

Synergistic plasticity of intrinsic conductance and electrical coupling restores synchrony in an intact motor network

Motor neurons of the crustacean cardiac ganglion generate virtually identical, synchronized output despite the fact that each neuron uses distinct conductance magnitudes. As a result of this variability, manipulations that target ionic conductances have distinct effects on neurons within the same ganglion, disrupting synchronized motor neuron output that is necessary for proper cardiac function. We hypothesized that robustness in network output is accomplished via plasticity that counters such destabilizing influences. By blocking high-threshold K⁺ conductances in motor neurons within the ongoing cardiac network, we discovered that compensation both resynchronized the network and helped restore excitability. Using model findings to guide experimentation, we determined that compensatory increases of both G_A and electrical coupling restored function in the network. This is one of the first direct demonstrations of the physiological regulation of coupling conductance in a compensatory context, and of synergistic plasticity across cell- and network-level mechanisms in the restoration of output.

DOI:http://dx.doi.org/10.7554/eLife.16879.001

Neurons can communicate with each other by releasing chemicals called neurotransmitters, or by forming direct connections with each other known as gap junctions. These direct connections allow electrical impulses to flow from one neuron to another via pores in the membranes between the cells. Unlike communication via neurotransmitters, gap junctions are usually thought to be hard-wired and unchanging over the life of the animal.

Lane et al. recorded electrical activity in a network of neurons that generates rhythmic heart contractions in the Jonah crab. Neurons in this network usually all fire an electrical impulse at the same time, which is crucial to make sure that the whole heart contracts at the same time. The experiments show that drugs that block potassium channel pores in the membrane cause the neurons to fire too much and at different times to each other.

However, the network of neurons soon adapted to the changes caused by the drugs and returned to working as normal. Mimicking these changes in a computer model of the neuron network, together with experimental data, showed that changes to the gap junctions play a major role in restoring normal activity to the network.

The next step following on from this research is to understand how a network of neurons ‘senses’ that it is not working normally and changes its electrical activity.

DOI:http://dx.doi.org/10.7554/eLife.16879.002

Complicating connectomes: Electrical coupling creates parallel pathways and degenerate circuit mechanisms

Electrical coupling in circuits can produce non‐intuitive circuit dynamics, as seen in both experimental work from the crustacean stomatogastric ganglion and in computational models inspired by the connectivity in this preparation. Ambiguities in interpreting the results of electrophysiological recordings can arise if sets of pre‐ or postsynaptic neurons are electrically coupled, or if the electrical coupling exhibits some specificity (e.g. rectifying, or voltage‐dependent). Even in small circuits, electrical coupling can produce parallel pathways that can allow information to travel by monosynaptic and/or polysynaptic pathways. Consequently, similar changes in circuit dynamics can arise from entirely different underlying mechanisms. When neurons are coupled both chemically and electrically, modifying the relative strengths of the two interactions provides a mechanism for flexibility in circuit outputs. This, together with neuromodulation of gap junctions and coupled neurons is important both in developing and adult circuits. © 2016 Wiley Periodicals, Inc. Develop Neurobiol 77: 597–609, 2017

Dynamical state of the network determines the efficacy of single neuron properties in shaping the network activity

Spike patterns are among the most common electrophysiological descriptors of neuron types. Surprisingly, it is not clear how the diversity in firing patterns of the neurons in a network affects its activity dynamics. Here, we introduce the state-dependent stochastic bursting neuron model allowing for a change in its firing patterns independent of changes in its input-output firing rate relationship. Using this model, we show that the effect of single neuron spiking on the network dynamics is contingent on the network activity state. While spike bursting can both generate and disrupt oscillations, these patterns are ineffective in large regions of the network state space in changing the network activity qualitatively. Finally, we show that when single-neuron properties are made dependent on the population activity, a hysteresis like dynamics emerges. This novel phenomenon has important implications for determining the network response to time-varying inputs and for the network sensitivity at different operating points.

Reverberation of excitation in neuronal networks interconnected through voltage-gated gap junction channels

Voltage-dependent gap junction gating contributes to reverberation in neuronal circuits.

We combined Hodgkin–Huxley equations and gating models of gap junction (GJ) channels to simulate the spread of excitation in two-dimensional networks composed of neurons interconnected by voltage-gated GJs. Each GJ channel contains two fast and slow gates, each exhibiting current–voltage (I-V) rectification and gating properties that depend on transjunctional voltage (V_j). The data obtained show how junctional conductance (g_j), which is necessary for synchronization of the neuronal network, depends on its size and the intrinsic firing rate of neurons. A phase shift between action potentials (APs) of neighboring neurons creates bipolar, short-lasting V_j spikes of approximately ±100 mV that induce V_j gating, leading to a small decay of g_j, which can accumulate into larger decays during bursting activity of neurons. We show that I-V rectification of GJs in local regions of the two-dimensional network of neurons can lead to unidirectional AP transfer and consequently to reverberation of excitation. This reverberation can be initiated by a single electrical pulse and terminated by a low-amplitude pulse applied in a specific window of reverberation cycle. Thus, the model accounts for the influence of dynamically modulatable electrical synapses in shaping the function of a neuronal network and the formation of reverberation, which, as proposed earlier, may be important for the development of short-term memory and its consolidation into long-term memory.

Opioids potentiate electrical transmission at mixed synapses on the Mauthner cell

Opioid receptors were shown to modulate a variety of cellular processes in the vertebrate central nervous system, including synaptic transmission. While the effects of opioid receptors on chemically mediated transmission have been extensively investigated, little is known of their actions on gap junction-mediated electrical synapses. Here we report that pharmacological activation of mu-opioid receptors led to a long-term enhancement of electrical (and glutamatergic) transmission at identifiable mixed synapses on the goldfish Mauthner cells. The effect also required activation of both dopamine D1/5 receptors and postsynaptic cAMP-dependent protein kinase A, suggesting that opioid-evoked actions are mediated indirectly via the release of dopamine from varicosities known to be located in the vicinity of the synaptic contacts. Moreover, inhibitory inputs situated in the immediate vicinity of these excitatory synapses on the lateral dendrite of the Mauthner cell were not affected by activation of mu-opioid receptors, indicating that their actions are restricted to electrical and glutamatergic transmissions co-existing at mixed contacts. Thus, as their chemical counterparts, electrical synapses can be a target for the modulatory actions of the opioid system. Because gap junctions at these mixed synapses are formed by fish homologs of the neuronal connexin 36, which is widespread in mammalian brain, it is likely that this regulatory property applies to electrical synapses elsewhere as well.

Asymmetry and modulation of spike timing in electrically coupled neurons

Electrical coupling mediates interactions between neurons of the thalamic reticular nucleus (TRN), which play a critical role in regulating thalamocortical and corticothalamic communication by inhibiting thalamic relay cells. Accumulating evidence has shown that asymmetry of electrical synapses is a fundamental and dynamic property, but the effect of asymmetry on coupled networks is unexplored. Recording from patched pairs in rat brain slices, we investigate asymmetry in the subthreshold regime and show that electrical synapses can exert powerful effects on the spike times of coupled neighbors. Electrical synaptic signaling modulates spike timing by 10–20 ms, in an effect that also exhibits asymmetry. Furthermore, we show through modeling that coupling asymmetry expands the set of outputs for pairs of coupled neurons through enhanced regions of synchrony and reversals of spike order. These results highlight the power and specificity of signaling exerted by electrical synapses, which contribute to information flow across the brain.

Computational models in the age of large datasets

Technological advances in experimental neuroscience are generating vast quantities of data, from the dynamics of single molecules to the structure and activity patterns of large networks of neurons. How do we make sense of these voluminous, complex, disparate and often incomplete data? How do we find general principles in the morass of detail? Computational models are invaluable and necessary in this task and yield insights that cannot otherwise be obtained. However, building and interpreting good computational models is a substantial challenge, especially so in the era of large datasets. Fitting detailed models to experimental data is difficult and often requires onerous assumptions, while more loosely constrained conceptual models that explore broad hypotheses and principles can yield more useful insights.

Modulation of a Single Neuron Has State-Dependent Actions on Circuit Dynamics,

We use computational models to examine the circumstances under which modulation of a single neuron can alter the dynamics of an entire circuit. We show that under some circumstances, the circuit's behavior is robust to the neuromodulation of a single hub neuron, while under other circumstances the same neuromodulatory action of a single neuron can produce a large variety of circuit outcomes.

Cover Figure

Robust circuit rhythms in small circuits arise from variable circuit components and mechanisms

Small central pattern generating circuits found in invertebrates have significant advantages for the study of the circuit mechanisms that generate brain rhythms. Experimental and computational studies of small oscillatory circuits reveal that similar rhythms can arise from disparate mechanisms. Animal-to-animal variation in the properties of single neurons and synapses may underly robust circuit performance, and can be revealed by perturbations. Neuromodulation can produce altered circuit performance but also ensure reliable circuit function.

Hemichannel composition and electrical synaptic transmission: molecular diversity and its implications for electrical rectification

Unapposed hemichannels (HCs) formed by hexamers of gap junction proteins are now known to be involved in various cellular processes under both physiological and pathological conditions. On the other hand, less is known regarding how differences in the molecular composition of HCs impact electrical synaptic transmission between neurons when they form intercellular heterotypic gap junctions (GJs). Here we review data indicating that molecular differences between apposed HCs at electrical synapses are generally associated with rectification of electrical transmission. Furthermore, this association has been observed at both innexin and connexin (Cx) based electrical synapses. We discuss the possible molecular mechanisms underlying electrical rectification, as well as the potential contribution of intracellular soluble factors to this phenomenon. We conclude that asymmetries in molecular composition and sensitivity to cellular factors of each contributing hemichannel can profoundly influence the transmission of electrical signals, endowing electrical synapses with more complex functional properties.

Electrical coupling and innexin expression in the stomatogastric ganglion of the crab Cancer borealis

Gap junctions are intercellular channels that allow for the movement of small molecules and ions between the cytoplasm of adjacent cells and form electrical synapses between neurons. In invertebrates, the gap junction proteins are coded for by the innexin family of genes. The stomatogastric ganglion (STG) in the crab Cancer borealis contains a small number of identified and electrically coupled neurons. We identified Innexin 1 (Inx1), Innexin 2 (Inx2), Innexin 3 (Inx3), Innexin 4 (Inx4), Innexin 5 (Inx5), and Innexin 6 (Inx6) members of the C. borealis innexin family. We also identified six members of the innexin family from the lobster Homarus americanus transcriptome. These innexins show significant sequence similarity to other arthropod innexins. Using in situ hybridization and reverse transcriptase-quantitative PCR (RT-qPCR), we determined that all the cells in the crab STG express multiple innexin genes. Electrophysiological recordings of coupling coefficients between identified pairs of pyloric dilator (PD) cells and PD-lateral posterior gastric (LPG) neurons show that the PD-PD electrical synapse is nonrectifying while the PD-LPG synapse is apparently strongly rectifying.

Molecular determinants of magnesium-dependent synaptic plasticity at electrical synapses formed by connexin36

Neuronal gap junction (GJ) channels composed of connexin36 (Cx36) play an important role in neuronal synchronization and network dynamics. Here we show that Cx36-containing electrical synapses between inhibitory neurons of the thalamic reticular nucleus are bidirectionally modulated by changes in intracellular free magnesium concentration ([Mg(2+)]i). Chimeragenesis demonstrates that the first extracellular loop of Cx36 contains a Mg(2+)-sensitive domain, and site-directed mutagenesis shows that the pore-lining residue D47 is critical in determining high Mg(2+)-sensitivity. Single-channel analysis of Mg(2+)-sensitive chimeras and mutants reveals that [Mg(2+)]i controls the strength of electrical coupling mostly via gating mechanisms. In addition, asymmetric transjunctional [Mg(2+)]i induces strong instantaneous rectification, providing a novel mechanism for electrical rectification in homotypic Cx36 GJs. We suggest that Mg(2+)-dependent synaptic plasticity of Cx36-containing electrical synapses could underlie neuronal circuit reconfiguration via changes in brain energy metabolism that affects neuronal levels of intracellular ATP and [Mg(2+)]i.

Activity-dependent feedback regulates correlated ion channel mRNA levels in single identified motor neurons

Neurons generate cell-specific outputs via interactions of conductances carried by ion channel proteins that are homeostatically regulated to maintain key quantitative relationships among subsets of conductances. Given the challenges of both normal channel protein turnover and short-term plasticity, how is the balance of membrane conductances maintained over long-term timescales to ensure stable electrophysiological phenotype? One possible mechanism is to dynamically regulate production of channel protein via feedback that constrains relationships at the channel mRNA level. Recent modeling work has postulated that such mRNA relationships could emerge as a result of activity-dependent homeostatic tuning rules that ensure an appropriate ratio of mRNA for key ion channels is maintained to preserve robust cellular output. Yet, this has never been demonstrated in biological neurons. In this study, we quantified multiple ion channel mRNAs from single identified motor neurons of the stomatogastric ganglion to determine whether correlations among channel mRNAs are actively maintained, and, if so, by what form of feedback. In these neurons, we identified correlations among mRNAs for voltage-gated calcium and potassium channels. By performing experiments that decoupled activity, synaptic connectivity, and neuromodulatory state, we determined that correlated channel mRNAs are maintained by an activity-dependent process. This is the first study to demonstrate that distinct relationships across channel mRNAs are dynamically maintained in an activity-dependent manner. This feedback from cellular activity to coordinated transcriptome-level interactions represents a novel aspect of regulation of neuronal output with implications for long-term stability of neuron function.

Mechanisms of coordination in distributed neural circuits: decoding and integration of coordinating information

We describe the synaptic connections through which information required to coordinate limb movements reaches the modular microcircuits that control individual limbs on different abdominal segments of the crayfish, Pacifastacus leniusculus. In each segmental ganglion, a local commissural interneuron, ComInt 1, integrates information about other limbs and transmits it to one microcircuit. Five types of nonspiking local interneurons are components of each microcircuit's pattern-generating kernel (Smarandache-Wellmann et al., 2013). We demonstrate here, using paired microelectrode recordings, that the pathway through which information reaches this kernel is an electrical synapse between ComInt 1 and one of these five types, an IRSh interneuron. Using single-electrode voltage clamp, we show that brief changes of ComInt 1's membrane potential affect the timing of its microcircuit's motor output. Changing ComInt 1's membrane potential also changes the phase, duration, and strengths of bursts of spikes in its microcircuit's motor neurons and corresponding changes in its efferent coordinating neurons that project to other ganglia. These effects on coordinating neurons cause changes in the phases of motor output from other microcircuits in those distant ganglia. ComInt 1s function as hub neurons in the intersegmental circuit that synchronizes distributed microcircuits. The synapse between each ComInt 1 and its microcircuit's IRSh neuron completes a five synapse pathway in which analog information is encoded as a digital signal by efference-copy neurons and decoded from digital to analog form by ComInt 1. The synaptic organization of this pathway provides a cellular explanation of this nervous system's key dynamic properties.