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Burst discharges in the immature brain may contribute to its enhanced seizure susceptibility. The cellular mechanisms underlying burst discharges in the CA1 area of the immature versus adult hippocampus were investigated with simultaneous wholecell and field-potential recordings. When GABAA receptors were blocked pharmacologically, bursts in CA1 were either graded or all-or-none (or mixed) as a function of electrical stimulation intensity. Most CA1 minislices from immature rats displayed all-or-none or mixed bursts, whereas the slices from adult rats predominantly elicited graded bursts. The frequency and amplitude of spontaneous excitatory postsynaptic currents (sEPSCs) were greater in CA1 pyramidal cells from the immature than the adult slices. The developmental differences in CA1 bursting were also detected in slices adjusted for maturational changes in brain volume (i.e., 350 mm thick for immature vs. 450 mm thick for adult rats). Neither N-methyl-D-aspartate (NMDA) nor group I metabotropic glutamate (mGlu1) receptor antagonists blocked the network-driven bursts in immature CA1, but an a-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor blocker abolished them. Robust excitatory postsynaptic potentials (EPSPs) occurred after bursts in some immature CA1 slices (23%) but never in slices from the adult. The input-output (amount of current injected vs. number of action potentials generated) relationship was markedly greater in CA1 pyramidal cells in the immature compared with the adult hippocampus. These data suggest that the CA1 area of the immature brain is capable of generating network-driven bursts, which declines in adult rats. The increased propensity of burst generation in immature CA1 appears to involve a greater AMPA receptor-mediated synaptic network and an increased intrinsic spike-generating ability. [ABSTRACT FROM AUTHOR]

Place cells develop spatially-tuned receptive fields during the early stages of novel environment exploration. The generative mechanism underlying these spatially-selective responses remains largely elusive, but has been associated with theta rhythmicity. An important factor implicating the transformation of silent cells to place cells is a spatially-uniform depolarization that is mediated by a persistent sodium current. This neuronal current is modulated by extracellular calcium concentration, which, in turn, is actively controlled by astrocytes. However, there is no established relationship between the neuronal depolarization and astrocytic activity. To consider this link, we designed a bioplausible computational model of a neuronal-astrocytic network, where astrocytes induced the transient emergence of place fields in silent cells, and accelerated the plasticity-induced consolidation of place cells. Interestingly, theta oscillations emerged naturally at the network level, resulting from the astrocytic modulation of subcellular neuronal properties. Our results suggest that astrocytes participate in spatial mapping and exploration, and further highlight the computational roles of these cells in the brain. [ABSTRACT FROM AUTHOR]

Networks of spiking neurons with adaption have been shown to be able to reproduce a wide range of neural activities, including the emergent population bursting and spike synchrony that underpin brain disorders and normal function. Exact mean-field models derived from spiking neural networks are extremely valuable, as such models can be used to determine how individual neurons and the network they reside within interact to produce macroscopic network behaviours. In the paper, we derive and analyze a set of exact mean-field equations for the neural network with spike frequency adaptation. Specifically, our model is a network of Izhikevich neurons, where each neuron is modeled by a two dimensional system consisting of a quadratic integrate and fire equation plus an equation which implements spike frequency adaptation. Previous work deriving a mean-field model for this type of network, relied on the assumption of sufficiently slow dynamics of the adaptation variable. However, this approximation did not succeed in establishing an exact correspondence between the macroscopic description and the realistic neural network, especially when the adaptation time constant was not large. The challenge lies in how to achieve a closed set of mean-field equations with the inclusion of the mean-field dynamics of the adaptation variable. We address this problem by using a Lorentzian ansatz combined with the moment closure approach to arrive at a mean-field system in the thermodynamic limit. The resulting macroscopic description is capable of qualitatively and quantitatively describing the collective dynamics of the neural network, including transition between states where the individual neurons exhibit asynchronous tonic firing and synchronous bursting. We extend the approach to a network of two populations of neurons and discuss the accuracy and efficacy of our mean-field approximations by examining all assumptions that are imposed during the derivation. Numerical bifurcation analysis of our mean-field models reveals bifurcations not previously observed in the models, including a novel mechanism for emergence of bursting in the network. We anticipate our results will provide a tractable and reliable tool to investigate the underlying mechanism of brain function and dysfunction from the perspective of computational neuroscience. [ABSTRACT FROM AUTHOR]

Enhancers are central for the regulation of metazoan transcription but have proven difficult to study, primarily due to a myriad of interdependent variables shaping their activity. Consequently, synthetic biology has emerged as the main approach for dissecting mechanisms of enhancer function. We start by reviewing simple but highly parallel reporter assays, which have been successful in quantifying the complexity of the activator/coactivator mechanisms at enhancers. We then describe studies that examine how enhancers function in the genomic context and in combination with other enhancers, revealing that they activate genes through a variety of different mechanisms, working together as a system. Here, we primarily focus on synthetic reporter genes that can quantify the dynamics of enhancer biology through time. We end by considering the consequences of having many genes and enhancers within a 'local environment', which we believe leads to correlated gene expression and likely reports on the general principles of enhancer biology.

Motivated by an attractive problem of elucidating the causes for the occurrence of complex oscillatory regimes in chemical reactions, we study the constructive role of noise in a three-dimensional enzymatic "substrate-two products" model. Stochastic effects are investigated in the parameter zone of birhythmicity where regular oscillatory attractors coexist with chaotic ones. Chaos–order transformations caused by stochastic transitions between these attractors are studied parametrically using the Lyapunov exponents. A special form of stochastic excitement of large-amplitude bursts consisting of the high-frequency spikes is revealed and investigated by statistical analysis. [ABSTRACT FROM AUTHOR]

Noise can shape the firing behaviors of neurons. Here, we show that noise acting on the fast variable of the Hedgehog burster can tune the spike counts of bursts via the self-induced stochastic resonance (SISR) phenomenon. Using the distance matching condition, the critical transition positions on the slow manifolds can be predicted and the stochastic periodic orbits for various noise strengths are obtained. The critical transition positions on the slow manifold with non-monotonic potential differences exhibit a staircase-like dependence on the noise strength, which is also revealed by the stepwise change in the period of the stochastic periodic orbit. The noise-tuned bursting is more coherent within each step while displaying mixed-mode oscillations near the boundaries between the steps. When noise is large enough, noise-induced trapping of the slow variable can be observed, where the number of coexisting traps increases with the noise strength. It is argued that the robustness of SISR underlies the generality of the results discovered in this paper. [ABSTRACT FROM AUTHOR]

The endocrine cells of the anterior pituitary gland are electrically active when stimulated or, in some cases, when not inhibited. The activity pattern thought to be most effective in releasing hormones is bursting, which consists of depolarization with small spikes that are much longer than single spikes. Although a majority of the research on cellular activity patterns has been performed on dispersed cells, the environment in situ is characterized by networks of coupled cells of the same type, at least in the case of somatotrophs and lactotrophs. This produces some degree of synchronization of their activity, which can be greatly increased by hormones and changes in the physiological state. In this computational study, we examine how electrical coupling among model cells influences synchronization of bursting oscillations among the population. We focus primarily on weak electrical coupling, since strong coupling leads to complete synchronization that is not characteristic of pituitary cell networks. We first look at small networks to point out several unexpected behaviors of the coupled system, and then consider a larger random scalefree network to determine what features of the structural network formed through gap junctional coupling among cells produce a high degree of functional coupling, i.e., clusters of synchronized cells. We employ several network centrality measures, and find that cells that are closely related in terms of their closeness centrality are most likely to be synchronized. We also find that structural hubs (cells with extensive coupling to other cells) are typically not functional hubs (cells synchronized with many other cells). Overall, in the case of weak electrical coupling, it is hard to predict the functional network that arises from a structural network, or to use a functional network as a means for determining the structural network that gives rise to it. [ABSTRACT FROM AUTHOR]

Under specific conditions, the fruit on citrus trees will split open. The damaged fruit is unmarketable and provides a habitat for fungal and insect pests that can reproduce and then damage currently marketable fruit. Losses of 30 to over 50 percent of the crop are possible with some cultivars. This is a physiological disorder that starts with nutrient imbalances at flowering that result in mechanically weak areas in the rind. These rupture if interior parts of the fruit expand faster than the peel can stretch. The disconnect between problem initiation and symptom expression provides many challenges to experimental designs and interpretation. Consequently, no solution has been found despite over a century of research into the problem. This is also a problem for growers because they can only see the problem after it is too late to correct. Our goal is to define the problem and highlight successes and failures in finding a solution. The review should help direct continuing research and provide information to extension personnel to help guide growers towards productive solutions. [ABSTRACT FROM AUTHOR]

Neuromodulation is central to the adaptation and robustness of animal nervous systems. This paper explores the classical paradigm of indirect adaptive control to design neuromodulatory controllers in conductance-based neuronal models. The adaptive control of maximal conductance parameters is shown to provide a methodology aligned with the central concepts of neuromodulation in physiology and of impedance control in robotics. [ABSTRACT FROM AUTHOR]

The endocrine cells of the anterior pituitary gland are electrically active when stimulated or, in some cases, when not inhibited. The activity pattern thought to be most effective in releasing hormones is bursting, which consists of depolarization with small spikes that are much longer than single spikes. Although a majority of the research on cellular activity patterns has been performed on dispersed cells, the environment in situ is characterized by networks of coupled cells of the same type, at least in the case of somatotrophs and lactotrophs. This produces some degree of synchronization of their activity, which can be greatly increased by hormones and changes in the physiological state. In this computational study, we examine how electrical coupling among model cells influences synchronization of bursting oscillations among the population. We focus primarily on weak electrical coupling, since strong coupling leads to complete synchronization that is not characteristic of pituitary cell networks. We first look at small networks to point out several unexpected behaviors of the coupled system, and then consider a larger random scale-free network to determine what features of the structural network formed through gap junctional coupling among cells produce a high degree of functional coupling, i.e., clusters of synchronized cells. We employ several network centrality measures, and find that cells that are closely related in terms of their closeness centrality are most likely to be synchronized. We also find that structural hubs (cells with extensive coupling to other cells) are typically not functional hubs (cells synchronized with many other cells). Overall, in the case of weak electrical coupling, it is hard to predict the functional network that arises from a structural network, or to use a functional network as a means for determining the structural network that gives rise to it.

FitzHugh-Nagumo-Rinzel model is an important model for the dynamics of single neuron. We observed some patterns of Bursting specially Mixed Mode Oscillation (MMO) in this model. In some ranges of parameters we can find a robust canard in this system. These phenomena have been observed by many researchers in systems with one fast variable and two slow variables. The interesting point of our work is that our system has one slow variable and two fast variables../files/site1/files/71/6.pdf

We describe a time-resolved nascent single-cell RNA sequencing (RNA-seq) approach that measures gene-specific transcriptional noise and the fraction of active genes in S. cerevisiae. Most genes are expressed with near-constitutive behavior, while a subset of genes show high mRNA variance suggestive of transcription bursting. Transcriptional noise is highest in the cofactor/coactivator-redundant (CR) gene class (dependent on both SAGA and TFIID) and strongest in TATA-containing CR genes. Using this approach, we also find that histone gene transcription switches from a low-level, low-noise constitutive mode during M and M/G1 to an activated state in S phase that shows both an increase in the fraction of active promoters and a switch to a noisy and bursty transcription mode. Rapid depletion of cofactors SAGA and MED Tail indicates that both factors play an important role in stimulating the fraction of active promoters at CR genes, with a more modest role in transcriptional noise. [Display omitted] • Method developed to probe genome-wide transcription noise and promoter activation • Only a subset of yeast mRNAs shows high variance suggestive of bursting • Transcription properties dependent on cofactor response class and promoter type • SAGA and MED Tail function primarily to stimulate the fraction of active promoters Schofield and Hahn use nascent single-cell RNA-seq to investigate transcriptional noise and gene activation. Only a subset of genes shows high mRNA variance suggestive of transcription bursting. Cofactors SAGA and Mediator Tail play an important role in stimulating the fraction of active promoters, with a modest role in transcriptional noise. [ABSTRACT FROM AUTHOR]

We study the exit time of two-dimensional dynamical systems perturbed by a small noise that exhibits two peculiar behaviors: (1) The maximum of the probability density function of trajectories is not located at the point attractor. The distance between the maximum and the attractor increases with the noise amplitude σ , as shown by using WKB approximation and numerical simulations. (2) For such systems, exiting from the basin of attraction is not sufficient to guarantee a full escape, due to trajectories that can return several times inside the basin of attraction after crossing the boundary, before eventually escaping far away. We apply these results to study neuronal networks that can generate bursting events. To analyze interburst durations and their statistics, we study the phase space of a mean-field model, based on synaptic short-term changes, that exhibit burst and interburst dynamics. We find that the interburst corresponds to an escape with multiple reentries inside the basin of attraction. To conclude, escaping far away from a basin of attraction is not equivalent to reaching the boundary, thus providing an explanation for non-Poissonian long interburst durations present in neuronal dynamics. [ABSTRACT FROM AUTHOR]

We report a detailed analysis on the emergence of bursting in a recently developed neural mass model that includes short-term synaptic plasticity. Neural mass models can mimic the collective dynamics of large-scale neuronal populations in terms of a few macroscopic variables like mean membrane potential and firing rate. The present one is particularly important, as it represents an exact meanfield limit of synaptically coupled quadratic integrate and fire (QIF) neurons. Without synaptic dynamics, a periodic external current with slow frequency ε can lead to burst-like dynamics. The firing patterns can be understood using singular perturbation theory, specifically slow–fast dissection. With synaptic dynamics, timescale separation leads to a variety of slow–fast phenomena and their role for bursting becomes inordinately more intricate. Canards are crucial to understand the route to bursting. They describe trajectories evolving nearby repelling locally invariant sets of the system and exist at the transition between subthreshold dynamics and bursting. Near the singular limit ε = 0 , we report peculiar jump-on canards, which block a continuous transition to bursting. In the biologically more plausible ε -regime, this transition becomes continuous and bursts emerge via consecutive spike-adding transitions. The onset of bursting is complex and involves mixed-type-like torus canards, which form the very first spikes of the burst and follow fast-subsystem repelling limit cycles. We numerically evidence the same mechanisms to be responsible for bursting emergence in the QIF network with plastic synapses. The main conclusions apply for the network, owing to the exactness of the meanfield limit. [ABSTRACT FROM AUTHOR]

To conduct an in‐depth analysis of the bursting of coal slime in its early stage of combustion, a high‐speed camera was used to film the bursting process in a horizontal tube furnace. Three different types of coal slime with water contents of 5%, 10%, 15%, and 20% under different temperatures of 750°C, 850°C, and 950°C were tested. The behavior of coal slime bursting and the influence of water content and temperature were obtained. It appears that there is a critical water content and a deduced range to determine primary bursting intensity. The bursting intensity index (BII) increases with furnace temperature and water content. So a comprehensive consideration of temperature and water content is crucial for industrial design. To investigate influence induced by the bursting, analysis of the micromorphology and pore structure changes of the coal slime samples before and after bursting at 850°C has been done and shows that the coal slime structure after bursting changes greatly compared with the original state of the coal slime. The calculation results of the fractal dimension show that the pore structure of coal slime after bursting becomes more complicated, and the portion of pores in the coal slime generally increases after bursting. [ABSTRACT FROM AUTHOR]

In the present study, two sets (I and II) of needle-punched nonwoven fabrics using virgin and recycled polyester fibers were prepared varying machine parameters. In the set first (set I) three different parameters namely grams/m2 (GSM), needling density and blend ratio with three different levels and in the second set (set II) three different parameters, i.e. calender roller pressure, calender roller temperature and calender roller speed with three different levels were used. For the first set fabrics, it has been seen that the bursting strength increased with the increase in GSM, needling density as well increased virgin polyester fiber in the blend. In the second set increase in calender roller pressure, roller temperature caused increase in bursting strength, but with the increase in roller speed it decreased. The comparison of both sets fabric revealed that set II fabric formation is economical since there is less consumption of polyester fibers. The investigation of two arrangements of fabrics uncovers that legal choice of calendering parameters may result economical nonwoven fabrics by requiring lesser fibrous strands for the assembling of needle bonded fabrics, moreover it will lessen the contamination by using the waste polyester bottles additionally the reliance on normal oil-based virgin polyester will be reduced. [ABSTRACT FROM AUTHOR]

Mechanical properties of textile fabric are one of the most important parameters of fabric in the selection of appropriate fabric for clothing industries. The main aim of this paper is to study the effect of the tension applied during weaving on tear, tensile, and bursting strength of plain woven cotton fabric. Five plain woven cotton fabrics were produced on an air-jet loom at different tension levels (0.9KN, 1.3KN, 1.6KN, 2KN, and 2.3KN). The results obtained from ANOVA and bar chart showed that as the tension of the warp yarn and the fabric increase during weaving, the tear strength, tensile strength, and bursting strength of the plain cotton woven fabric decreased significantly. The effect is more noticeable in the warp direction of the fabric for tear and tensile strength as the tension was applied in the warp direction. [ABSTRACT FROM AUTHOR]

Theoretical results obtained within the framework of the weakly nonlinear model of a developed boundary layer in a flow past a narrow flat plate are verified with the use of methods of direct numerical simulation of the Navier–Stokes equations. The mechanism of gas ejection (bursting) from the surface of a thermally insulated plate in a supersonic gas flow with the Mach number M = 2 is studied within the framework of the model of complete nonlinear interaction. It is demonstrated that the transition from the laminar to turbulent flow past the plate in the case of weak external perturbations occurs due to resonant three-wave interaction. Theoretical results relating the energy redistribution between the oscillations and the process of spatial structure formation are confirmed. [ABSTRACT FROM AUTHOR]

Biochemical reaction systems, in particular those that govern the expression of genes in single cells, involve discrete numbers of molecules and are inherently stochastic. This study concerns reaction systems with two molecular species and an arbitrary number of reactions, the rates of which conform to a scaling of the classical type in the first species (but not the second). For limiting values of the scaling parameter, the first species is highly abundant, evolves slowly, and buffers the relatively fast fluctuation of the second, scarce, species. The scale separation facilitates the construction of asymptotic approximations to the molecular distributions: the large-time behavior is described by a WKB approximation, which is further resolved into a tractable mixture of metastable modes; the earlier-time dynamics are described by quasi-stationary and linear noise approximations. The paper presents the theory and the algebraic recipes that are required to implement it. The framework is applied on two reaction systems with positive feedback: a delayed feedback circuit and a gene autoregulation model with cooperative binding of the protein to the promoter. For the former, the approximation scheme results into a mixture of Gaussian/Poisson modes for the inactive/active protein distribution. For the latter, the analysis elucidates the effects of bursty gene expression, promoter responsivity, and protein sequestration on bimodality of protein distributions. [ABSTRACT FROM AUTHOR]

The expression of individual genes into functional protein molecules is a noisy dynamical process. Here we model the protein concentration as a jump-drift process which combines discrete stochastic production bursts (jumps) with continuous deterministic decay (drift). We allow the drift rate, the jump rate, and the jump size to depend on the protein level to implement feedback in protein stability, burst frequency, and burst size. We specifically focus on positive feedback in burst size, while allowing for arbitrary autoregulation in burst frequency and protein stability. Two versions of feedback in burst size are thereby considered: in the first, newly produced molecules instantly participate in feedback, even within the same burst; in the second, within-burst regulation does not occur due to the so-called infinitesimal delay. Without infinitesimal delay, the model is explicitly solvable; with its inclusion, an exact distribution to the model is unavailable, but we are able to construct a WKB approximation that applies in the asymptotic regime of small but frequent bursts. Comparing the asymptotic behaviour of the two model versions, we report that they yield the same WKB quasi-potential but a different exponential prefactor. We illustrate the difference on the case of a bimodal protein distribution sustained by a sigmoid feedback in burst size: we show that the omission of the infinitesimal delay overestimates the weight of the upper mode of the protein distribution. The analytic results are supported by kinetic Monte-Carlo simulations. [ABSTRACT FROM AUTHOR]

The pancreatic islets of Langerhans are biomedically important because they are home to the beta cells that secrete insulin and are hence important for understanding diabetes. They are also an important case study for the mechanisms of bursting oscillations and how these oscillations emerge from the electrical coupling of highly heterogeneous cells. Early work has pointed to a voting/democratic paradigm, where the islet properties are a nonlinear average of the cell properties, with no 'conductor leading the orchestra'. Recent experimental work has uncovered new facets of this heterogeneity, and has identified small world networks dominated by a small subset of cells with a high degree of functional connectivity, assessed via correlations of calcium oscillations. It has also been suggested that these connectivity hubs act as pacemakers necessary for islet oscillations. We reviewed modeling studies that have confirmed the existence of small worldness, and we did not find evidence for obligatory pacemakers. We conclude that democracy rather than oligarchy remains the most likely organizing principle of the islets. [ABSTRACT FROM AUTHOR]

Developing spinal motor networks produce a diverse array of outputs, including episodic and continuous patterns of rhythmic activity. Variation in excitability state and neuromodulatory tone can facilitate transitions between episodic and continuous rhythms; however, the intrinsic mechanisms that govern these rhythms and their transitions are poorly understood. Here, we tested the capacity of a single central pattern generator (CPG) circuit with tunable properties to generate multiple outputs. To address this, we deployed a computational model composed of an inhibitory half-center oscillator (HCO). Following predictions of our computational model, we tested the contributions of key properties to the generation of an episodic rhythm produced by isolated spinal cords of the newborn mouse. The model recapitulates the diverse state-dependent rhythms evoked by dopamine. In the model, episodic bursting depended predominantly on the endogenous oscillatory properties of neurons, with Na+/K+ ATPase pump (I Pump) and hyperpolarization-activated currents (I h ) playing key roles. Modulation of either I Pump or I h produced transitions between episodic and continuous rhythms and silence. As maximal activity of I Pump decreased, the interepisode interval and period increased along with a reduction in episode duration. Decreasing maximal conductance of I h decreased episode duration and increased interepisode interval. Pharmacological manipulations of I h with ivabradine, and I Pump with ouabain or monensin in isolated spinal cords produced findings consistent with the model. Our modeling and experimental results highlight key roles of I h and I Pump in producing episodic rhythms and provide insight into mechanisms that permit a single CPG to produce multiple patterns of rhythmicity. [ABSTRACT FROM AUTHOR]

Delayed production can substantially alter the qualitative behaviour of feedback systems. Motivated by stochastic mechanisms in gene expression, we consider a protein molecule which is produced in randomly timed bursts, requires an exponentially distributed time to activate and then partakes in positive regulation of its burst frequency. Asymptotically analysing the underlying master equation in the large-delay regime, we provide tractable approximations to time-dependent probability distributions of molecular copy numbers. Importantly, the presented analysis demonstrates that positive feedback systems with large production delays can constitute a stable toggle switch even if they operate with low copy numbers of active molecules. [ABSTRACT FROM AUTHOR]

This paper mainly studied firing patterns and related bifurcations in the Purkinje cell dendrite model. Based on the methods of equivalent potentials and time scale analysis, the initial six-dimensional (6D) dendrite model is reduced to a 3D form to facilitate the calculation. We numerically show that the dendrite model could exhibit period-adding bifurcation and four bursting patterns for several vital parameters. Then the bifurcation mechanisms and transition of these four bursting patterns are discussed by phase plane analysis, and two-parameter bifurcation analysis of the fast subsystem, respectively. Moreover, we computed the first Lyapunov coefficient to determine the stability of Hopf bifurcation. Ultimately, we analyzed the codimension-two bifurcation of the whole system and gave a detailed theoretical derivation of the Bogdanov–Takens bifurcation. [ABSTRACT FROM AUTHOR]

Neuronal bursting is an electrophysiological behavior participating in physiological or pathological functions and a complex nonlinear behavior alternating between burst and quiescent state modulated by slow variables. Identification of dynamics of bursting modulated by two slow variables is still an open problem. In the present paper, a novel fast–slow variable dissection method with two slow variables is proposed to analyze the complex bursting simulated in a four-dimensional neuronal model to describe firing associated with pathological pain. The lumenal ( C lum ) and intracellular ( C in ) calcium concentrations are the slowest variables, respectively, in the quiescent state and burst duration. Questions encountered when the traditional method with one slow variable is used. When C lum is taken as slow variable, the burst is successfully identified to terminate near the saddle-homoclinic bifurcation point of the fast subsystem and begin not from the saddle-node bifurcation. With C in chosen as slow variable, C lum value of the initiation point of burst is far from the saddle-node bifurcation point, due to C lum not contained in the equation of the membrane potential. To overcome this problem, both C in and C lum are regarded as slow variables; the two-dimensional fast subsystem exhibits a saddle-node bifurcation point, which is extended to a saddle-node bifurcation curve by introducing the C lum dimension. Then, the initial point of burst is successfully identified to be near the saddle-node bifurcation curve. The results present a feasible method for fast–slow variable dissection and a deep understanding of the complex bursting behavior with two slow variables, which is helpful for the modulation to pathological pain. [ABSTRACT FROM AUTHOR]

Ammonia (NH4+) is a by-product of cell metabolism and may elicit subcellular effects with specific physiological responses. Chronic effects have been implicated in several neurological diseases and attributed to persistent elevation in blood ammonia levels transferred to the brain. In previous studies the activities of neurons and astrocytes have been examined at ammonia concentrations an order of magnitude higher than measured in the blood. The effects developed within several minutes. Here we focused upon acute responses of neurons to ammonia and whether they may occur at much lower doses. To this end, we combined patch-clamp in CA1 neurons with glutamate imaging in hippocampal slices. Particular attention was paid to the Rett syndrome that has been originally attributed to hyperammonemia. We compared the responses in the wild-type (WT) and model Rett mice (MECP2-null, RTT) to ammonia doses from 0.3 mM on. In both preparations NH4+ promptly depolarized neurons and increased the ambient glutamate. The bursting activity emerged in WT and it was augmented in RTT. Searching for subcellular mechanisms we examined possible modulation of ion channels by ammonia. We did not find any changes in HCN- and Ca2+ currents, which substantially contribute to the bursting activity. The non-selective cation channels were markedly potentiated by ammonia. ASIC channels had a major contribution to the augmentation of neuronal activity by ammonia. Interestingly, their general blocker amiloride (100 μM) moderately excited CA1 cells akin to NH4+. In its presence subsequent ammonia effects were markedly compromised. Blockade of TRPC1 channels partially occluded NH4+ effects. ASIC and TRPC1 blockers decreased the amplitude of excitatory postsynaptic currents (EPSC) and neuronal bursts, congruent with a postsynaptic location of the channels. Inhibition of TRPV1 channels potentiated the responses to NH4+. EPSC amplitudes did not change, but the frequency decreased, indicating presynaptic effects. All extracellular NH4+ actions were observed at concentrations as low as 0.3 mM and the neurons reacted immediately after ammonia arrived the slice. We propose that a brief augmentation of neuronal activity by NH4+ may occur either spontaneously during arousal or induced by inhalation of smelling salts.

Based on the standard Fitzhugh–Nagumo model for myocardial cell excitations and electrical activities, the effect of electromagnetic induction is considered and through which mixed frequencies magnetic radiation is imposed to detect the mode transition. Indeed, time-varying electromagnetic field can be induced when myocardial cell is exposed or surrounded by electromagnetic field and thus the effect of electromagnetic induction should be considered. From the analyzes of sampled series for membrane potentials, the improved model holds many bifurcation parameters and the mode of excitations and electric activities can be detected and observed in larger parameter zones. It is found that apart from exciting a myocardial cell, the mixed frequencies magnetic radiation can promote mode transition to bursting type behavior as the frequency is increased as well as suppress the electrical activities to quiescent state under high intensities magnetic radiations, which are consistent with biological experiments.

Developing spinal motor networks produce a diverse array of outputs, including episodic and continuous patterns of rhythmic activity. Variation in excitability state and neuromodulatory tone can facilitate transitions between episodic and continuous rhythms; however, the intrinsic mechanisms that govern these rhythms and their transitions are poorly understood. Here, we tested the capacity of a single central pattern generator (CPG) circuit with tunable properties to generate multiple outputs. To address this, we deployed a computational model composed of an inhibitory half-center oscillator (HCO). Following predictions of our computational model, we tested the contributions of key properties to the generation of an episodic rhythm produced by isolated spinal cords of the newborn mouse. The model recapitulates the diverse state-dependent rhythms evoked by dopamine. In the model, episodic bursting depended predominantly on the endogenous oscillatory properties of neurons, with Na+/K+ ATPase pump (IPump) and hyperpolarization-activated currents (Ih) playing key roles. Modulation of either IPump or Ih produced transitions between episodic and continuous rhythms and silence. As maximal activity of IPump decreased, the interepisode interval and period increased along with a reduction in episode duration. Decreasing maximal conductance of Ih decreased episode duration and increased interepisode interval. Pharmacological manipulations of Ih with ivabradine, and IPump with ouabain or monensin in isolated spinal cords produced findings consistent with the model. Our modeling and experimental results highlight key roles of Ih and IPump in producing episodic rhythms and provide insight into mechanisms that permit a single CPG to produce multiple patterns of rhythmicity.

We introduce a voltage-gated conductance model for an artificial neuron that exhibits tonic, fast, and two types of intrinsic burst spiking. The spike generation is achieved with a single voltage-gated channel that exploits the conductance commutation properties of a two-terminal memristive device. Our circuit implementation is of unprecedented simplicity, using just four electronic components, all conventional, cheap and out-of-the-shelf. Our bursting neuron is a two-compartment model, similar to the Pinsky–Rinzel model. We obtain the full phase diagram and discuss the origin of the different regions. We find that the spike traces of the model bare striking similarity to experimental biological neuronal recordings. Our work may open a new way to investigate neural pathologies, such as epilepsy and Parkinson’s disease, from the study of the phase diagram and the transitions between spiking states of physical neuron models.

Transcription occurs as irregular bursts in a very wide range of systems, including numerous different species and many genes within these. In this review, we examine the underlying theories, discuss how these relate to experimental measurements, and explore some of the discrepancies that have emerged among various studies. Finally, we consider more recent works that integrate novel concepts, such as the involvement of biomolecular condensates in enhancer-promoter interactions and their effects on the dynamics of transcriptional bursting., (© 2024 The Author(s).)

Insulin is secreted in a pulsatile pattern, with important physiological ramifications. In pancreatic β-cells, which are the cells that synthesize insulin, insulin exocytosis is elicited by pulses of elevated intracellular Ca2+ initiated by bursts of electrical activity. In parallel with these electrical and Ca2+ oscillations are oscillations in metabolism, and the periods of all of these oscillatory processes are similar. A key question that remains unresolved is whether the electrical oscillations are responsible for the metabolic oscillations via the effects of Ca2+, or whether the metabolic oscillations are responsible for the electrical oscillations due to the effects of ATP on ATP-sensitive ion channels? Mathematical modeling is a useful tool for addressing this and related questions as modeling can aid in the design of well-focused experiments that can test the predictions of particular models and subsequently be used to improve the models in an iterative fashion. In this article, we discuss a recent mathematical model, the Integrated Oscillator Model (IOM), that was the product of many years of development. We use the model to demonstrate that the relationship between calcium and metabolism in beta cells is symbiotic: in some contexts, the electrical oscillations drive the metabolic oscillations, while in other contexts it is the opposite. We provide new insights regarding these results and illustrate that what might at first appear to be contradictory data are actually compatible when viewed holistically with the IOM. [ABSTRACT FROM AUTHOR]

Strategically located between the thalamus and the cortex, the inhibitory thalamic reticular nucleus (TRN) is a hub to regulate selective attention during wakefulness and control the thalamic and cortical oscillations during sleep. A salient feature of TRN neurons contributing to these functions is their characteristic firing patterns, ranging in a continuum from tonic spiking to bursting spiking. However, the dynamical mechanism under these firing behaviors is not well understood. In this study, by applying a reduction method to a full conductance-based neuron model, we construct a reduced three-variable model to investigate the dynamics of TRN neurons. We show that the reduced model can effectively reproduce the spiking patterns of TRN neurons as observed in vivo and in vitro experiments, and meanwhile allow us to perform bifurcation analysis of the spiking dynamics. Specifically, we demonstrate that the rebound bursting of a TRN neuron is a type of "fold/homo-clinic" bifurcation, and the tonic spiking is the fold cycle bifurcation. Further one-parameter bifurcation analysis reveals that the transition between these discharge patterns can be controlled by the external current. We expect that this reduced neuron model will help us to further study the complicated dynamics and functions of the TRN network. [ABSTRACT FROM AUTHOR]

Based on the three-dimensional endocrine neuron model, a four-dimensional endocrine neuron model was constructed by introducing the magnetic flux variable and induced current according to the law of electromagnetic induction. Firstly, the codimension-one bifurcation and Interspike Intervals (ISIs) analysis were applied to study the bifurcation structure with respect to external stimuli and parameter k 0 , and two dynamical behaviors were found: period-adding and period-doubling bifurcation leading to chaos. Besides, Hopf bifurcation was specially discussed corresponding to the transformation of the state. Secondly, the different firing patterns such as regular bursting, subthreshold oscillations, fast spiking, mixed-mode oscillations (MMOs) etc. can be observed by changing the external stimuli and the induced current. The neuron model presented more firing activities under strong coupling strength. Finally, the codimension-two bifurcation analysis shown more details of bifurcation. At the same time, the Bogdanov-Takens bifurcation point was also analyzed and three bifurcation curves were derived. [ABSTRACT FROM AUTHOR]

The gene Tas1r3 codes for the protein T1R3, which dimerizes with T1R2 to form a sweetener-binding receptor in taste cells. Tas1r3 influences sweetener preferences in mice, as shown by work with a 129.B6-Tas1r3 segregating congenic strain on a 129P3/J (129) genetic background; members of this strain vary in whether they do or do not have one copy of a donor fragment with the C57BL/6ByJ (B6) allele for Tas1r3 (B6/129 and 129/129 mice, respectively). Taste-evoked neural responses were measured in the nucleus of the solitary tract (NST), the first central gustatory relay, in B6/129 and 129/129 littermates, to examine how the activity dependent on the T1R2/T1R3 receptor is distributed across neurons and over time. Responses to sucrose were larger in B6/129 than in 129/129 mice, but only during a later, tonic response portion (>600 ms) sent to different cells than the earlier, phasic response. Similar results were found for artificial sweeteners, whose responses were best considered as complex spatiotemporal patterns. There were also group differences in burst firing of NST cells, with a significant positive correlation between bursting prevalence and sucrose response size in only the 129/129 group. The results indicate that sweetener transduction initially occurs through T1R3-independent mechanisms, after which the T1R2/T1R3 receptor initiates a separate, spatially distinct response, with the later period dominating sweet taste perceptions and driving sugar preferences. Furthermore, the current data suggest that burst firing is distributed across NST neurons nonrandomly and in a manner that may amplify weak incoming gustatory signals. [ABSTRACT FROM AUTHOR]

A hallmark neuronal correlate of working memory (WM) is stimulus-selective spiking activity of neurons in PFC during mnemonic delays. These observations have motivated an influential computational modeling framework in which WM is supported by persistent activity. Recently, this framework has been challenged by arguments that observed persistent activity may be an artifact of trial-averaging, which potentially masks high variability of delay activity at the single-trial level. In an alternative scenario, WM delay activity could be encoded in bursts of selective neuronal firing which occur intermittently across trials. However, this alternative proposal has not been tested on single-neuron spike-train data. Here, we developed a framework for addressing this issue by characterizing the trial-to-trial variability of neuronal spiking quantified by Fano factor (FF). By building a doubly stochastic Poisson spiking model, we first demonstrated that the burst-coding proposal implies a significant increase in FF positively correlated with firing rate, and thus loss of stability across trials during the delay. Simulation of spiking cortical circuit WM models further confirmed that FF is a sensitive measure that can well dissociate distinct WM mechanisms. We then tested these predictions on datasets of single-neuron recordings from macaque PFC during three WM tasks. In sharp contrast to the burst-coding model predictions, we only found a small fraction of neurons showing increased WM-dependent burstiness, and stability across trials during delay was strengthened in empirical data. Therefore, reduced trial-to-trial variability during delay provides strong constraints on the contribution of single-neuron intermittent bursting to WM maintenance. [ABSTRACT FROM AUTHOR]

Insulin is secreted in a pulsatile pattern, with important physiological ramifications. In pancreatic β-cells, which are the cells that synthesize insulin, insulin exocytosis is elicited by pulses of elevated intracellular Ca2+ initiated by bursts of electrical activity. In parallel with these electrical and Ca2+ oscillations are oscillations in metabolism, and the periods of all of these oscillatory processes are similar. A key question that remains unresolved is whether the electrical oscillations are responsible for the metabolic oscillations via the effects of Ca2+, or whether the metabolic oscillations are responsible for the electrical oscillations due to the effects of ATP on ATP-sensitive ion channels? Mathematical modeling is a useful tool for addressing this and related questions as modeling can aid in the design of well-focused experiments that can test the predictions of particular models and subsequently be used to improve the models in an iterative fashion. In this article, we discuss a recent mathematical model, the Integrated Oscillator Model (IOM), that was the product of many years of development. We use the model to demonstrate that the relationship between calcium and metabolism in beta cells is symbiotic: in some contexts, the electrical oscillations drive the metabolic oscillations, while in other contexts it is the opposite. We provide new insights regarding these results and illustrate that what might at first appear to be contradictory data are actually compatible when viewed holistically with the IOM.

Strategically located between the thalamus and the cortex, the inhibitory thalamic reticular nucleus (TRN) is a hub to regulate selective attention during wakefulness and control the thalamic and cortical oscillations during sleep. A salient feature of TRN neurons contributing to these functions is their characteristic firing patterns, ranging in a continuum from tonic spiking to bursting spiking. However, the dynamical mechanism under these firing behaviors is not well understood. In this study, by applying a reduction method to a full conductance-based neuron model, we construct a reduced three-variable model to investigate the dynamics of TRN neurons. We show that the reduced model can effectively reproduce the spiking patterns of TRN neurons as observed in vivo and in vitro experiments, and meanwhile allow us to perform bifurcation analysis of the spiking dynamics. Specifically, we demonstrate that the rebound bursting of a TRN neuron is a type of “fold/homo-clinic” bifurcation, and the tonic spiking is the fold cycle bifurcation. Further one-parameter bifurcation analysis reveals that the transition between these discharge patterns can be controlled by the external current. We expect that this reduced neuron model will help us to further study the complicated dynamics and functions of the TRN network.

Large portions of the thalamus receive strong driving input from cortical layer 5 (L5) neurons but the role of this important pathway in cortical and thalamic computations is not well understood. L5-recipient “higher-order” thalamic regions participate in cortico-thalamo-cortical (CTC) circuits that are increasingly recognized to be (1) anatomically and functionally distinct from better-studied “first-order” CTC networks, and (2) integral to cortical activity related to learning and perception. Additionally, studies are beginning to elucidate the clinical relevance of these networks, as dysfunction across these pathways have been implicated in several pathological states. In this review, we highlight recent advances in understanding L5 CTC networks across sensory modalities and brain regions, particularly studies leveraging cell-type-specific tools that allow precise experimental access to L5 CTC circuits. We aim to provide a focused and accessible summary of the anatomical, physiological, and computational properties of L5-originating CTC networks, and outline their underappreciated contribution in pathology. We particularly seek to connect single-neuron and synaptic properties to network (dys)function and emerging theories of cortical computation, and highlight information processing in L5 CTC networks as a promising focus for computational studies.

Mathematical models at multiple temporal and spatial scales can unveil the fundamental mechanisms of critical transitions in brain activities. Neural mass models (NMMs) consider the average temporal dynamics of interconnected neuronal subpopulations without explicitly representing the underlying cellular activity. The mesoscopic level offered by the neural mass formulation has been used to model electroencephalographic (EEG) recordings and to investigate various cerebral mechanisms, such as the generation of physiological and pathological brain activities. In this work, we consider a NMM widely accepted in the context of epilepsy, which includes four interacting neuronal subpopulations with different synaptic kinetics. Due to the resulting three-time-scale structure, the model yields complex oscillations of relaxation and bursting types. By applying the principles of geometric singular perturbation theory, we unveil the existence of the canard solutions and detail how they organize the complex oscillations and excitability properties of the model. In particular, we show that boundaries between pathological epileptic discharges and physiological background activity are determined by the canard solutions. Finally we report the existence of canard-mediated small-amplitude frequency-specific oscillations in simulated local field potentials for decreased inhibition conditions. Interestingly, such oscillations are actually observed in intracerebral EEG signals recorded in epileptic patients during pre-ictal periods, close to seizure onsets. [ABSTRACT FROM AUTHOR]

Large portions of the thalamus receive strong driving input from cortical layer 5 (L5) neurons but the role of this important pathway in cortical and thalamic computations is not well understood. L5-recipient "higher-order" thalamic regions participate in cortico-thalamo-cortical (CTC) circuits that are increasingly recognized to be (1) anatomically and functionally distinct from better-studied "first-order" CTC networks, and (2) integral to cortical activity related to learning and perception. Additionally, studies are beginning to elucidate the clinical relevance of these networks, as dysfunction across these pathways have been implicated in several pathological states. In this review, we highlight recent advances in understanding L5 CTC networks across sensory modalities and brain regions, particularly studies leveraging cell-type-specific tools that allow precise experimental access to L5 CTC circuits. We aim to provide a focused and accessible summary of the anatomical, physiological, and computational properties of L5-originating CTC networks, and outline their underappreciated contribution in pathology. We particularly seek to connect single-neuron and synaptic properties to network (dys)function and emerging theories of cortical computation, and highlight information processing in L5 CTC networks as a promising focus for computational studies. [ABSTRACT FROM AUTHOR]

In the traditional viewpoint, inhibitory and excitatory effects always induce opposite responses. In the present study, the enhanced bursting activities induced by excitatory autapses, which are consistent with the recent experimental observations, and those induced by inhibitory autapses, which is a paradoxical phenomenon, were simulated using the Chay model. The same bifurcations and different ionic currents for the same responses were acquired with fast-slow variable dissection and current decomposition, respectively. As the inhibitory or excitatory autaptic conductance increased, the ending phase of the burst related to a homoclinic bifurcation of the fast subsystem changed to widen the burst duration to contain more spikes, which was induced by an elevated minimal potential (Vmin) of spiking of the fast subsystem. Larger inhibitory and excitatory autaptic conductances induced smaller and larger maximal potentials (Vmax) of spiking, respectively. During the downstroke, a weaker potassium current induced by the smaller Vmax played a dominant role for the inhibitory autapse, and the stronger potassium current induced by the larger Vmax became weaker due to the opposite autaptic current of the excitatory autapse, which induced the Vmin elevated. The results present the nonlinear and biophysical mechanisms of the same responses to opposite effects, which extends nonlinear dynamics knowledge and provides potential modulation measures for the nervous system. [ABSTRACT FROM AUTHOR]

Throughout the brain, astrocytes form networks mediated by gap junction channels that promote the activity of neuronal ensembles. Although their inputs on neuronal information processing are well established, how molecular gap junction channels shape neuronal network patterns remains unclear. Here, using astroglial connexin-deficient mice, in which astrocytes are disconnected and neuronal bursting patterns are abnormal, we show that astrocyte networks strengthen bursting activity via dynamic regulation of extracellular potassium levels, independently of glutamate homeostasis or metabolic support. Using a facilitation-depression model, we identify neuronal afterhyperpolarization as the key parameter underlying bursting pattern regulation by extracellular potassium in mice with disconnected astrocytes. We confirm this prediction experimentally and reveal that astroglial network control of extracellular potassium sustains neuronal afterhyperpolarization via KCNQ voltage-gated K+ channels. Altogether, these data delineate how astroglial gap junctions mechanistically strengthen neuronal population bursts and point to approaches for controlling aberrant activity in neurological diseases. [Display omitted] • We here identify how gap-junction-mediated astroglial networks regulate population bursts • Astrocyte networks strengthen bursting activity via regulation of extracellular potassium • This sustains neuronal afterhyperpolarization via KCNQ voltage-gated potassium channels • This astroglial regulation promotes in vivo delta-theta oscillatory physiological activity Dossi et al. investigate the mechanisms underlying neuronal network activity modulation by gap-junction-mediated astroglial networks. Combining modeling and experimental approaches, they show that astroglial networks strengthen hippocampal bursting patterns by sustaining neuronal afterhyperpolarization via extracellular potassium modulation of KCNQ potassium channels. This pathway controls in vivo physiological oscillatory activity. [ABSTRACT FROM AUTHOR]

Pipelines are widely used in transporting large quantities of oil and gas productions over long distances due to their efficiency, safety and low cost. Pipeline integrity is crucial for reliable pipeline operations, preventing expensive downtime, and failures resulting in leaking or spilling oil or gas content to the environment. In this paper, the influence of construction quality and corresponding uncertainties on the submarine pipelines integrity regarding the simultaneous effect of corrosion and bursting failure are investigated in a reliability analysis to predict critical failure year of the pipe. Also, sensitivity analysis is implemented to estimate how the important parameters affect the probability of failure using Monte Carlo simulation approach. Besides, consequences of failure also included in this study in terms of a ‘cost’ function considering post-failure inspection and repairs costs. Results illustrate that wall thickness is the dominant parameter in pipeline bursting. Also, allowable fabrication tolerances which are represented in DNV have an inherent probability of failure and it can be deteriorated by a degrading mechanism such as corrosion.

Since the introduction of memristors, it has been widely recognized that they can be successfully employed as synapses in neuromorphic circuits. This paper focuses on showing that memristor circuits can be also used for mimicking some features of the dynamics exhibited by neurons in response to an external stimulus. The proposed approach relies on exploiting multistability of memristor circuits, i.e., the coexistence of infinitely many attractors, and employing a suitable pulse-programmed input for switching among the different attractors. Specifically, it is first shown that a circuit composed of a resistor, an inductor, a capacitor and an ideal charge-controlled memristor displays infinitely many stable equilibrium points and limit cycles, each one pertaining to a planar invariant manifold. Moreover, each limit cycle is approximated via a first-order periodic approximation analytically obtained via the Describing Function (DF) method, a well-known technique in the Harmonic Balance (HB) context. Then, it is shown that the memristor charge is capable to mimic some simplified models of the neuron response when an external independent pulse-programmed current source is introduced in the circuit. The memristor charge behavior is generated via the concatenation of convergent and oscillatory behaviors which are obtained by switching between equilibrium points and limit cycles via a properly designed pulse timing of the current source. The design procedure takes also into account some relationships between the pulse features and the circuit parameters which are derived exploiting the analytic approximation of the limit cycles obtained via the DF method.

Pre-Bötzinger complex (PBC) neurons located in mammalian brain are the necessary conditions to produce respiratory rhythm, which has been widely verified experimentally and numerically. At present, one of the two different types of bursting mechanisms found in PBC mainly depends on the calcium-activated of non-specific cation current (ICaN). In order to study the influence of ICaN and stimulus current Iexc in PBC inspiratory neurons, a single compartment model was simplified, and firing patterns of the model was discussed by using stability theory, bifurcation analysis, fast, and slow decomposition technology combined with numerical simulation. Under the stimulation of different somatic applied currents, the firing behavior of neurons are studied and exhibit multiple mix bursting patterns, which is helpful to further understand the mechanism of respiratory rhythms of PBC neurons.

Neural hyperactivity induced by sound exposure often correlates with the development of hyperacusis and/or tinnitus. In laboratory animals, hyperactivity is typically induced by unilateral sound exposure to preserve one ear for further testing of hearing performance. Most ascending fibers in the auditory system cross into the superior olivary complex and then ascend contralaterally. Therefore, unilateral exposure should be expected to mostly affect the contralateral side above the auditory brain stem. On the other hand, it is well known that a significant number of neurons have crossing fibers at every level of the auditory pathway, which may spread the effect of unilateral exposure onto the ipsilateral side. Here we demonstrate that unilateral sound exposure causes development of hyperactivity in both the contra and ipsilateral inferior colliculus in mice. We found that both the spontaneous firing rate and bursting activity were increased significantly compared to unexposed mice. The neurons with characteristic frequencies at or above the center frequency of exposure showed the greatest increase. Surprisingly, this increase was more pronounced in the ipsilateral inferior colliculus. This study highlights the importance of considering both ipsi- and contralateral effects in future studies utilizing unilateral sound exposure.