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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 (I CaN ). In order to study the influence of I CaN and stimulus current I exc 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The identification of nonlinear dynamics of bursting patterns related to multiple time scales and pathology of brain tissues is still an open problem. In the present paper, representative cases of bursting related to seizure (SZ) and spreading depression (SD) simulated in a theoretical model are analyzed. When the fast–slow variable dissection method with only one slow variable (extracellular potassium concentration, [ K + ] o ) taken as the bifurcation parameter of the fast subsystem is used, the mismatch between bifurcation points of the fast subsystem and the beginning and ending phases of burst appears. To overcome this problem, both slow variables [ K + ] o and [ Na + ] i (intracellular sodium concentration) are regarded as bifurcation parameters of the fast subsystem, which exhibits three codimension-2 bifurcation points and multiple codimension-1 bifurcation curves containing the saddle-node bifurcation on an invariant cycle (SNIC), the supercritical Hopf bifurcation (the border between spiking and the depolarization block), and the saddle homoclinic (HC) bifurcation. The bursting patterns for SD are related to the Hopf bifurcation and the depolarization block while for SZ to SNIC. Furthermore, at the intersection points between the bursting trajectory and the bifurcation curves in plane ( [ K + ] o , [ Na + ] i ), the initial or termination phases of burst match the SNIC or HC point well or the Hopf point to a certain extent due to the slow passage effect, showing that the fast–slow variable dissection method with suitable process is still effective to analyze bursting activities. The results present the complex bifurcations underlying the bursting patterns and a proper performing process for the fast–slow variable dissection with two slow variables, which are helpful for modulation to bursting patterns related to brain disfunction. [ABSTRACT FROM AUTHOR]

The conventional rice production system of Pakistan is escalating due to the higher level of labor involved, shortage of water and higher cost of production due to the rapidly increasing cost of energy resources. Dry direct seeded aerobic rice (DDSAR) is a valuable option to ease the problem of labor, water, and energy resources. In this study, screening of four rice varieties of conventional transplanted rice was evaluated under DDSAR in terms of yield, milling recoveries, grain and cooking quality. Four rice cultivars, viz; Super Basmati; Basmati 2000; Basmati 515 and PS-2 were sown at the Research Station of the Engro Fertilizers, Sheikhupura, Pakistan during three consecutive summer seasons (2016 to 2018). The sowing was accomplished in well prepared dry fields. Each variety performed well in terms of yield and quality traits in DDSAR but in terms of yield, Basmati-515 outperformed the other varieties and showed consistency in yield for three consecutive years of cultivation. PS-2 also gave yield statistically similar to Basmati-515 but maximum cooked grain length (17.1-17.5 mm) and grain elongation ratio (1.69-1.7) was recorded for PS-2. In contrast to other varieties, the minimum head rice percentage (40.5-43.5%) was recorded in PS-2 cultivar besides having the second-highest total milled rice percentage (50.5-73.4%) after Basmati-515 (81.0-82.8%). DDSAR did not affect the cooking quality of rice except bursting. In crux, the cultivation of low land rice cultivars under DDSAR not only maintained or increased the grain yield but also the grain and cooking quality of rice. [ABSTRACT FROM AUTHOR]

The woven agrotextiles used in a wide variety of agricultural applications in the product cultivation and protection activities, horticulture and floriculture, aquaculture, forestry as well as animal husbandry activities have an important role to protect silages from bird/insect attacks or damages related to environmental conditions. In this study, nine different woven silage covering fabrics made of polyethylene monofilaments were designed according to desired areal porosity ratio. Afterwards, the effect of weave type and weft setting on mechanical and air permeability properties of the produced agrotextiles were investigated. The obtained results were discussed statistically. The highest values for bursting and shear strength were measured as 2.60 kN and 0.25 kN for P1 plain fabric, respectively. Twill and mat fabric structures did not burst during testing. Woven silage covering fabrics made of polyethylene monofilaments were produced according to desired areal porosity ratio. The effect of weave type and weft setting on mechanical and air permeability properties of the produced agrotextiles were investigated. The highest values for bursting and shear strength were measured as 2.60 kN and 0.25 kN for P1 plain fabric, respectively. Besides, no bursting was observed in mat and twill fabrics. [ABSTRACT FROM AUTHOR]

Biological neurons exposed to an external electric field can induce polarization and charge fluctuation. Indeed, the exchange of calcium, sodium and potassium ions across the cell membrane can induce an electric field as a result of a time-varying electromagnetic field set up. This field could further modulate the cell electrical activity by inducing multiple firing modes. Based on the physical law of electric field, an improved model which includes an additive electrical field variable is constructed for a network of neurons to study wave propagation and mode transition by exploring the longtime dynamics of slightly perturbed plane waves in the network. Wave pattern and mode transition dependence on the different parameters of external electric field are discussed. It is found that the plane wave propagating in the coupled system breaks down to localized structures under the activation of modulational instability. The network under high-low external electric field supports bursting synchronization. This could be a fruitful avenue to discern the occurrence of paroxysmal epilepsy.

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.

The interplay between excitation and inhibition is crucial for neuronal circuitry in the brain. Inhibitory cell fractions in the neocortex and hippocampus are typically maintained at 15 to 30%, which is assumed to be important for stable dynamics. We have studied systematically the role of precisely controlled excitatory/inhibitory (E/I) cellular ratios on network activity using mice hippocampal cultures. Surprisingly, networks with varying E/I ratios maintain stable bursting dynamics. Interburst intervals remain constant for most ratios, except in the extremes of 0 to 10% and 90 to 100% inhibitory cells. Single-cell recordings and modeling suggest that networks adapt to chronic alterations of E/I compositions by balancing E/I connectivity. Gradual blockade of inhibition substantiates the agreement between the model and experiment and defines its limits. Combining measurements of population and single-cell activity with theoretical modeling, we provide a clearer picture of how E/I balance is preserved and where it fails in living neuronal networks. [ABSTRACT FROM AUTHOR]

Although the bursting patterns with spike undershoot are involved with the achievement of physiological or cognitive functions of brain with synaptic noise, noise induced-coherence resonance (CR) from resting state or subthreshold oscillations instead of bursting has been widely identified to play positive roles in information process. Instead, in the present paper, CR characterized by the increase firstly and then decease of peak value of power spectrum of spike trains is evoked from a bursting pattern with spike undershoot, which means that the minimal membrane potential within burst is lower than that of the subthreshold oscillations between bursts, while CR cannot be evoked from the bursting pattern without spike undershoot. With bifurcations and fast-slow variable dissection method, the bursting patterns with and without spike undershoot are classified into "Sub-Hopf/Fold" bursting and "Fold/Homoclinic" bursting, respectively. For the bursting with spike undershoot, the trajectory of the subthreshold oscillations is very close to that of the spikes within burst. Therefore, noise can induce more spikes from the subthreshold oscillations and modulate the bursting regularity, which leads to the appearance of CR. For the bursting pattern without spike undershoot, the trajectory of the quiescent state is not close to that of the spikes within burst, and noise cannot induce spikes from the quiescent state between bursts, which is cause for non-CR. The result provides a novel case of CR phenomenon and extends the scopes of CR concept, presents that noise can enhance rather than suppress information of the bursting patterns with spike undershoot, which are helpful for understanding the dynamics and the potential physiological or cognitive functions of the nerve fiber or brain neurons with such bursting patterns. [ABSTRACT FROM AUTHOR]

Neuromorphic computing using spike‐based learning has broad prospects in reducing computing power. Memristive neurons composed with two locally active memristors have been used to mimic the dynamical behaviors of biological neurons. Herein, the dynamic operating conditions of NbO2‐based memristive neurons and their transformation boundaries between the spiking and the bursting are comprehensively investigated. Furthermore, the underlying mechanism of bursting is analyzed, and the controllability of the number of spikes during each burst period is demonstrated. Finally, pattern classification and information transmitting in a perceptron neural network by using the number of spikes per bursting period to encode information is proposed. The results show a promising approach for the practical implementation of neuristor in spiking neural networks.

Rapid-eye movement (REM) sleep is a paradoxical sleep state characterized by brain activity similar to wakefulness, rapid-eye-movement, and lack of muscle tone. REM sleep is a fundamental brain function, evolutionary conserved across species, including human, mouse, bird, and even reptiles. The physiological importance of REM sleep is highlighted by severe sleep disorders incurred by a failure in REM sleep regulation. Despite the intense interest in the mechanism of REM sleep regulation, the molecular machinery is largely left to be investigated. In models of REM sleep regulation, acetylcholine has been a pivotal component. However, even newly emerged techniques such as pharmacogenetics and optogenetics have not fully clarified the function of acetylcholine either at the cellular level or neural-circuit level. Recently, we discovered that the Gq type muscarinic acetylcholine receptor genes, Chrm1 and Chrm3, are essential for REM sleep. In this review, we develop the perspective of current knowledge on REM sleep from a molecular viewpoint. This should be a starting point to clarify the molecular and cellular machinery underlying REM sleep regulation and will provide insights to explore physiological functions of REM sleep and its pathological roles in REM-sleep-related disorders such as depression, PTSD, and neurodegenerative diseases.

Abstract Cellular decision‐making and environmental adaptation are dependent upon a heterogeneous response of gene expression to external cues. Heterogeneity arises in transcription from random switching between transcriptionally active and inactive states, resulting in bursts of RNA synthesis. Furthermore, the cellular state influences the competency of transcription, thereby globally affecting gene expression in a cell‐specific manner. We determined how external stimuli interplay with cellular state to modulate the kinetics of bursting. To this end, single‐cell dynamics of nascent transcripts were monitored at the endogenous estrogen‐responsive GREB1 locus. Stochastic modeling of gene expression implicated a two‐state promoter model in which the estrogen stimulus modulates the frequency of transcriptional bursting. The cellular state affects transcriptional dynamics by altering initiation and elongation kinetics and acts globally, as GREB1 alleles in the same cell correlate in their transcriptional output. Our results suggest that cellular state strongly affects the first step of the central dogma of gene expression, to promote heterogeneity in the transcriptional output of isogenic cells.

A variety of firing rhythms can be generated spontaneously in the pre-Bötzinger complex. External stimuli can cause changes in the pattern of the firing rhythm, which may cause different physiological effects in the body. In this study, by the fast and slow time scale dynamics, with one- and two-parameter bifurcation analysis, we study the bursting patterns and their transition mechanisms of the pre-Bötzinger complex under washout filter controller. The results may help us understand the relationship between different firing patterns of neurons and external stimuli, and further reveal the mechanisms of disease due to external stimuli. [ABSTRACT FROM AUTHOR]

Paradoxical enhancement rather than reduction in firing activity induced by inhibitory effect is very important for both nonlinear dynamics and neuroscience. In the present paper, to build a more comprehensive viewpoint related to excitatory effect, a paradoxical phenomenon modulated by the excitatory self-feedback of autapse is extended to bursting activity in a modified Morris–Lecar model. With increasing the strength of excitatory autapse, the bursting patterns exhibit inverse period-adding bifurcations to spiking pattern via chaos, and the burst duration, the spike number per burst, and the firing frequency of bursting decrease, which is different from the traditional view that firing frequency should be enhanced. Furthermore, the paradoxical reduction in bursting activity is well explained with the nonlinear dynamics of the fast subsystem. The burst begins from neighborhood of a fold bifurcation of equilibrium point and terminates at a saddle homoclinic (SH) bifurcation. With increasing conductance of autapse, the fold bifurcation point remains unchanged, which is due to too small autaptic current near the fold point to influence the dynamics, and the SH point shifts left, which follows from the enhanced potassium current at the minimal value of the stable limit cycle. Therefore, the range between the fold and SH point becomes narrower to shorten the burst duration to reduce spike number per burst and firing frequency. The novel example of paradoxical reduction modulated by positive self-feedback and the associated bifurcation mechanism enrich the phenomena of nonlinear science and present the potential functions of excitatory autapse in the brain neurons with bursting behavior. [ABSTRACT FROM AUTHOR]

Biological neurons can receive inputs and capture a variety of external stimuli, which can be encoded and transmitted as different electric signals. Thus, the membrane potential is adjusted to activate the appropriate firing modes. Indeed, reliable neuron models should take intrinsic biophysical effects and functional encoding into consideration. One fascinating and important question is the physical mechanism for the transcription of external signals. External signals can be transmitted as a transmembrane current or a signal voltage for generating action potentials. We present a photosensitive neuron model to estimate the nonlinear encoding and responses of neurons driven by external optical signals. In the model, a photocell (phototube) is used to activate a simple FitzHugh-Nagumo (FHN) neuron, and then external optical signals (illumination) are imposed to excite the photocell for generating a time-varying current/voltage source. The photocell-coupled FHN neuron can therefore capture and encode external optical signals, similar to artificial eyes. We also present detailed bifurcation analysis for estimating the mode transition and firing pattern selection of neuronal electrical activities. The sampled time series can reproduce the main characteristics of biological neurons (quiescent, spiking, bursting, and even chaotic behaviors) by activating the photocell in the neural circuit. These results could be helpful in giving possible guidance for studying neurodynamics and applying neural circuits to detect optical signals. [ABSTRACT FROM AUTHOR]

Neuromorphic computing using spike‐based learning has broad prospects in reducing computing power. Memristive neurons composed with two locally active memristors have been used to mimic the dynamical behaviors of biological neurons. Herein, the dynamic operating conditions of NbO2‐based memristive neurons and their transformation boundaries between the spiking and the bursting are comprehensively investigated. Furthermore, the underlying mechanism of bursting is analyzed, and the controllability of the number of spikes during each burst period is demonstrated. Finally, pattern classification and information transmitting in a perceptron neural network by using the number of spikes per bursting period to encode information is proposed. The results show a promising approach for the practical implementation of neuristor in spiking neural networks. [ABSTRACT FROM AUTHOR]

Temperature affects the firing pattern and electrical activity of neurons in animals, eliciting diverse responses depending on neuronal cell type. However, the mechanisms underlying such diverse responses are not well understood. In the present study, we performed in vitro recording of abdominal ganglia cells of Aplysia juliana, and analyzed their burst firing patterns. We identified atypical bursting patterns dependent on temperature that were totally different from classical bursting patterns observed in R15 neurons of A. juliana. We classified these abnormal bursting patterns into type 1 and type 2; type 1 abnormal single bursts are composed of two kinds of spikes with a long interspike interval (ISI) followed by short ISI regular firing, while type 2 abnormal single bursts are composed of complex multiplets. To investigate the mechanism underlying the temperature dependence of abnormal bursting, we employed simulations using a modified Plant model and determined that the temperature dependence of type 2 abnormal bursting is related to temperaturedependent scaling factors and activation or inactivation of potassium or sodium channels. [ABSTRACT FROM AUTHOR]

Noise in gene expression can be substantively affected by the presence of production delay. Here we consider a mathematical model with bursty production of protein, a one-step production delay (the passage of which activates the protein), and feedback in the frequency of bursts. We specifically focus on examining the steady-state behaviour of the model in the slow-activation (i.e. large-delay) regime. Using a formal asymptotic approach, we derive an autonomous ordinary differential equation for the inactive protein that applies in the slow-activation regime. If the differential equation is monostable, the steady-state distribution of the inactive (active) protein is approximated by a single Gaussian (Poisson) mode located at the globally stable fixed point of the differential equation. If the differential equation is bistable (due to cooperative positive feedback), the steady-state distribution of the inactive (active) protein is approximated by a mixture of Gaussian (Poisson) modes located at the stable fixed points; the weights of the modes are determined from a WKB approximation to the stationary distribution. The asymptotic results are compared to numerical solutions of the chemical master equation. [ABSTRACT FROM AUTHOR]

Transcription in several organisms from certain bacteria to humans has been observed to be stochastic in nature: toggling between active and inactive states. Periods of active nascent RNA synthesis known as bursts represent individual gene activation events in which multiple polymerases are initiated. Therefore, bursting is the single locus illustration of both gene activation and repression. Although transcriptional bursting was originally observed decades ago, only recently have technological advances enabled the field to begin elucidating gene regulation at the single-locus level. In this review, we focus on how biochemical, genomic, and single-cell data describe the regulatory steps of transcriptional bursts. [ABSTRACT FROM AUTHOR]

Coherence resonance (CR), which is typical nonlinear phenomenon that noise plays construct roles, has been widely investigated in single neurons at resting state instead of bursting behavior when noise free. In the present paper, multiple CRs evoked from bursting instead of resting state and the underlying bifurcation mechanism are studied in a theoretical neuron model composed of fast subsystem and slow variable, which is very important for the bursting neurons receiving strong synaptic noise in the central nervous system. With increasing noise intensity within a range, the bursting period decreases to induce the burst number increases firstly and then becomes irregular, which results in the increase firstly and then decrease in the corresponding peak of the power spectrum of membrane potentials, i.e., CR is evoked from bursting instead of resting state. With further increasing noise intensity, two other peaks exhibit CR phenomenon, one at middle frequency and middle noise intensity and the other at large frequency and strong noise intensity, which shows that multiple CRs are evoked from bursting. Furthermore, the bifurcation mechanism of the latter two resonant peaks is acquired with fast–slow variable dissection method. With increasing the value of slow variable, the fast subsystem exhibits a fold bifurcation of limit cycle and a subcritical Hopf bifurcation to a stable focus, and the imaginary part of the characteristic value of the focus increases, which implies that spikes evoked from the focus exhibit increasing frequency. The trajectory of the deterministic bursting in phase space locates between the two bifurcations and alternates between the coexisting limit cycle and focus of the fast subsystem. With increasing noise intensity, the value of slow variable of the stochastic bursting increases and moves to a range of the focus of the fast subsystem, and the spikes of the stochastic bursting are evoked from the focus by noise. Therefore, the stronger the noise intensity, the larger the value of slow variable, and the higher frequency the spikes, due to the changes of characteristic values, which is the cause that the peaks with middle and high frequency appear at middle and strong noise intensity, respectively. The results of the present paper extend the concept of CR to multiple CRs evoked from bursting, provide the bifurcation mechanism underlying the multiple CRs, and imply multiple chances to utilize noise to enhance information of bursting neurons. [ABSTRACT FROM AUTHOR]

In this paper, a non-autonomous memristive FitzHugh-Nagumo (FHN) circuit is constructed using a second-order memristive diode bridge with LC network. For convenience of circuit implementation, an AC voltage source is adopted to substitute the original AC current stimulus. Stimulated by the slowly varying AC voltage source, the number, locations and stabilities of the equilibrium points slowly evolve with the time, which are thus indicated as the AC equilibrium points. Different sequences of fold and/or Hopf bifurcations are encountered in a full period of time series evolutions, leading to various kinds of chaotic or periodic bursting activities. To figure out the related bifurcation mechanisms, the fold and Hopf bifurcation sets are mathematically formulated to locate the critical bifurcation points. On this basis, the transitions between the resting and repetitive spiking states are clearly illustrated by the time series of the AC equilibrium points and state variables, from which Hopf/subHopf, Hopf/Hopf, and Hopf/fold bursting oscillations are identified in the specified parameter regions. Finally, based on a fabricated hardware circuit, the experimental measurements are executed. The results verify that the presented memristive FHN circuit indeed exhibits complex bursting activities, which enriches the family of memristor-based FHN circuits with bursting dynamics. [ABSTRACT FROM AUTHOR]

Adaptive nonlinear optimal control methods, as proposed in the literature, give rise to some questions around practical implementation in robotics, especially how to find a solution in a reasonable time and how to deal with gravity. This paper proposes a method to solve these problems by using a neural network with local basis-function domains, specifically the Cerebellar Model Articulation Controller (CMAC). The algorithm uses the local domains in order to keep track of the value of local cost-functionals. In this way, it can freeze the learning of the network's weights in a feedforward-like component in the CMAC when the bias has been overcome identified by using an error-based cost-functional e.g. automatic gravity compensation in a robot. After the feedforward component has been established, the algorithm then starts to learn another set of weights which contribute to feedback-like terms in the CMAC and these weights get frozen when they no longer reduce a cost-functional that includes additional control effort e.g. in a robot the control effort beyond that needed to compensate for gravity is penalized. Lyapunov methods guarantee uniformly ultimately bounded signals and ensure weight drift and bursting do not occur. One advantage is that the training time for finding a near-optimal control does not increase over previous neural-adaptive methods. Another advantage is that penalizing the control effort in a search for optimization does result in any steady-state error due to gravity. Simulations show that the proposed method significantly outperforms a standard adaptive-CMAC control using e-modification, without increasing control effort or training time. An experimental flexible-joint robot verifies that the adaptive method significantly outperforms a linear quadratic regulator. [ABSTRACT FROM AUTHOR]

By showing that there is no any memristor in the integer-order Hindmarsh–Rose (H–R) model, the slow ion channel is remodeled by a fractional-order memristor, where the fractional-order derivative is related to the memory effect and the decay rate of the ion current. Then a fractional-order memristive (FOM) H–R model without equilibrium is proposed. Due to a small parameter, the FOM H–R model is a fast–slow system which can be taken as the small perturbation system of the fast subsystem. By Lyapunov direct method, the boundedness of the fast subsystem is proved. With the help of the boundedness and stability of the fast system, the hidden dynamics of the FOM H–R model is discussed. As the small parameter is fixed, it is shown that the membrane potential of the FOM H–R model limits to a quiescent state as the fractional order is less than 0.5 and limits to a periodic spiking as the fractional order is greater than 0.5 less than 1. Without the constraint of the small parameter, the periodic and chaotic bursting appears in the FOM H–R model, which implies the small parameter makes the membrane potential activity simpler. It can be drawn a conclusion that the ion current with the slow decay rate can inhibit the neurons. [ABSTRACT FROM AUTHOR]

For conventional gas‐liquid‐solid three‐phase heterogeneous hydrogenation reactions, hydrogen must be dissolved into the solvent to be a participating reactant, restricting the reaction rates. In this study, we demonstrate that gaseous hydrogen could be directly involved in gas‐liquid‐solid hydrogenation reactions through a bioinspired hollow nanoreactor with superaerophilic surface to enhance the reaction rates. We produce Pd@meso‐SiO2 hollow nanoreactor, whose external surface is modified with perfluorodecyltriethoxysilane (PFDTS). In aqueous solutions, H2 gas could be spread quickly on the surface and stored in the cavity of hollow spheres, and participated in hydrogenation reactions, thereby enhancing H2 concentration around Pd nanoparticles. In hydrogenation of olefin reactions, such three‐phase interface allows rapid and direct transportation of H2 bubbles to the surface of Pd nanoparticles rather than through diffusion of dissolved H2 in liquid phase, leading to an enhanced catalytic rate. This strategy is expected to be useful for designing and developing new catalytic systems of gas‐liquid‐solid three‐phase reaction. [ABSTRACT FROM AUTHOR]

Rapid-eye movement (REM) sleep is a paradoxical sleep state characterized by brain activity similar to wakefulness, rapid-eye-movement, and lack of muscle tone. REM sleep is a fundamental brain function, evolutionary conserved across species, including human, mouse, bird, and even reptiles. The physiological importance of REM sleep is highlighted by severe sleep disorders incurred by a failure in REM sleep regulation. Despite the intense interest in the mechanism of REM sleep regulation, the molecular machinery is largely left to be investigated. In models of REM sleep regulation, acetylcholine has been a pivotal component. However, even newly emerged techniques such as pharmacogenetics and optogenetics have not fully clarified the function of acetylcholine either at the cellular level or neural-circuit level. Recently, we discovered that the G q type muscarinic acetylcholine receptor genes, Chrm1 and Chrm3 , are essential for REM sleep. In this review, we develop the perspective of current knowledge on REM sleep from a molecular viewpoint. This should be a starting point to clarify the molecular and cellular machinery underlying REM sleep regulation and will provide insights to explore physiological functions of REM sleep and its pathological roles in REM-sleep-related disorders such as depression, PTSD, and neurodegenerative diseases. [ABSTRACT FROM AUTHOR]

Sharp‐wave ripples (SWRs) are spontaneous, synchronized neural population events in the hippocampus widely thought to play a role in memory consolidation and retrieval. They occur predominantly in sleep and quiet immobility, and in primates, they also appear during active visual exploration. Typical measures of SWRs in behaving rats include changes in the rate of occurrence, or in the incidence of specific neural ensemble activity contained within the categorical SWR event. Much less is known about the relevance of spatiotemporal SWR features, though they may index underlying activity of specific cell types including ensemble‐specific internally generated sequences. Furthermore, changes in SWR features during active exploratory states are unknown. In this study, we recorded hippocampal local‐field potentials and single‐units during periods of quiescence and as macaques performed a memory‐guided visual search task. We observed that (a) ripples during quiescence have greater amplitudes and larger postripple waves (PRW) compared to those in task epochs, and (b) during "remembered" trials, ripples have larger amplitudes than during "forgotten" trials, with no change in duration or PRWs. We further found that spiking activity influences SWR features as a function of cell type and ripple timing. As expected, larger ripple amplitudes were associated with putative pyramidal or putative basket interneuron (IN) activity, even when the spikes in question exceed the duration of the ripple. In contrast, the PRW was attenuated with activity from low firing rate cells and enhanced with activity from high firing rate cells, with putative IN spikes during ripples leading to the most prominent PRW peaks. The selective changes in SWR features as a function of time window, cell type, and cognitive/vigilance states suggest that this mesoscopic field event can offer additional information about the local network and animal's state than would be appreciated from SWR event rates alone. [ABSTRACT FROM AUTHOR]

Microwave-assisted breakage of cementitious materials has emerged as a promising green and low-carbon method for dismantling cementitious structures. To understand the mechanism of microwave-induced cracking in structures, it is essential to study the thermal behaviors of cement and mortar under microwave treatment. In this paper, the effects of mixture ratio, water content, and microwave power on the microwave heating characteristics of cement and mortar specimens were investigated through real-time temperature and mass monitoring. In particular, the influence of microwave power on the bursting effect of cement and mortar specimens was analysed, and the mechanism of specimen bursting was explained. The results show that moisture content, water-cement ratio, and microwave power significantly impact the heating rate and mass loss of cement and mortar during microwave treatment. Based on the heating rate, the heating process of cement and mortar under microwave treatment can be divided into three to four stages, depending on the moisture content. The primary reasons for variations in the heating rate are water evaporation and the decomposition of hydrolysis products. The thin-wall ball model based on steam pressure theory can explain the bursting of cement and mortar specimens. Our findings suggest that increasing microwave power and water content in mortar specimens can lead to microwave-induced cracking. • Instantaneously measured the temperature and mass changes of cement and mortar while microwave heating. • Investigated the influence of mix ratio, water content and power on microwave heating and bursting of cement and mortar. • Examined the thermal decomposition kinematics of cement hydration products while microwave heating. • Reveals the dual role of water in the microwave heating process. [ABSTRACT FROM AUTHOR]

The comprehension of neuronal network functioning, from most basic mechanisms of signal transmission to complex patterns of memory and decision making, is at the basis of the modern research in experimental and computational neurophysiology. While mechanistic knowledge of neurons and synapses structure increased, the study of functional and effective networks is more complex, involving emergent phenomena, nonlinear responses, collective waves, correlation and causal interactions. Refined data analysis may help in inferring functional/effective interactions and connectivity from neuronal activity. The Transfer Entropy (TE) technique is, among other things, well suited to predict structural interactions between neurons, and to infer both effective and structural connectivity in small- and large-scale networks. To efficiently disentangle the excitatory and inhibitory neural activities, in the article we present a revised version of TE, split in two contributions and characterized by a suited delay time. The method is tested on in silico small neuronal networks, built to simulate the calcium activity as measured via calcium imaging in two-dimensional neuronal cultures. The inhibitory connections are well characterized, still preserving a high accuracy for excitatory connections prediction. The method could be applied to study effective and structural interactions in systems of excitable cells, both in physiological and in pathological conditions.

High-frequency “burst” clusters of spikes are a generic output pattern of many neurons. While bursting is a ubiquitous computational feature of different nervous systems across animal species, the encoding of synaptic inputs by bursts is not well understood. We find that bursting neurons in the rodent thalamus employ “multiplexing” to differentially encode low- and high-frequency stimulus features associated with either T-type calcium “low-threshold” or fast sodium spiking events, respectively, and these events adapt differently. Thus, thalamic bursts encode disparate information in three channels: (1) burst size, (2) burst onset time, and (3) precise spike timing within bursts. Strikingly, this latter “intraburst” encoding channel shows millisecond-level feature selectivity and adapts across statistical contexts to maintain stable information encoded per spike. Consequently, calcium events both encode low-frequency stimuli and, in parallel, gate a transient window for high-frequency, adaptive stimulus encoding by sodium spike timing, allowing bursts to efficiently convey fine-scale temporal information.

Heterogeneity of neural properties within a given neural class is ubiquitous in the nervous system and permits different sub-classes of neurons to specialize for specific purposes. This principle has been thoroughly investigated in the hindbrain of the weakly electric fish A. leptorhynchus in the primary electrosensory area, the Electrosensory Lateral Line lobe (ELL). The pyramidal cells (PCs) that receive inputs from tuberous electroreceptors are organized in three maps in distinct segments of the ELL. The properties of these cells vary greatly across maps due to differences in connectivity, receptor expression, and ion channel composition. These cells are a seminal example of bursting neurons and their bursting dynamic relies on the presence of voltage-gated Na+ channels in the extensive apical dendrites of the superficial PCs. Other ion channels can affect burst generation and their expression varies across ELL neurons and segments. For example, SK channels cause hyperpolarizing after-potentials decreasing the likelihood of bursting, yet bursting propensity is similar across segments. We question whether the depolarizing mechanism that generates the bursts presents quantitative differences across segments that could counterbalance other differences having the opposite effect. Although their presence and role are established, the distribution and density of the apical dendrites’ Na+ channels have not been quantified and compared across ELL maps. Therefore, we test the hypothesis that Na+ channel density varies across segment by quantifying their distribution in the apical dendrites of immunolabeled ELL sections. We found the Na+ channels to be two-fold denser in the lateral segment (LS) than in the centro-medial segment (CMS), the centro-lateral segment (CLS) being intermediate. Our results imply that this differential expression of voltage-gated Na+ channels could counterbalance or interact with other aspects of neuronal physiology that vary across segments (e.g., SK channels). We argue that burst coding of sensory signals, and the way the network regulates bursting, should be influenced by these variations in Na+ channel density.

Transient synchronization of bursting activity in neuronal networks, which occurs in patterns of metastable itinerant phase relationships between neurons, is a notable feature of network dynamics observed in vivo . However, the mechanisms that contribute to this dynamical complexity in neuronal circuits are not well understood. Local circuits in cortical regions consist of populations of neurons with diverse intrinsic oscillatory features. In this study, we numerically show that the phenomenon of transient synchronization, also referred to as metastability, can emerge in an inhibitory neuronal population when the neurons' intrinsic fast-spiking dynamics are appropriately modulated by slower inputs from an excitatory neuronal population. Using a compact model of a mesoscopic-scale network consisting of excitatory pyramidal and inhibitory fast-spiking neurons, our work demonstrates a relationship between the frequency of pyramidal population oscillations and the features of emergent metastability in the inhibitory population. In addition, we introduce a method to characterize collective transitions in metastable networks. Finally, we discuss potential applications of this study in mechanistically understanding cortical network dynamics., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Venkadesh, Shaikh, Shakeri, Barreto and Van Horn.)

Nonselective cation channels promote persistent spiking in many neurons from a diversity of animals. In the hermaphroditic marinesnail, Aplysia californica, synaptic input to the neuroendocrine bag cell neurons triggers various cation channels, causing an --30 min afterdischarge of action potentials and the secretion of egg-laying hormone. During the afterdischarge, protein kinase C is also activated, which in turn elevates hydrogen peroxide (H202), likely by stimulating nicotinamide adenine dinucleotide phosphate oxidase. The present study investigated whether H202 regulates cation channels to drive the afterdischarge. In single, cultured bag cell neurons, H202 elicited a prolonged, concentration- and voltage-dependent inward current, associated with an increase in membrane conductance and a reversal potential of ~ + 30 mV. Compared with normal saline, the presence of Ca2+-free, Na+-free, or Na +/Ca2+-free extracellular saline, lowered the current amplitude and left-shifted the reversal potential, consistent with a nonselective cationic conductance. Preventing H202 reduction with the glutathione peroxidase inhibitor, mercaptosuccinate, enhanced the H202-induced current, while boosting glutathione production with its precursor, JV-acetylcysteine, or adding the reducing agent, dithiothreitol, lessened the response. Moreover, the current generated by the alkylating agent, V-ethylmaleimide, occluded the effect of H202. The H202-induced current was inhibited by tetrodotoxin as well as the cation channel blockers, 9-phenanthrol and clotrimazole. In current-clamp, II, 02 stimulated burst firing, but this was attenuated or prevented altogether by the channel blockers. Finally, H202 evoked an afterdischarge from whole bag cell neuron clusters recorded ex vivo by sharp-electrode. H202 may regulate a cation channel to influence long-term changes in activity and ultimately reproduction. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Vibration Engineering is the property of Nanjing University of Aeronautics & Astronautics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Electrophysiological recordings of neuronal activity show spontaneous and task-dependent changes in their frequency-domain power spectra. These changes are conventionally interpreted as modulations in the amplitude of underlying oscillations. However, this overlooks the possibility of underlying transient spectral 'bursts' or events whose dynamics can map to changes in trial-average spectral power in numerous ways. Under this emerging perspective, a key challenge is to perform burst detection, i.e. to characterise single-trial transient spectral events, in a principled manner. Here, we describe how transient spectral events can be operationalised and estimated using Hidden Markov Models (HMMs). The HMM overcomes a number of the limitations of the standard amplitude-thresholding approach to burst detection; in that it is able to concurrently detect different types of bursts, each with distinct spectral content, without the need to predefine frequency bands of interest, and does so with less dependence on a priori threshold specification. We describe how the HMM can be used for burst detection and illustrate its benefits on simulated data. Finally, we apply this method to empirical data to detect multiple burst types in a task-MEG dataset, and illustrate how we can compute burst metrics, such as the task-evoked timecourse of burst duration. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of High Pressure Physics is the property of Chinese Journal of High Pressure Physics Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This work proposes modifications to the adaptive update law for a cerebellar model articulation controller (CMAC) and develops a model of a transcritical organic rankine cycle (ORC) to test it on. Owing to the local nature of its basis functions, the CMAC exhibits more weight drift (overlearning) than other types of neural networks, and practical applications have been restricted to systems without persistent oscillations of the inputs. The proposed solution to this problem here involves identifying a set of weights that is the best found so far in the training, and keeps the weights from drifting too far from these best weights. The method results in uniformly ultimately bounded signals, established through Lyapunov analysis. To show the improved training algorithm now allows the CMAC to control more general systems, it is applied to the control of a transcritical ORC. Part of the contribution of this paper also includes developing a model to describe the behaviour of a supercritical fluid in the ORC evaporator. The control method is compared with proportional–integral control, where the controls have to provide robustness to fluctuations and step changes in heat source temperatures. [ABSTRACT FROM AUTHOR]

Heterogeneity of neural properties within a given neural class is ubiquitous in the nervous system and permits different sub-classes of neurons to specialize for specific purposes. This principle has been thoroughly investigated in the hindbrain of the weakly electric fish A. leptorhynchus in the primary electrosensory area, the Electrosensory Lateral Line lobe (ELL). The pyramidal cells (PCs) that receive inputs from tuberous electroreceptors are organized in three maps in distinct segments of the ELL. The properties of these cells vary greatly across maps due to differences in connectivity, receptor expression, and ion channel composition. These cells are a seminal example of bursting neurons and their bursting dynamic relies on the presence of voltage-gated Na+ channels in the extensive apical dendrites of the superficial PCs. Other ion channels can affect burst generation and their expression varies across ELL neurons and segments. For example, SK channels cause hyperpolarizing after-potentials decreasing the likelihood of bursting, yet bursting propensity is similar across segments. We question whether the depolarizing mechanism that generates the bursts presents quantitative differences across segments that could counterbalance other differences having the opposite effect. Although their presence and role are established, the distribution and density of the apical dendrites' Na+ channels have not been quantified and compared across ELL maps. Therefore, we test the hypothesis that Na+ channel density varies across segment by quantifying their distribution in the apical dendrites of immunolabeled ELL sections. We found the Na+ channels to be two-fold denser in the lateral segment (LS) than in the centro-medial segment (CMS), the centro-lateral segment (CLS) being intermediate. Our results imply that this differential expression of voltage-gated Na+ channels could counterbalance or interact with other aspects of neuronal physiology that vary across segments (e.g., SK channels). We argue that burst coding of sensory signals, and the way the network regulates bursting, should be influenced by these variations in Na+ channel density. [ABSTRACT FROM AUTHOR]

Temperature fluctuations can affect neurological processes at a variety of levels, with the overall output that higher temperatures in general increase neuronal activity. While variations in firing rates can happen with the neuronal system maintaining its homeostatic firing pattern of tonic firing, or bursting, changes in firing rates can also be associated with transitions between the two patterns of firing. Our computer simulations suggest a possible mechanism directly related to the shortening of the duration of the action potential for higher firing rates with temperature increase. Increased temperatures also shorten the period doubling cascade and chaos transition between tonic and burting regimes. [ABSTRACT FROM AUTHOR]

To explore the influence of the microstructure of reinforcement fabric on the mechanical properties of curved composite, the basalt fabrics with differed organizational structures including plain, twill, sarin, and weft-free structure were immersed in a mixed solution of epoxy resin and coring agent, to prepare a series of carved composite materials by pressurize composite molding in a special mold. The being strength and flexural modulus of the carved composes Were measured by a three-point being test method. The impact properties, strength and failure mechanism of the curved composites were studied. The results indicated that the basalt basalt-fiber-reinforced curved composites with plain weave reinforcement have optimum bending performance, but those with a sarin structure have optimum impact optimum performance and tumuli the bending strength. On the other hand, the curved compo rites with the sarin structure have ability lower bursting strength than those with a twill structure. [ABSTRACT FROM AUTHOR]

Highlights • We create and verify a biophysically-detailed model of the olfactory blub external tufted cell. • Depolarizing (but not hyperpolaryzing) inputs received during the inter-burst interval can advance burst timing. • Specific currents controlling each burst characteristic are identified. • A heterogeneous population produces reliable responses to a range of periodic inputs, even though individual cells are entrained by inputs with higher, rather than lower frequencies. Abstract We introduce a novel detailed conductance-based model of the bursting activity in external tufted (ET) cells of the olfactory bulb. We investigate the mechanisms underlying their bursting, and make experimentally-testable predictions. The ionic currents included in the model are specific to ET cells, and their kinetic and other parameters are based on experimental recordings. We validate the model by showing that its bursting characteristics under various conditions (e.g. blocking various currents) are consistent with experimental observations. Further, we identify the bifurcation structure and dynamics that explain bursting behavior. This analysis allows us to make predictions of the response of the cell to current pulses at different burst phases. We find that depolarizing (but not hyperpolarizing) inputs received during the interburst interval can advance burst timing, creating the substrate for synchronization by excitatory connections. It has been hypothesized that such synchronization among the ET cells within one glomerulus might help coordinate the glomerular output. Next we investigate model parameter sensitivity and identify parameters that play the most prominent role in controlling each burst characteristic, such as the burst frequency and duration. Finally, the response of the cell to periodic inputs is examined, reflecting the sniffing-modulated input that these cell receive in vivo. We find that individual cells can be better entrained by inputs with higher, rather than lower, frequencies than the intrinsic bursting frequency of the cell. Nevertheless, a heterogeneous population of ET cells (as may be found in a glomerulus) is able to produce reliable periodic population responses even at lower input frequencies. [ABSTRACT FROM AUTHOR]

Brief bursts of high-frequency spikes are a common firing pattern of neurons. The cellular mechanisms of bursting and its biological significance remain a matter of debate. Focusing on the energy aspect, this paper proposes a neural energy calculation method based on the Chay model of bursting. The flow of ions across the membrane of the bursting neuron with or without current stimulation and its power which contributes to the change of the transmembrane electrical potential energy are analyzed here in detail. We find that during the depolarization of spikes in bursting this power becomes negative, which was also discovered in previous research with another energy model. We also find that the neuron's energy consumption during bursting is minimal. Especially in the spontaneous state without stimulation, the total energy consumption (2.152 × 10−7 J) during 30 s of bursting is very similar to the biological energy consumption (2.468 × 10−7 J) during the generation of a single action potential, as shown in Wang et al. (Neural Plast 2017, 2017a). Our results suggest that this property of low energy consumption could simply be the consequence of the biophysics of generating bursts, which is consistent with the principle of energy minimization. Our results also imply that neural energy plays a critical role in neural coding, which opens a new avenue for research of a central challenge facing neuroscience today. [ABSTRACT FROM AUTHOR]

Continuous pump and transmission of charges such as calcium, potassium, sodium in the cell can induce time-varying electromagnetic field, and the induced electric field can further modulate the propagation of ions in the cell. Based on the physical laws of static electric field, the effect of electric field in isolate neuron is investigated by introducing additive variable E on the model. Each neuron is considered as a charged body with complex distribution of charges, and electric field is triggered to receive and give response to external electric field and electric stimulus. That is, the electric field is considered as a new variable to describe the polarization modulation of media resulting from external electric field and intrinsic change of density distribution in charges or ions. The dynamical behaviors in electrical activities are analyzed and discussed in the new neuron model, and it confirms that electric field can cause distinct mode transition in electrical activities of neuron exposed to different kinds of electric field. It could provide new insights to understand signal encoding and propagation in nervous system. Finally, it also suggests that new model can be used for signal propagation between neurons when synapse coupling is suppressed. [ABSTRACT FROM AUTHOR]

Despite the intensive studies on neurons, the control mechanism in real interactions of neurons is still unclear. This paper presents an understanding of this kind of control mechanism, controlling a neuron by stimulating another coupled neuron, with the uncertainties taken into consideration for both neurons. Two observers and a differentiator, which comprise the first-order low-pass filters, are first designed for estimating the uncertainties. Then, with the estimated values combined, a robust nonlinear controller with a saturation function is presented to track the desired membrane potential. Finally, two typical bursters of neurons with the desired membrane potentials are proposed in the simulation, and the numerical results show that they are tracked very well by the proposed controller. [ABSTRACT FROM AUTHOR]

Abstract An experimental investigation on the self-excited spiky oscillations in a glow discharge plasma device is presented. The system showed a continuous transition from chaotic bursting to chaotic spiking states with the increase in the applied discharge voltage at a particular pressure. Below a threshold discharge voltage, the system exhibits a fixed point dynamical behaviour and with the increase in the discharge voltage bursting type oscillations appear which are identified as "fold/fold circle" type. The occurrence of the relaxation type spiky oscillations is attributed to the formation and disruption of anode double layer. The burst phases occurred intermittently and the frequency of their occurrence increased with increase in the discharge voltage and finally the oscillation turned into spiking behaviour. The intermittent oscillations manifested the scaling law of the average laminar phase with respect to the change in the discharge voltage. The scaling law of the intermittent oscillations was similar to type III intermittency. During the transition, the system changes its behaviour from long range correlation to long range anti correlation. Detrended fluctuation analysis technique has been used to identify the nature of long range correlations. We found that bursting oscillations show scale invariant, long-range correlation behaviour whereas spiking oscillations show scale invariant, long range anti correlation behaviour. Highlights • Transition from chaotic bursting to chaotic spiking behaviour is observed. • Floating potential fluctuations are intermittent in nature. • We found transition from long range correlation to long range anti correlation behaviour. • Long range correlation behaviour investigated using detrended fluctuation analysis. [ABSTRACT FROM AUTHOR]