Synchronous Bursts Research Articles

Subthalamic nucleus activity dynamics and limb movement prediction in Parkinson's disease.

Whilst exaggerated bursts of beta frequency band oscillatory synchronization in the subthalamic nucleus have been associated with motor impairment in Parkinson's disease, a plausible mechanism linking the two phenomena has been lacking. Here we test the hypothesis that increased synchronization denoted by beta bursting might compromise information coding capacity in basal ganglia networks. To this end we recorded local field potential activity in the subthalamic nucleus of 18 patients with Parkinson's disease as they executed cued upper and lower limb movements. We used the accuracy of local field potential-based classification of the limb to be moved on each trial as an index of the information held by the system with respect to intended action. Machine learning using the naïve Bayes conditional probability model was used for classification. Local field potential dynamics allowed accurate prediction of intended movements well ahead of their execution, with an area under the receiver operator characteristic curve of 0.80 ± 0.04 before imperative cues when the demanded action was known ahead of time. The presence of bursts of local field potential activity in the alpha, and even more so, in the beta frequency band significantly compromised the prediction of the limb to be moved. We conclude that low frequency bursts, particularly those in the beta band, restrict the capacity of the basal ganglia system to encode physiologically relevant information about intended actions. The current findings are also important as they suggest that local subthalamic activity may potentially be decoded to enable effector selection, in addition to force control in restorative brain-machine interface applications.

Emergence of bursting in two coupled neurons of different types of excitability

Abstract In this manuscript, a spiking neuron of type I excitability and a silent neuron of type II excitability are coupled through a gap junction with unequal coupling strengths, and none of the coupled neurons can burst intrinsically. By applying the theory of dynamical systems (e.g. bifurcation theory), we investigate how the coupling strength affects the dynamics of the neurons, when one of the coupling strengths is fixed and the other varies. We report four different regimes of oscillations as the coupling strength increases. (1) Spike–Spike Phase–Locking, where both neurons are in tonic spiking mode but with different frequencies; (2) Spike–Burst mode, where the type II neuron bursts while the type I neuron remains in tonic spiking mode; (3) Burst–Burst synchronization, where the neurons burst synchronously, i.e., both neurons enter and exit the active phase almost together; (4) Spike–Spike Synchronization, where the neurons synchronize as two oscillators, i.e., they oscillate with equal time period and fraquency. An interesting finding is that there exist two different synchronous behaviours, one of them corresponds to 1 − burst synchronization of the neurons and the other corresponds to the synchronizations of 1 − bursting oscillations in type II neuron and tonic spiking oscillations in type I neuron. Finally it should be pointed out that all through increasing the coupling strength we observe sequences of intermittency in the neurons, which is an abrupt and irregular transition between periodic oscillations and chaotic dynamics.

Nutrient restriction causes reversible G2 arrest in Xenopus neural progenitors.

Nutrient status affects brain development; however, the effects of nutrient availability on neural progenitor cell proliferation in vivo are poorly understood. Without food, Xenopus laevis tadpoles enter a period of stasis during which neural progenitor proliferation is drastically reduced, but resumes when food becomes available. Here, we investigate how neural progenitors halt cell division in response to nutrient restriction and subsequently re-enter the cell cycle upon feeding. We demonstrate that nutrient restriction causes neural progenitors to arrest in G2 of the cell cycle with increased DNA content, and that nutrient availability triggers progenitors to re-enter the cell cycle at M phase. Initiation of the nutrient restriction-induced G2 arrest is rapamycin insensitive, but cell cycle re-entry requires mTOR. Finally, we show that activation of insulin receptor signaling is sufficient to increase neural progenitor cell proliferation in the absence of food. A G2 arrest mechanism provides an adaptive strategy to control brain development in response to nutrient availability by triggering a synchronous burst of cell proliferation when nutrients become available. This may be a general cellular mechanism that allows developmental flexibility during times of limited resources.

Synchronization patterns in a blinking multilayer neuronal network

Synchronization is one of the most prominent collective behaviors in neuroscience which can be associated with information processing and many pathological patterns of the brain. Since multilayer networks have crucial roles in better understanding the real complex systems, in this paper, we study a two-layer neuronal network of Hindmarsh–Rose neurons. Moreover, the network is considered to have blinking structure which can refer to the duration of spikes arrivals and also the synaptic plasticity. The blinking network is composed of the non-locally coupled neurons and time-variant on–off couplings between any other pair of neurons. Particularly, we investigate the synchronization patterns emerging in the network by varying coupling strength and wiring probability, in different values of external current. Variation of the coupling parameters can cause the emergence of various dynamical states such as chimera state, imperfect synchronization and change of synchronous spikes to synchronous bursts or vice versa. It can also lead to synchronization transition between FHC and FH bursting types.

Field of coherence of GPS-measured earth tremors

A new method for investigating the coherence field of the noise component of high-frequency GPS time series is proposed. The method is applied to the main territory of the USA, which is characterized by a dense network of GPS stations. The data are presented in steps of 5 min from February 28, 2013, until June 29, 2019, on the Nevada Geodetic Laboratory Web site. The proposed method estimates the spatial distribution of the mean values of multiple coherence, calculated within nodes of a regular grid, between GPS coordinates of a given number of nearest operable stations and the periods at which the maximum values of coherence are reached. The two-dimensional probability density of the positions of places where the coherence maximum is most often realized is estimated. These estimates can be obtained for the entire history of observations and also in a sliding time window of a given length, which makes it possible to trace the dynamics of changes in time in the coherence field of the earth’s tremor. The entropy of the two-dimensional probability density of places of concentration of maximum values of coherence allows us to distinguish seasonal changes in the structure of the coherence field of GPS noise. To study the temporal dynamics, we use the auxiliary time series of changes in the maximum multiple coherence at 50 reference points located throughout the study area. The study of the coherence properties of this auxiliary 50-dimensional time series (“secondary coherence”) in a 180-day sliding time window highlighted a series of synchronization bursts of earth’s surface tremors.

Energetic substrate availability regulates synchronous activity in an excitatory neural network.

Neural networks are required to meet significant metabolic demands associated with performing sophisticated computational tasks in the brain. The necessity for efficient transmission of information imposes stringent constraints on the metabolic pathways that can be used for energy generation at the synapse, and thus low availability of energetic substrates can reduce the efficacy of synaptic function. Here we study the effects of energetic substrate availability on global neural network behavior and find that glucose alone can sustain excitatory neurotransmission required to generate high-frequency synchronous bursting that emerges in culture. In contrast, obligatory oxidative energetic substrates such as lactate and pyruvate are unable to substitute for glucose, indicating that processes involving glucose metabolism form the primary energy-generating pathways supporting coordinated network activity. Our experimental results are discussed in the context of the role that metabolism plays in supporting the performance of individual synapses, including the relative contributions from postsynaptic responses, astrocytes, and presynaptic vesicle cycling. We propose a simple computational model for our excitatory cultures that accurately captures the inability of metabolically compromised synapses to sustain synchronous bursting when extracellular glucose is depleted.

Sensorimotor transformation elicits systematic patterns of activity along the dorsoventral extent of the superior colliculus in the macaque monkey

The superior colliculus (SC) is an excellent substrate to study sensorimotor transformations. To date, the spatial and temporal properties of population activity along its dorsoventral axis have been inferred from single electrode studies. Here, we recorded SC population activity in non-human primates using a linear multi-contact array during delayed saccade tasks. We show that during the visual epoch, information appeared first in dorsal layers and systematically later in ventral layers. During the delay period, the laminar organization of low-spiking rate activity matched that of the visual epoch. During the pre-saccadic epoch, spiking activity emerged first in a more ventral layer, ~ 100 ms before saccade onset. This buildup of activity appeared later on nearby neurons situated both dorsally and ventrally, culminating in a synchronous burst across the dorsoventral axis, ~ 28 ms before saccade onset. Collectively, these results reveal a principled spatiotemporal organization of SC population activity underlying sensorimotor transformation for the control of gaze.

Cluster burst synchronization in a scale-free network of inhibitory bursting neurons.

We consider a scale-free network of inhibitory Hindmarsh-Rose (HR) bursting neurons, and make a computational study on coupling-induced cluster burst synchronization by varying the average coupling strength . For sufficiently small , non-cluster desynchronized states exist. However, when passing a critical point , the whole population is segregated into 3 clusters via a constructive role of synaptic inhibition to stimulate dynamical clustering between individual burstings, and thus 3-cluster desynchronized states appear. As is further increased and passes a lower threshold , a transition to 3-cluster burst synchronization occurs due to another constructive role of synaptic inhibition to favor population synchronization. In this case, HR neurons in each cluster make burstings every 3rd cycle of the instantaneous burst rate of the whole population, and exhibit burst synchronization. However, as passes an intermediate threshold , HR neurons fire burstings intermittently at a 4th cycle of via burst skipping rather than at its 3rd cycle, and hence they begin to make intermittent hoppings between the 3 clusters. Due to such intermittent intercluster hoppings via burst skippings, the 3 clusters become broken up (i.e., the 3 clusters are integrated into a single one). However, in spite of such break-up (i.e., disappearance) of the 3-cluster states, (non-cluster) burst synchronization persists in the whole population, which is well visualized in the raster plot of burst onset times where bursting stripes (composed of burst onset times and indicating burst synchronization) appear successively. With further increase in , intercluster hoppings are intensified, and bursting stripes also become dispersed more and more due to a destructive role of synaptic inhibition to spoil the burst synchronization. Eventually, when passing a higher threshold a transition to desynchronization occurs via complete overlap between the bursting stripes. Finally, we also investigate the effects of stochastic noise on both 3-cluster burst synchronization and intercluster hoppings.

Preliminary results of simultaneous recording of auroral and geomagnetic pulsations at the ISTP SB RAS station Istok

The paper presents the results on first synchronous observations of variations in auroral luminosity and geomagnetic field, made with high temporal resolution at the ISTP SB RAS high-latitude station Istok (70° N, 88° E) in September–December 2018. Auroras were recorded with all-sky camera, pulsations in the auroras were recorded by a photometer in four spectral ranges with silicon photomultipliers. Continuous monitoring of geomagnetic pulsations was performed using a LEMI-30 three-component induction magnetometer.
 Both synchronous bursts of auroras and magnetic field pulsations, as well as disturbances of auroras, not accompanied by disturbances in the geomagnetic field, were observed. We note that the photometer clearly recorded short-period (~20 min) variations in in auroral luminosity. At the same time, some instability of the photometer signal level occurred at sufficiently long time intervals.
 In the photometer data, there are powerful signal bursts, probably of a hardware nature. Nevertheless, the temporary distribution analysis of the registration moments (registration frequency) of signal bursts indicates the possible dependence of the burst registration frequency on the geomagnetic activity level.

Предварительные результаты синхронной регистрации авроральных и геомагнитных пульсаций на станции «Исток» ИСЗФ СО РАН

The paper presents the results on first synchronous observations of variations in auroral luminosity and geomagnetic field, made with high temporal resolution at the ISTP SB RAS high-latitude station Istok (70° N, 88° E) in September–December 2018. Auroras were recorded with all-sky camera, pulsations in the auroras were recorded by a photometer in four spectral ranges with silicon photomultipliers. Continuous monitoring of geomagnetic pulsations was performed using a LEMI-30 three-component induction magnetometer.
 Both synchronous bursts of auroras and magnetic field pulsations, as well as disturbances of auroras, not accompanied by disturbances in the geomagnetic field, were observed. We note that the photometer clearly recorded short-period (~20 min) variations in in auroral luminosity. At the same time, some instability of the photometer signal level occurred at sufficiently long time intervals.
 In the photometer data, there are powerful signal bursts, probably of a hardware nature. Nevertheless, the temporary distribution analysis of the registration moments (registration frequency) of signal bursts indicates the possible dependence of the burst registration frequency on the geomagnetic activity level.

Inhomogeneities in Network Structure and Excitability Govern Initiation and Propagation of Spontaneous Burst Activity.

The mesoscale architecture of neuronal networks strongly influences the initiation of spontaneous activity and its pathways of propagation. Spontaneous activity has been studied extensively in networks of cultured cortical neurons that generate complex yet reproducible patterns of synchronous bursting events that resemble the activity dynamics in developing neuronal networks in vivo. Synchronous bursts are mostly thought to be triggered at burst initiation sites due to build-up of noise or by highly active neurons, or to reflect reverberating activity that circulates within larger networks, although neither of these has been observed directly. Inferring such collective dynamics in neuronal populations from electrophysiological recordings crucially depends on the spatial resolution and sampling ratio relative to the size of the networks assessed. Using large-scale microelectrode arrays with 1024 electrodes at 0.3 mm pitch that covered the full extent of in vitro networks on about 1 cm2, we investigated where bursts of spontaneous activity arise and how their propagation patterns relate to the regions of origin, the network’s structure, and to the overall distribution of activity. A set of alternating burst initiation zones (BIZ) dominated the initiation of distinct bursting events and triggered specific propagation patterns. Moreover, BIZs were typically located in areas with moderate activity levels, i.e., at transitions between hot and cold spots. The activity-dependent alternation between these zones suggests that the local networks forming the dominating BIZ enter a transient depressed state after several cycles (similar to Eytan et al., 2003), allowing other BIZs to take over temporarily. We propose that inhomogeneities in the network structure define such BIZs and that the depletion of local synaptic resources limit repetitive burst initiation.

PCNN Mechanism and its Parameter Settings.

The pulse-coupled neural network (PCNN) model is a third-generation artificial neural network without training that uses the synchronous pulse bursts of neurons to process digital images, but the lack of in-depth theoretical research limits its extensive application. By analyzing the working mechanism of the PCNN, we present an expression for the fire-extinguishing time of neurons that fire in the second iteration and an expression for the firing time of neurons that extinguish in the second iteration. In addition, we find a phenomenon of the PCNN and name it mathematically coupled fire extinguishing. Based on the above analysis, we propose a new working mode for the PCNN, where the refiring of fire-extinguishing neurons is only allowed when all firing neurons are extinguished. We also work out the constraint conditions of the parameter settings under this mode. Furthermore, we analyze the relationship between the network parameters and mathematically coupled fire extinguishing, the coupling of neighboring neurons, and the convergence rate of the PCNN, respectively. In addition, we demonstrate the essential regularity of extinguished neuron in the PCNN and then propose an optimal parameter setting to achieve the best comprehensive performance of the PCNN.

Bistable Firing Pattern in a Neural Network Model.

Excessively high, neural synchronization has been associated with epileptic seizures, one of the most common brain diseases worldwide. A better understanding of neural synchronization mechanisms can thus help control or even treat epilepsy. In this paper, we study neural synchronization in a random network where nodes are neurons with excitatory and inhibitory synapses, and neural activity for each node is provided by the adaptive exponential integrate-and-fire model. In this framework, we verify that the decrease in the influence of inhibition can generate synchronization originating from a pattern of desynchronized spikes. The transition from desynchronous spikes to synchronous bursts of activity, induced by varying the synaptic coupling, emerges in a hysteresis loop due to bistability where abnormal (excessively high synchronous) regimes exist. We verify that, for parameters in the bistability regime, a square current pulse can trigger excessively high (abnormal) synchronization, a process that can reproduce features of epileptic seizures. Then, we show that it is possible to suppress such abnormal synchronization by applying a small-amplitude external current on > 10% of the neurons in the network. Our results demonstrate that external electrical stimulation not only can trigger synchronous behavior, but more importantly, it can be used as a means to reduce abnormal synchronization and thus, control or treat effectively epileptic seizures.

Synchronous spike patterns in differently mixed cultures of human iPSC-derived glutamatergic and GABAergic neurons

Human induced-pluripotent stem cell (hiPSC)-derived neurons develop organized neuronal networks under in vitro cultivation conditions. Here, using a multielectrode array system, we examined whether the spike patterns of hiPSC-derived neuronal populations differed in a manner that depended on the proportions of glutamatergic and gamma-aminobutyric acid (GABA)ergic neurons in the cultures. Synchronous burst firing events spanning multiple electrodes became more frequent as the number of days in culture increased. However, at all developmental stages, the event rates of synchronous burst firing, the repertoires of synchronous burst firing, and the frequencies of sporadic spikes did not differ in cultures with different glutamatergic-to-GABAergic ratios. Pharmacological blockade of GABAergic synaptic transmission increased the frequencies of spike patterns specifically in cultures with lower glutamatergic-to-GABAergic ratios. These results demonstrate that a robust homeostatic property of developing hiPSC-derived neuronal networks in culture counteracts chronically imbalanced glutamatergic and GABAergic signaling.

In vitro neuronal network activity as a new functional diagnostic system to detect effects of Cerebrospinal fluid from autoimmune encephalitis patients

The intent of this study was to investigate if cerebrospinal fluid (CSF) from autoimmune encephalitis (AE) patients regulates in vitro neuronal network activity differentially to healthy human control CSF (hCSF). To this end, electrophysiological effects of CSF from AE patients or hCSF were measured by in vitro neuronal network activity (ivNNA) recorded with microelectrode arrays (MEA). CSF from patients with either N-methyl-D-aspartate-receptor-antibody (pCSFNMDAR, n = 7) or Leucine-rich-glioma-inactivated-1-Ab (pCSFLGI1, n = 6) associated AE suppressed global spiking activity of neuronal networks by a factor of 2.17 (p < 0.05) or 2.42 (p < 0.05) compared to hCSF. The former also suppressed synchronous network bursting by a factor of 1.93 (p < 0.05) in comparison to hCSF (n = 13). As a functional diagnostic test, this parameter reached a sensitivity of 86% for NMDAR-Ab- and 100% for LGI1-Ab-associated AE vs. hCSF at a specificity of 85%. To explore if modulation at the NMDAR influences effects of hCSF or pathological CSF, we applied the NMDAR-antagonist 2-Amino-5-phosphono-pentanoic acid (AP5). In CSF from NMDAR-Ab-associated AE patients, spike rate reduction by AP5 was more than 2-fold larger than in hCSF (p < 0.05), and network burst rate reduction more than 18-fold (p < 0.01). Recording ivNNA might help discriminating between functional effects of CSF from AE patients and hCSF, and thus could be used as a functional diagnostic test in AE. The pronounced suppression of ivNNA by CSF from NMDAR-Ab-associated AE patients and simultaneous antagonism at the NMDAR by AP5, particularly in burst activity, compared to hCSF plus AP5, confirms that the former contains additional ivNNA-suppressing factors.

Non‐cooperative burst detection and synchronisation in downlink TDMA‐based wireless communication networks

Blind signal detection is very important in various applications such as cognitive radio, spectrum surveillance, and eavesdropping. This gets trickier when one needs to deal with burst signals (as opposed to continuously transmitted signals) in non-cooperative environments. Here, existing methods for signal detection are studied and developed to use for burst detection. For the special case of downlink time division multiple access (TDMA) burst transmission, performances of these detection methods are improved by proposing a blind synchronisation algorithm which is applied to the output result of detection algorithms. The results of Monte–Carlo simulations demonstrate the performance of the proposed detection and synchronisation algorithms.

Synchronization domains in two coupled neural networks

We investigate the dynamical properties of two coupled neural networks with 2,048 identical Hodgkin--Huxley type bursting neurons. The internal connection architecture of each network follows a small-world topology and the external connection scheme is based on the local mean field potential, where one network receives the signal from the other. To analyze the system, we use Kuramoto order parameter computed over each neuron data, and recurrence quantification analyses, particularly the ratio of recurrent points belonging to diagonal lines of the recurrence plot RP, namely the determinism, computed over the local mean field potential of the networks, an easier experimentally accessible data. We analyze the complex synchronization scenario depicted by the network as a function of internal and external coupling parameters. Particularly, we identify regions of non-monotonic dependence of the synchronization level as a function of the coupling strength; coupling induced phase desynchronization (PD), where the synchronization levels are similar to those expected for randomly distributed phases; almost complete spike synchronization (SS) for which even spikes composing a burst are synchronized. This regime occurs as a product of the fast modulated signal imposed by the coupling between networks and weak internal coupling; finally, bursting synchronization (BS) regions are associated with slow modulated internal coupling.

Electrophysiological properties of identified oxytocin and vasopressin neurones.

To understand the contribution of intrinsic membrane properties to the different in vivo firing patterns of oxytocin (OT) and vasopressin (VP) neurones, in vitro studies are needed, where stable intracellular recordings can be made. Combining immunochemistry for OT and VP and intracellular dye injections allows characterisation of identified OT and VP neurones, and several differences between the two cell types have emerged. These include a greater transient K+ current that delays spiking to stimulus onset, and a higher Na+ current density leading to greater spike amplitude and a more stable spike threshold, in VP neurones. VP neurones also show a greater incidence of both fast and slow Ca2+ -dependent depolarising afterpotentials, the latter of which summate to plateau potentials and contribute to phasic bursting. By contrast, OT neurones exhibit a sustained outwardly rectifying potential (SOR), as well as a consequent depolarising rebound potential, not found in VP neurones. The SOR makes OT neurones more susceptible to spontaneous inhibitory synaptic inputs and correlates with a longer period of spike frequency adaptation in these neurones. Although both types exhibit prominent Ca2+ -dependent afterhyperpolarising potentials (AHPs) that limit firing rate and contribute to bursting patterns, Ca2+ -dependent AHPs in OT neurones selectively show significant increases during pregnancy and lactation. In OT neurones, but not VP neurones, AHPs are highly dependent on the constitutive presence of the second messenger, phosphatidylinositol 4,5-bisphosphate, which permissively gates N-type channels that contribute the Ca2+ during spike trains that activates the AHP. By contrast to the intrinsic properties supporting phasic bursting in VP neurones, the synchronous bursting of OT neurones has only been demonstrated in vitro in cultured hypothalamic explants and is completely dependent on synaptic transmission. Additional differences in Ca2+ channel expression between the two neurosecretory terminal types suggests these channels are also critical players in the differential release of OT and VP during repetitive spiking, in addition to their importance to the potentials controlling firing patterns.

Calcium imaging, MEA recordings, and immunostaining images dataset of neuron-astrocyte networks in culture under the effect of norepinephrine.

BackgroundMonitoring the activity and morphology of neuron-astrocyte networks in culture is a powerful tool for studying dynamics, structure, and communication in neuron-astrocyte networks independently or as a model of the sub-brain network. These cultures are known to produce stereotypical patterns of activity, e.g., highly synchronized network bursts resembling sleep or seizure states, thus it enables the exploration of behaviors that can relate to brain function and disease. High-resolution microscopy of calcium imaging combined with simultaneous electrical recording provides a comprehensive overview on the network's dynamics. This setup makes it possible to apply global perturbations of electrical and chemical stimulation on the cultures during the recording task and to record the effects on network activity on-line. Morphological changes in the cultures can be obtained to have a complete dataset for structure-function study of neuron-astrocyte networks in vitro.FindingsThe 4 TB of data presented here was recorded and imaged as part of an accompanying study looking at in vitro structure-function of neuron-astrocyte networks. Simultaneous optical (calcium imaging) and electrical (micro-electrode array) recordings lasted 5–12 minutes and included spontaneous activity recording, electrical and chemical stimulation of neuron-astrocyte, and isolated astrocyte cultures. The data include activity recordings of 58 different cultures, with 1–2 regions of interest recorded for each culture. Production procedures, experimental protocols, and reuse options are included. The data have been suitable to reveal changes in the activity and morphology of the cultures and enabled observation and analysis of neuron-astrocyte and isolated astrocyte culture behaviors under the applied perturbations.ConclusionsOur dataset is sufficient to show significant changes in activity and morphology of neuron-astrocyte networks in culture under the applied stimulations. More than 100 recordings of 58 different cultures give insight of the observation's significance and led to conclusions about astrocyte activity and neuron-astrocyte network communication. Making it available here will allow others to test new tools for calcium imaging analysis and extracellular neuronal voltage recordings.

Effects of Time Delay on Burst Synchronization Transition of Neuronal Networks

In this paper, we focus on investigating the effects of time delay on burst synchronization transitions of a neuronal network which is locally modeled by Hindmarsh–Rose neurons. Here, neurons inside the neuronal network are connected through electrical synapses or chemical synapses. With the numerical results, it is revealed that burst synchronization transitions of both electrically and chemically coupled neuronal networks could be induced by time delay just when the coupling strength is large enough. Meanwhile, it is found that, in electrically and excitatory chemically coupled neuronal networks, burst synchronization transitions are observed through change of spiking number per burst when coupling strength is large enough; while in inhibitory chemically coupled neuronal network, burst synchronization transitions are observed for large enough coupling strength through changing fold-Hopf bursting activity to fold-homoclinic bursting activity and vice versa. Namely, two types of burst synchronization transitions are observed. One type of burst synchronization transitions occurs through change of spiking numbers per burst and the other type of burst synchronization transition occurs through change of bursting types.