Synchronization In Neuronal Networks Research Articles

Firing synchronization of learning neuronal networks with small-world connectivity

The properties of firing synchronization of learning neuronal networks, electrically and chemically coupled ones, with small-world connectivity are studied. First, the variation properties of synaptic weights are examined. Next the effects of the synaptic learning rate on the properties of firing rate and synchronization are investigated. The influences of the coupling strength and the shortcut probability on synchronization are also explored. It is shown that synaptic learning suppresses over-excitement for the networks, helps synchronization for the electrically coupled neuronal network but destroys synchronization for the chemically coupled one. Both introducing shortcuts and increasing the coupling strength are helpful in improving synchronization of the neuronal networks. The spatio-temporal patterns illustrate and confirm the above results.

Delay-induced intermittent transition of synchronization in neuronal networks with hybrid synapses

We study the dependence of synchronization transitions in scale-free networks of bursting neurons with hybrid synapses on the information transmission delay and the probability of inhibitory synapses. It is shown that, irrespective of the probability of inhibitory synapses, the delay always plays a subtle role during synchronization transition of the scale-free neuronal networks. In particular, regions of irregular and regular propagating excitatory fronts appear intermittently as the delay increases. These delay-induced synchronization transitions are manifested as well-expressed minima in the measure for spatiotemporal synchrony. In addition, it is found that, for smaller and larger probability of inhibitory synapses, intermittent synchronization transition is relatively profound, while for the moderate probability of inhibitory synapses, synchronization transition seems less profound. More interestingly, it is found that as the probability of inhibitory synapses is large, regions of synchronization are upscattering.

Mesoscale and clusters of synchrony in networks of bursting neurons

We study the role of network architecture in the formation of synchronous clusters in synaptically coupled networks of bursting neurons. We give a simple combinatorial algorithm that finds the largest synchronous clusters from the network topology. We demonstrate that networks with a certain degree of internal symmetries are likely to have cluster decompositions with relatively large clusters, leading potentially to cluster synchronization at the mesoscale network level. We also address the asymptotic stability of cluster synchronization in excitatory networks of Hindmarsh-Rose bursting neurons and derive explicit thresholds for the coupling strength that guarantees stable cluster synchronization.

Neuroscience: What We Cannot Model, We Do Not Understand

To understand computations in neuronal circuits, a model of a small patch of cortex has been developed that can describe the firing regime in the visual system remarkably well.

Natural Frequency Adaptation as a Mechanism for Phase Synchronization in Neural Systems

AbstractWe consider the problem of adaptive phase synchronization in a system of coupled phase oscillators. The system is limited to a pair of phase oscillators of which the natural frequencies are uncertain, yet they can be tuned. Coupling between the oscillators is allowed to depend on the natural frequencies nonlinearly. Three different mechanisms for the natural frequency self-tuning leading to the emergence of synchronous states are presented and analyzed. The problem is relevant for explaining and modelling phase synchronization and purposeful frequency adaptation in neuronal networks.

Synchronization of the small-world neuronal network with unreliable synapses

As is well known, synchronization phenomena are ubiquitous in neuronal systems. Recently a lot of work concerning the synchronization of the neuronal network has been accomplished. In these works, the synapses are usually considered reliable, but experimental results show that, in biological neuronal networks, synapses are usually unreliable. In our previous work, we have studied the synchronization of the neuronal network with unreliable synapses; however, we have not paid attention to the effect of topology on the synchronization of the neuronal network. Several recent studies have found that biological neuronal networks have typical properties of small-world networks, characterized by a short path length and high clustering coefficient. In this work, mainly based on the small-world neuronal network (SWNN) with inhibitory neurons, we study the effect of network topology on the synchronization of the neuronal network with unreliable synapses. Together with the network topology, the effects of the GABAergic reversal potential, time delay and noise are also considered. Interestingly, we found a counter-intuitive phenomenon for the SWNN with specific shortcut adding probability, that is, the less reliable the synapses, the better the synchronization performance of the SWNN. We also consider the effects of both local noise and global noise in this work. It is shown that these two different types of noise have distinct effects on the synchronization: one is negative and the other is positive.

Acetylcholine in the cerebral cortex

Cholinergic inputs from the basal forebrain to the neocortex and hippocampus have a key role in mechanisms of arousal, attention, sensory processing, and memory. Acetylcholine (ACh) exerts multiple effects in the cerebral cortex via muscarinic (mAChR) and nicotinic (nAChR) receptors located presynaptically and postsynaptically in both pyramidal glutamatergic projection and local γ-aminobutyric acid (GABA)-ergic neurons. Through its multiple actions, ACh affects signal-to-noise ratio during sensory processing and modulates synchronization of neuronal networks. The physiologic effects of ACh include enhancement of both attention to sensory stimuli and encoding of memory for specific stimuli. Experimental studies using a variety of approaches have provided insight into the mechanisms of cholinergic modulation of cortical function and cognition. The basal forebrain cholinergic system is affected in several neurodegenerative disorders, including Alzheimer disease (AD), Parkinson disease (PD), and dementia with Lewy bodies (DLB), and may contribute to behavioral manifestations of psychiatric disorders such as schizophrenia. Functional neuroimaging allows the exploration of the effects of cholinergic cortical modulation in healthy subjects and its alterations in patients with neurodegenerative disorders. The recognition of the importance of ACh in normal cortical function has stimulated major advances in the discovery of novel pharmacologic approaches to these conditions. Many of these subjects have been comprehensively covered in excellent reviews.1–12 ### Main connections. Neurons of the basal forebrain are the major source of ACh supplying the neocortex and hippocampus (figure 1). They include the Ch1–Ch3 subgroups located in the medial septum and diagonal band of Broca, providing innervation of the hippocampus, and the Ch4 subgroup located in the nucleus basalis magnocellularis (NBM) and innervating the cerebral cortex and amygdala.1 Survival of basal forebrain cholinergic neurons depends on the trophic effects nerve growth factor, which is synthesized and secreted by cells in the cortex and hippocampus, binds to tyrosine kinase A receptors, and travels …

Phase-response curves and synchronized neural networks

We review the principal assumptions underlying the application of phase-response curves (PRCs) to synchronization in neuronal networks. The PRC measures how much a given synaptic input perturbs spike timing in a neural oscillator. Among other applications, PRCs make explicit predictions about whether a given network of interconnected neurons will synchronize, as is often observed in cortical structures. Regarding the assumptions of the PRC theory, we conclude: (i) The assumption of noise-tolerant cellular oscillations at or near the network frequency holds in some but not all cases. (ii) Reduced models for PRC-based analysis can be formally related to more realistic models. (iii) Spike-rate adaptation limits PRC-based analysis but does not invalidate it. (iv) The dependence of PRCs on synaptic location emphasizes the importance of improving methods of synaptic stimulation. (v) New methods can distinguish between oscillations that derive from mutual connections and those arising from common drive. (vi) It is helpful to assume linear summation of effects of synaptic inputs; experiments with trains of inputs call this assumption into question. (vii) Relatively subtle changes in network structure can invalidate PRC-based predictions. (viii) Heterogeneity in the preferred frequencies of component neurons does not invalidate PRC analysis, but can annihilate synchronous activity.

NETWORK COMPLEXITY AND SYNCHRONOUS BEHAVIOR — AN EXPERIMENTAL APPROACH

We discuss synchronization in networks of Hindmarsh-Rose neurons that are interconnected via gap junctions, also known as electrical synapses. We present theoretical results for interactions without time-delay. These results are supported by experiments with a setup consisting of sixteen electronic equivalents of the Hindmarsh-Rose neuron. We show experimental results of networks where time-delay on the interaction is taken into account. We discuss in particular the influence of the network topology on the synchronization.

Not Again! the Role of Blood–Brain Barrier Failure in Epileptogenesis: Amolecular Update

Transcriptome Profiling Reveals TGF-β Signaling Involvement in Epileptogenesis. Cacheaux LP, Ivens S, David Y, Lakhter AJ, Bar-Klein G, Shapira M, Heinemann U, Friedman A, Kaufer D. J Neurosci 2009;29(28):8927–8935. Brain injury may result in the development of epilepsy, one of the most common neurological disorders. We previously demonstrated that albumin is critical in the generation of epilepsy after blood–brain barrier (BBB) compromise. Here, we identify TGF-β pathway activation as the underlying mechanism. We demonstrate that direct activation of the TGF-β pathway by TGF-β1 results in epileptiform activity similar to that after exposure to albumin. Coimmunoprecipitation revealed binding of albumin to TGF-β receptor II, and Smad2 phosphorylation confirmed downstream activation of this pathway. Transcriptome profiling demonstrated similar expression patterns after BBB breakdown, albumin, and TGF-β1 exposure, including modulation of genes associated with the TGF-β pathway, early astrocytic activation, inflammation, and reduced inhibitory transmission. Importantly, TGF-β pathway blockers suppressed most albumin-induced transcriptional changes and prevented the generation of epileptiform activity. Our present data identifies the TGF-β pathway as a novel putative epileptogenic signaling cascade and therapeutic target for the prevention of injury-induced epilepsy. Astrocytic Dysfunction in Epileptogenesis: Consequence of Altered Potassium and Glutamate Homeostasis? David Y, Cacheaux LP, Ivens S, Lapilover E, Heinemann U, Kaufer D, Friedman A. J Neurosci 2009;29(34):10588–10599. Focal epilepsy often develops following traumatic, ischemic, or infectious brain injury. While the electrical activity of the epileptic brain is well characterized, the mechanisms underlying epileptogenesis are poorly understood. We have recently shown that in the rat neocortex, long-lasting breakdown of the blood–brain barrier (BBB) or direct exposure of the neocortex to serum-derived albumin leads to rapid upregulation of the astrocytic marker glial fibrillary acidic protein, followed by delayed (within 4–7 day) development of an epileptic focus. We investigated the role of astrocytes in epileptogenesis in the BBB-breakdown and albumin models of epileptogenesis. We found similar, robust changes in astrocytic gene expression in the neocortex within hours following treatment with deoxycholic acid (BBB breakdown) or albumin. These changes predict reduced clearance capacity for both extracellular glutamate and potassium. Electrophysiological recordings in vitro confirmed the reduced clearance of activity-dependent accumulation of both potassium and glutamate 24 hour following exposure to albumin. We used a NEURON model to simulate the consequences of reduced astrocytic uptake of potassium and glutamate on EPSPs. The model predicted that the accumulation of glutamate is associated with frequency-dependent (>100 Hz) decreased facilitation of EPSPs, while potassium accumulation leads to frequency-dependent (10–50 Hz) and NMDA-dependent synaptic facilitation. In vitro electrophysiological recordings during epileptogenesis confirmed frequency-dependent synaptic facilitation leading to seizure-like activity. Our data indicate a transcription-mediated astrocytic transformation early during epileptogenesis. We suggest that the resulting reduction in the clearance of extracellular potassium underlies frequency-dependent neuronal hyperexcitability and network synchronization.

Phase Response Curve Analysis of a Full Morphological Globus Pallidus Neuron Model Reveals Distinct Perisomatic and Dendritic Modes of Synaptic Integration

Synchronization of globus pallidus (GP) neurons and cortically entrained oscillations between GP and other basal ganglia nuclei are key features of the pathophysiology of Parkinson's disease. Phase response curves (PRCs), which tabulate the effects of phasic inputs within a neuron's spike cycle on output spike timing, are efficient tools for predicting the emergence of synchronization in neuronal networks and entrainment to periodic input. In this study we apply physiologically realistic synaptic conductance inputs to a full morphological GP neuron model to determine the phase response properties of the soma and different regions of the dendritic tree. We find that perisomatic excitatory inputs delivered throughout the interspike interval advance the phase of the spontaneous spike cycle yielding a type I PRC. In contrast, we demonstrate that distal dendritic excitatory inputs can either delay or advance the next spike depending on whether they occur early or late in the spike cycle. We find this latter pattern of responses, summarized by a biphasic (type II) PRC, was a consequence of dendritic activation of the small conductance calcium-activated potassium current, SK. We also evaluate the spike-frequency dependence of somatic and dendritic PRC shapes, and we demonstrate the robustness of our results to variations of conductance densities, distributions, and kinetic parameters. We conclude that the distal dendrite of GP neurons embodies a distinct dynamical subsystem that could promote synchronization of pallidal networks to excitatory inputs. These results highlight the need to consider different effects of perisomatic and dendritic inputs in the control of network behavior.

Neuroprotective Effect of Piperine on Primarily Cultured Hippocampal Neurons

It was previously reported that piperine (PIP) significantly blocks convulsions induced by intracerebroventricular injection of threshold doses of kainate, but had no or only slight effects on convulsions induced by L-glutamate, N-methyl-D-aspartate and guanidinosuccinate. In traditional Chinese medicine, black pepper has been used for epileptic treatment; however, the exact mechanism is still unclear. We reported here in that appropriate concentration of PIP effectively inhibites the synchronized oscillation of intracellular calcium in rat hippocampal neuronal networks and represses spontaneous synaptic activities in terms of spontaneous synaptic currents (SSC) and spontaneous excitatory postsynaptic currents (sEPSC). Moreover, pretreatment with PIP expects protective effect on glutamate-induced decrease of cell viability and apoptosis of hippocampal neurons. These data suggest that the neuroprotective effects of PIP might be associated with suppression of synchronization of neuronal networks, presynaptic glutamic acid release, and Ca(2+) overloading.

Astrocytic Dysfunction in Epileptogenesis: Consequence of Altered Potassium and Glutamate Homeostasis?

Focal epilepsy often develops following traumatic, ischemic, or infectious brain injury. While the electrical activity of the epileptic brain is well characterized, the mechanisms underlying epileptogenesis are poorly understood. We have recently shown that in the rat neocortex, long-lasting breakdown of the blood-brain barrier (BBB) or direct exposure of the neocortex to serum-derived albumin leads to rapid upregulation of the astrocytic marker GFAP (glial fibrillary acidic protein), followed by delayed (within 4-7 d) development of an epileptic focus. We investigated the role of astrocytes in epileptogenesis in the BBB-breakdown and albumin models of epileptogenesis. We found similar, robust changes in astrocytic gene expression in the neocortex within hours following treatment with deoxycholic acid (BBB breakdown) or albumin. These changes predict reduced clearance capacity for both extracellular glutamate and potassium. Electrophysiological recordings in vitro confirmed the reduced clearance of activity-dependent accumulation of both potassium and glutamate 24 h following exposure to albumin. We used a NEURON model to simulate the consequences of reduced astrocytic uptake of potassium and glutamate on EPSPs. The model predicted that the accumulation of glutamate is associated with frequency-dependent (>100 Hz) decreased facilitation of EPSPs, while potassium accumulation leads to frequency-dependent (10-50 Hz) and NMDA-dependent synaptic facilitation. In vitro electrophysiological recordings during epileptogenesis confirmed frequency-dependent synaptic facilitation leading to seizure-like activity. Our data indicate a transcription-mediated astrocytic transformation early during epileptogenesis. We suggest that the resulting reduction in the clearance of extracellular potassium underlies frequency-dependent neuronal hyperexcitability and network synchronization.

The comodulation measure of neuronal oscillations with general harmonic wavelet bicoherence and application to sleep analysis

Brain functions are related to neuronal networks of different sizes and distribution, and neuronal networks of different sizes oscillate at different frequencies. Thus the synchronization of neuronal networks is often reflected by cross-frequency interaction. The description of this cross-frequency interaction is therefore a crucial issue in understanding the modulation mechanisms between neuronal populations. A number of different kinds of interaction between frequencies have been reported. In this paper, we develop a general harmonic wavelet transform based bicoherence using a phase randomization method. This allows us to measure the comodulation of oscillations between different frequency bands in neuronal populations. The performance of the method is evaluated by a simulation study. The results show that the improved wavelet bicoherence method can detect a reliable phase coupling value, and also identify zero bicoherence for waves that are not phase-coupled. Spurious bicoherences can be effectively eliminated through the phase randomization method. Finally, this method is applied to electrocorticogram data recorded from rats during transitions between slow-wave sleep, rapid-eye movement sleep and waking. The phase coupling in rapid-eye movement sleep is statistically lower than that during slow-wave sleep, and slightly less than those in the wakeful state. The degree of phase coupling in rapid-eye movement sleep after slow-wave sleep is greater than in rapid-eye movement sleep prior to waking. This method could be applied to investigate the cross-frequency interactions in other physiological signals.

Structural connectivity and nonperiodic synchronization in large-scale networks of spiking neurons.

Structural connectivity and nonperiodic synchronization in large-scale networks of spiking neurons.

Nonlinear dynamical analysis of carbachol induced hippocampal oscillations in mice

Hippocampal neuronal network and synaptic impairment underlie learning and memory deficit in Alzheimer's disease (AD) patients and animal models. In this paper, we analyzed the dynamics and complexity of hippocampal neuronal network synchronization induced by acute exposure to carbachol, a nicotinic and muscarinic receptor co-agonist, using the nonlinear dynamical model based on the Lempel-Ziv estimator. We compared the dynamics of hippocampal oscillations between wild-type (WT) and triple-transgenic (3xTg) mice, as an AD animal model. We also compared these dynamic alterations between different age groups (5 and 10 months). We hypothesize that there is an impairment of complexity of CCh-induced hippocampal oscillations in 3xTg AD mice compared to WT mice, and that this impairment is age-dependent. To test this hypothesis, we used electrophysiological recordings (field potential) in hippocampal slices. Acute exposure to 100 micromol/L CCh induced field potential oscillations in hippocampal CA1 region, which exhibited three distinct patterns: (1) continuous neural firing, (2) repeated burst neural firing and (3) the mixed (continuous and burst) pattern in both WT and 3xTg AD mice. Based on Lempel-Ziv estimator, pattern (2) was significantly lower than patterns (1) and (3) in 3xTg AD mice compared to WT mice (P<0.001), and also in 10-month old WT mice compared to those in 5-month old WT mice (P<0.01). These results suggest that the burst pattern (theta oscillation) of hippocampal network is selectively impaired in 3xTg AD mouse model, which may reflect a learning and memory deficit in the AD patients.

Complete and phase synchronization in a heterogeneous small-world neuronal network

Synchronous firing of neurons is thought to be important for information communication in neuronal networks. This paper investigates the complete and phase synchronization in a heterogeneous small-world chaotic Hindmarsh–Rose neuronal network. The effects of various network parameters on synchronization behaviour are discussed with some biological explanations. Complete synchronization of small-world neuronal networks is studied theoretically by the master stability function method. It is shown that the coupling strength necessary for complete or phase synchronization decreases with the neuron number, the node degree and the connection density are increased. The effect of heterogeneity of neuronal networks is also considered and it is found that the network heterogeneity has an adverse effect on synchrony.

Cannabinoid receptor activation reverses kainate-induced synchronized population burst firing in rat hippocampus

Cannabinoids have been shown to possess anticonvulsant properties in whole animal models of epilepsy. The present investigation sought to examine the effects of cannabinoid receptor activation on kainic acid (KA)-induced epileptiform neuronal excitability. Under urethane anesthesia, acute KA treatment (10 mg kg−1, i.p.) entrained the spiking mode of simultaneously recorded neurons from random firing to synchronous bursting (% change in burst rate). Injection of the high-affinity cannabinoid agonist (-)-11-hydroxy-8-tetrahydrocannabinol-dimethyl-heptyl (HU210, 100 μg kg−1, i.p.) following KA markedly reduced the burst frequency (% decrease in burst frequency) and reversed synchronized firing patterns back to baseline levels. Pre-treatment with the central cannabinoid receptor (CB1) antagonist N-piperidino-5-(4-clorophenyl)-1-(2,4-dichlorophenyl)-4-methyl-3-pyrazole-carboxamide (rimonabant, SR141716A 3 mg kg−1, i.p.) completely prevented the actions of HU210. The present results indicate that cannabinoids exert their antiepileptic effects by impeding pathological synchronization of neuronal networks in the hippocampus.

Chaotic burst synchronization in heterogeneous small-world neuronal network with noise

Chaotic bursting is a fundamental behavior of neurons. In this paper, global and local burst synchronization is studied in a heterogeneous small-world neuronal network of non-identical Hindmarsh–Rose (HR) neurons with noise. It is found that the network can achieve global burst synchronization much more easily than phase synchronization and nearly complete synchronization. Moreover, local burst synchronized clusters have already formed before global burst synchronization happens. We study the effect of the shortcut-adding probability and the heterogeneity coefficient on local and global burst synchronization of the network and find that the introduction of shortcuts facilitates burst synchronization while the heterogeneity has little effect. Moreover, we study the spatiotemporal pattern of the network and find that there is an optimal coupling strength range in which the periodicity of the network is very apparent.

Influence of synaptic interaction on firing synchronization and spike death in excitatory neuronal networks

We investigate the influence of efficacy of synaptic interaction on firing synchronization in excitatory neuronal networks. We find spike death phenomena: namely, the state of neurons transits from the limit cycle to a fixed point or transient state. The phenomena occur under the perturbation of an excitatory synaptic interaction, which has a high efficacy. We show that the decrease of synaptic current results in spike death through depressing the feedback of the sodium ionic current. In the networks with the spike death property the degree of synchronization is lower and insensitive to the heterogeneity of neurons. The mechanism of the influence is that the transition of the neuron state disrupts the adjustment of the rhythm of the neurons oscillation and prevents a further increase of the firing synchronization.