Synchronization In Neuronal Networks Research Articles

WONOEP appraisal: optogenetic tools to suppress seizures and explore the mechanisms of epileptogenesis.

Optogenetics is a novel technology that combines optics and genetics by optical control of microbial opsins, targeted to living cell membranes. The versatility and the electrophysiologic characteristics of the light-sensitive ion-channels channelrhodopsin-2 (ChR2), halorhodopsin (NpHR), and the light-sensitive proton pump archaerhodopsin-3 (Arch) make these optogenetic tools potent candidates in controlling neuronal firing in models of epilepsy and in providing insights into the physiology and pathology of neuronal network organization and synchronization. Opsins allow selective activation of excitatory neurons and inhibitory interneurons, or subclasses of interneurons, to study their activity patterns in distinct brain-states in vivo and to dissect their role in generation of synchrony and seizures. The influence of gliotransmission on epileptic network function is another topic of great interest that can be further explored by using light-activated Gq protein-coupled opsins for selective activation of astrocytes. The ever-growing optogenetic toolbox can also be combined with emerging techniques that have greatly expanded our ability to record specific subtypes of cortical and hippocampal neurons in awake behaving animals such as juxtacellular recording and two-photon guided whole-cell recording, to identify the specific subtypes of neurons that are altered in epileptic networks. Finally, optogenetic tools allow rapid and reversible suppression of epileptic electroencephalography (EEG) activity upon photoactivation. This review outlines the most recent advances achieved with optogenetic techniques in the field of epilepsy by summarizing the presentations contributed to the 13th ILAE WONOEP meeting held in the Laurentian Mountains, Quebec, in June 2013.

Local and global synchronization transitions induced by time delays in small-world neuronal networks with chemical synapses.

Effects of time delay on the local and global synchronization in small-world neuronal networks with chemical synapses are investigated in this paper. Numerical results show that, for both excitatory and inhibitory coupling types, the information transmission delay can always induce synchronization transitions of spiking neurons in small-world networks. In particular, regions of in-phase and out-of-phase synchronization of connected neurons emerge intermittently as the synaptic delay increases. For excitatory coupling, all transitions to spiking synchronization occur approximately at integer multiples of the firing period of individual neurons; while for inhibitory coupling, these transitions appear at the odd multiples of the half of the firing period of neurons. More importantly, the local synchronization transition is more profound than the global synchronization transition, depending on the type of coupling synapse. For excitatory synapses, the local in-phase synchronization observed for some values of the delay also occur at a global scale; while for inhibitory ones, this synchronization, observed at the local scale, disappears at a global scale. Furthermore, the small-world structure can also affect the phase synchronization of neuronal networks. It is demonstrated that increasing the rewiring probability can always improve the global synchronization of neuronal activity, but has little effect on the local synchronization of neighboring neurons.

Activity-dependent changes in excitability of perirhinal cortex networks in vitro.

Rat brain slices comprising the perirhinal cortex (PC) and a portion of the lateral nucleus of the amygdala (LA), in standard medium, can generate synchronous oscillatory activity that is associated with action potential discharge and reflects the activation of glutamatergic and GABAergic receptors. We report here that similar synchronous oscillatory events are recorded in the PC in response to single-shock, electrical stimuli delivered in LA. In addition, we found that the latency of these responses progressively increased when the stimulus interval was varied from 10 to 1 s; for example, the response latency during stimuli delivered at 1 Hz was more than twofold longer than that seen during stimulation at 0.1 Hz. This prolongation in latency occurred after approximately 5 stimuli, attained a steady value after 24-35 stimuli, and recovered to control values 30 s after stimulation arrest. These frequency-dependent changes in latency continued to occur during NMDA receptor antagonism but weakened following application of GABAA and/or GABAB receptor blockers. Our findings identify a new type of short-term plasticity that is mediated by GABA receptor function and may play a role in decreasing neuronal network synchronization during repeated activation. We propose that this frequency-dependent adaptive mechanism influences the excitability of limbic networks, thus potentially controlling epileptiform synchronization.

Time delay and long-range connection induced synchronization transitions in Newman-Watts small-world neuronal networks.

The synchronization transitions in Newman-Watts small-world neuronal networks (SWNNs) induced by time delay and long-range connection (LRC) probability have been investigated by synchronization parameter and space-time plots. Four distinct parameter regions, that is, asynchronous region, transition region, synchronous region, and oscillatory region have been discovered at certain LRC probability as time delay is increased. Interestingly, desynchronization is observed in oscillatory region. More importantly, we consider the spatiotemporal patterns obtained in delayed Newman-Watts SWNNs are the competition results between long-range drivings (LRDs) and neighboring interactions. In addition, for moderate time delay, the synchronization of neuronal network can be enhanced remarkably by increasing LRC probability. Furthermore, lag synchronization has been found between weak synchronization and complete synchronization as LRC probability is a little less than 1.0. Finally, the two necessary conditions, moderate time delay and large numbers of LRCs, are exposed explicitly for synchronization in delayed Newman-Watts SWNNs.

Inhibitory Feedback Loop Induces Anticipated Synchronization in Neuronal Networks

Inhibitory Feedback Loop Induces Anticipated Synchronization in Neuronal Networks

Delay-induced synchronization transitions in modular scale-free neuronal networks with hybrid electrical and chemical synapses

We study the dependence of synchronization transitions in modular networks of bursting neurons with hybrid electrical–chemical synapses on the information transmission delay and the probability of electrical synapses. The modular network is composed of subnetworks (clusters); each of them presents the scale-free property. It is shown that, irrespective of the probability of electrical synapses, the time delay can always induce synchronization transitions in modular neuronal networks. Regions of synchronization and non-synchronization appear intermittently as the delay increases. In particular, all these transitions to burst synchronization occur approximately at integer multiples of oscillatory period of individual neurons. In addition, for larger probability of electrical synapses, the intermittent synchronization transition is more profound, due to the stronger synchronization capability of electrical synapses compared with chemical ones. Furthermore, the transition to synchronous bursting can also be induced by the variation of modular network parameters, that is, the coupling strength between neurons, the interconnection probability between different subnetworks, as well as the number of subnetworks. Particularly, we find that a modular neuronal network is harder to get global synchronization when constituting neurons are dispersed over more clusters. On the other hand, chemical and electrical synapses can perform complementary roles in the synchronization of hybrid modular neuronal networks: the larger the electrical synapse strength is the smaller the chemical synapse strength needed to achieve burst synchronization.

Pinning synchronization of unilateral coupling neuron network with stochastic noise

In this paper, pinning synchronization of unilateral coupling time delay neuron network with stochastic noise is investigated. Based on Lyapunov stability theory, by designing appropriate controller and particular Lyapunov function, pinning synchronization of unilateral coupling Hindmarsh–Rose network with stochastic noise is obtained. This method needs only one single controller. Simulation results are given to verify the effectiveness of the proposed scheme. From the simulations, the relation between the time needed to achieve pinning synchronization of unilateral coupling neuron network with stochastic noise and the number of nodes, the noise intensity, the coupling intensity is illustrated.

Mechanisms of Epileptiform Synchronization in Cortical Neuronal Networks

Neuronal synchronization supports different physiological states such as cognitive functions and sleep, and it is mirrored by identifiable EEG patterns ranging from gamma to delta oscillations. However, excessive neuronal synchronization is often the hallmark of epileptic activity in both generalized and partial epileptic disorders. Here, I will review the synchronizing mechanisms involved in generating epileptiform activity in the limbic system, which is closely involved in the pathophysiogenesis of temporal lobe epilepsy (TLE). TLE is often associated to a typical pattern of brain damage known as mesial temporal sclerosis, and it is one of the most refractory adult form of partial epilepsy. This epileptic disorder can be reproduced in animals by topical or systemic injection of pilocarpine or kainic acid, or by repetitive electrical stimulation; these procedures induce an initial status epilepticus and cause 1-4 weeks later a chronic condition of recurrent limbic seizures. Remarkably, a similar, seizure-free, latent period can be identified in TLE patients who suffered an initial insult in childhood and develop partial seizures in adolescence or early adulthood. Specifically, I will focus here on the neuronal mechanisms underlying three abnormal types of neuronal synchronization seen in both TLE patients and animal models mimicking this disorder: (i) interictal spikes; (ii) high frequency oscillations (80-500 Hz); and (iii) ictal (i.e., seizure) discharges. In addition, I will discuss the relationship between interictal spikes and ictal activity as well as recent evidence suggesting that specific seizure onsets in the pilocarpine model of TLE are characterized by distinctive patterns of spiking (also termed preictal) and high frequency oscillations.

Cluster synchronization in networks of neurons with chemical synapses

In this work, we study the cluster synchronization of chemically coupled and generally formulated networks which are allowed to be nonidentical. The sufficient condition for the existence of stably synchronous clusters is derived. Specifically, we only need to check the stability of the origins of m decoupled linear systems. Here, m is the number of subpopulations. Examples of nonidentical networks such as Hindmarsh-Rose (HR) neurons with various choices of parameters in different subpopulations, or HR neurons in one subpopulation and FitzHugh-Nagumo neurons in the other subpopulation are provided. Explicit threshold for the coupling strength that guarantees the stably cluster synchronization can be obtained.

Noise and Synchronization Analysis of the Cold-Receptor Neuronal Network Model

This paper analyzes the dynamics of the cold receptor neural network model. First, it examines noise effects on neuronal stimulus in the model. FromISIplots, it is shown that there are considerable differences between purely deterministic simulations and noisy ones. TheISI-distance is used to measure the noise effects on spike trains quantitatively. It is found that spike trains observed in neural models can be more strongly affected by noise for different temperatures in some aspects; meanwhile, spike train has greater variability with the noise intensity increasing. The synchronization of neuronal network with different connectivity patterns is also studied. It is shown that chaotic and high period patterns are more difficult to get complete synchronization than the situation in single spike and low period patterns. The neuronal network will exhibit various patterns of firing synchronization by varying some key parameters such as the coupling strength. Different types of firing synchronization are diagnosed by a correlation coefficient and theISI-distance method. The simulations show that the synchronization status of neurons is related to the network connectivity patterns.

Dynamics, control and information in delay-coupled systems: an overview

Dynamics, control and information in delay-coupled systems: an overview

Aging of the Suprachiasmatic Clock

More than half of the elderly in today’s society suffer from sleep disorders with detrimental effects on brain function, behavior, and social life. A major contribution to the regulation of sleep stems from the circadian system. The central circadian clock located in the suprachiasmatic nucleus of the hypothalamus is like other brain regions subject to age-associated changes. Age affects different levels of the clock machinery from molecular rhythms, intracellular messenger, and membrane properties to neuronal network synchronization. While some of the age-sensitive components of the circadian clock, like ion channels and neurotransmitters, have been described, little is known about the underlying mechanisms. In any case, the result is a reduction in the amplitude of the circadian timing signal produced by the suprachiasmatic nucleus, a weakening in the control of peripheral oscillators and a decrease in amplitude and precision of daily rhythms in physiology and behavior. The distortion in temporal organization is thought to be related to a number of serious health problems and promote neurodegeneration. Understanding the mechanisms underlying age-related deficits in circadian clock function will therefore not only benefit rhythm disorders but also alleviate age-associated diseases aggravated by clock dysfunction.

Delay-induced synchronization transitions in small-world neuronal networks with hybrid electrical and chemical synapses

We study the dependence of synchronization transitions in small-world networks of bursting neurons with hybrid electrical–chemical synapses on the information transmission delay, the probability of electrical synapses, and the rewiring probability. It is shown that, irrespective of the probability of electrical synapses, the information transmission delay can always induce synchronization transitions in small-world neuronal networks, i.e., regions of synchronization and nonsynchronization appear intermittently as the delay increases. In particular, all these transitions to burst synchronization occur approximately at integer multiples of the bursting period of individual neurons. In addition, for larger probability of electrical synapses, the intermittent synchronization transition is more profound, due to the stronger synchronization ability of electrical synapses compared with chemical ones. More importantly, chemical and electrical synapses can perform complementary roles in the synchronization of hybrid small-world neuronal networks: the larger the electrical synapse strength is, the smaller the chemical synapse strength needed to achieve burst synchronization. Furthermore, the small-world topology has a significant effect on the synchronization transition in hybrid neuronal networks. It is found that increasing the rewiring probability can always enhance the synchronization of neuronal activity. The results obtained are instructive for understanding the synchronous behavior of neural systems.

Adaptive coupling-enhanced spiking synchronization in Newman-Watts neuronal networks with time delays

In this paper, we study how adaptive coupling with time-periodic growth speed (TPGS) affects the spiking synchronization of weighted adaptive Newman-Watts Hodgkin-Huxley neuron networks with time delays. It is found that the neuronal spiking intermittently exhibits synchronization transitions between desynchronization and in-phase synchronization or anti-phase synchronization as TPGS amplitude or frequency is varied, showing multiple synchronization transitions. These transitions depend on the values of time delay and can occur only when time delay is close to those values that can induce synchronization transitions when the growth speed is fixed. These results show that the adaptive coupling with TPGS has great influence on the spiking synchronization of the neuronal networks and thus plays a crucial role in the information processing and transmission in neural systems.

Bursting synchronization in clustered neuronal networks

Neuronal networks in the brain exhibit the modular (clustered) property, i.e., they are composed of certain subnetworks with differential internal and external connectivity. We investigate bursting synchronization in a clustered neuronal network. A transition to mutual-phase synchronization takes place on the bursting time scale of coupled neurons, while on the spiking time scale, they behave asynchronously. This synchronization transition can be induced by the variations of inter- and intracoupling strengths, as well as the probability of random links between different subnetworks. Considering that some pathological conditions are related with the synchronization of bursting neurons in the brain, we analyze the control of bursting synchronization by using a time-periodic external signal in the clustered neuronal network. Simulation results show a frequency locking tongue in the driving parameter plane, where bursting synchronization is maintained, even in the presence of external driving. Hence, effective synchronization suppression can be realized with the driving parameters outside the frequency locking region.

Delayed feedback control of bursting synchronization in small-world neuronal networks

Neuronal networks in some areas of the brain cortex present the small-world property. We investigate the delayed feedback control of bursting synchronization in small-world neuronal networks. Without control, a transition to mutual synchronization takes place on the bursting time scale of coupled neurons, while on the spiking time scale, they behave asynchronously. It is shown that the synchronization of small-world neuronal networks is greatly enhanced by a large fraction of shortcuts, but saturates when it exceeds a critical value. We investigate the suppression of such synchronized activity of the neuron population using a linear delayed feedback control. Domains of effective synchronization suppression are depicted in terms of feedback strength and time delay. We get that the overall efficiency of synchronization suppression of a small-world network is much higher than for global coupling and scale-free populations with the same initial synchronization strength. Considering that some pathological conditions are related with the synchronization of bursting neurons in the brain, the presented results could have important implications for the application of time-delayed feedback in the deep brain stimulation.

IN-PHASE BURST SYNCHRONIZATION AND RHYTHM DYNAMICS OF COMPLEX NEURONAL NETWORKS

In-phase burst synchronization, spatiotemporal order and rhythm dynamics of a complex neuronal network with electrical or chemically excitatory synapses are studied in this paper. A quantitative characteristic, the width factor, is introduced to describe the rhythm dynamics of an individual neuron, and the average width factor is used to characterize the rhythm dynamics of a neural network. The in-phase burst synchronization is studied in terms of the burst phase order parameter. We also study the effects of the coupling schemes, the intrinsic neuronal property and the network topology on the rhythm dynamics of the network. It is found that the neuronal network with electrical coupling is easier to realize the in-phase burst synchronization than that with the chemically excitatory coupling. The bursting type of short bursting neuronal networks is unchanged for different coupling schemes with the coupling strength increasing. Moreover, the short bursting type is robust both to the coupling strength and the coupling scheme. As for the network topology, more links can only change the bursting type of long bursting neurons, but short bursting neurons are robust to the link numbers.

Ontogenetic changes in the distribution of the vesicular GABA transporter VGAT correlate with the excitation/inhibition shift of GABA action

GABA is the major inhibitory neurotransmitter in the adult CNS and is among others involved in the synchronization of large neuronal networks. During development, GABA acts as a morphogenetic factor and has transient excitatory actions in many brain regions. One distinct protein, the vesicular GABA transporter (VGAT), has been identified accumulating GABA into presynaptic vesicles prior to its exocytotic release. The function of VGAT and its distribution is well defined in the adult, but its contribution to the transient excitatory action at putative GABAergic nerve terminals in the immature brain and its potential roles in putative glutamatergic nerve terminals remain elusive. We have studied VGAT expression in the brain from late embryonic stages through several postnatal stages until adulthood. Quantitative immunoblotting and immunolabeling of tissue sections at the light microscope and the electron microscope levels show an abrupt augmentation in VGAT staining in the cerebral cortex during the first three postnatal weeks, resembling the increase in other proteins involved in GABA synthesis and recycling in the same time frame – such as GAD65, GAD67, GAT1 (Slc6a1) and SN1 (Slc38a3) – and coincides with the synaptogenetic spurt. Dynamic changes in the expression of VGAT are seen in many cellular populations and in several layers in different brain regions. However, mossy fiber terminals (MFT) elude staining for VGAT. We also demonstrate that VGAT+ nerve terminals undergo a developmental reorganization so that from targeting primarily the dendrites of the principal neurons in several brain regions in the immature brain, they target the soma of the same cells in the adult. This shift in the targeted subcellular compartment coincides with the conversion of the chloride gradient across neuronal membranes and suggests that it may be important for the shift of GABA action from excitation to inhibition and for the establishment of the potent synchronization of neuronal networks.

Memantine potentiates hippocampal theta oscillations at a therapeutic dose in anesthetized mice: A mechanistic link to its cognitive-enhancing properties

Memantine is an uncompetitive, low-affinity NMDA receptor antagonist clinically used for the treatment of cognitive deficits in moderate to severe Alzheimer’s disease. Both neurophysiological and behavioral studies in rodents have suggested a beneficial effect of memantine on synaptic plasticity and learning performances. In the present study, we investigated the effect of memantine on pedonculopontine-elicited theta oscillations in the hippocampus of urethane anesthetized mice, a model shown to be sensitive to several pharmacological agents exhibiting cognitive-enhancing properties. We found that a low dose of memantine potentiated elicited theta power while a high dose was disruptive. The low dose of memantine used was shown to yield an unbound brain concentration well within the range of therapeutic concentrations reported in rodent brain extracellular fluid and human cerebrospinal fluid. For further comparison, the effect of another uncompetitive NMDA receptor antagonist with higher affinity, i.e. MK-801, was also investigated. MK-801 was at a low dose devoid of effect on elicited theta power, while a high dose, within the range of doses reported to induce cognitive deficits in a variety of hippocampal-dependent learning paradigms in mice, was found disruptive on elicited theta waves. Taken together, our results suggest that clinically relevant doses of memantine promote neuronal network synchronization in the hippocampus, which may represent an underlying mechanism for the reported cognitive-enhancing properties in both preclinical and clinical studies.

Effects of information transmission delay and channel blocking on synchronization in scale-free Hodgkin-Huxley neuronal networks

In this paper, we investigate the evolution of spatiotemporal patterns and synchronization transitions in dependence on the information transmission delay and ion channel blocking in scale-free neuronal networks. As the underlying model of neuronal dynamics, we use the Hodgkin-Huxley equations incorporating channel blocking and intrinsic noise. It is shown that delays play a significant yet subtle role in shaping the dynamics of neuronal networks. In particular, regions of irregular and regular propagating excitatory fronts related to the synchronization transitions appear intermittently as the delay increases. Moreover, the fraction of working sodium and potassium ion channels can also have a significant impact on the spatiotemporal dynamics of neuronal networks. As the fraction of blocked sodium channels increases, the frequency of excitatory events decreases, which in turn manifests as an increase in the neuronal synchrony that, however, is dysfunctional due to the virtual absence of large-amplitude excitations. Expectedly, we also show that larger coupling strengths improve synchronization irrespective of the information transmission delay and channel blocking. The presented results are also robust against the variation of the network size, thus providing insights that could facilitate understanding of the joint impact of ion channel blocking and information transmission delay on the spatiotemporal dynamics of neuronal networks.