Spike Burst Activity Research Articles

Focal seizures induce spatiotemporally organized spiking activity in the human cortex

Epileptic seizures are debilitating because of the clinical symptoms they produce. These symptoms, in turn, may stem directly from disruptions in neural coding. Recent evidence has suggested that the specific temporal order, or sequence, of spiking across a population of cortical neurons may encode information. Here, we investigate how seizures disrupt neuronal spiking sequences in the human brain by recording multi-unit activity from the cerebral cortex in five male participants undergoing monitoring for seizures. We find that pathological discharges during seizures are associated with bursts of spiking activity across a population of cortical neurons. These bursts are organized into highly consistent and stereotyped temporal sequences. As the seizure evolves, spiking sequences diverge from the sequences observed at baseline and become more spatially organized. The direction of this spatial organization matches the direction of the ictal discharges, which spread over the cortex as traveling waves. Our data therefore suggest that seizures can entrain cortical spiking sequences by changing the spatial organization of neuronal firing, providing a possible mechanism by which seizures create symptoms.

Relationship Between Intestinal Slow-waves, Spike-bursts, and Motility, as Defined Through High-resolution Electrical and Video Mapping

Background/AimsHigh-resolution extracellular mapping has improved our understanding of bioelectric slow-wave and spike-burst activity in the small intestine. The spatiotemporal correlation of electrophysiology and motility patterns is of critical interest to intestinal function but remains incompletely defined.MethodsIntestinal jejunum segments from in vivo pigs and rabbits were exteriorized, and simultaneous high-resolution extracellular recordings and video recordings were performed. Contractions were quantified with strain fields, and the frequencies and velocities of motility patterns were calculated. The amplitudes, frequencies, and velocities of slow-wave propagation patterns and spike-bursts were quantified and visualized. In addition, the duration, size and energy of spike-burst patches were quantified.ResultsSlow-wave associated spike-bursts activated periodically at 10.8 ± 4.0 cycles per minute (cpm) in pigs and 10.2 ± 3.2 cpm in rabbits, while independent spike-bursts activated at a frequency of 3.2 ± 1.8 cpm. Independent spike-bursts had higher amplitude and longer duration than slow-wave associated spike-bursts (1.4 ± 0.8 mV vs 0.1 ± 0.1 mV, P < 0.001; 1.8 ± 1.4 seconds vs 0.8 ± 0.3 seconds, P < 0.001 in pigs). Spike-bursts that activated as longitudinal or circumferential patches were associated with contractions in the respective directions. Spontaneous peristaltic contractions were elicited by independent spike-bursts and travelled slower than slow-wave velocity (3.7 ± 0.5 mm/sec vs 10.1 ± 4.7 mm/sec, P = 0.007). Cyclic peristaltic contractions were driven by slow-wave associated spike-bursts and were coupled to slow-wave velocity and frequency in rabbit (14.2 ± 2.3 mm/sec vs 11.5 ± 4.6 mm/sec, P = 0.162; 11.0 ± 0.6 cpm vs 10.8 ± 0.6 cpm, P = 0.970).ConclusionsMotility patterns were dictated by patterns of spike-burst patches. When spike-bursts were coupled to slow-waves, periodic motility patterns were observed, while when spike-bursts were not coupled to slow-waves, spontaneous aperiodic motility patterns were captured.

Distribution of spiking and bursting in Rulkov’s neuron model

Large-scale brain simulations require the investigation of large networks of realistic neuron models, usually represented by sets of differential equations. Here we report a detailed fine-scale study of the dynamical response over extended parameter ranges of a computationally inexpensive model, the two-dimensional Rulkov map, which reproduces well the spiking and spiking-bursting activity of real biological neurons. In addition, we provide evidence of the existence of nested arithmetic progressions among periodic pulsing and bursting phases of Rulkov’s neuron. We find that specific remarkably complex nested sequences of periodic neural oscillations can be expressed as simple linear combinations of pairs of certain basal periodicities. Moreover, such nested progressions are robust and can be observed abundantly in diverse control parameter planes which are described in detail. We believe such findings to add significantly to the knowledge of Rulkov neuron dynamics and to be potentially helpful in large-scale simulations of the brain and other complex neuron networks.

Synaptic changes modulate spontaneous transitions between tonic and bursting neural activities in coupled Hindmarsh-Rose neurons.

Experimentally, certain cells in the brain exhibit a spike-burst activity with burst synchronization at transition to and during sleep (or drowsiness), while they demonstrate a desynchronized tonic activity in the waking state. We herein investigated the neural activities and their transitions by using a model of coupled Hindmarsh-Rose neurons in an Erdős-Rényi random network. By tuning synaptic strength, spontaneous transitions between tonic and bursting neural activities can be realized. With excitatory chemical synapses or electrical synapses, slow-wave activity (SWA) similar to that observed during sleep can appear, as a result of synchronized bursting activities. SWA cannot appear in a network that is dominated by inhibitory chemical synapses, because neurons exhibit desynchronized bursting activities. Moreover, we found that the critical synaptic strength related to the transitions of neural activities depends only on the network average degree (i.e., the average number of signals that all the neurons receive). We demonstrated, both numerically and analytically, that the critical synaptic strength and the network average degree obey a power-law relation with an exponent of -1. Our study provides a possible dynamical network mechanism of the transitions between tonic and bursting neural activities for the wakefulness-sleep cycle, and of the SWA during sleep. Further interesting and challenging investigations are briefly discussed as well.

Real-Time Monitoring of Levetiracetam Effect on the Electrophysiology of an Heterogenous Human iPSC-Derived Neuronal Cell Culture Using Microelectrode Array Technology.

Levetiracetam (LEV) is a broad-spectrum and widely used antiepileptic drug that also has neuroprotective effects in different neurological conditions. Given its complex interaction with neuronal physiology, a better comprehension of LEV effects on neurons activity is needed. Microelectrode arrays (MEAs) represent an advanced technology for the non-invasive study of electrophysiological activity of neuronal cell cultures. In this study, we exploited the Maestro Edge MEA system, a platform that allows a deep analysis of the electrical network behavior, to study the electrophysiological effect of LEV on a mixed population of human neurons (glutamatergic, GABAergic and dopaminergic neurons, and astrocytes). We found that LEV significantly affected different variables such as spiking, single-electrode bursting, and network bursting activity, with a pronounced effect after 15 min. Moreover, neuronal cell culture completely rescued its baseline activity after 24 h without LEV. In summary, MEA technology confirmed its high sensitivity in detecting drug-induced electrophysiological modifications. Moreover, our results allow one to extend the knowledge on the electrophysiological effects of LEV on the complex neuronal population that resembles the human cortex.

In vitro ictogenesis is stochastic at the single neuron level.

Seizure initiation is the least understood and most disabling element of epilepsy. Studies of ictogenesis require high speed recordings at cellular resolution in the area of seizure onset. However, in vivo seizure onset areas cannot be determined at the level of resolution necessary to enable such studies. To circumvent these challenges, we used novel GCaMP7-based calcium imaging in the organotypic hippocampal slice culture model of post-traumatic epilepsy in mice. Organotypic hippocampal slice cultures generate spontaneous, recurrent seizures in a preparation in which it is feasible to image the activity of the entire network (with no unseen inputs existing). Chronic calcium imaging of the entire hippocampal network, with paired electrophysiology, revealed three patterns of seizure onset: (i) low amplitude fast activity; (ii) sentinel spike; and (iii) spike burst and low amplitude fast activity onset. These patterns recapitulate common features of human seizure onset, including low voltage fast activity and spike discharges. Weeks-long imaging of seizure activity showed a characteristic evolution in onset type and a refinement of the seizure onset zone. Longitudinal tracking of individual neurons revealed that seizure onset is stochastic at the single neuron level, suggesting that seizure initiation activates neurons in non-stereotyped sequences seizure to seizure. This study demonstrates for the first time that transitions to seizure are not initiated by a small number of neuronal 'bad actors' (such as overly connected hub cells), but rather by network changes which enable the onset of pathology among large populations of neurons.

Synaptic modifications driven by spike-timing-dependent plasticity in weakly coupled bursting neurons.

In the course of development, sleep, or mental disorders, certain neurons in the brain display spontaneous spike-burst activity. The synaptic plasticity evoked by such activity is here studied in the presence of spike-timing-dependent plasticity (STDP). In two chemically coupled bursting model neurons, the spike-burst activity can translate the STDP related to pre- and postsynaptic spike activity into burst-timing-dependent plasticity (BTDP), based on the timing of bursts of pre- and postsynaptic neurons. The resulting BTDP exhibits exponential decays with the same time scales as those of STDP. In weakly coupled bursting neuron networks, the synaptic modification driven by the spike-burst activity obeys a power-law distribution. The model can also produce a power-law distribution of synaptic weights. Here, the considered bursting behavior is made of stereotypical groups of spikes, and bursting is evenly spaced by long intervals.

Synaptic Potential and Plasticity of an SK2 Channel Gate Regulate Spike Burst Activity in Cerebellar Purkinje Cells

SummaryNeurons store information and participate in memory engrams as a result of experience-dependent changes in synaptic weights and in membrane excitability. Here, we examine excitatory postsynaptic potential (EPSP) amplitude and neuronal excitability in relation to these two mechanisms of plasticity. We analyze somato-dendritic double-patch recordings from cerebellar Purkinje cells while inducing intrinsic, SK2 channel-dependent plasticity or blocking SK channels with bath application of apamin. Both manipulations increase the build-up of EPSP amplitudes during an EPSP train and enhance the number of EPSP-evoked spikes, yielding insights into the mechanistic contribution of EPSP amplitude to single spikes and spike bursts. EPSP amplitude has an impact on whether spikes are fired or not, but direct measures of excitability (spike threshold/AHP) are better predictors of whether individual spikes or spike bursts are fired. Our findings show that Purkinje cell spiking is synaptically driven but that burst firing is gated by SK2 channel modulation and plasticity.

Modulation of Pulvinar Neuronal Activity by Arousal.

In this chapter, we discuss the modulation of pulvinar neuronal activity by arousal. In contrast to electrophysiological recordings in the early visual cortex, neuronal activity in the pulvinar is particularly sensitive to anesthesia. In the absence of sensory stimulation, pulvinar neurons can be characterized by spontaneous low-frequency rhythmic bursts of spiking activity. However, multisensory stimulation capable of arousing the animal from deeper anesthesia levels is able to reestablish the necessary neuronal dynamics and switch the pulvinar into an active state. Under these conditions, cortical slow-wave activity is substituted by a higher-frequency oscillatory pattern associated with arousal. Here, we describe two types of transitions in pulvinar activity pattern that can be observed when arousing the animal with multisensory stimulation.

Spike Burst Coding of Translatory Optic Flow and Depth from Motion in the Fly Visual System

Many animals use the visual motion generated by traveling straight-the translatory optic flow-to successfully navigate obstacles: near objects appear larger and to move more quickly than distant objects. Flies are expert at navigating cluttered environments, and while their visual processing of rotatory optic flow is understood in exquisite detail, how they process translatory optic flow remains a mystery. We present novel cell types that have local motion receptive fields matched to translation self-motion, the vertical translation (VT) cells. One of these, the VT1 cell, encodes self-motion in the forward-sideslip direction and fires action potentials in spike bursts as well as single spikes. We show that the spike burst coding is size and speed-tuned and is selectively modulated by motion parallax-the relative motion experienced during translation. These properties are spatially organized, so that the cell is most excited by clutter rather than isolated objects. When the fly is presented with a simulation of flying past an elevated object, the spike burst activity is modulated by the height of the object, and the rate of single spikes is unaffected. When the moving object alone is experienced, the cell is weakly driven. Meanwhile, the VT2-3 cells have motion receptive fields matched to the lift axis. In conjunction with previously described horizontal cells, the VT cells have properties well suited to the visual navigation of clutter and to encode the fly's movements along near cardinal axes of thrust, lift, and forward sideslip.

Mdm2 mediates FMRP- and Gp1 mGluR-dependent protein translation and neural network activity.

Activating Group 1 (Gp1) metabotropic glutamate receptors (mGluRs), including mGluR1 and mGluR5, elicits translation-dependent neural plasticity mechanisms that are crucial to animal behavior and circuit development. Dysregulated Gp1 mGluR signaling has been observed in numerous neurological and psychiatric disorders. However, the molecular pathways underlying Gp1 mGluR-dependent plasticity mechanisms are complex and have been elusive. In this study, we identified a novel mechanism through which Gp1 mGluR mediates protein translation and neural plasticity. Using a multi-electrode array (MEA) recording system, we showed that activating Gp1 mGluR elevates neural network activity, as demonstrated by increased spontaneous spike frequency and burst activity. Importantly, we validated that elevating neural network activity requires protein translation and is dependent on fragile X mental retardation protein (FMRP), the protein that is deficient in the most common inherited form of mental retardation and autism, fragile X syndrome (FXS). In an effort to determine the mechanism by which FMRP mediates protein translation and neural network activity, we demonstrated that a ubiquitin E3 ligase, murine double minute-2 (Mdm2), is required for Gp1 mGluR-induced translation and neural network activity. Our data showed that Mdm2 acts as a translation suppressor, and FMRP is required for its ubiquitination and down-regulation upon Gp1 mGluR activation. These data revealed a novel mechanism by which Gp1 mGluR and FMRP mediate protein translation and neural network activity, potentially through de-repressing Mdm2. Our results also introduce an alternative way for understanding altered protein translation and brain circuit excitability associated with Gp1 mGluR in neurological diseases such as FXS.

Synchronization of bursting neurons with a slowly varying d. c. current

Bursting of neuronal firing is an interesting dynamical consequences depending on fast/slow dynamics. Certain cells in different brain regions produce spike-burst activity. We study such firing activity and its transitions to synchronization using identical as well as non-identical coupled bursting Morris-Lecar (M-L) neurons. Synchronization of different firing activity is a multi-time-scale phenomenon and burst synchronization presents the precursor to spike synchronization. Chemical synapses are one of the dynamical means of information processing between neurons. Electrical synapses play a major role for synchronous activity in a certain network of neurons. Synaptically coupled neural cells exhibit different types of synchronization such as in phase or anti-phase depending on the nature and strength of coupling functions and the synchronization regimes are analyzed by similarity functions. The sequential transitions to synchronization regime are examined by the maximum transverse Lyapunov exponents. Synchronization of voltage traces of two types of planar bursting mechanisms is explored for both kind of synapses under realistic conditions. The noisy influence effects on the transmission of signals and strongly acts to the firing activity (such as periodic firing and bursting) and integration of signals for a network. It has been examined using the mean interspike interval analysis. The transition to synchronization states of coupled and a network of bursting neurons may be useful for further research in information processing and even the origins of certain neurological disorders.

Asymmetry Factors Shaping Regular and Irregular Bursting Rhythms in Central Pattern Generators.

Central Pattern Generator (CPG) circuits are neural networks that generate rhythmic motor patterns. These circuits are typically built of half-center oscillator subcircuits with reciprocally inhibitory connections. Another common property in many CPGs is the remarkable rich spiking-bursting dynamics of their constituent cells, which balance robustness and flexibility to generate their joint coordinated rhythms. In this paper, we use conductance-based models and realistic connection topologies inspired by the crustacean pyloric CPG to address the study of asymmetry factors shaping CPG bursting rhythms. In particular, we assess the role of asymmetric maximal synaptic conductances, time constants and gap-junction connectivity to establish the regularity of half-center oscillator based CPGs. We map and characterize the synaptic parameter space that lead to regular and irregular bursting activity in these networks. The analysis indicates that asymmetric configurations display robust regular rhythms and that large regions of both regular and irregular but coordinated rhythms exist as a function of the asymmetry in the circuit. Our results show that asymmetry both in the maximal conductances and in the temporal dynamics of mutually inhibitory neurons can synergistically contribute to shape wide regimes of regular spiking-bursting activity in CPGs. Finally, we discuss how a closed-loop protocol driven by a regularity goal can be used to find and characterize regular regimes when there is not time to perform an exhaustive search, as in most experimental studies.

Elevated intracellular Na+ concentrations in developing spinal neurons.

Over 25years ago it was first reported that intracellular chloride levels (Cl-in ) were higher in developing neurons than in maturity. This finding has had significant implications for understanding the excitability of developing networks and recognizing the underlying causes of hyperexcitability associated with disease and neural injury. While there is some evidence that intracellular sodium levels (Na+in ) change during the development of non-neural cells, it has largely been assumed that Na+in is the same in developing and mature neurons. Here, using the sodium indicator SBFI, we test this idea and find that Na+in is significantly higher in embryonic spinal motoneurons and interneurons than in maturity. We find that Na+in reaches ~60mM in mid-embryonic development and is then reduced to ~30mM in late embryonic development. By retrogradely labeling motoneurons with SBFI we can reliably follow Na+in levels invitro for hours. Bursts of spiking activity, and blocking voltage-gated sodium channels did not influence observed motoneuron sodium levels. On the other hand, Na+in was reduced by blocking the Na+ -K+ -2Cl- cotransporter NKCC1, and was highly sensitive to changes in external Na+ and a blocker of the Na+ /K+ ATPase. Our findings suggest that the Na+ gradient is weaker in embryonic neuronal development and strengthens in maturity in a manner similar to that of Cl- .

Quantization of Map-Based Neuronal Model for Embedded Simulations of Neurobiological Networks in Real-Time

The discreet-time (map-based) approach to modeling nonlinear dynamics of spiking and spiking-bursting activity of neurons has demonstrated its very high efficiency in simulations of neuro-biologically realistic behavior both in large-scale network models for brain activity studies and in real-time operation of Central Pattern Generator network models for biomimetic robotics. This paper studies the next step in improving the model computational efficiency that includes quantization of model variables and makes the network models suitable for embedded solutions. We modify a map-based neuron model to enable simulations using only integer arithmetic and demonstrate a significant reduction of computation time in an embedded system using readily available, inexpensive ARM Cortex L4 microprocessors.

Regularization of a half-center oscillator network by closed-loop control

Central Pattern Generators (CPGs) are neural circuits that control muscle functioning by means of rhythmic patterns. These networks are usually built up on a minimal configuration based on reciprocal inhibitory connections responsible for the production of alternating spiking-bursting activity. Experimental observations in the crustacean pyloric CPG show that most neurons, when isolated, present a highly irregular, in fact chaotic, bursting activity [1-3]. This rich intrinsic dynamics provides flexibility for negotiating rhythms through the reciprocal inhibitory connections between neurons which lead to the regularization of the chaotic behavior when the neurons interact within the circuit [4]. Closed-loop interactions are typically used in electrophysiological experiments using dynamic clamp protocols [5] and have been generalized for different description levels of the nervous system [6]. In this work we show that feedback protocols can also be used in theoretical studies to search for specific dynamics or explore the parameter space of a given model. We have built a CPG model based on a minimal network with two neurons connected by bidirectional fast chemical inhibitory synapses. The network generates alternating bursting activity in the neurons, which can be regular or irregular depending on the maximal conductances of the inhibitory synapses. We employ a simple adaptive closed-loop protocol to regularize the alternating chaotic activity of the model (see Figure ​Figure11 panel A). This protocol adapts online the maximal conductance of one of the synapsis to achieve the aimed regular alternating bursting activity (see Figure ​Figure1,1, panel B). Moreover, the closed-loop algorithm can be used to automatically map the region of maximal conductance values that lead to regular activity. Figure 1 Panel A: Activity of the system using the closed-loop algorithm. Panel B: Schematic representation of the closed-loop protocol.

Active Dendrites under Parental Supervision

Pyramidal cell dendrites are able to produce a variety of active calcium signals in brain slices. In this issue of Neuron, Grienberger etal. (2014) investigate dendritic function in the hippocampus of live mice.

Alterations in the Intrinsic Burst Activity of Purkinje Neurons in Offspring Maternally Exposed to the CB1 Cannabinoid Agonist WIN 55212-2

Burst firing plays an important role in normal neuronal function and dysfunction. In Purkinje neurons, where the firing rate and discharge pattern encode the timing signals necessary for motor function, any alteration in firing properties, including burst activity, may affect the motor output. Therefore, we examined whether maternal exposure to the cannabinoid receptor agonist WIN 55212-2 (WIN) may affect the burst firing properties of cerebellar Purkinje cells in offspring. Whole-cell somatic patch-clamp recordings were made from cerebellar slices of adult male rats that were exposed to WIN prenatally. WIN exposure during pregnancy induced long-term alterations in the burst firing behavior of Purkinje neurons in rat offspring as evidenced by a significant increase in the mean number of spikes per burst (p<0.05) and the prolongation of burst firing activity (p<0.01). The postburst afterhyperpolarization potential (p<0.001), the mean intraburst interspike intervals (p<0.001) and the mean intraburst firing frequency (p<0.001) were also significantly increased in the WIN-treated group. Prenatal exposure to WIN enhanced the firing irregularity as reflected by a significant decrease in the coefficient of variation of the intraburst interspike interval (p<0.05). Furthermore, whole-cell voltage-clamp recordings revealed that prenatal WIN exposure significantly enhanced Ca(2+) channel current amplitude in offspring Purkinje neurons compared to control cells. Overall, the data presented here strongly suggest that maternal exposure to cannabinoids can induce long-term changes in complex spike burst activity, which in turn may lead to alterations in neuronal output.

The spontaneous electrical and mechanical activity of the longitudinal smooth muscle of the rabbit duodenum and its modification by drugs and temperature changes.

Abstract The electrical and mechanical activity of strips of longitudinal smooth muscle from the rabbit duodenum was recorded using the sucrose gap method. The muscle exhibited rhythmic tension changes each of which was associated with a slow potential wave of electric depolarization surmounted by a burst of spike activity (a multispike complex). Cooling the tissue reduced the frequency of tension waves and multispike complexes. Catecholamines produced a reduction in the amplitude of tension waves. This was associated with hyperpolarization and decreased spike activity. Slow wave frequency and amplitude were unaffected. Acetylcholine, methacholine and histamine produced tension wave fusion associated with depolarization and increased spike activity.

Local Neural Processing and the Generation of Dynamic Motor Commands within the Saccadic Premotor Network

The ability to accurately control movement requires the computation of a precise motor command. However, the computations that take place within premotor pathways to determine the dynamics of movements are not understood. Here we studied the local processing that generates dynamic motor commands by simultaneously recording spikes and local field potentials (LFPs) in the network that commands saccades. We first compared the information encoded by LFPs and spikes recorded from individual premotor and motoneurons (saccadic burst neurons, omnipause neurons, and motoneurons) in monkeys. LFP responses consistent with net depolarizations occurred in association with bursts of spiking activity when saccades were made in a neuron's preferred direction. In contrast, when saccades were made in a neuron's nonpreferred direction, neurons ceased spiking and the associated LFP responses were consistent with net hyperpolarizations. Surprisingly, hyperpolarizing and depolarizing LFPs encoded movement dynamics with equal robustness and accuracy. Second, we compared spiking responses at one hierarchical level of processing to LFPs at the next stage. Latencies and spike-triggered averages of LFP responses were consistent with each neuron's place within this circuit. LFPs reflected relatively local events (<500 microm) and encoded important features not available from the spiking train (i.e., hyperpolarizing response). Notably, quantification of their time-varying profiles revealed that a precise balance of depolarization and hyperpolarization underlies the production of precise saccadic eye movement commands at both motor and premotor levels. Overall, simultaneous recordings of LFPs and spiking responses provides an effective means for evaluating the local computations that take place to produce accurate motor commands.