Irregular Firing Research Articles

Changes in action potential features during focal seizure discharges in the entorhinal cortex of the in vitro isolated guinea pig brain

Temporal lobe seizures in humans correlate with stereotyped electrophysiological patterns that can be reproduced in animal models to study the cellular and network changes responsible for ictogenesis. Seizure-like discharges that mimic seizure patterns in humans were induced in the entorhinal cortex of the in vitro isolated guinea pig brain by 3-min arterial applications of the GABA(A) receptor antagonist bicuculline. The onset of seizure is characterized by a paradoxical interruption of firing for several seconds in principal neurons coupled with both enhanced interneuronal firing and increased extracellular potassium (Gnatkovsky et al. 2008). The evolution of action potential features from firing break to excessive and synchronous activity associated with the progression of seizure itself is analyzed here. We utilized phase plot analysis to characterize action potential features of entorhinal cortex neurons in different phases of a seizure. Compared with preictal action potentials, resumed spikes in layer II-III neurons (n = 17) during the early phase of the seizure-like discharge displayed 1) depolarized threshold, 2) lower peak amplitude, 3) depolarized voltage of repolarization and 4) decelerated depolarizing phase, and 5) spike doublettes. Action potentials in deep-layer principal cells (n = 8) during seizure did not show the marked feature changes observed in superficial layer neurons. Action potential reappearance correlated with an increase in extracellular potassium. High-threshold, slow-action potentials similar to those observed in the irregular firing phase of a seizure were reproduced in layer II-III neurons by direct cortical application of a highly concentrated potassium solution (12-24 mM). We propose that the generation of possibly nonsomatic action potentials by increased extracellular potassium represents a crucial step toward reestablish firing after an initial depression in an acute model of temporal lobe seizures. Resumed firing reengages principal neurons into seizure discharge and promotes the transition toward the synchronized burst firing that characterizes the late phase of a seizure.

Striatal cellular properties conserved from lampreys to mammals

The striatum of the lamprey, the first vertebrate group to appear in evolution, shows striking similarities to that of mammals with respect to histochemical markers, afferent and efferent projections and the effect of dopamine depletion, which leads to hypokinetic motor symptoms. The cellular properties of lamprey striatal neurons were studied here using patch-clamp recordings in acute striatal slices. Sixty-five per cent of recorded neurons were characterised by a prominent inward rectification due to a K+ conductance of the Kir type. They had a ramping response with a long delay to the first action potential due to activation of a low-voltage-activated A-type K+ current. Many such inwardly rectifying neurons (IRNs) had a hyperpolarised resting membrane potential and some had spiny dendrites. The remaining 35% of the neurons (non-IRNs) represent a heterogeneous group, including some with characteristics similar to the fast-spiking interneuron of the mammalian striatum. They showed short-lasting, large after hyperpolarisations (AHPs) and discharged action potentials at high frequency. None of the recorded neurons were spontaneously active but they received GABAergic and glutamatergic synaptic input. The fact that most lamprey striatal neurons display inward rectification indicates that this is a conserved characteristic of striatal neurons throughout vertebrate phylogeny. This is a cellular property of critical importance for the operations of the striatum in mammals.

New determinants of firing rates and patterns of vasopressinergic magnocellular neurons: predictions using a mathematical model of osmodetection

Arginine vasopressin (AVP), one of the most important hormones involved in hydromineral homeostasis, is secreted by hypothalamic magnocellular neurons (MCNs). Here, we implemented two critical parameters for MCN physiology into a Hodgkin-Huxley simulation of the MCN. By incorporating the mechanosensitive channel (MSC) responsible for osmodetection and the synaptic inputs whose frequencies are modulated by changes in ambient osmolality into our model, we were able to develop an improved model with increased physiological relevance and gain new insight into the determinants of the firing patterns of AVP magnocellular neurons. Our results with this MCN model predict that 1) a single MCN is able to display all the firing patterns experimentally observed: silent, irregular, phasic and continuous firing patterns; 2) under conditions of hyperosmolality, burst durations are regulated by the frequency-dependent fatigue of dynorphin secretion; and 3) the transitions between firing patterns are controlled by EPSP and IPSP frequencies (0, 2, 4, 8, 16, 32, 64 and 128 Hz). Moreover, this simulation predicts that EPSPs and IPSPs do not modify the spiking frequency (SF) of phasic firing patterns (0.0034 Hz/Hz [EPSP]; 0.0012 Hz/Hz [IPSP]). Rather, these afferents strongly regulate SF during irregular and continuous firing patterns (0.075 Hz/Hz [EPSP]; 0.027 Hz/Hz [IPSP]). The use of the realistic MCN model developed here allows for an improved understanding of the determinants driving the firing patterns and spiking frequencies of vasopressinergic magnocellular neurons.

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.

Spontaneous Activity Signatures of Morphologically Identified Interneurons in the Vestibulocerebellum

Cerebellar cortical interneurons such as Golgi cells, basket cells, stellate cells, unipolar brush cells, and granule cells play an essential role in the operations of the cerebellum. However, detailed functional studies of the activity of these cells in both anesthetized and behaving animals have been hampered by problems in recognizing their physiological signatures. We have extracellularly recorded the spontaneous activity of vestibulocerebellar interneurons in ketamine/xylazine-anesthetized rats and subsequently labeled them with Neurobiotin using the juxtacellular technique. After recovery and morphological identification of these cells, they were related to statistical measures of their spontaneous activity. Golgi cells display a somewhat irregular firing pattern with relatively low average frequencies. Unipolar brush cells are characterized by more regular firing at higher rates. Basket and stellate cells are alike in their firing characteristics, which mainly stand out by their irregularity; some of them are set apart by their very slow average rate. The spontaneous activity of interneurons examined in the ketamine/xylazine rabbit fit within this general pattern. In the rabbit, granule cells were identified by the spontaneous occurrence of extremely high-frequency bursts of action potentials, which were also recognized in the rat. On the basis of these observations, we devised an algorithm that reliably determined the identity of 75% of the cells with only 2% incorrect classifications. The remaining cells were placed into border categories within which no classification was attempted. We propose that this algorithm can be used to help classify vestibulocerebellar interneurons recorded in awake, behaving animals.

Reservoirs of Stability: Dynamic Flux Tubes in Cortical Circuits

Reservoirs of Stability: Dynamic Flux Tubes in Cortical Circuits

Parvalbumin deficiency affects burst discharges but not network properties of the RTN.

Parvalbumin deficiency affects burst discharges but not network properties of the RTN.

Neighboring Pallidal Neurons Do Not Exhibit more Synchronous Oscillations than Remote Ones in the MPTP Primate Model of Parkinson's Disease

In the healthy primate, neurons of the external and internal segments of the globus pallidus (GP) present a primarily irregular firing pattern, and a negligible level of synchrony is observed between pairs of neurons. This holds even for neighboring cells, despite their higher probability to receive common inputs and to innervate each other via lateral connectivity. In the Parkinsonian primate, this changes drastically, and many pairs of GP cells show synchronous oscillations. To address the relation between distance and synchrony in the Parkinsonian state, we compared the synchrony of discharge of close pairs of neurons, recorded by the same electrode, with remote pairs, recorded by different ones. However, spike trains of neighboring cells recorded by the same extracellular electrode exhibit the shadowing effect; i.e., lack of detection of spikes that occur within a few milliseconds of each other. Here, we demonstrate that the shadowing artifact can both induce apparent correlations between non-correlated neurons, as well as conceal existing correlations between neighboring ones. We therefore introduced artificial shadowing in the remote pairs, similar to the effect we observed in the close ones. After the artificial shadowing, neighboring cells did not show a higher tendency to oscillate synchronously than remote ones. On the contrary, the average percentage (over all sessions) of artificially shadowed remote pairs exhibiting synchronous oscillations was 35.4% compared to 17.2% in the close ones. Similar trend was found when the unshadowed remote pairs were separated according to the estimated distance between electrode tips: 29.9% of pairs at approximate distance of less than 750 μm were significantly synchronized, in comparison with 28.5% of the pairs whose distance was more than 750 μm. We conclude that the synchronous oscillations in the GP of MPTP treated primates are homogenously distributed.

Does High Firing Irregularity Enhance Learning?

In this note, we demonstrate that the high firing irregularity produced by the leaky integrate-and-fire neuron with the partial somatic reset mechanism, which has been shown to be the most likely candidate to reflect the mechanism used in the brain for reproducing the highly irregular cortical neuron firing at high rates (Bugmann, Christodoulou, & Taylor, 1997; Christodoulou & Bugmann, 2001), enhances learning. More specifically, it enhances reward-modulated spike-timing-dependent plasticity with eligibility trace when used in spiking neural networks, as shown by the results when tested in the simple benchmark problem of XOR, as well as in a complex multiagent setting task.

Spiking Neural Networks with Different Reinforcement Learning (RL) Schemes in a Multiagent Setting

This paper investigates the effectiveness of spiking agents when trained with reinforcement learning (RL) in a challenging multiagent task. In particular, it explores learning through reward-modulated spike-timing dependent plasticity (STDP) and compares it to reinforcement of stochastic synaptic transmission in the general-sum game of the Iterated Prisoner's Dilemma (IPD). More specifically, a computational model is developed where we implement two spiking neural networks as two "selfish" agents learning simultaneously but independently, competing in the IPD game. The purpose of our system (or collective) is to maximise its accumulated reward in the presence of reward-driven competing agents within the collective. This can only be achieved when the agents engage in a behaviour of mutual cooperation during the IPD. Previously, we successfully applied reinforcement of stochastic synaptic transmission to the IPD game. The current study utilises reward-modulated STDP with eligibility trace and results show that the system managed to exhibit the desired behaviour by establishing mutual cooperation between the agents. It is noted that the cooperative outcome was attained after a relatively short learning period which enhanced the accumulation of reward by the system. As in our previous implementation, the successful application of the learning algorithm to the IPD becomes possible only after we extended it with additional global reinforcement signals in order to enhance competition at the neuronal level. Moreover it is also shown that learning is enhanced (as indicated by an increased IPD cooperative outcome) through: (i) strong memory for each agent (regulated by a high eligibility trace time constant) and (ii) firing irregularity produced by equipping the agents' LIF neurons with a partial somatic reset mechanism.

Reading Between the Spikes of the Hypothalamic Neural Code

Reading the spike coding of hypothalamic neurones presents a considerable challenge because they exhibit highly irregular firing patterns. Electrophysiologists working in the motor and sensory systems, in which neurones fire more regularly, have devised satisfactory methods to describe the firing of cells, although the statistical assumptions that underlie the methods do not apply to hypothalamic neurones. Measurement of neural activity is nevertheless vital to characterise the activity of neuroendocrine cells. It has thus become necessary to develop methods suitable for the analysis of the highly irregular spike discharge patterns of both spontaneous and stimulus-evoked firing of hypothalamic neurones. We review techniques used to meet this challenge and demonstrate their considerable capacity to address important physiological questions. We also introduce a novel approach for valid statistical estimation of the information conveyed by the response of a single neurone to a periodic stimulus. The approach demonstrated significant diurnal rhythms of synaptic connectivity between hypothalamic nuclei.

SCN5A mutations in atrial fibrillation

Atrial fibrillation, characterized by rapid and irregular atrial firing, is the most prevalent clinically relevant arrhythmia. It is a major cause of morbidity and mortality because it increases the risk for stroke and heart failure and compels the use of drugs that not only affect atrial electrophysiology but also exert proarrhythmic effects on ventricular electrical activity.1–3 Atrial fibrillation also can occur in individuals with no risk factors (“lone atrial fibrillation”). Mutations in genes encoding cardiac sodium or potassium channels recently have been linked to lone atrial fibrillation.

Estimating Network Parameters From Combined Dynamics of Firing Rate and Irregularity of Single Neurons

High firing irregularity is a hallmark of cortical neurons in vivo, and modeling studies suggest a balance of excitation and inhibition is necessary to explain this high irregularity. Such a balance must be generated, at least partly, from local interconnected networks of excitatory and inhibitory neurons, but the details of the local network structure are largely unknown. The dynamics of the neural activity depends on the local network structure; this in turn suggests the possibility of estimating network structure from the dynamics of the firing statistics. Here we report a new method to estimate properties of the local cortical network from the instantaneous firing rate and irregularity (CV(2)) under the assumption that recorded neurons are a part of a randomly connected sparse network. The firing irregularity, measured in monkey motor cortex, exhibits two features; many neurons show relatively stable firing irregularity in time and across different task conditions; the time-averaged CV(2) is widely distributed from quasi-regular to irregular (CV(2) = 0.3-1.0). For each recorded neuron, we estimate the three parameters of a local network [balance of local excitation-inhibition, number of recurrent connections per neuron, and excitatory postsynaptic potential (EPSP) size] that best describe the dynamics of the measured firing rates and irregularities. Our analysis shows that optimal parameter sets form a two-dimensional manifold in the three-dimensional parameter space that is confined for most of the neurons to the inhibition-dominated region. High irregularity neurons tend to be more strongly connected to the local network, either in terms of larger EPSP and inhibitory PSP size or larger number of recurrent connections, compared with the low irregularity neurons, for a given excitatory/inhibitory balance. Incorporating either synaptic short-term depression or conductance-based synapses leads many low CV(2) neurons to move to the excitation-dominated region as well as to an increase of EPSP size.

Distinct types of non-cholinergic pedunculopontine neurons are differentially modulated during global brain states

The pedunculopontine nucleus (PPN) is critically involved in brain-state transitions that promote neocortical activation. In addition, the PPN is involved in the control of several behavioral processes including locomotion, motivation and reward, but the neuronal substrates that underlie such an array of functions remain elusive. Here we analyzed the physiological properties of non-cholinergic PPN neurons in vivo across distinct brain states, and correlated these with their morphological properties after juxtacellular labeling. We show that non-cholinergic neurons in the PPN whose firing is not strongly correlated to neocortical activity are highly heterogeneous and are composed of at least three different subtypes: (1) “quiescent” neurons, which are nearly silent during slow-wave activity (SWA) but respond robustly to neocortical activation; (2) “tonic firing” neurons, which have a stationary firing rate that is independent of neocortical activity across different brain states; and (3) “irregular firing” neurons, which exhibit a variable level of correlation with neocortical activity. The majority of non-cholinergic neurons have an ascending axonal trajectory, with the exception of some irregular firing neurons that have descending axons. Furthermore, we observed asymmetric synaptic contacts within the PPN arising from the axon collaterals of labeled neurons, suggesting that excitatory, non-cholinergic neurons can shape the activity of neighboring cells. Our results provide the first evidence of distinct firing properties associated with non-cholinergic neuronal subtypes in the PPN, suggesting a functional heterogeneity, and support the notion of a local network assembled by projection neurons, the properties of which are likely to determine the output of the PPN in diverse behavioral contexts.

A computational model of Suprachiasmatic Nucleus (SCN) for circadian rhythm modulation based on ion channel conductance and calcium dynamics

The suprachiasmatic nucleus (SCN), the master biological clock of circadian rhythms, has been highly interested for biological rhythms in animals. Physiological and molecular biological studies [1-3] and computational modeling approach [4] have investigated channels contributing to circadian rhythms of spike firing frequency. The aim of this study was to investigate possible contribution of each channel to circadian rhythms using Hodgkin-Huxley-type model containing BK channel, potassium channel, sodium channel, and calcium concentration oscillation. We found that the change in channel conductance modulated firing rates from high regular firing to low irregular firing with high sensitivity of the channel. In agreement with experimental data, the persistent sodium currents also highly contributed to modulation in spike firing frequency. The leak potassium currents and fast delayed rectifier currents exhibited to restrict the circadian firing range and regulation of interspike intervals. Most interestingly, the sinusoidal shape of the diurnal change in the channel conductance reproduced the change in diurnal firing rates. The calcium concentration oscillation and BK channel activity were examined to determine the synchronized circadian oscillation and phase shifting of firing rate in the neural network models structured by graph theory. We suggest that the model may be a guidance of channel properties in experimental conditions and be helpful to explain the circadian behaviors of SCN neurons. Figure 1 Minimum & Maximum firing rates with varied conductance values of calcium and sodium channels. Figure 2 Firing rate distributions with change in sodium and potassium channel conductances

Interspike Interval Analyses Reveal Irregular Firing Patterns at Short, But Not Long, Intervals in Rat Head Direction Cells

Previous studies have shown that a subset of neurons in the rat anterodorsal thalamus discharge as a function of the animal's head direction (HD) in the horizontal plane, independent of the animal's location and behavior. These cells have consistent firing properties across a wide range of conditions and cell discharge appears highly regular when listened to through a loudspeaker. In contrast, interspike interval (ISI) analyses on cortical cells have found that cell firing is irregular, even under constant stimulus conditions. Here, we analyzed HD cells from the anterodorsal thalamus, while rats foraged for food pellets, to determine whether their firing was regular or irregular. ISIs were measured when the animal's HD was maintained within ± 6° of the cell's preferred firing direction. ISIs were highly variable with a mean coefficient of variation (CV) of 0.681. For each cell, the CV values at HDs ± 24° away from the cell's preferred direction were similar to the coefficient measured at the cell's preferred direction. A second recording session showed that cells had similar coefficients of variation as the first session, suggesting that the degree of variability in cell spiking was a characteristic property for each cell. There was little correlation between ISIs and angular head velocity or translational speed. ISIs measured in HD cells from the postsubiculum and lateral mammillary nuclei showed higher CV values. These results indicate that despite the appearance of regularity in their firing, HD cells, like cortical cells, have irregular ISIs. In contrast to the irregular firing observed for ISIs, analyses over longer time intervals indicated that HD cell firing was much more regular, more nearly resembling a rate code. These findings have implications for attractor networks that model the HD signal and for models proposed to explain the generation of grid cell signals in entorhinal cortex.

A new tool for your novelty centre

A new tool for your novelty centre

Bistable, Irregular Firing and Population Oscillations in a Modular Attractor Memory Network

Attractor neural networks are thought to underlie working memory functions in the cerebral cortex. Several such models have been proposed that successfully reproduce firing properties of neurons recorded from monkeys performing working memory tasks. However, the regular temporal structure of spike trains in these models is often incompatible with experimental data. Here, we show that the in vivo observations of bistable activity with irregular firing at the single cell level can be achieved in a large-scale network model with a modular structure in terms of several connected hypercolumns. Despite high irregularity of individual spike trains, the model shows population oscillations in the beta and gamma band in ground and active states, respectively. Irregular firing typically emerges in a high-conductance regime of balanced excitation and inhibition. Population oscillations can produce such a regime, but in previous models only a non-coding ground state was oscillatory. Due to the modular structure of our network, the oscillatory and irregular firing was maintained also in the active state without fine-tuning. Our model provides a novel mechanistic view of how irregular firing emerges in cortical populations as they go from beta to gamma oscillations during memory retrieval.

Self-Sustained Irregular Activity in 2-D Small-World Networks of Excitatory and Inhibitory Neurons

In this paper, we study the self-sustained irregular firing activity in 2-D small-world (SW) neural networks consisting of both excitatory and inhibitory neurons by computational modeling. For a proper proportion of unidirectional shortcuts, the stable self-sustained activity with irregular firing states indeed occurs in the considered network. By varying the shortcut density while keeping other system parameters fixed, different levels of irregular firing states, from weakly irregular to Poisson-like and burst firing states, are obtained in 2-D SW neural networks. It is also observed that this activity is sensitive to small perturbations, which might provide a possible mechanism for producing chaos. On the other hand, we find that several other system parameters, such as the network size and refractory period, have significant impact on this activity. Further simulation results show that the 2-D SW neural network can sustain such long-lasting firing behavior by using a smaller number of connections than the random neural network.

Properties of GABAergic Neurons in the Rostral Solitary Tract Nucleus in Mice

The rostral nucleus of the solitary tract (rNST) plays a pivotal role in taste processing. The rNST contains projection neurons and interneurons that differ in morphology and intrinsic membrane properties. Although characteristics of the projection neurons have been detailed, similar information is lacking on the interneurons. We determined the intrinsic properties of the rNST GABAergic interneurons using a transgenic mouse model that expresses enhanced green fluorescent protein under the control of a GAD67 promoter. Glutamic acid decarboxylase-green fluorescent protein (GAD67-GFP) neurons were distributed throughout the rNST but were concentrated in the ventral subdivision with minimal interaction with the terminal field of the afferent input. Furthermore, the density of the GAD67-GFP neurons decreased in more rostral areas of rNST. In whole cell recordings, GAD67-GFP neurons responded with either an initial burst (73%), tonic (18%), or irregular (9%) discharge pattern of action potentials (APs) in response to membrane depolarization. These three groups also differed in passive and AP characteristics. Initial burst neurons had small ovoid or fusiform cell bodies, whereas tonic firing neurons had large multipolar or fusiform cell bodies. Irregular firing neurons had larger spherical soma. Some of the initial burst and tonic firing neurons were also spontaneously active. The GAD67-GFP neurons could also be categorized in subgroups based on colocalization with somatostatin and parvalbumin immunolabeling. Initial burst neurons would transmit the early dynamic portion of the encoded sensory stimuli, whereas tonic firing neurons could respond to both dynamic and static components of the sensory input, suggesting different roles for GAD67-GFP neurons in taste processing.