Population behavior and self-organization in the genesis of spontaneous rhythmic activity by developing spinal networks

During development spinal networks generate recurring episodes of rhythmic bursting that can be recorded from motoneurons and interneurons. Optical imaging has identified a set of propriospinal interneurons that may be important in the production of this activity. These neurons are rhythmically active, are recurrently interconnected and have powerful projections to motoneurons. The excitability of this propriospinal network is depressed by activity and recovers in the interval between episodes. These and other observations have been formulated into a qualitative model in which population behavior and self-organization are responsible for the spontaneous activity generated by developing spinal networks.     

Development of motor behaviour

The development of motor behaviour depends on the differentiation of underlying circuitry. Recent work with the zebrafish brings the simple swimming behaviour of lower vertebrates and their embryos into focus as a suitable model to study the development of motor circuitry and its genetic control. Changes in connectivity and excitability contribute to the development of swimming in this simple system. In the chick embryo, limb motor circuitry is spontaneously active before motor axons reach their muscle targets, and it has properties in common with the spontaneously active networks in the retina. The early rhythmic activity responsible for embryonic movement is probably a generalised property of developing spinal networks that precedes, and may be required for, the completion of functional locomotor circuitry.     

Hebb and homeostasis in neuronal plasticity

The positive-feedback nature of Hebbian plasticity can destabilize the properties of neuronal networks. Recent work has demonstrated that this destabilizing influence is counteracted by a number of homeostatic plasticity mechanisms that stabilize neuronal activity. Such mechanisms include global changes in synaptic strengths, changes in neuronal excitability, and the regulation of synapse number. These recent studies suggest that Hebbian and homeostatic plasticity often target the same molecular substrates, and have opposing effects on synaptic or neuronal properties. These advances significantly broaden our framework for understanding the effects of activity on synaptic function and neuronal excitability.     

Effect of static load on motor behavior of the cockroach Periplaneta americana

Effect of static load on activity of motor centers controlling motor activity (walking flight) was studied in the American cockroach Periplaneta americana L. It has been established that under effect of load on the animal body the relative excitability of these centers increases. A suggestion is put forward about the presence of common neuronal elements in the generator networks providing motor acts in the American cockroach; a role of afferent systems in control of excitability of locomotor centers functioning in the regime of static load is shown.     

Effect of static load on motor behavior of the cockroach Periplaneta americana

Effect of static load on activity of motor centers controlling motor activity (walking, flight) was studied in the American cockroach Periplaneta americana L. It has been established that under effect of load on the animal body the relative excitability of these centers increases. A suggestion is put forward about the presence of common neuronal elements in the generator networks providing motor acts in the American cockroach; a role of afferent systems in control of excitability of loco-motor centers functioning in the regime of static load is shown.     

Reliable Activation of Immature Neurons in the Adult Hippocampus

Neurons born in the adult dentate gyrus develop, mature, and connect over a long interval that can last from six to eight weeks. It has been proposed that, during this period, developing neurons play a relevant role in hippocampal signal processing owing to their distinctive electrical properties. However, it has remained unknown whether immature neurons can be recruited into a network before synaptic and functional maturity have been achieved. To address this question, we used retroviral expression of green fluorescent protein to identify developing granule cells of the adult mouse hippocampus and investigate the balance of afferent excitation, intrinsic excitability, and firing behavior by patch clamp recordings in acute slices. We found that glutamatergic inputs onto young neurons are significantly weaker than those of mature cells, yet stimulation of cortical excitatory axons elicits a similar spiking probability in neurons at either developmental stage. Young neurons are highly efficient in transducing ionic currents into membrane depolarization due to their high input resistance, which decreases substantially in mature neurons as the inward rectifier potassium (Kir) conductance increases. Pharmacological blockade of Kir channels in mature neurons mimics the high excitability characteristic of young neurons. Conversely, Kir overexpression induces mature-like firing properties in young neurons. Therefore, the differences in excitatory drive of young and mature neurons are compensated by changes in membrane excitability that render an equalized firing activity. These observations demonstrate that the adult hippocampus continuously generates a population of highly excitable young neurons capable of information processing.     

Some properties of randomly connected networks of neuron-like elements with refractory

Dynamic properties of randomly connected networks consisting of neuron-like elements with refractory are investigated from a macroscopic point of view. Equations describing the transition of the activity level of the network — a macroscopic state — are derived under some hypotheses on the stochastic properties of the network. The equations are characterized by a set of parameters which are determined by distributions of the threshold values of elements and the weighting values of connection between elements. It is shown that a network behaves like a monostable, bistable or astable circuit when its refractory period is less than one time unit and that a network is monostable or bistable when its refractory period is longer than two time units. An oscillatory network, on the other hand, is always realized if the network has a feedback mechanism which decreases the excitability of neurons when high activity level is sustained. Some results of computer simulation of randomly connected neuron networks are also presented.     

Plasticity of dendritic excitability

Dendrites are equipped with a plethora of voltage-gated ion channels that greatly enrich the computational and storage capacity of neurons. The excitability of dendrites and dendritic function display plasticity under diverse circumstances such as neuromodulation, adaptation, learning and memory, trauma, or disorders. This adaptability arises from alterations in the biophysical properties or the expression levels of voltage-gated ion channels-induced by the activity of neurotransmitters, neuromodulators, and second-messenger cascades. In this review we discuss how this plasticity of dendritic excitability could alter information transfer and processing within dendrites, neurons, and neural networks under physiological and pathological conditions.     

Structure-Dynamics Relationships in Bursting Neuronal Networks Revealed Using a Prediction Framework

The question of how the structure of a neuronal network affects its functionality has gained a lot of attention in neuroscience. However, the vast majority of the studies on structure-dynamics relationships consider few types of network structures and assess limited numbers of structural measures. In this in silico study, we employ a wide diversity of network topologies and search among many possibilities the aspects of structure that have the greatest effect on the network excitability. The network activity is simulated using two point-neuron models, where the neurons are activated by noisy fluctuation of the membrane potential and their connections are described by chemical synapse models, and statistics on the number and quality of the emergent network bursts are collected for each network type. We apply a prediction framework to the obtained data in order to find out the most relevant aspects of network structure. In this framework, predictors that use different sets of graph-theoretic measures are trained to estimate the activity properties, such as burst count or burst length, of the networks. The performances of these predictors are compared with each other. We show that the best performance in prediction of activity properties for networks with sharp in-degree distribution is obtained when the prediction is based on clustering coefficient. By contrast, for networks with broad in-degree distribution, the maximum eigenvalue of the connectivity graph gives the most accurate prediction. The results shown for small () networks hold with few exceptions when different neuron models, different choices of neuron population and different average degrees are applied. We confirm our conclusions using larger () networks as well. Our findings reveal the relevance of different aspects of network structure from the viewpoint of network excitability, and our integrative method could serve as a general framework for structure-dynamics studies in biosciences.     

Effect of ginseng preparations on the activity of identified neurons of Heliz lucorum snails

It has been demonstrated that the effects of aqueous extracts from the native ginseng and extracts of genseng tissue culture on the activity of identified neurones are identical. Neuronal excitability, tested intracellularly, significantly increases to the 60th minute of drug application, whereas gradually developing depolarization simultaneously disappears. Rhythmic orthodromic stimulation revealed the increase in neuronal responses during ginseng perfusion, the synaptic efficiency remaining constant. It is suggested that changes in transmembrane potential level evoked by administration of ginseng preparations are not related to changes in the excitability. Changes in the adaptive capacities of the neurones in invertebrate animals are due to nonspecific endoneuronal shifts in cellular metabolism induced by ginseng administation.     

Probing neural circuitry and function with electrical microstimulation

Since the discovery of the nervous system's electrical excitability more than 200 years ago, neuroscientists have used electrical stimulation to manipulate brain activity in order to study its function. Microstimulation has been a valuable technique for probing neural circuitry and identifying networks of neurons that underlie perception, movement and cognition. In this review, we focus on the use of stimulation in behaving primates, an experimental system that permits causal inferences to be made about the effect of stimulation-induced activity on the resulting behaviour or neural signals elsewhere in the brain.     

The Ionic Dependence of Cardiac Excitability and Contractility

In contrast to the large volume of data supporting the dependence of cardiac excitability and phasic contractility on external Na, Van der Kloot and Rubin (1962) and Singh (1962) have reported the persistence of both electrical and phasic mechanical activity in frog atrial and ventricular preparations soaked in isotonic sucrose solutions. The acute ionic dependence of excitability and contractility in small frog atrial trabeculae has been investigated with the conclusion that excitability and phasic contractions may continue for extended periods of time in sucrose media if the extracellular ionic concentrations remain above 2% of normal. This behavior is attributed to the slow exchange properties of the cell surfaces of the frog cardiac trabeculae and the antagonistic effects of Na, K, and Ca ions on both membrane excitability and fiber contractility.     

State transitions through inhibitory interneurons in a cortical network model

Inhibitory interneurons shape the spiking characteristics and computational properties of cortical networks. Interneuron subtypes can precisely regulate cortical function but the roles of interneuron subtypes for promoting different regimes of cortical activity remains unclear. Therefore, we investigated the impact of fast spiking and non-fast spiking interneuron subtypes on cortical activity using a network model with connectivity and synaptic properties constrained by experimental data. We found that network properties were more sensitive to modulation of the fast spiking population, with reductions of fast spiking excitability generating strong spike correlations and network oscillations. Paradoxically, reduced fast spiking excitability produced a reduction of global excitation-inhibition balance and features of an inhibition stabilised network, in which firing rates were driven by the activity of excitatory neurons within the network. Further analysis revealed that the synaptic interactions and biophysical features associated with fast spiking interneurons, in particular their rapid intrinsic response properties and short synaptic latency, enabled this state transition by enhancing gain within the excitatory population. Therefore, fast spiking interneurons may be uniquely positioned to control the strength of recurrent excitatory connectivity and the transition to an inhibition stabilised regime. Overall, our results suggest that interneuron subtypes can exert selective control over excitatory gain allowing for differential modulation of global network state.     

Independent Component Analysis in Spiking Neurons

Although models based on independent component analysis (ICA) have been successful in explaining various properties of sensory coding in the cortex, it remains unclear how networks of spiking neurons using realistic plasticity rules can realize such computation. Here, we propose a biologically plausible mechanism for ICA-like learning with spiking neurons. Our model combines spike-timing dependent plasticity and synaptic scaling with an intrinsic plasticity rule that regulates neuronal excitability to maximize information transmission. We show that a stochastically spiking neuron learns one independent component for inputs encoded either as rates or using spike-spike correlations. Furthermore, different independent components can be recovered, when the activity of different neurons is decorrelated by adaptive lateral inhibition.     

Translational regulation of neuronal electrical properties

The nervous system has an in-built capability to adjust its responsiveness to excitation according to the history of electrical activity faced by the neurons embedded within its networks. This control over excitability represents a form of homeostasis and is exhibited at multiple stages in the flow of information from the genome to the expression and modification of protein products. Information on the nature of the homeostatic phenomenon at some of these stages is still limited and emerging. This article outlines the various stages at which such neuronal intrinsic plasticity has been observed and draws particular attention to the role of the translation repressor protein, Pumilio, as an important factor in the process. The study of this protein is providing insights into the regulation of neuronal excitability and offers an important research target with benefits to investigators in many areas of neuroscience.     

Control of neuronal excitability by GSK-3beta: Epilepsy and beyond

Glycogen synthase kinase 3beta (GSK-3β) is an enzyme with a variety of cellular functions in addition to the regulation of glycogen metabolism. In the central nervous system, different intracellular signaling pathways converge on GSK-3β through a cascade of phosphorylation events that ultimately control a broad range of neuronal functions in the development and adulthood. In mice, genetically removing or increasing GSK-3β cause distinct functional and structural neuronal phenotypes and consequently affect cognition. Precise control of GSK-3β activity is important for such processes as neuronal migration, development of neuronal morphology, synaptic plasticity, excitability, and gene expression. Altered GSK-3β activity contributes to aberrant plasticity within neuronal circuits leading to neurological, psychiatric disorders, and neurodegenerative diseases. Therapeutically targeting GSK-3β can restore the aberrant plasticity of neuronal networks at least in animal models of these diseases. Although the complete repertoire of GSK-3β neuronal substrates has not been defined, emerging evidence shows that different ion channels and their accessory proteins controlling excitability, neurotransmitter release, and synaptic transmission are regulated by GSK-3β, thereby supporting mechanisms of synaptic plasticity in cognition. Dysregulation of ion channel function by defective GSK-3β activity sustains abnormal excitability in the development of epilepsy and other GSK-3β-linked human diseases.     

A Diffusive Homeostatic Signal Maintains Neural Heterogeneity and Responsiveness in Cortical Networks

Gaseous neurotransmitters such as nitric oxide (NO) provide a unique and often overlooked mechanism for neurons to communicate through diffusion within a network, independent of synaptic connectivity. NO provides homeostatic control of intrinsic excitability. Here we conduct a theoretical investigation of the distinguishing roles of NO-mediated diffusive homeostasis in comparison with canonical non-diffusive homeostasis in cortical networks. We find that both forms of homeostasis provide a robust mechanism for maintaining stable activity following perturbations. However, the resulting networks differ, with diffusive homeostasis maintaining substantial heterogeneity in activity levels of individual neurons, a feature disrupted in networks with non-diffusive homeostasis. This results in networks capable of representing input heterogeneity, and linearly responding over a broader range of inputs than those undergoing non-diffusive homeostasis. We further show that these properties are preserved when homeostatic and Hebbian plasticity are combined. These results suggest a mechanism for dynamically maintaining neural heterogeneity, and expose computational advantages of non-local homeostatic processes.     

Pannexin 1 activity in astroglia sets hippocampal neuronal network patterns

Astroglial release of molecules is thought to actively modulate neuronal activity, but the nature, release pathway, and cellular targets of these neuroactive molecules are still unclear. Pannexin 1, expressed by neurons and astrocytes, form nonselective large pore channels that mediate extracellular exchange of molecules. The functional relevance of these channels has been mostly studied in brain tissues, without considering their specific role in different cell types, or in neurons. Thus, our knowledge of astroglial pannexin 1 regulation and its control of neuronal activity remains very limited, largely due to the lack of tools targeting these channels in a cell-specific way. We here show that astroglial pannexin 1 expression in mice is developmentally regulated and that its activation is activity-dependent. Using astrocyte-specific molecular tools, we found that astroglial-specific pannexin 1 channel activation, in contrast to pannexin 1 activation in all cell types, selectively and negatively regulates hippocampal networks, with their disruption inducing a drastic switch from bursts to paroxysmal activity. This decrease in neuronal excitability occurs via an unconventional astroglial mechanism whereby pannexin 1 channel activity drives purinergic signaling-mediated regulation of hyperpolarisation-activated cyclic nucleotide (HCN)-gated channels. Our findings suggest that astroglial pannexin 1 channel activation serves as a negative feedback mechanism crucial for the inhibition of hippocampal neuronal networks.

Astrocytes have mostly been shown to boost neuronal activity. This study reveals that activity-dependent activation of astroglial pannexin 1 channels inhibits hippocampal neuronal networks by decreasing neuronal excitability via purinergic signaling, uncovering a novel astroglial negative feedback loop mechanism.     

Manipulations of spinal cord excitability evoke developmentally-dependent compensatory changes in the lamprey spinal cord

We have examined homeostatic or compensatory plasticity evoked by tonic changes in spinal cord excitability in the lamprey, a model system for investigating spinal cord function. In larval animals, reducing excitability by incubating in tetrodotoxin or the glutamate receptor antagonists CNQX or CNQX/AP5 for 20–48 h resulted in a diverse set of cellular and synaptic changes that together were consistent with an increase in spinal cord excitability. Similar changes occurred to a tonic increase in excitation evoked by incubating in high potassium physiological solution (i.e. responses were unidirectional). We also examined developmental influences on these effects. In animals developing from the larval to adult form effects were reduced or absent, suggesting that at this stage the spinal cord was more tolerant of changes in activity levels. Responses had returned in adult animals, but they were now bi-directional (i.e. opposite effects were evoked by an increase or decrease in excitability). The spinal cord can thus monitor and adapt cellular and synaptic properties to tonic changes in excitability levels. This should be considered in analyses of spinal cord plasticity and injury.