Management of synchronized network activity by highly active neurons

Increasing evidence supports the idea that spontaneous brain activity may have an important functional role. Cultured neuronal networks provide a suitable model system to search for the mechanisms by which neuronal spontaneous activity is maintained and regulated. This activity is marked by synchronized bursting events (SBEs)--short time windows (hundreds of milliseconds) of rapid neuronal firing separated by long quiescent periods (seconds). However, there exists a special subset of rapidly firing neurons whose activity also persists between SBEs. It has been proposed that these highly active (HA) neurons play an important role in the management (i.e. establishment, maintenance and regulation) of the synchronized network activity. Here, we studied the dynamical properties and the functional role of HA neurons in homogeneous and engineered networks, during early network development, upon recovery from chemical inhibition and in response to electrical stimulations. We found that their sequences of inter-spike intervals (ISI) exhibit long time correlations and a unimodal distribution. During the network's development and under intense inhibition, the observed activity follows a transition period during which mostly HA neurons are active. Studying networks with engineered geometry, we found that HA neurons are precursors (the first to fire) of the spontaneous SBEs and are more responsive to electrical stimulations.     

Volume transmission in activity-dependent regulation of myelinating glia

The importance of neural impulse activity in regulating neuronal plasticity is widely appreciated; increasingly, it is becoming apparent that activity-dependent communication between neurons and glia is critical in regulating many aspects of nervous system development and plasticity. This communication takes place not only at the synapse, but also between premyelinating axons and glia, which form myelin in the PNS and CNS. Recent work indicates that neural impulse activity releases ATP and adenosine from non-synaptic regions of neurons, which activates purinergic receptors on myelinating glia. Acting through this receptor system, neural impulse activity can regulate gene expression, mitosis, differentiation, and myelination of Schwann cells (SCs) and oligodendrocytes, helping coordinate nervous system development with functional activity in the perinatal period. ATP and adenosine have opposite effects on differentiation of Schwann cells and oligodendrocytes, providing a possible explanation for the opposite effects of impulse activity reported on myelination in the CNS and PNS.     

ER and Golgi trafficking in axons,dendrites, and glial processes

Both neurons and glia in mammalian brains are highly ramified. Neurons form complex neural networks using axons and dendrites. Axons are long with few branches and form pre-synaptic boutons that connect to target neurons and effector tissues. Dendrites are shorter, highly branched, and form post-synaptic boutons. Astrocyte processes contact synapses and blood vessels in order to regulate neuronal activity and blood flow, respectively. Oligodendrocyte processes extend toward axons to make myelin sheaths. Microglia processes dynamically survey their environments. Here, we describe the local secretory system (ER and Golgi) in neuronal and glial processes. We focus on Golgi outpost functions in acentrosomal microtubule nucleation, cargo trafficking, and protein glycosylation. Thus, satellite ER and Golgi are critical for local structure and function in neurons and glia.     

Transitions between irregular and rhythmic firing patterns in excitatory-inhibitory neuronal networks

Changes in firing patterns are an important hallmark of the functional status of neuronal networks. We apply dynamical systems methods to understand transitions between irregular and rhythmic firing in an excitatory-inhibitory neuronal network model. Using the geometric theory of singular perturbations, we systematically reduce the full model to a simpler set of equations, one that can be studied analytically. The analytic tools are used to understand how an excitatory-inhibitory network with a fixed architecture can generate both activity patterns for possibly different values of the intrinsic and synaptic parameters. These results are applied to a recently developed model for the subthalamopallidal network of the basal ganglia. The results suggest that an increase in correlated activity, corresponding to a pathological state, may be due to an increased level of inhibition from the striatum to the inhibitory GPe cells along with an increased ability of the excitatory STN neurons to generate rebound bursts. Action Editor: Carson Chow     

Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks IV

In neuronal networks, the changes of synaptic strength (or weight) performed by spike-timing-dependent plasticity (STDP) are hypothesized to give rise to functional network structure. This article investigates how this phenomenon occurs for the excitatory recurrent connections of a network with fixed input weights that is stimulated by external spike trains. We develop a theoretical framework based on the Poisson neuron model to analyze the interplay between the neuronal activity (firing rates and the spike-time correlations) and the learning dynamics, when the network is stimulated by correlated pools of homogeneous Poisson spike trains. STDP can lead to both a stabilization of all the neuron firing rates (homeostatic equilibrium) and a robust weight specialization. The pattern of specialization for the recurrent weights is determined by a relationship between the input firing-rate and correlation structures, the network topology, the STDP parameters and the synaptic response properties. We find conditions for feed-forward pathways or areas with strengthened self-feedback to emerge in an initially homogeneous recurrent network.     

Exploring how extracellular electric field modulates neuron activity through dynamical analysis of a two-compartment neuron model

To investigate how extracellular electric field modulates neuron activity, a reduced two-compartment neuron model in the presence of electric field is introduced in this study. Depending on neuronal geometric and internal coupling parameters, the behaviors of the model have been studied extensively. The neuron model can exist in quiescent state or repetitive spiking state in response to electric field stimulus. Negative electric field mainly acts as inhibitory stimulus to the neuron, positive weak electric field could modulate spiking frequency and spike timing when the neuron is already active, and positive electric fields with sufficient intensity could directly trigger neuronal spiking in the absence of other stimulations. By bifurcation analysis, it is observed that there is saddle-node on invariant circle bifurcation, supercritical Hopf bifurcation and subcritical Hopf bifurcation appearing in the obtained two parameter bifurcation diagrams. The bifurcation structures and electric field thresholds for triggering neuron firing are determined by neuronal geometric and coupling parameters. The model predicts that the neurons with a nonsymmetric morphology between soma and dendrite, are more sensitive to electric field stimulus than those with the spherical structure. These findings suggest that neuronal geometric features play a crucial role in electric field effects on the polarization of neuronal compartments. Moreover, by determining the electric field threshold of our biophysical model, we could accurately distinguish between suprathreshold and subthreshold electric fields. Our study highlights the effects of extracellular electric field on neuronal activity from the biophysical modeling point of view. These insights into the dynamical mechanism of electric field may contribute to the investigation and development of electromagnetic therapies, and the model in our study could be further extended to a neuronal network in which the effects of electric fields on network activity may be investigated.     

Recurrent networks of submucous neurons controlling intestinal secretion: a modeling study

Secretomotor neurons, immunoreactive for vasoactive intestinal peptide (VIP), are important in controlling chloride secretion in the small intestine. These neurons form functional synapses with other submucosal VIP neurons and transmit via slow excitatory postsynaptic potentials (EPSPs). Thus they form a recurrent network with positive feedback. Intrinsic sensory neurons within the submucosa are also likely to form recurrent networks with positive feedback, provide substantial output to VIP neurons, and receive input from VIP neurons. If positive feedback within recurrent networks is sufficiently large, then neurons in the network respond to even small stimuli by firing at their maximum possible rate, even after the stimulus is removed. However, it is not clear whether such a mechanism operates within the recurrent networks of submucous neurons. We investigated this question by performing computer simulations of realistic models of VIP and intrinsic sensory neuron networks. In the expected range of electrophysiological properties, we found that activity in the VIP neuron network decayed slowly after cessation of a stimulus, indicating that positive feedback is not strong enough to support the uncontrolled firing state. The addition of intrinsic sensory neurons produced a low stable firing rate consistent with the common finding that basal secretory activity is, in part, neurogenic. Changing electrophysiological properties enables these recurrent networks to support the uncontrolled firing state, which may have implications with hypersecretion in the presence of enterotoxins such as cholera-toxin.     

On the dynamics of the spontaneous activity in neuronal networks

Most neuronal networks, even in the absence of external stimuli, produce spontaneous bursts of spikes separated by periods of reduced activity. The origin and functional role of these neuronal events are still unclear. The present work shows that the spontaneous activity of two very different networks, intact leech ganglia and dissociated cultures of rat hippocampal neurons, share several features. Indeed, in both networks: i) the inter-spike intervals distribution of the spontaneous firing of single neurons is either regular or periodic or bursting, with the fraction of bursting neurons depending on the network activity; ii) bursts of spontaneous spikes have the same broad distributions of size and duration; iii) the degree of correlated activity increases with the bin width, and the power spectrum of the network firing rate has a 1/f behavior at low frequencies, indicating the existence of long-range temporal correlations; iv) the activity of excitatory synaptic pathways mediated by NMDA receptors is necessary for the onset of the long-range correlations and for the presence of large bursts; v) blockage of inhibitory synaptic pathways mediated by GABA(A) receptors causes instead an increase in the correlation among neurons and leads to a burst distribution composed only of very small and very large bursts. These results suggest that the spontaneous electrical activity in neuronal networks with different architectures and functions can have very similar properties and common dynamics.     

DPP6 establishes the A-type K(+) current gradient critical for the regulation of dendritic excitability in CA1 hippocampal neurons

Subthreshold-activating A-type K(+) currents are essential for the proper functioning of the brain, where they act to delay excitation and regulate firing frequency. In CA1 hippocampal pyramidal neuron dendrites, the density of A-type K(+) current increases with distance from the soma, playing an important role in synaptic integration and plasticity. The mechanism underlying this gradient has, however, remained elusive. Here, dendritic recordings from mice lacking the Kv4 transmembrane auxiliary subunit DPP6 revealed that this protein is critical for generating the A-current gradient. Loss of DPP6 led to a decrease in A-type current, specifically in distal dendrites. Decreased current density was accompanied by a depolarizing shift in the voltage dependence of channel activation. Together these changes resulted in hyperexcitable dendrites with enhanced dendritic AP back-propagation, calcium electrogenesis, and induction of synaptic long-term potentiation. Despite enhanced dendritic excitability, firing behavior evoked by somatic current injection was mainly unaffected in DPP6-KO recordings, indicating compartmentalized regulation of neuronal excitability.     

Pleiotropic effects of the bone morphogenetic proteins on development of the enteric nervous system

Formation of the enteric nervous system (ENS) from migratory neural crest-derived cells that colonize the primordial gut involves a complex interplay among different signaling molecules. The bone morphogenetic proteins (BMPs), specifically BMP2 and BMP4, play a particularly important role in virtually every stage of gut and ENS development. BMP signaling helps to pattern both the anterior-posterior axis and the radial axis of the gut prior to colonization by migratory crest progenitor cells. BMP signaling then helps regulate the migration of enteric neural crest-derived precursors as they colonize the fetal gut and form ganglia. BMP2 and -4 promote differentiation of enteric neurons in early fetal ENS development and glia at later stages. A major role for BMP signaling in the ENS is regulation of responses to other growth factors. Thus BMP signaling first regulates neurogenesis by modulating responses to GDNF and later gliogenesis through its effects on GGF-2 responses. Furthermore, BMPs promote growth factor dependency for survival of ENS neurons (on NT-3) and glia (on GGF-2) by inducing TrkC (neurons) and ErbB3 (glia). BMP signaling limits total neuron numbers, favoring the differentiation of later born neuronal phenotypes at the expense of earlier born ones thus influencing the neuronal composition of the ENS and the glia/neuron ratio. BMP2 and -4 also promote gangliogenesis via modification of neural cell adhesion molecules and promote differentiation of the circular and then longitudinal smooth muscles. Disruption of BMP signaling leads to defects in the gut and in ENS function commensurate with these complex developmental roles.     

Role of potassium lateral diffusion in non-synaptic epilepsy: a computational study

An increase of extracellular potassium ion concentration can result in neuronal hyperexcitability, and thus contribute to non-synaptic epileptiform activity. It has been shown that potassium lateral diffusion alone is sufficient for synchronization in the low-calcium epilepsy in-vitro model. However, it is not yet known whether the lateral diffusion can, by itself, induce seizure activity. We hypothesize that spontaneous sustained neuronal activity can be generated by potassium coupling between neurons. To test this hypothesis, neuronal simulations with 2-cell or 4-cell models were used. Each model neuron was embedded in a bath of K+ and surrounded by interstitial space. Interstitial potassium concentration was regulated by both K+-pump and glial buffer mechanisms. Simulations performed with two coupled neurons with parameter values within physiological range show that, without chemical and electrical synapses, potassium lateral diffusion alone can generate and synchronize zero-Ca2+ non-synaptic epileptiform activity. Simulations performed with a network of four zero-Ca2+ CA1 pyramidal neurons modeled in zero-calcium conditions also show that spontaneous sustained activity can propagate by potassium lateral diffusion alone with a velocity of approximately 0.93 mm/sec. This diffusion model used for the simulations is based on physiological parameters, is robust for various kinetics, and is able to reproduce both the spontaneous triplet bursting of non-synaptic activity and speed of propagation in low-Ca2+ non-synaptic epilepsy experiments. These simulations suggest that potassium lateral diffusion can play an important role in the synchronization and generation on non-synaptic epilepsy.     

Predictive features of persistent activity emergence in regular spiking and intrinsic bursting model neurons

Proper functioning of working memory involves the expression of stimulus-selective persistent activity in pyramidal neurons of the prefrontal cortex (PFC), which refers to neural activity that persists for seconds beyond the end of the stimulus. The mechanisms which PFC pyramidal neurons use to discriminate between preferred vs. neutral inputs at the cellular level are largely unknown. Moreover, the presence of pyramidal cell subtypes with different firing patterns, such as regular spiking and intrinsic bursting, raises the question as to what their distinct role might be in persistent firing in the PFC. Here, we use a compartmental modeling approach to search for discriminatory features in the properties of incoming stimuli to a PFC pyramidal neuron and/or its response that signal which of these stimuli will result in persistent activity emergence. Furthermore, we use our modeling approach to study cell-type specific differences in persistent activity properties, via implementing a regular spiking (RS) and an intrinsic bursting (IB) model neuron. We identify synaptic location within the basal dendrites as a feature of stimulus selectivity. Specifically, persistent activity-inducing stimuli consist of activated synapses that are located more distally from the soma compared to non-inducing stimuli, in both model cells. In addition, the action potential (AP) latency and the first few inter-spike-intervals of the neuronal response can be used to reliably detect inducing vs. non-inducing inputs, suggesting a potential mechanism by which downstream neurons can rapidly decode the upcoming emergence of persistent activity. While the two model neurons did not differ in the coding features of persistent activity emergence, the properties of persistent activity, such as the firing pattern and the duration of temporally-restricted persistent activity were distinct. Collectively, our results pinpoint to specific features of the neuronal response to a given stimulus that code for its ability to induce persistent activity and predict differential roles of RS and IB neurons in persistent activity expression.     

Fibroblast growth factor-2 stimulates cell proliferation and decreases sexually dimorphic cell death in an avian song control nucleus

The neural system controlling song in birds has proven a useful model for investigating how neuronal growth and survival are regulated by sexual differentiation. The present study focused on one song control area, the robust nucleus of the archistriatum (RA), and explored how sex differences in the proliferation of putative glia cells in this region influence sexually dimorphic cell survival. In zebra finches (Poephila guttata), RA neuron death is much greater in young females than in males, resulting in marked sex differences in RA neuron number. An earlier study indicated that just prior to this sexually dimorphic neuron death the proliferation of putative glia cells within the RA is significantly lower in females than in males and remains so throughout the peak of neuron death. This suggests that sex differences in glia (or glia-derived molecules) might regulate neuron survival during sexual differentiation of the RA. To determine whether increased cell proliferation within the RA favors increased cell survival, we infused the potent glia mitogen fibroblast growth factor-2 (FGF-2) into the RA unilaterally in young females. We find that FGF-2 infusions increase RA cell proliferation and concurrently decrease the incidence of degenerating RA cells, results consistent with the hypothesis that glia exert neurotrophic effects on RA neurons during sexual differentiation. © 1998 John Wiley & Sons, Inc. J Neurobiol 37: 573–581, 1998     

Turning up the heat on L-type Ca2+ channels promotes neuronal firing and seizure activity

It is well recognized clinically that fever in young children (< 6 y of age) may lead to seizure activity in a small, but significant percentage of these individuals, which may have negative consequences for the developing brain and progressive cognitive function. In rodent models, exposure of acute brain slices to hyperthermic temperatures (i.e., 38–41°C) is reported to evoke membrane depolarization and increased neuronal firing, although the underlying molecular/cellular events responsible for these phenomena are not fully understood. Elevated temperature may alter membrane excitability by influencing individual ion channels within a given neuron, or alter the behavior and connectivity of neurons and glia that operate within a local network. In the present study, Radzicki and colleagues have examined the possibility that modest increases in tissue/body temperature (up to 40.5°C) may enhance the activity of voltage-gated Ca²⁺ channels, which could then promote spontaneous firing of individual neurons and greater network discharge. The results of this work indicate that fever-like temperatures positively and reversibly influence the gating properties of L-type Ca²⁺ channels, and that the L-type blocker nimodipine reduces both temperature-induced increases in spontaneous neuronal firing and the incidence/duration of discharge activity in a whole animal model of febrile seizure.     

Calcium waves propagate through radial glial cells and modulate proliferation in the developing neocortex

The majority of neurons in the adult neocortex are produced embryonically during a brief but intense period of neuronal proliferation. The radial glial cell, a transient embryonic cell type known for its crucial role in neuronal migration, has recently been shown to function as a neuronal progenitor cell and appears to produce most cortical pyramidal neurons. Radial glial cell modulation could thus affect neuron production, neuronal migration, and overall cortical architecture; however, signaling mechanisms among radial glia have not been studied directly. We demonstrate here that calcium waves propagate through radial glial cells in the proliferative cortical ventricular zone (VZ). Radial glial calcium waves occur spontaneously and require connexin hemichannels, P2Y1 ATP receptors, and intracellular IP3-mediated calcium release. Furthermore, we show that wave disruption decreases VZ proliferation during the peak of embryonic neurogenesis. Taken together, these results demonstrate a radial glial signaling mechanism that may regulate cortical neuronal production.     

Library-based numerical reduction of the Hodgkin–Huxley neuron for network simulation

We present an efficient library-based numerical method for simulating the Hodgkin–Huxley (HH) neuronal networks. The key components in our numerical method involve (i) a pre-computed high resolution data library which contains typical neuronal trajectories (i.e., the time-courses of membrane potential and gating variables) during the interval of an action potential (spike), thus allowing us to avoid resolving the spikes in detail and to use large numerical time steps for evolving the HH neuron equations; (ii) an algorithm of spike-spike corrections within the groups of strongly coupled neurons to account for spike-spike interactions in a single large time step. By using the library method, we can evolve the HH networks using time steps one order of magnitude larger than the typical time steps used for resolving the trajectories without the library, while achieving comparable resolution in statistical quantifications of the network activity, such as average firing rate, interspike interval distribution, power spectra of voltage traces. Moreover, our large time steps using the library method can break the stability requirement of standard methods (such as Runge–Kutta (RK) methods) for the original dynamics. We compare our library-based method with RK methods, and find that our method can capture very well phase-locked, synchronous, and chaotic dynamics of HH neuronal networks. It is important to point out that, in essence, our library-based HH neuron solver can be viewed as a numerical reduction of the HH neuron to an integrate-and-fire (I&F) neuronal representation that does not sacrifice the gating dynamics (as normally done in the analytical reduction to an I&F neuron).     

Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks. II. Input selectivity—symmetry breaking

Spike-timing-dependent plasticity (STDP) is believed to structure neuronal networks by slowly changing the strengths (or weights) of the synaptic connections between neurons depending upon their spiking activity, which in turn modifies the neuronal firing dynamics. In this paper, we investigate the change in synaptic weights induced by STDP in a recurrently connected network in which the input weights are plastic but the recurrent weights are fixed. The inputs are divided into two pools with identical constant firing rates and equal within-pool spike-time correlations, but with no between-pool correlations. Our analysis uses the Poisson neuron model in order to predict the evolution of the input synaptic weights and focuses on the asymptotic weight distribution that emerges due to STDP. The learning dynamics induces a symmetry breaking for the individual neurons, namely for sufficiently strong within-pool spike-time correlation each neuron specializes to one of the input pools. We show that the presence of fixed excitatory recurrent connections between neurons induces a group symmetry-breaking effect, in which neurons tend to specialize to the same input pool. Consequently STDP generates a functional structure on the input connections of the network.     

Enhancement of information transmission of sub-threshold signals applied to distal positions of dendritic trees in hippocampal CA1 neuron models with stochastic resonance

Stochastic resonance (SR) has been shown to enhance the signal-to-noise ratio and detection of low level signals in neurons. It is not yet clear how this effect of SR plays an important role in the information processing of neural networks. The objective of this article is to test the hypothesis that information transmission can be enhanced with SR when sub-threshold signals are applied to distal positions of the dendrites of hippocampal CA1 neuron models. In the computer simulation, random sub-threshold signals were presented repeatedly to a distal position of the main apical branch, while the homogeneous Poisson shot noise was applied as a background noise to the mid-point of a basal dendrite in the CA1 neuron model consisting of the soma with one sodium, one calcium, and five potassium channels. From spike firing times recorded at the soma, the mutual information and information rate of the spike trains were estimated. The simulation results obtained showed a typical resonance curve of SR, and that as the activity (intensity) of sub-threshold signals increased, the maximum value of the information rate tended to increased and eventually SR disappeared. It is concluded that SR can play a key role in enhancing the information transmission of sub-threshold stimuli applied to distal positions on the dendritic trees.     

Activity-dependent clustering of functional synaptic inputs on developing hippocampal dendrites

During brain development, before sensory systems become functional, neuronal networks spontaneously generate repetitive bursts of neuronal activity, which are typically synchronized across many neurons. Such activity patterns have been described on the level of networks and cells, but the fine-structure of inputs received by an individual neuron during spontaneous network activity has not been studied. Here, we used calcium imaging to record activity at many synapses of hippocampal pyramidal neurons simultaneously to establish the activity patterns in the majority of synapses of an entire cell. Analysis of the spatiotemporal patterns of synaptic activity revealed a fine-scale connectivity rule: neighboring synapses (<16?μm intersynapse distance) are more likely to be coactive than synapses that are farther away from each other. Blocking spiking activity or NMDA receptor activation revealed that the clustering of synaptic inputs required neuronal activity, demonstrating a role of developmentally expressed spontaneous activity for connecting neurons with subcellular precision.