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PubMedDate not supplied

Astroglia and glutamate in physiology and pathology: aspects on glutamate transport, glutamate-induced cell swelling and gap-junction communication.

Astroglia have the capacity to monitor extracellular glutamate (Glu) and maintain it at low levels, metabolize Glu, or release it back into the extracellular space. Glu can induce an increase in astroglial cell volume with a resulting decrease of the extracellular space, and thereby alter the concentration of extracellular substances. Many lines of evidence show that K(+) can be buffered within the astroglial gap-junction-coupled network, and recent results show that gap junctions are permeable for Glu. All these events occur dynamically: the astroglial network has the capacity to interfere actively with neurotransmission, thereby contributing to a high signal-to-noise ratio for the Glu transmission. High-quality neuronal messages during normal physiology can then be maintained. With the same mechanisms, astroglia might exert a neuroprotective function in situations of moderately increased extracellular Glu concentrations, i.e., corresponding to conditions of pathological hyper-excitability, or corresponding to early stages of an acute brain injury. If the astroglial functions are failing, neuronal dysfunction can be reinforced.

Animals↗
PubMed2005

The selection of family planning discussion partners in Nepal.

There is growing evidence that the information women receive about family planning from their social network is influential in their decisions to use a contraceptive method. Less is known, however, regarding the role individuals play in constructing their social network and, thereby, determining the nature of its influence. This study examined the criteria women use to select their family planning discussion partners and the individual-level factors that promote the addition of a contraceptive user to one's discussion network. Sociometric data were collected in November 1997 and February 1999 from all currently married women aged 15 to 49 years in three villages of Dang District in the Mid-Western Region of Nepal (panel N = 281). Preference for women from one's ethnic group and the strategic selection of contraceptive users was observed. Contraceptive use and attitudes toward family planning were both positively associated with the addition of a contraceptive user to one's discussion network, suggesting that women seek contraceptive users to confirm their existing beliefs and behaviors. Understanding the dynamics of social network formation can assist programs to better utilize the behavior change potential of peer networks.

Adolescent↗
PubMed2006

Topological filters and high-pass/low-pass devices for solitons in inhomogeneous networks.

We show that, by inserting suitable finite networks at a site of a chain, it is possible to realize filters and high-pass/low-pass devices for solitons propagating along the chain. The results are presented in the framework of coupled optical waveguides; possible applications to different contexts, such as photonic lattices and Bose-Einstein condensates in optical networks are also discussed. Our results provide a first step in the control of the soliton dynamics through the network topology.

Journal Article↗
PubMed2006

Functional screening of traditional antidepressants with primary cortical neuronal networks grown on multielectrode neurochips.

We optimized the novel technique of multielectrode neurochip recordings for the rapid and efficient screening of neuroactivity. Changes in the spontaneous activity of cultured networks of primary cortical neurons were quantified to evaluate the action of drugs on the firing dynamics of complex network activity. The multiparametric assessment of electrical activity changes caused by psychoactive herbal extracts from Hypericum, Passiflora and Valeriana, and various combinations thereof revealed a receptor-specific and concentration-dependent inhibition of the firing patterns. The spike and burst rates showed significant substance-dependent effects and significant differences in potency. The effects of specific receptor blockades on the inhibitory responses provided evidence that the herbal extracts act on gamma-amino butyric acid (GABA) and serotonin (5-HT) receptors, which are recognized targets of pharmacological antidepressant treatment. A biphasic effect, serotonergic stimulation of activity at low concentrations that is overridden by GABAergic inhibition at higher concentrations, is apparent with Hypericum alone and the triple combination of the extracts. The more potent neuroactivity of the triple combination compared to Hypericum alone and the additive effect of Passiflora and Valeriana suggest a synergy between constituent herbal extracts. The extracts and their combinations affected the set of derived activity parameters in a concomitant manner suggesting that all three constituent extracts and their combinations have largely similar modes of action. This study also demonstrates the sensitivity, selectivity and robustness of neurochip recordings for high content screening of complex mixtures of neuroactive substances and for providing multiparametric information on neuronal activity changes to assess the therapeutic potential of psychoactive substances.

Action Potentials↗
PubMed1996

Binary-oscillator networks: bridging a gap between experimental and abstract modeling of neural networks.

This paper proposes a simplified oscillator model, called binary-oscillator, and develops a class of neural network models having binary-oscillators as basic units. The binary-oscillator has a binary dynamic variable v = +/- 1 modeling the "membrane potential" of a neuron, and due to the presence of a "slow current" (as in a classical relaxation-oscillator) it can oscillate between two states. The purpose of the simplification is to enable abstract algorithmic study on the dynamics of oscillator networks. A binary-oscillator network is formally analogous to a system of stochastic binary spins (atomic magnets) in statistical mechanics.

Algorithms↗
PubMed2004

Efficiency and reliability of epidemic data dissemination in complex networks.

We study the dynamics of epidemic spreading processes aimed at spontaneous dissemination of information updates in populations with complex connectivity patterns. The influence of the topological structure of the network in these processes is studied by analyzing the behavior of several global parameters, such as reliability, efficiency, and load. Large-scale numerical simulations of update-spreading processes show that while networks with homogeneous connectivity patterns permit a higher reliability, scale-free topologies allow for a better efficiency.

Journal Article↗
PubMed2024

Seasonal hydrological dynamics affected the diversity and assembly process of the antibiotic resistome in a canal network.

The significant threat of antibiotic resistance genes (ARGs) to aquatic environments health has been widely acknowledged. To date, several studies have focused on the distribution and diversity of ARGs in a single river while their profiles in complex river networks are largely known. Here, the spatiotemporal dynamics of ARG profiles in a canal network were examined using high-throughput quantitative PCR, and the underlying assembly processes and its main environmental influencing factors were elucidated using multiple statistical analyses. The results demonstrated significant seasonal dynamics with greater richness and relative abundance of ARGs observed during the dry season compared to the wet season. ARG profiles exhibited a pronounced distance-decay pattern in the dry season, whereas no such pattern was evident in the wet season. Null model analysis indicated that deterministic processes, in contrast to stochastic processes, had a significant impact on shaping the ARG profiles. Furthermore, it was found that Firmicutes and pH emerged as the foremost factors influencing these profiles. This study enhanced our comprehension of the variations in ARG profiles within canal networks, which may contribute to the design of efficient management approaches aimed at restraining the propagation of ARGs.

Seasons↗
PubMed2003

Dynamic critical behavior of the XY model in small-world networks.

The critical behavior of the XY model on small-world network is investigated by means of dynamic Monte Carlo simulations. We use the short-time relaxation scheme, i.e., the critical behavior is studied from the nonequilibrium relaxation to equilibrium. Static and dynamic critical exponents are extracted through the use of the dynamic finite-size scaling analysis. It is concluded that the dynamic universality class at the transition is of the mean-field nature. We also confirm numerically that the value of dynamic critical exponent is independent of the rewiring probability P for P greater, similar 0.03.

Journal Article↗
PubMed2004

Dynamical scaling behavior of percolation clusters in scale-free networks.

In this work we investigate the spectra of Laplacian matrices that determine many dynamic properties of scale-free networks below and at the percolation threshold. We use a replica formalism to develop analytically, based on an integral equation, a systematic way to determine the ensemble averaged eigenvalue spectrum for a general type of treelike networks. Close to the percolation threshold we find characteristic scaling functions for the density of states rho(lambda) of scale-free networks. rho(lambda) shows characteristic power laws rho (lambda) approximately lambda (alpha(1) ) or rho (lambda) approximately lambda (d(2) ) for small lambda, where alpha(1) holds below and alpha(2) at the percolation threshold. In the range where the spectra are accessible from a numerical diagonalization procedure the two methods lead to very similar results.

Journal Article↗
PubMed1998

Nonuniformity in the linear network model of the oculomotor integrator produces approximately fractional-order dynamics and more realistic neuron behavior.

The oculomotor integrator is a network that is composed of neurons in the medial vestibular nuclei and nuclei prepositus hypoglossi in the brainstem. Those neurons act approximately as fractional integrators of various orders, converting eye velocity commands into signals that are intermediate between velocity and position. The oculomotor integrator has been modeled as a network of linear neural elements, the time constants of which are lengthened by positive feedback through reciprocal inhibition. In this model, in which each neuron reciprocally inhibits its neighbors with the same Gaussian profile, all model neurons behave as identical, first-order, low-pass filters with dynamics that do not match the variable, approximately fractional-order dynamics of the neurons that compose the actual oculomotor integrator. Fractional-order integrators can be approximated by weighted sums of first-order, low-pass filters with diverse, broadly distributed time constants. Dynamic systems analysis reveals that the model integrator indeed has many broadly distributed time constants. However, only one time constant is expressed in the model due to the uniformity of its network connections. If the model network is made nonuniform by removing the reciprocal connections to and from a small number of neurons, then many more time constants are expressed. The dynamics of the neurons in the nonuniform network model are variable, approximately fractional-order, and resemble those of the neurons that compose the actual oculomotor integrator. Completely removing the connections to and from a neuron is equivalent to eliminating it, an operation done previously to demonstrate the robustness of the integrator network model. Ironically, the resulting nonuniform network model, previously supposed to represent a pathological integrator, may in fact represent a healthy integrator containing neurons with realistically variable, approximately fractional-order dynamics.

Animals↗
PubMed1993

Acetylcholine and memory.

Acetylcholine may set the dynamics of cortical networks to those appropriate for learning of new information, while decreased cholinergic modulation may set the appropriate dynamics for recall. In slice preparations of the olfactory cortex, acetylcholine selectively suppresses intrinsic but not afferent fiber synaptic transmission, while decreasing the adaptation of pyramidal cells. In biologically realistic models of this region, the selective suppression of synaptic transmission prevents recall of previously learned memories from interfering with the learning of new memories, while the decrease in adaptation enhances the response to afferent input and the modification of synapses. This theoretical framework may serve to guide future studies linking neuromodulators to cortical memory function.

Acetylcholine↗
PubMed1991

Transient expression of mouse hair keratins in transfected HeLa cells: interactions between "hard" and "soft" keratins.

Although it has been shown previously that an acidic (type I) "soft" keratin can interact with many basic (type II) "soft" keratins to form 10-nm intermediate filaments, it has been unclear whether "soft" keratins are compatible with the "hard" keratins typically found in hair and nail. To address this issue and to generate more structural information about hard keratins, we have isolated and sequenced a cDNA clone that encodes a mouse hair basic keratin (b4). Our sequence data revealed new information regarding the structural conservation of hard keratins as a group, being significantly different from soft keratins. Using expression vectors containing appropriate cDNA inserts, we studied the expression of this basic (b4) as well as an acidic (a1) mouse hair keratin in HeLa cells. The expression of these alien hair keratins in the transfected cells was surveyed using a panel of monoclonal and polyclonal antibodies. Our results indicated that the basic and acidic hair keratin readily incorporated into the existing endogenous soft keratin network of HeLa cells. Overproduction of hair keratin, however, occasionally led to the formation of cytoplasmic aggregates containing both hard and soft keratins. These data suggest that although small amounts of newly synthesized hair keratins can incorporate into the "scaffolding" of the preformed soft keratin filament network, possibly through dynamic subunit exchange, overproduction of hard keratins can lead to the partial collapse of the soft keratin network. These observations, along with the deduced amino acid sequence data, support and extend the concept that hard and soft keratins, although closely related, are divergent enough to justify their being divided into two separate subgroups.

Animals↗
PubMed2006

Trapped water molecules are essential to structural dynamics and function of a ribozyme.

Ribozymes are catalytically competent examples of highly structured noncoding RNAs, which are ubiquitous in the processing and regulation of genetic information. Combining explicit-solvent molecular dynamics simulation and single molecule fluorescence spectroscopy approaches, we find that a ribozyme from a subviral plant pathogen exhibits a coupled hydrogen bonding network that communicates dynamic structural rearrangements throughout the catalytic core in response to site-specific chemical modification. Trapped long-residency water molecules are critical for this network and only occasionally exchange with bulk solvent as they pass through a breathing interdomain base stack. These highly structured water molecules line up in a string that may potentially also be involved in specific base catalysis. Our observations suggest important, still underappreciated roles for specifically bound water molecules in the structural dynamics and function of noncoding RNAs.

Base Pairing↗
PubMed2004

Dynamical optimal training for interval type-2 fuzzy neural network (T2FNN).

Type-2 fuzzy logic system (FLS) cascaded with neural network, type-2 fuzzy neural network (T2FNN), is presented in this paper to handle uncertainty with dynamical optimal learning. A T2FNN consists of a type-2 fuzzy linguistic process as the antecedent part, and the two-layer interval neural network as the consequent part. A general T2FNN is computational-intensive due to the complexity of type 2 to type 1 reduction. Therefore, the interval T2FNN is adopted in this paper to simplify the computational process. The dynamical optimal training algorithm for the two-layer consequent part of interval T2FNN is first developed. The stable and optimal left and right learning rates for the interval neural network, in the sense of maximum error reduction, can be derived for each iteration in the training process (back propagation). It can also be shown both learning rates cannot be both negative. Further, due to variation of the initial MF parameters, i.e., the spread level of uncertain means or deviations of interval Gaussian MFs, the performance of back propagation training process may be affected. To achieve better total performance, a genetic algorithm (GA) is designed to search optimal spread rate for uncertain means and optimal learning for the antecedent part. Several examples are fully illustrated. Excellent results are obtained for the truck backing-up control and the identification of nonlinear system, which yield more improved performance than those using type-1 FNN.

Algorithms↗
PubMedDate not supplied

Effects of transmission delays and noise in recurrent excitatory neural networks.

Random perturbations, referred to as noise, are omnipresent in the nervous system. We investigate how noise modifies the dynamics of the neural networks according to the delay. In this report, we examine the effect of transmission delay on both the dynamics of a single neuron receiving a recurrent excitation and the dynamics of fully interconnected excitatory networks. In the case of the single neuron with a recurrent connection, depending on the value of the delay, the discharge pattern changes from regular to multiplets. More complicated patterns appears when noise is added, and depends on both the delay and the noise intensity, but classification can be described. In certain conditions, noise reduces the synchronization, whereas in others it increases the regularity of the network activity. Finally, the same network codes the input amplitude either using mean activity amplitude coding when short delays exist, and using frequency modulation when long delays exist.

Animals↗
PubMed1996

Representation of spatial orientation by the intrinsic dynamics of the head-direction cell ensemble: a theory.

The head-direction (HD) cells found in the limbic system in freely mov ing rats represent the instantaneous head direction of the animal in the horizontal plane regardless of the location of the animal. The internal direction represented by these cells uses both self-motion information for inertially based updating and familiar visual landmarks for calibration. Here, a model of the dynamics of the HD cell ensemble is presented. The stability of a localized static activity profile in the network and a dynamic shift mechanism are explained naturally by synaptic weight distribution components with even and odd symmetry, respectively. Under symmetric weights or symmetric reciprocal connections, a stable activity profile close to the known directional tuning curves will emerge. By adding a slight asymmetry to the weights, the activity profile will shift continuously without disturbances to its shape, and the shift speed can be controlled accurately by the strength of the odd-weight component. The generic formulation of the shift mechanism is determined uniquely within the current theoretical framework. The attractor dynamics of the system ensures modality-independence of the internal representation and facilitates the correction for cumulative error by the putative local-view detectors. The model offers a specific one-dimensional example of a computational mechanism in which a truly world-centered representation can be derived from observer-centered sensory inputs by integrating self-motion information.

Animals↗
PubMed2005

Topology of biological networks and reliability of information processing.

Survival of living cells and organisms is largely based on highly reliable function of their regulatory networks. However, the elements of biological networks, e.g., regulatory genes in genetic networks or neurons in the nervous system, are far from being reliable dynamical elements. How can networks of unreliable elements perform reliably? We here address this question in networks of autonomous noisy elements with fluctuating timing and study the conditions for an overall system behavior being reproducible in the presence of such noise. We find a clear distinction between reliable and unreliable dynamical attractors. In the reliable case, synchrony is sustained in the network, whereas in the unreliable scenario, fluctuating timing of single elements can gradually desynchronize the system, leading to nonreproducible behavior. The likelihood of reliable dynamical attractors strongly depends on the underlying topology of a network. Comparing with the observed architectures of gene regulation networks, we find that those 3-node subgraphs that allow for reliable dynamics are also those that are more abundant in nature, suggesting that specific topologies of regulatory networks may provide a selective advantage in evolution through their resistance against noise.

Biological Evolution↗
PubMed2003

AMPA receptors regulate dynamic equilibrium of presynaptic terminals in mature hippocampal networks.

The formation and disassembly of synapses in mature neuropil could provide a substrate to encode experience in the brain. Although there is evidence for postsynaptic spine dynamics in mature systems, contributions to circuit rearrangements by presynaptic terminals have remained unclear. We used hippocampal slice cultures from mice expressing spectral variants of green fluorescent protein (GFP) that are targeted to the membrane and/or synaptic vesicles in neuronal subsets to image identified presynaptic terminals. In mature tissues with no net change in synapse numbers, subpopulations of presynaptic terminals appeared and disappeared within 1-3 days. The three terminal types established by mossy fibers had distinct properties. High-frequency stimulation increased the fraction of dynamic terminals for 1-2 days, a process mediated by activation of AMPA receptors, protein kinase A (PKA) and protein synthesis. Thus, synaptic activity can make stable presynaptic terminals become dynamic, providing a candidate mechanism to convert experience into changes in network connectivity.

Animals↗