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At least 181 records · Page 10Linked to original sources
PubMed2004

Chaotic itinerancy as a mechanism of irregular changes between synchronization and desynchronization in a neural network.

We investigate the dynamic character of a network of electrotonically coupled cells consisting of class I point neurons, in terms of a finite dimensional dynamical system. We classify a subclass of class I point neurons, called class I* point neurons. Based on this classification, we use a reduced Hindmarsh-Rose (H-R) model, which consists of two dynamical variables, to construct a network model consisting of electrotonically coupled H-R neurons. Although biologically simple, the system is sufficient to extract the essence of the complex dynamics, which the system may yield under certain physiological conditions. The network model produces a transitory behavior as well as a periodic motion and spatio-temporal chaos. The transitory dynamics that the network model exhibits is shown numerically to be chaotic itinerancy. The transitions appear between various metachronal waves and all-synchronization states. The network model shows that this transitory dynamics can be viewed as a chaotic switch between synchronized and desynchronized states. Despite the use of spatially discrete point neurons as basic elements of the network, the overall dynamics exhibits scale-free activity including various scales of spatio-temporal patterns.

Action Potentials↗
PubMed1993

A simple network model simulates hippocampal place fields: parametric analyses and physiological predictions.

Hippocampal place cells may be the computational units of a neuronal cognitive mapping system. A network model trained to compute locations from distal cues simulated the defining properties of hippocampal place cells (i.e., place-specific activation). The model produced units with detailed properties of place cells, including multiple subfields, "silent" and "noisy" cells, fields that persisted after cue removal, and groups of simulated fields that overlapped in multiple clusters. Quantitative variants of the model showed that different properties of the fields were influenced by the complexity of the visual input (the number of spatial cues), the available computational resources (the number of hidden units), and the output encoding used to represent location. The simulations provide a framework for testing relationships between place field properties, variations in spatial environments, and the integrity of the hippocampal system.

Animals↗
PubMed1989

Nonlinear SPICE models for physiologic systems.

Most biological systems are nonlinear but investigators interested in modeling them often make linear approximations to avoid performing tedious manual calculations. SPICE (Simulation Program with Integrated Circuit Emphasis, developed at the University of California, Berkeley, CA), an electrical circuit simulation program, is frequently used for creating and analyzing linear network models of physiologic and pathophysiologic processes. However, few investigators use the full capabilities of the program by modeling nonlinear elements. We developed six nonlinear SPICE elements, allowing simplified modeling of most commonly encountered physiologic processes. These are provided as subcircuits that can be easily incorporated into existing SPICE models. Included are voltage and current controlled nonlinear resistors, capacitors and inductors. In addition, we describe adders, multipliers, powers, inverse, and derivative functions.

Computer Simulation↗
PubMed1999

Changes in motor network expression related to moulting behaviour in lobster: role of moult-induced deep hypoxia

The well known rhythmically active pyloric neural network in intact and freely behaving lobsters Homarus gammarus was monitored prior to and following ecdysis. Despite long-lasting hormonal and metabolic alterations associated with this process, spontaneous pyloric network activity remained largely unaltered until the last 12-48 h before exuviation. At this time, the most notable change was a progressive lengthening of pyloric cycle period, which eventually attained 500-600 % of control values. It was only in the very last minutes before ecdysis that burst patterning became irregular and the otherwise strictly alternating motor sequence broke down. After the moult, coordinated rhythmicity was re-established within 10 min. Concomitant with these final changes in motor network expression at ecdysis was a drastic reduction in blood oxygen levels which led to a temporary near-anoxia. By imposing similarly deep hypoxic conditions both on intermoult animals and on the pyloric network in vitro, we mimicked to a large extent the moult-induced changes in pyloric network performance. Our data suggest that, despite major surrounding physiological perturbations, the pyloric network in vivo retains stable pattern-generating properties throughout much of the moulting process. Moreover, some of the most significant modifications in motor expression just prior to ecdysis can be related to a substantial reduction in oxygen levels in the blood.

Journal Article↗
PubMed2005

Angiogenesis--a self-adapting principle in hypoxia.

Normal tissue function depends on adequate supply of oxygen through blood vessels. Reduced oxygen supply (hypoxia) induces a variety of specific adaptation mechanisms in mammals that occur at the cellular, local and systemic level. These mechanisms are in part governed by the activation of the hypoxia-inducible transcription factors HIF-1 and HIF-2. Prolyl and asparaginyl hydroxylases as recently characterized oxygen sensors allow the regulation of HIFs that in turn modulate expression of hypoxically regulated genes such as VEGF. VEGF plays a key role in the formation of a functional and integrated vascular network required during physiological processes such as embryogenesis or female reproductive cycle as well as during a variety of pathological processes such tumor growth, wound healing, retinopathy and ischemic diseases (myocardial infarction, cerebral ischemia). However, other angiogenic factors, such as angiopoietins, PDGF, ephrins and erythropoietin are additionally needed to enable the formation of a functional vascular network. Many of these factors are activated during hypoxia although no HIF binding sites have yet been identified in the regulatory sequences of theses genes. Hypoxia-induced gene products that result in new vessel growth may be part of a self-regulated physiological protection mechanism preventing cell injury, especially under conditions of chronically reduced blood blow (chronic ischemia).

Animals↗
PubMed2003

Sugar and phytohormone response pathways: navigating a signalling network.

Many plant developmental, physiological and metabolic processes are regulated, at least in part, by nutrient availability. In particular, alterations in the availability of soluble sugars, such as glucose and sucrose, help regulate a diverse array of processes. Multiple lines of evidence indicate that many of these processes are also regulated in response to other signalling molecules, such as phytohormones. This review draws examples from a variety of plant systems, including bean, Arabidopsis, potato, and cereals. Five of the most interesting and best developed examples of processes regulated via 'interactions' or 'crosstalk' between sugars and phytohormones are described, including embryogenesis, seed germination, early seedling development, tuberization, and the regulation of alpha-amylase activity. The types of mechanisms by which different response pathways are known or postulated to interact are also described. These mechanisms include regulation of the metabolism and/or transport of a signalling molecule by a different response pathway. For example, sugars have been postulated to help regulate the synthesis, conjugation and/or transport of phytohormones, such as gibberellins and abscisic acid. Conversely, phytohormones, such as abscisic acid, gibberellins and cytokinins have been shown to help regulate sugar metabolism and/or transport. Similarly, sugars have been shown to regulate the expression of components of phytohormone-response pathways and phytohormones regulate the expression of some genes encoding possible components of sugar-response pathways. Examples of proteins and second messengers that appear to act in multiple response pathways are also described.

Arabidopsis↗
PubMed1990

Simulation study on dynamics transition in neuronal activity during sleep cycle by using asynchronous and symmetry neural network model.

We have found that single neuronal activities in different regions in the brain commonly exhibit the distinct dynamics transition during sleep-waking cycle in cats. Especially, power spectral densities of single neuronal activities change their profiles from the white to the 1/f along with sleep cycle from slow wave sleep (SWS) to paradoxical sleep (PS). Each region has different neural network structure and physiological function. This suggests a globally working mechanism may be underlying the dynamics transition we concern. Pharmacological studies have shown that a change in a wide-spread serotonergic input to these regions possibly causes the neuronal dynamics transition during sleep cycle. In this paper, based on these experimental results, an asynchronous and symmetry neural network model including inhibitory input, which represents the role of the serotonergic system, is utilized to examine the reality of our idea that the inhibitory input level varying during sleep cycle induce that transition. Simulation results show that the globally applied inhibitory input can control the dynamics of single neuronal state evolution in the artificial neural network: 1/f-like power spectral density profiles result under weak inhibition, which possibly corresponds to PS, and white profiles under strong inhibition, which possibly corresponds to SWS. An asynchronous neural network is known to change its state according to its energy function. The geometrical structure of network energy function is thought to vary along with the change in inhibitory level, which is expected to cause the dynamics transition of neuronal state evolution in the network model. These simulation results support the possibility that the serotonergic system is essential for the dynamics transition of single neuronal activities during sleep cycle.

Animals↗
PubMed2001

Stepping out of the box: information processing in the neural networks of the basal ganglia.

The Albin-DeLong 'box and arrow' model has long been the accepted standard model for the basal ganglia network. However, advances in physiological and anatomical research have enabled a more detailed neural network approach. Recent computational models hold that the basal ganglia use reinforcement signals and local competitive learning rules to reduce the dimensionality of sparse cortical information. These models predict a steady-state situation with diminished efficacy of lateral inhibition and low synchronization. In this framework, Parkinson's disease can be characterized as a persistent state of negative reinforcement, inefficient dimensionality reduction, and abnormally synchronized basal ganglia activity.

Animals↗
PubMed2001

Thymectomy-induced deterioration of learning and memory.

Age-associated immunodeficiency and cognitive deterioration are two predominant features of the aging process, but the mutual influences between them are not clear yet. Research on the neuroendocrine immunomodulation (NIM) network indicate reciprocal interactions between the neuroendocrine and the immune systems mediated by neurotransmitters, neuropeptides, hormones and cytokines, which form an integrated network to maintain normal physiological functions of the body. An imbalance in the NIM network is believed to accelerate the aging process, in which the thymus plays an important role. We recently discovered that thymectomy in mice not only reduces the immune response, but also deteriorates learning performances. Cytokines such as interleukin-1, interleukin-6 and tumor necrosis factor, and corticosterone affect the induction of hippocampal long-term potentiation, a synaptic model of memory. Clinical studies have demonstrated that Alzheimer's patients show disordered immune function in addition to cognitive deficit, and the brain lesions of Alzheimer's patients may be associated with abnormal immune reactions occurring in the brain. With these findings, it is speculated that the disordered immune function may induce an imbalance in the NIM network, which consequently influences central cognitive function.

Aging↗
PubMed2004

Uniform sampling of steady-state flux spaces: means to design experiments and to interpret enzymopathies.

Reconstruction of genome-scale metabolic networks is now possible using multiple different data types. Constraint-based modeling is an approach to interrogate capabilities of reconstructed networks by constraining possible cellular behavior through the imposition of physicochemical laws. As a result, a steady-state flux space is defined that contains all possible functional states of the network. Uniform random sampling of the steady-state flux space allows for the unbiased appraisal of its contents. Monte Carlo sampling of the steady-state flux space of the reconstructed human red blood cell metabolic network under simulated physiologic conditions yielded the following key results: 1), probability distributions for the values of individual metabolic fluxes showed a wide variety of shapes that could not have been inferred without computation; 2), pairwise correlation coefficients were calculated between all fluxes, determining the level of independence between the measurement of any two fluxes, and identifying highly correlated reaction sets; and 3), the network-wide effects of the change in one (or a few) variables (i.e., a simulated enzymopathy or fixing a flux range based on measurements) were computed. Mathematical models provide the most compact and informative representation of a hypothesis of how a cell works. Thus, understanding model predictions clearly is vital to driving forward the iterative model-building procedure that is at the heart of systems biology. Taken together, the Monte Carlo sampling procedure provides a broadening of the constraint-based approach by allowing for the unbiased and detailed assessment of the impact of the applied physicochemical constraints on a reconstructed network.

Animals↗
PubMed1996

A dynamic network simulation of the nematode tap withdrawal circuit: predictions concerning synaptic function using behavioral criteria.

The nematode tap withdrawal reflex demonstrates several forms of behavioral plasticity. Although the neural connectivity that supports this behavior is identified (Integration of mechanosensory stimuli in Caenorhabditis elegans, Wicks and Rankin, 1995, J Neurosci 15:2434-2444), the neurotransmitter phenotypes, and hence whether the synapses in the circuit are excitatory or inhibitory, remain uncharacterized. Here we use a novel strategy to predict the polarity configuration, i.e., the array of excitatory and inhibitory connections, of the nematode tap withdrawal circuit using an anatomically and physiologically justifiable dynamic network simulation of that circuit. The output of the modeled circuit was optimized to the behavior of animals, which possessed circuits altered by surgical ablation by exhaustively enumerating an array of synaptic signs that constituted the modeled circuit. All possible polarity configurations were then compared, and a statistical analysis was used to determine whether, for a given synaptic class, a particular polarity was associated with a good fit to behavioral data. The results from four related experiments were used to predict the polarities of seven of the nine cell classes of the tap withdrawal circuit. In addition, the model was used to assess possible roles for two novel mechanosensory integration neurons: DVA and PVD.

Animals↗
PubMedDate not supplied

Novel lists of 7 +/- 2 known items can be reliably stored in an oscillatory short-term memory network: interaction with long-term memory.

This paper proposes a model for the short-term memory (STM) of unique lists of known items, as, for instance, a phone number. We show that the ability to accurately store such lists in STM depends strongly on interaction with the preexisting long-term memory (LTM) for individual items (e.g., digits). We have examined this interaction in computer simulations of a network based on physiologically realistic membrane conductances, synaptic plasticity processes, and brain oscillations. In the model, seven STMs can be kept active, each in a different gamma-frequency subcycle of a theta-frequency oscillation. Each STM is maintained and timed by an activity-dependent ramping process. LTM is stored by the strength of synapses in recurrent collaterals. The presence of preexisting LTM for an item greatly enhances the ability of the network to store an item in STM. Without LTM, the precise timing required to keep cells firing within a given gamma subcycle cannot be maintained and STM is gradually degraded. With LTM, timing errors can be corrected and the accuracy and order of items is maintained. This attractor property of STM storage is remarkable because it occurs even though there is no LTM that identifies which items are on the list or their order. Multiple known items can be stored in STM, even though their representation is overlapping. However, multiple, identical memories cannot be stored in STM, consistent with the psychophysical demonstration of repetition blindness. Our results indicate that meaningful computation (memory completion) can occur in the millisecond range during an individual gamma cycle.

Computer Simulation↗
PubMed2006

The role of feedback in shaping the extra-classical receptive field of cortical neurons: a recurrent network model.

The responses of neurons in sensory cortices are affected by the spatial context within which stimuli are embedded. In the primary visual cortex (V1), orientation-selective responses to stimuli in the receptive field (RF) center are suppressed by similarly oriented stimuli in the RF surround. Surround suppression, a likely neural correlate of perceptual figure-ground segregation, is traditionally thought to be generated within V1 by long-range horizontal connections. Recently however, it has been shown that these connections are too short and too slow to mediate fast suppression from distant regions of the RF surround. We use an anatomically and physiologically constrained recurrent network model of macaque V1 to show how interareal feedback connections, which are faster and longer-range than horizontal connections, can generate "far" surround suppression. We provide a novel solution to the puzzle of how surround suppression can arise from excitatory feedback axons contacting predominantly excitatory neurons in V1. The basic mechanism involves divergent feedback connections from the far surround targeting pyramidal neurons sending monosynaptic horizontal connections to excitatory and inhibitory neurons in the RF center. One of several predictions of our model is that the "suppressive far surround" is not always suppressive, but can facilitate the response of the RF center, depending on the amount of excitatory drive to the local inhibitors. Our model provides a general mechanism of how top-down feedback signals directly contribute to generating cortical neuron responses to simple sensory stimuli.

Action Potentials↗
PubMed2005

Semi-synthetic mammalian gene regulatory networks.

In recent years gene network engineers have celebrated spectacular success: Genetic devices such as epigenetic toggle switches and oscillating networks have been engineered and pioneered a new ever-increasing scientific community known as synthetic biology. While synthetic biology was until recently restricted to network assembly and testing in prokaryotes, decisive advances have been achieved in eukaryotic systems based on current availability of different human-compatible transgene control technologies. Most prominent examples include the epigenetic gene network enabling metastable fully inheritable transgene expression states in mice, artificial regulatory cascades managing multi-level expression control and Boolean-type BioLogic gates supporting near-digital expression readout. The majority of transgene control networks available to date are fully synthetic and integrate artificial extracellular signals in a desired host metabolism-independent manner. Yet, in order to develop their full anticipated therapeutic potential, synthetic transgene control circuits need to be well interconnected with the host cell's regulatory networks in order to enable physiologic control of prosthetic molecular expression units. We have designed three semi-synthetic transcription control networks able to integrate physiologic oxygen levels and artificial antibiotic signals to produce expression readout with NOT IF or NOR-type Boolean logic or discrete multi-level control of several intracellular and secreted model product proteins. Subtle differences in the regulation performance of the endogenous oxygen-sensing system in CHO-K1 and human HT-1080 switched the semi-synthetic network's readout from a classic four-level (high, medium, low, basal) regulatory cascade to a network enabling six discrete transgene expression levels. These findings are in excellent correspondence with a mathematical model. Prosthetic networks, precisely embedded in host regulatory networks and co-fine-tuned by physiologic as well as pharmacologic input signals, will foster future advances in gene therapy and tissue engineering.

Animals↗
PubMedDate not supplied

Wave transmission and input impedance of a model of skeletal muscle microvasculature.

We analyzed wave transmission properties and input impedance of a microvascular network model. The model, derived from rat spinotrapezius muscle and previously described and validated by other investigators for steady pressure-flow relations, was expanded to include pulsatile phenomena. Microvessels are considered purely elastic, with compliances a function of vessel type; viscous dissipation follows Poiseuille's law. Linear and nonlinear results are presented. In the nonlinear case, shear rate-dependent viscosity of blood and transmural pressure-dependent vascular diameters were calculated and small signal perturbations were imposed around several working points. We investigated effects on input impedance of physiological variability of network parameters and structure: distribution of capillary diameters, capillary segment length, and presence or absence of cross-connecting capillaries. Results show that although wave transmission properties are complex, input impedance is simple. Apparent wave speeds differ substantially from phase velocities and change markedly from branch to branch; pressure and flow waves appear to travel at different speeds. These features result from the mesh-like structure of the network and the prominence of reflection at branchpoints. Input impedance displays a similar form under all conditions: Magnitude is a monotonically decreasing function of frequency, and phase decreases from 0 to approximately -45 degrees. Consideration of the characteristic impedance of a microvessel leads to modification of the three-element Windkessel as a reduced model of the observed input impedance.

Animals↗
PubMed1991

Induction of anti-idiotypic T cells through a network mechanism.

BALB/c mouse T cells that recognized the idiotype expressed on M104E(mu, lambda 1) were induced by immunization with Dextran B-1355. T cells derived from mice immunized with 1 mg of Dextran B-1355 showed a marked proliferative response against M104E, whereas T cells from mice immunized with Ficoll or smaller amounts of Dextran B-1355 did not. BCL1Id, which had an identical isotype, did not induce proliferation of T cells. The T cell proliferative response against the idiotype on M104E required macrophages as antigen-presenting cells. The proliferative response was inhibited when antigen-presenting cells were treated with NH4Cl or chloroquine, which are antigen-processing inhibitors. These results indicate that anti-idiotypic T cells which recognized processed idiotopes could be induced physiologically through a network mechanism.

Animals↗