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At least 1,747 records · Page 97Linked to original sources
PubMed2000

Modelling the growth of Listeria monocytogenes in dynamic conditions.

A recurrent neural network for the prediction of Listeria monocytogenes growth under pH and a(w) variable conditions was developed. The use of this model offered the possibility to take into account the consequences of the variations of the factors on L. monocytogenes growth. The effects of solutions, such as NaCl, acetic acid and NaOH, and their interactions on the response of L. monocytogenes cells were studied. Furthermore, the results showed the capacity of the recurrent neural network to predict growths carried out in different experimental conditions without using those used for its elaboration.

Animals↗
PubMed2005

Simultaneous perturbation learning rule for recurrent neural networks and its FPGA implementation.

Recurrent neural networks have interesting properties and can handle dynamic information processing unlike ordinary feedforward neural networks. However, they are generally difficult to use because there is no convenient learning scheme. In this paper, a recursive learning scheme for recurrent neural networks using the simultaneous perturbation method is described. The detailed procedure of the scheme for recurrent neural networks is explained. Unlike ordinary correlation learning, this method is applicable to analog learning and the learning of oscillatory solutions of recurrent neural networks. Moreover, as a typical example of recurrent neural networks, we consider the hardware implementation of Hopfield neural networks using a field-programmable gate array (FPGA). The details of the implementation are described. Two examples of a Hopfield neural network system for analog and oscillatory targets are shown. These results show that the learning scheme proposed here is feasible.

Algorithms↗
PubMed2004

An improved transiently chaotic neural network for the maximum independent set problem.

By analyzing the dynamic behaviors of the transiently chaotic neural network and greedy heuristic for the maximum independent set (MIS) problem, we present an improved transiently chaotic neural network for the MIS problem in this paper. Extensive simulations are performed and the results show that this proposed transiently chaotic neural network can yield better solutions to p-random graphs than other existing algorithms. The efficiency of the new model is also confirmed by the results on the complement graphs of some DIMACS clique instances in the second DIMACS challenge. Moreover, the improved model uses fewer steps to converge to stable state in comparison with the original transiently chaotic neural network.

Algorithms↗
PubMed1980

Distributed processing by visual interneurons of crayfish brain. II. Network organization and stimulus modulation of synaptic efficacy.

1. Multiple interactions were examined between five or six visual neurons simultaneously monitored in the circumesophageal connective. 2. A single neuron can make divergent connections to at least five other visual interneurons. 3. Conversely, a single cell may receive convergent inputs from up to four visual interneurons. 4. The convergent interactions are sufficiently intense so that 80--90% of a postsynaptic cell's visual activity can be attributed to observed network interactions. 5. Connectivity diagrams suggest that the descending interneurons, which arise in the visual neuropil of the brain, are organized into three interconnected layers: a) neurons that receive input from the optic nerve and project to other visual interneurons, b) neurons that both receive input and project to other descending interneurons in the brain--these cells exhibit a preponderance of reciprocal interactions, c) neurons that receive input from both the first and second network layers and project exclusively to the more caudal ganglia of the ventral nerve cord. 6. The network is systematically organized with respect to visual and nonvisual responsiveness. The cells of the first layer exhibit the strongest visual responses. The cells of the third layer exhibit spontaneous activity and the strongest tactile and/or proprioceptive responses. 7. The intensity of the network interactions is under stimulus control. The synaptic efficacy of a presynaptic spike can vary by over 100-fold as a consequence of stimulus presentation and/or location. The expressed organization of the network thus exhibits a dynamic, stimulus-dependent, plasticity. 8. The results indicate that the descending visual interneurons of the brain rather than forming a parallel tract actually constitute a complex distributed network. Furthermore, the results indicate the feasibility of population neural coding based on stimulus-dependent inpulse coordination in an array of neurons.

Animals↗
PubMed2005

Towards a proteome-scale map of the human protein-protein interaction network.

Systematic mapping of protein-protein interactions, or 'interactome' mapping, was initiated in model organisms, starting with defined biological processes and then expanding to the scale of the proteome. Although far from complete, such maps have revealed global topological and dynamic features of interactome networks that relate to known biological properties, suggesting that a human interactome map will provide insight into development and disease mechanisms at a systems level. Here we describe an initial version of a proteome-scale map of human binary protein-protein interactions. Using a stringent, high-throughput yeast two-hybrid system, we tested pairwise interactions among the products of approximately 8,100 currently available Gateway-cloned open reading frames and detected approximately 2,800 interactions. This data set, called CCSB-HI1, has a verification rate of approximately 78% as revealed by an independent co-affinity purification assay, and correlates significantly with other biological attributes. The CCSB-HI1 data set increases by approximately 70% the set of available binary interactions within the tested space and reveals more than 300 new connections to over 100 disease-associated proteins. This work represents an important step towards a systematic and comprehensive human interactome project.

Cloning, Molecular↗
PubMed2001

Emergence of a dominant unit in a network of chaotic units with a delayed connection change.

We study here a model of globally coupled units with adaptive interaction weights that has a delay in the updating rule. Simulations show that the model with such delayed synaptic change exhibits dynamical self organization of network structure. With suitably chosen parameters, "dominant" unit emerges spontaneously, in the sense that the connections from such a unit to almost all of the other units are especially strengthened. Such weight structure facilitates the coherent activity among units.

Journal Article↗
PubMed2004

Model of neural circuit comparing static and adaptive synapses.

Replacing static synapses with the adaptive ones can affect the behaviour of neuronal network. Several network setups containing synapses modelled by alpha-functions, called here static synapses, are compared with corresponding setups containing more complex, dynamic synapses. The dynamic synapses have four state variables and the time constants are of different orders of magnitude. Response of the network to modelled stimulations was studied together with effects of neuronal interconnectivity, the axonal delays and the proportion of excitatory and inhibitory neurons on the network output. Dependency of synaptic strength on synaptic activity was also studied. We found that dynamic synapses enable network to exhibit broader spectrum of responses to given input and they make the network more sensitive to changes of network parameters. As a step towards memory modelling, retention of input sequences in the network with static and dynamic synapses was studied. The network with dynamic synapses was found to be more flexible in reducing the interference between adjacent inputs in comparison to the network containing static synapses.

Humans↗
PubMedDate not supplied

Microcomputer simulation as an aid in analyzing data and teaching the principles of glomerular dynamics.

This report describes a simple program, written in BASIC language, that closely emulates a previously published network thermodynamic model of glomerular dynamics. While the latter requires the SPICE 2 simulation program and a mainframe computer for its execution, the present program operates on any IBM-compatible microcomputer. It has equal utility as an aid in the interpretation of laboratory studies of glomerular dynamics and as a tool for teaching the intricacies of the control of glomerular function. The program is available in 'user friendly' format that obviates the need for any expertise in the use of computers.

Computer Simulation↗
PubMed2001

Bose-Einstein condensation in complex networks.

The evolution of many complex systems, including the World Wide Web, business, and citation networks, is encoded in the dynamic web describing the interactions between the system's constituents. Despite their irreversible and nonequilibrium nature these networks follow Bose statistics and can undergo Bose-Einstein condensation. Addressing the dynamical properties of these nonequilibrium systems within the framework of equilibrium quantum gases predicts that the "first-mover-advantage," "fit-get-rich," and "winner-takes-all" phenomena observed in competitive systems are thermodynamically distinct phases of the underlying evolving networks.

Journal Article↗
PubMedDate not supplied

"Spiritlinking": a key to dynamic change. Fostering chaos enables leaders to form the networks and unity needed to fulfill their mission.

To contend with the anxiety and chaos inherent in rapid change, leaders can turn to ¿spiritlinking,¿ the deliberate and untiring act of building the high-energy networks where new ideas are born and new ways of delivering service take form. Spiritlinking leaders are able to envision and promote the paradox of disequilibrium. They seek truth, pushing the organization into a condition of imbalance where staid settledness gives way to new paradigms founded on constant transformation. Spiritlinking leaders are not bound by organizational charts. They have discovered that the greater the participation in the organization, the greater the access to vast amounts of information and insight, which will ultimately lead to profound transformation. Spiritlinking is directed toward networking, community forming, and coalition building, often across chasms of ideological differences. Leaders must have the skill to manage the vision, which entails generating courage and belief through the cloudiness of ambiguity. Spiritlinking leaders must also create synergy from conflict, gathering strong-minded, self-assured persons who perhaps hold vastly differing perspectives, yet, in working for the common good, arrive at surprising, wonderful decisions. Finally, spiritlinking leaders assist the organization in working through resistance by identifying the mode, motive, and meaning of the resistant behavior and determining the action the organization is willing to take to move beyond it.

Canada↗
PubMed2006

Consistent dynamics suggests tight regulation of biophysical parameters in a small network of bursting neurons.

The neuronal firing patterns in the pyloric network of crustaceans are remarkably consistent among animals. Although this characteristic of the pyloric network is well-known, the biophysical mechanisms underlying the regulation of the systems output are receiving renewed attention. Computer simulations of the pyloric network recently demonstrated that consistent motor output can be achieved from neurons with disparate biophysical parameters among animals. Here we address this hypothesis by pharmacologically manipulating the pyloric network and analyzing the emerging voltage oscillations and firing patterns. Our results show that the pyloric network of the lobster stomatogastric ganglion maintains consistent and regular firing patterns even when entire populations of specific voltage-gated channels and synaptic receptors are blocked. The variations of temporal parameters used to characterize the burst patterns of the neurons as well as their intraburst spike dynamics do not display statistically significant increase after blocking the transient K-currents (with 4-aminopyridine), the glutamatergic inhibitory synapses (with picrotoxin), or the cholinergic synapses (with atropine) in pyloric networks from different animals. These data suggest that in this very compact circuit, the biophysical parameters are cell-specific and tightly regulated.

4-Aminopyridine↗
PubMed1979

Spatial firing patterns of auditory neuron network modelling by computer simulation.

This communication examines, in digital computer simulated network, input signals and response patterns established at excitatory neurons' level i.e. the membrane potential of neuron soma. It is restricted to spatial patterns of the auditory neuron networks and time factor for nervous conduction and transmission is neglected compared with long maintained membrane potentials of neuron somas. The model analyzes the change in the spatial patterns of the membrane potential in the two dimensional networks of the auditory system. In order to evaluate the contribution of the various parameters, it is started that the simplest model has only one parameter, lateral inhibition. The other parameters are then added, one at a time, to successive models. The lateral inhibition is a necessary condition in the auditory nervous system if any sharpening of the response areas in the single neurons is to occur. A necessary condition for the validity of the model is that is should be applicable to the other senses such as vision and chemical patterns, taste. The threshold feature of auditory neurons aids in producing a sharpening in the neuron of the auditory relay nuclei. It does this clipping the spatial response patterns in one dimensional arrays of excitatory neurons. Recurrent inhibition seems a necessary condition in the sensory nervous system that any kinds of input signals are to be preserved over a wide range of stimulus intensity. In other words, this network has a wide dynamic range against any kinds of input signals. A simple self-recurrent negative feedback does not contribute to the sharpening, but more complex socalled averaged type does. A neuron network is capable of responding stably to stimuli with a wide range of intensity and with any kind of spatial patterns if there is a simple negative feedback mechanism. When there is no negative feedback, input signals soon disappear or saturate in the neuron network. Therefore, recurrent inhibition is the most important mechanism. Spontaneous activity appears to aid in the sharpening by providing a kind of contrast, that is by reducting the amount of activity in neurons adjacent to the excitatory area. Moreover, the effect of spontaneous activity in the model seems to make repples around the excitatory area and suggests that an introduction of activity at any stage of the networks, from whatever source for example reticulum formation and thalamus, might appreciably alter the response patterns at subsequent neuron network. This suggests that the mechanism of the consciousness that might be controlled by the thalamus and or reticular formation. These two dimensional neuron networks may be expanded to three dimensional neuron networks. The former might simulate the auditory nervous system while the latter might simulate the visual system.

Animals↗
PubMed2005

Determinants of inspiratory activity.

In vitro and in vivo studies have identified the pre-Bötzinger complex as an important kernel for the generation of inspiratory activity. The mechanisms underlying inspiratory rhythm generation involve pacemaker as well as synaptic mechanisms. In slice preparations, blockade of pacemaker properties with blockers for the persistent Na+ current, and the Ca2+-activated inward cationic current, abolishes respiratory activity. Here we show that blockade of the persistent Na+ current alone is sufficient to abolish respiratory activity in the in situ preparation. Although pacemaker neurons may be critical for establishing the basic respiratory rhythm, their rhythmic output is modulated by many elements of the respiratory network. For example, levels of synaptic inhibition control whether they burst or not, and endogenously released neuromodulators, such as serotonin and substance P modulate their intrinsic membrane currents. We hypothesize that the balance between synaptic and intrinsic pacemaker properties in the respiratory network is plastic, and that alterations of this balance may lead to dynamic reconfigurations of the respiratory network, which ultimately give rise to different activity patterns.

Animals↗
PubMed2003

Random Boolean network models and the yeast transcriptional network.

The recently measured yeast transcriptional network is analyzed in terms of simplified Boolean network models, with the aim of determining feasible rule structures, given the requirement of stable solutions of the generated Boolean networks. We find that, for ensembles of generated models, those with canalyzing Boolean rules are remarkably stable, whereas those with random Boolean rules are only marginally stable. Furthermore, substantial parts of the generated networks are frozen, in the sense that they reach the same state, regardless of initial state. Thus, our ensemble approach suggests that the yeast network shows highly ordered dynamics.

Computational Biology↗
PubMed2025

MNMO: discover driver genes from a multi-omics data based-multi-layer network.

MOTIVATION: Cancer as a public health problem is driven by genomic variations in "cancer driver" genes. The identification of driver genes is critical for the discovery of key biomarkers and the development of personalized therapy. RESULTS: We propose a prediction method MNMO: a multi-layer network model based on multi-omics data. MNMO firstly constructs a dynamically adjusted four-layer network composed of miRNAs and three kinds of genes with different features. Then three kinds of scores, i.e. control capacity, mutation score, and network score, are devised and calculated by harmonic mean to produce the integrated gene score. Experiments were performed on three kinds of real cancer data to compare the identification performance of method MNMO with that of six state-of-the-art ones. The results indicate that method MNMO presents the best identification performance under most circumstances. The genes prioritized by method MNMO not only have a better match to the benchmark ones than those identified by the other methods, but also are all associated with the development and progression of cancers. In addition, some extended versions of method MNMO can further achieve better performance on most evaluation metrics for some specific datasets. They may be more conducive to identifying tissue-specific genes, which has been verified through a number of experiments. AVAILABILITY AND IMPLEMENTATION: The source code and the R package "MNMO" are available at https://github.com/Zheng-D/MNMO. The dataset and code are archived at https://doi.org/10.5281/zenodo.14969986.

Humans↗
PubMed2005

Spatial prisoner's dilemma game with volunteering in Newman-Watts small-world networks.

A modified spatial prisoner's dilemma game with voluntary participation in Newman-Watts small-world networks is studied. Some reasonable ingredients are introduced to the game evolutionary dynamics: each agent in the network is a pure strategist and can only take one of three strategies (cooperator, defector, and loner); its strategical transformation is associated with both the number of strategical states and the magnitude of average profits, which are adopted and acquired by its coplayers in the previous round of play; a stochastic strategy mutation is applied when it gets into the trouble of local commons that the agent and its neighbors are in the same state and get the same average payoffs. In the case of very low temptation to defect, it is found that agents are willing to participate in the game in typical small-world region and intensive collective oscillations arise in more random region.

Journal Article↗
PubMed2006

Lag synchrony measures dynamical processes underlying progression of seizure states.

We investigate the dynamics of bursting behavior in an intact hippocampal preparation using causal entropy, an adaptive measure of lag synchrony. This analysis, together with a heuristic model of coupled bursting networks, separates experimentally observed bursting dynamics into two dynamical regimes, when bursting is driven by (1) the intranetwork dynamics of a single region, or (2) internetwork feedback between spatially disjoint neural populations. Our results suggest that the abrupt transition between these two states heralds the gradual desynchronization of bursting activity. These results illustrate how superficially homogeneous behavior across loosely coupled networks may harbor hidden, but robust, dynamical processes.

Action Potentials↗
PubMed2004

Hysteresis and cell cycle transitions: how crucial is it?

Recently, experiments have shown that cyclin-dependent kinase (CDK) activity exhibits hysteresis in its response to total cyclin when cyclin is made nondegradable and controlled externally. This observation was taken to support mathematical modeling predictions regarding the underlying dynamics of the cell cycle. However, cell cycle dynamics can also be generated by other nonhysteretic mechanisms. To examine the robustness of the hysteretic response of CDK activity to total cyclin, we simulated various cell cycle signal transduction networks, and correlated the dynamics to the response function of CDK activity versus total cyclin. By randomly searching the parameter space, we assessed robustness by estimating the frequency of hysteretic versus nonhysteretic dynamical mechanisms. When the dynamical instabilities were caused by feedback loops in CDK phosphorylation and dephosphorylation or by feedback between cyclin and the CDK inhibitor, the response function of CDK activity versus total cyclin correlated well with the dynamical instabilities. However, when the dynamical instabilities originated from feedback between cyclin and APC-CDH1 or RB-E2F, the response function did not correlate with dynamical instabilities. Thus, although a hysteretic response is neither necessary nor sufficient, it is in general a much more robust mechanism for generating cell cycle dynamics than nonhysteretic mechanisms.

Biological Clocks↗