On the complex dynamics of intracellular ganglion cell light responses in the cat retina

We recorded intracellular responses from cat retinal ganglion cells to sinusoidal flickering lights, and compared the response dynamics with a theoretical model based on coupled nonlinear oscillators. Flicker responses for several different spot sizes were separated in a smooth generator (G) potential and corresponding spike trains. We have previously shown that the G-potential reveals complex, stimulus-dependent, oscillatory behavior in response to sinusoidally flickering lights. Such behavior could be simulated by a modified van der Pol oscillator. In this paper, we extend the model to account for spike generation as well, by including extended Hodgkin-Huxley equations describing local membrane properties. We quantified spike responses by several parameters describing the mean and standard deviation of spike burst duration, timing (phase shift) of bursts, and the number of spikes in a burst. The dependence of these response parameters on stimulus frequency and spot size could be reproduced in great detail by coupling the van der Pol oscillator and Hodgkin-Huxley equations. The model mimics many experimentally observed response patterns, including non-phase-locked irregular oscillations. Our findings suggest that the information in the ganglion cell spike train reflects both intraretinal processing, simulated by the van der Pol oscillator, and local membrane properties described by Hodgkin-Huxley equations. The interplay between these complex processes can be simulated by changing the coupling coefficients between the two oscillators. Our simulations therefore show that irregularities in spike trains, which normally are considered to be noise, may be interpreted as complex oscillations that might carry information.To the memory of Prof. Otto-Joachim Grusser     

Spatiotemporal analysis of simultaneous single-unit activity in the dragonfly

The present work describes a new technique for the identification of functional connectivity between neural firing patterns. The simultaneous singleunit recordings obtained from over 50 individual cells in the dragonfly mesothoracic ganglion during three consecutive behavioral states: pre-flight, flight and postflight were evaluated. Each individual spike train was converted into a synthesized analog gradient designed to capture crucial physiological characteristics of the cell from which the spike train emanated. Estimates of network functional connectivity were calculated using correlations between analog gradient spike trains for all possible cell pairings. Both functional excitation and inhibition could be detected in the correlations. The detection of functional connectivity was relatively independent of cell firing rate. More detailed analyses indicated the existence of cellular firing histories and connectivity patterns during flight that strongly resembled the characteristics of a bi-stable oscillator. Such an oscillator, hypothetically, could drive the elevator and depressor motor neuron firing paterns that support wing kinematics. There was no evidence for the functional existence of such an oscillator within either preor post-flight spike records. The detected spatiotemporal patterns of neural activity are hypothesized to be consistent with neural command sequences that the dragonfly might use to control flight. The demonstrated capability to define short-time scale functional relationships between spike trains obtained from dragonfly ganglia should have valuable applications to the comparative study of neural information processing strategies in a variety of other neural systems.     

A model for the neuronal implementation of selective visual attention based on temporal correlation among neurons

We propose a model for the neuronal implementation of selective visual attention based on temporal correlation among groups of neurons. Neurons in primary visual cortex respond to visual stimuli with a Poisson distributed spike train with an appropriate, stimulus-dependent mean firing rate. The spike trains of neurons whose receptive fields donot overlap with the focus of attention are distributed according to homogeneous (time-independent) Poisson process with no correlation between action potentials of different neurons. In contrast, spike trains of neurons with receptive fields within the focus of attention are distributed according to non-homogeneous (time-dependent) Poisson processes. Since the short-term average spike rates of all neurons with receptive fields in the focus of attention covary, correlations between these spike trains are introduced which are detected by inhibitory interneurons in V4. These cells, modeled as modified integrate-and-fire neurons, function as coincidence detectors and suppress the response of V4 cells associated with non-attended visual stimuli. The model reproduces quantitatively experimental data obtained in cortical area V4 of monkey by Moran and Desimone (1985).     

Continuous functions determined by spike trains of a neuron subject to stimulation

several ways of estimating a continuous function from the spike train output of a neuron subjected to repeated stimuli are compared: (i) the probability of firing function estimated by a PST-histogram (ii) the rate of discharge function estimated by a frequencygram (Bessou et al. 1968) and (iii) the interspike-interval function which is introduced in this paper. For a special class of neuronal responses, called deterministic, these functions may be expressed in terms of each other. It is shown that the current clamped Hodgkin-Huxley model of an action potential encoding membrane (Hodgkin and Huxley 1952) is able to generate such deterministic responses. As an experimental example, a deterministic response of a primary muscle spindle afferent is used to demonstrate the estimation of the functions. Interpretability and numerical estimatability of these spike train describing functions are discussed for deterministic neuronal responses.     

Performance Simulation of Cluster-Based Asynchronous Soft Real-Time Systems

In this paper, we present a model designed for interactive simulation of cluster-based asynchronous soft real-time systems such as the Jambala platform of Ericsson. To build the simulator, we selected PlasmaCORE – Ericsson's proprietary simulation framework that supports a wide range of run-time modifications to the simulated system. Based on this choice, the information model of the system was developed and a prototype tool was implemented. We describe the essential features of the model and subsequently, we demonstrate the feasibility of the tool by presenting the benchmark results that compare the model-based simulation results with measurements taken on a real Jambala cluster. The flexibility of the simulation tool is demonstrated on a number of what-if scenarios that also pinpoint some important features of such clusters.     

Genetic control of β-diketone and hydroxy-β-diketone synthesis in epicuticular waxes of barley

Summary Five eceriferum, (cer) mutants in barley which influence -diketone and hydroxy--diketone synthesis in spike and internode epicuticular waxes have been characterized. The mutation cer-u ⁶⁹ blocks the synthesis of hydroxy--diketones and leads to a compensatory increase in the amount of -diketones, indicating that -diketones are precursors of the hydroxy--diketones. Furthermore, highly lobed wax plates were observed for the first time on barley lemmas, in addition to the characteristic wax tubes. Both diketone classes are selectively and proportionally reduced in the spike wax of cer-i ¹⁶, which has shorter wax tubes. The three mutants cer-c ³⁶, -q ⁴², and -c,u ¹⁰⁸ synthesize neither diketone class and form no wax tubes. In contrast to the variable composition of most individual barley wax classes, only a single -diketone was identified, namely hentriacontan-14,16-dione.     

An intrinsic mechanism for the oscillatory contraction of muscle

A new model based on the theory of dynamical systems is proposed for the intrinsic random or pscudo-random mechanism underlying certain types of muscular tremor. The active length-tension curve of the individual sarcomere, in conjunction with the passive length-tension relation is a map from length to tension with an observed time delay between length change and resulting tension change. The passive length tension relation is assumed to instantaneously relate this tension change back to a change in length. The stability properties of this iterated interval map are investigated by means of computer simulation and computation of the Lyapunov exponent and the bifurcation tree. The resulting analysis is related to experimental tremor data in the literature in terms of period doubling, bifurcation points, and chaotic behavior. The model appears to have its most fruitful application in understanding the insect type and isometric mammalian types of tremor.     

Measuring the chi 1 torsion angle in protein by CH-CH cross-correlated relaxation: a new resolution-optimised experiment

Here we introduce an experiment with high sensitivity and resolution for the measurement of CH-CH dipolar-dipolar cross-correlated relaxation rates (CCRR) in protein side-chains. The new methodology aims to the determination of structural and dynamical parameters around the torsion angle ₁ by measuring CH-CH cross-correlated relaxation rates. The method is validated on the protein ubiquitin: the ₁ angles determined from the CCRR data are compared with the ₁ angles of a previously determined NMR structure. The agreement between the two data sets is excellent for most residues. The few discrepancies that were found between the CCR-derived ₁ angles and the angles of the previously determined NMR structure could be explained by taking internal motion into account. The new methodology represents a very powerful tool to determine both structure and dynamics of protein side-chains in only one experiment.     

Automatic search for model to simulate the differentiation of T lymphocytes within the thymus

The differentiation of T Lymphocytes within the thymus is an important biological phenomenon during wich these cell acquire their functions to further control the immune system. Numerous experiments under various conditions have been devised to understand the different mechanisms involved in this complex process. Nevertheless, interpretation of these experiments lead to still contradictory debatable hypotheses. Modelisation of this process through classical simulation methods cannot be envisaged because they are not adapted to modifications of the model structure, which is the point of interest. For these reasons, we proposed a new approach of automatic search for model. The program consists of four independent connected modules : The generator produces model, based on the rationale of formal grammars. Protocol and experimental data are stored in a set of experiments. The simulator using a protocol and a model provides simulated results. Finally, the supervisor by comparing simulated results and experimental data, adapts the model parameters to increase their fit and either chooses a new experiment to explore, or modifies the model structure. Change of the model structure is performed among still unexplored models according to their promise level, which is iteratively evaluated relatively to previously explored models through a proposed model distance. The generator is written in Prolog and the other modules in C++. The architecture of the program allows us to modify or complete a module without changing anything in the other modules. As a consequence, the proposed modeling approach conceived to study T lymphocyte differentiation within the thymus remains independent of this biological phenomenon and can be applied to other biological problems.     

Modelling of direct motor program learning in fast human arm motions

We propose and simulate a new paradigm for organization of motor control in fast and accurate human arm motions. We call the paradigm direct motor program learning since the control programs are learned directly without knowing or learning the dynamics of a controlled system.The idea is to approximate the dependence of the motor control programs on the vector of the task parameters rather than to use a model of the system dynamics. We apply iterative learning control and scattered data multivariate approximation techniques to achieve the goal. The advantage of the paradigm is that the control complexity depends neither on the order nor on the nonlinearity of the system dynamics.We simulate the direct motor program learning paradigm in the task of point-to-point control of fast planar human arm motions. Simulation takes into account nonlinear arm dynamics, muscle force dynamics, delay in low-level reflex feedback, time dependence of the feedback gains and coactivation of antagonist muscles. Despite highly nonlinear time-variant dynamics of the controlled system, reasonably good motion precision is obtained over a wide range of the task parameters (initial and final positions of the arm). The simulation results demonstrate that the paradigm is indeed viable and could be considered as a possible explanation for the organization of motor control of fast motions.     

Convergence to stationary distributions in two-species stochastic competition models

Two sets of sufficient conditions are given for convergence to stationary distributions, for some general models of two species competing in a randomly varying environment. The models are nonlinear stochastic difference equations which define Markov chains. One set of sufficient conditions involves strong continuity and -irreducibility of the transition probability for the chain. The second set has a much weaker irreducibility condition, but is only applicable to monotonic models. The results are applied to a stochastic two-species Ricker model, and to Chesson's lottery model with vacant space, to illustrate how the assumptions can be checked in specific models.     

Potential modification of the fluxes of nitrogen from the Humber Estuary catchment (U.K.) to the North Sea in response to changing agricultural inputs and climate patterns

The catchment of the Humber Estuary drains approximately 20% of the land area of England via two main rivers, the Trent and the Ouse, and a number of tributaries. The catchment is home to major metropolitan and industrial centres, as well as to extensive areas of agricultural land; for this reason, the river and estuarine systems have been subject to considerable anthropogenic inputs. The Humber Estuary is one of the largest U.K. estuaries and the major U.K. freshwater input to the North Sea. The U.K. Natural Environment Research Council (NERC) Land Ocean Interaction Study (LOIS), which combined extensive physical and biogeochemical measurements with an integrated modelling programme, was established to examine the transport and fate of nutrients and other constituents through the land-sea boundary. In this paper, a model of nitrogen (nitrate, nitrite, ammonium, particulate nitrogen) transport and cycling in the Humber Estuary, calibrated on the basis of measured constituent concentrations at its riverine and marine boundaries, is linked off-line to a Humber catchment and rivers model of nitrogen transport, which furnished simulated constituent values at the tidal limits, and the resulting estuarine nitrogen profiles compared to those of the standalone estuarine model. The estuarine model is then re-run using simulated concentration values at the tidal limits from catchment-river model simulations incorporating realistic changes in agricultural fertiliser inputs and climate forcing functions. The standalone estuarine model simulation estimated nitrate+nitrite (total nitrogen) export to the North Sea to be ca. 53000 t in 1994 and 44000 t in 1995. Following linkage of the estuarine and catchment-river models, the estimated fluxes for these years increased by 20–30%, {relative to the standalone simulation}. Higher {winter} riverine flows largely accounted for this difference. The altered flows also markedly changed the simulated concentrations and distributions of suspended particulate matter (SPM) within the estuary, indicating strongly that the transport and fluxes of particle-reactive and particle-associated constituents would show measurable differences. Scatter in the measured SPM data precluded identification of the more precise simulation run, however. Subsequent simulations using the linked models estimated that a 50% reduction in artificial fertiliser applications within the catchment gave a 10–15% decrease in nitrogen loads to the North Sea, relative to the 1994–95 input, whilst forcing the catchment model with a climate perhaps appropriate for the mid-21st century yielded nitrogen fluxes that were similar to those of the mid-1990s.     

Counting statistics of 1/f fluctuations in neuronal spike trains

The mesencephalic reticular formation (MRF) neurons are regarded as contributing to the activation of the celebral cortex. In this paper, the statistical features of single neuronal activities in MRF of cat during dream sleep are investigated; the neuronal spike train exhibits 1/f fluctuations. Counting statistics is applied to the neuronal spike train giving rise to a variance/mean curve which follows at -law. For an interpretation of these findings, the clustering Poisson process is applied which not only gives rise to at -law but also suggests a generation mechanism. The MRF neuronal activities are closely fitted by the clustering Poisson process and the underlying statistical parameters can be estimated. These findings strongly suggest that neuronal activities can be interpreted as superposition of randomly occuring clusters ( = bursts of spikes).     

On representation and approximation of nonlinear systems

In a discrete-time framework any nonlinear system can be approximated with arbitrarily small error by a Volterra series and also by a sandwich system.     

An automata-theoretical model of the vegetative and flowering development of Hieracium murorum L.

By means of a computer model certain essential aspects of the vegetative and flowering development of Hieracium murorum have been successfully simulated. The model is based on local control mechanisms operating over a large number of units and is stated in terms of the theory of developmental systems and languages. The model is constructed as a table deterministic 1,1 L-system. The model is especially concerned with the correlation mechanisms between the various differentiating parts of the plant.This work has been supported by a grant from the Netherlands Organization for the Advancement of Pure Research (Z.W.O.)     

Neuron classification based on temporal firing patterns by the dynamical analysis with changing time resolution (DCT) method

Spike train data of many neurons can be obtained by multirecording techniques; however, the data make it difficult to estimate the connective structure in a large network. Neuron classification should be helpful in that regard, assuming that multiple neurons having similar connections with other neurons show a similar temporal firing pattern. We propose a novel method for classifying neurons based on temporal firing patterns of spike train data called the dynamical analysis with changing time resolution (DCT) method. The DCT method can evaluate temporal firing patterns by a simple algorithm with few arbitrary factors and automatically classify neurons by similarity of temporal firing patterns. In the DCT method, temporal firing patterns were objectively evaluated by analyzing their dependence on temporal resolution. We confirmed the effectiveness of the DCT method using actual spike train data.     

Identification of beta subunit of the rhesus monkey chorionic gonadotropin (rmCG)

Chorionic gonadotropin (CG) is a placental derived hormone that plays a crucial role in successful implantation and establishment of early pregnancy in the primates. The rhesus monkey was chosen as a model to understand the feasibility of developing human DNA immuno-contraceptive. The coding region of rhesus monkey CG -subunit (rmCG) was isolated by the TDRT-PCR method. The nucleotide sequence including the leader peptide was 499 nucleotide long and encoded 166 amino acids. In comparing with the previous known primates CG -subunits, the rmCG was the highest degree of homology with baboon CG -subunit at the deduced amino acid sequence (94%), 79.5% homology with human CG -subunit and 70.4% homology with marmoset monkey CG -subunit. The eukaryotic expression vector pCMV4-rmCG inserted full-coding cDNA sequence of rmCG was constructed, and the expression of rmCG -subunit in HeLa cells transient expressing system in vitro and BALB/c mice in vivo was determined. The results demonstrated that the recombinant PCMV4-rmCG eukaryotic expression vector could express rmCG -subunit in vitro and in vivo.     

A computational model of vertical signal propagation in the primary visual cortex

A computational model of the flow of activity in a vertically organized slab of cat primary visual cortex (area 17) has been developed. The membrane potential of each cell in the model, as a function of time, is given by the solution of a system of first order, coupled, non-linear differential equations. When firing threshold is exceeded, an action potential waveform is pasted in. The behavior of the model following a brief simulated stimulus to afferents from the dorsal lateral geniculate nucleus (dLGN) is explored. Excitatory and inhibitory post-synaptic potential (E and IPSP) latencies, as a function of cortical depth, were generated by the model. These data were compared with the experimental literature. In general, good agreement was found for EPSPs. Many disynaptic inhibitory inputs were found to be masked by the firing of action potentials in the model. To our knowledge this phenomenon has not been reported in the experimental literature. The model demonstrates that whether a cell exhibits disynaptic or polysynaptic PSP latencies is not a fixed consequence of anatomical connectivity, but rather, can be influenced by connection strengths, and may be influenced by the ongoing pattern of activity in the cortex.Supported by a grant from Cray Research Inc.     

Random disturbance and diversity of competitive systems

Population size distribution within a community of species with a competitive hierarchy, is studied. With the introduction of a stochastic model of invasion and extinction due to random environmental disturbance, the stationary population size distribution is derived as a function of the parameter, which denotes the ratio of rates of random extinction and invasion. From this result it is shown that the Shannon-type diversity takes the maximum value under the situation that 10 20 percent of habitat sites remain unoccupied, and the number of species also becomes maximum at intermediate levels of disturbance. The dynamical properties of a one-sided competitive system are also discussed by use of the Lotka-Volterra equations.