Spatial eigenmodes and synchronous oscillation: co-incidence detection in simulated cerebral cortex

 Zero-lag synchronisation arises between points on the cerebral cortex receiving concurrent independent inputs; an observation generally ascribed to nonlinear mechanisms. Using simulations of cerebral cortex and Principal Component Analysis (PCA) we show patterns of zero-lag synchronisation (associated with empirically realistic spectral content) can arise from both linear and nonlinear mechanisms. For low levels of activation, we show the synchronous field is described by the eigenmodes of the resultant damped wave activity. The first and second spatial eigenmodes (which capture most of the signal variance) arise from the even and odd components of the independent input signals. The pattern of zero-lag synchronisation can be accounted for by the relative dominance of the first mode over the second, in the near-field of the inputs. The simulated cortical surface can act as a few millisecond response coincidence detector for concurrent, but uncorrelated, inputs. As cortical activation levels are increased, local damped oscillations in the gamma band undergo a transition to highly nonlinear undamped activity with 40 Hz dominant frequency. This is associated with ``locking' between active sites and spatially segregated phase patterns. The damped wave synchronisation and the locked nonlinear oscillations may combine to permit fast representation of multiple patterns of activity within the same field of neurons. Received: 20 January 1999 / Revised version: 22 September 2000 / Second revised version: 20 December 2001 / Published online: 26 June 2002     

Synchrony &; chaos in patchy ecosystems

The apparent synchronisation of spatially discrete populations is a well documented phenomenon. However, it is not clear what the governing mechanisms are for this synchrony, and whether they are robust over a range of environmental conditions and patch specific population dynamic behaviours. In this paper, we explore two (possibly interacting) modes of coupling, and investigate their theoretically discernible, and perhaps even experimentally measurable, signatures. To aid us in this investigation we employ a planktonic example system, with direct application to plankton patchiness. Furthermore, we address the role of chaos in complex spatio-temporal dynamics; we find that chaos associated with funnel attractors can play a distinguished role, over dynamics less sensitive to small variations, in being more susceptible to generalised synchronisation (such as phase synchronisation) in the presence of small local parameter variation. This is in contrast to the case for coupled systems with identical dynamics, and suggests that non-identically coupled systems are more vulnerable to global extinction events when exhibiting funnel-type chaotic dynamics.     

Associative recognition and storage in a model network of physiological neurons

We consider a neural network model in which the single neurons are chosen to closely resemble known physiological properties. The neurons are assumed to be linked by synapses which change their strength according to Hebbian rules on a short time scale (100ms). The dynamics of the network — the time evolution of the cell potentials and the synapses — is investigated by computer simulation. As in more abstract network models (Cooper 1973; Hopfield 1982; Kohonen 1984) it is found that the local dynamics of the cell potentials and the synaptic strengths result in global cooperative properties of the network and enable the network to process an incoming flux of information and to learn and store patterns associatively. A trained net can associate missing details of a pattern, can correct wrong details and can suppress noise in a pattern. The network can further abstract the prototype from a series of patterns with variations. A suitable coupling constant connecting the dynamics of the cell potentials with the synaptic strengths is derived by a mean field approximation. This coupling constant controls the neural sensitivity and thereby avoids both extremes of the network state, the state of permanent inactivity and the state of epileptic hyperactivity.     

Periodic synchronisation of dengue epidemics in Thailand over the last 5 decades driven by temperature and immunity

The spatial distribution of dengue and its vectors (spp. Aedes) may be the widest it has ever been, and projections suggest that climate change may allow the expansion to continue. However, less work has been done to understand how climate variability and change affects dengue in regions where the pathogen is already endemic. In these areas, the waxing and waning of immunity has a large impact on temporal dynamics of cases of dengue haemorrhagic fever. Here, we use 51 years of data across 72 provinces and characterise spatiotemporal patterns of dengue in Thailand, where dengue has caused almost 1.5 million cases over the last 30 years, and examine the roles played by temperature and dynamics of immunity in giving rise to those patterns. We find that timescales of multiannual oscillations in dengue vary in space and time and uncover an interesting spatial phenomenon: Thailand has experienced multiple, periodic synchronisation events. We show that although patterns in synchrony of dengue are similar to those observed in temperature, the relationship between the two is most consistent during synchronous periods, while during asynchronous periods, temperature plays a less prominent role. With simulations from temperature-driven models, we explore how dynamics of immunity interact with temperature to produce the observed patterns in synchrony. The simulations produced patterns in synchrony that were similar to observations, supporting an important role of immunity. We demonstrate that multiannual oscillations produced by immunity can lead to asynchronous dynamics and that synchrony in temperature can then synchronise these dengue dynamics. At higher mean temperatures, immune dynamics can be more predominant, and dengue dynamics more insensitive to multiannual fluctuations in temperature, suggesting that with rising mean temperatures, dengue dynamics may become increasingly asynchronous. These findings can help underpin predictions of disease patterns as global temperatures rise.

This study shows that spatially large-scale shifts in temperature can synchronize dengue dynamics across Thailand; however, as average temperatures rise, dengue dynamics may increasingly be dictated by dynamics of immunity, which may in turn mean fewer synchronous outbreaks in the future.     

Spatial coupling in cyclic population dynamics: models and data

We use a dynamic random field to model a spatial collection of coupled oscillators with discrete time stochastic dynamics. At each time step the phase of each cyclic local population is subject to random noise, incremented by a common dynamic, and pulled by a coupling force in the direction of some collective mean phase. We define asynchrony and derive expressions for its measurement in this model. We describe robust methods for phase estimation of cyclic population time series, for estimating strength of coupling between local populations, and for measuring variance of locally acting noise from field data. Proposed methods allow intermittently acting phase synchronizing events operating over large spatial scales to be distinguished from more continuous and possibly locally acting coupling, both of which could result in elevated levels of phase synchronization. We demonstrate the utility of this approach by applying it to classical spatial time series data of Canadian lynx. Analysis confirms findings of previous studies and reveals evidence to suggest that interpopulation coupling was weaker over the 20th century than for the 1800s. Analysis supports the notion that synchrony in these populations is maintained by a continuous and locally acting coupling between adjacent regions with large phase adjustments occurring only infrequently. When this coupling is absent, asynchrony develops between populations.     

Conditional entropy approach for the evaluation of the coupling strength

A method that enables measurement of the degree of coupling between two signals is presented. The method is based on the definition of an uncoupling function calculating, by means of entropy rates, the minimum amount of independent information (i.e. the information carried by one signal which cannot be derived from the other). An estimator of the uncoupling function able to deal with short segments of data (a few hundred samples) is proposed, thus enabling the method to be used for usual experimental recordings. A synchronisation index is derived from the estimate of the uncoupling function by means of a minimisation procedure. It quantifies the maximum amount of information exchanged between the two signals. Simulations in which non-linear coordination schemes are produced and changes in the coupling strength are artificially induced are used to check the ability of the proposed index to measure the degree of synchronisation between signals. The synchronisation analysis is utilised to measure the coupling strength between the beat-to-beat variability of the sympathetic discharge and ventilation in decerebrate artificially ventilated cats and the degree of synchronisation between the beat-to-beat variability of the heart period and ventricular repolarisation interval in normal subjects and myocardial infarction patients. The sympathetic discharge and ventilation are strongly coupled and the coupling strength is not affected by manoeuvres capable of increasing or depressing sympathetic activity. The synchronisation is lost after spinalisation. The synchronisation analysis confirms that the heart period and ventricular repolarisation interval are well coordinated. In normal subjects, the synchronisation index is not modified by experimental conditions inducing changes in the sympathovagal balance. On the contrary, it strongly decreases after myocardial infarction, thus detecting and measuring the uncoupling between the heart period and ventricular repolarisation interval. Received: 29 October 1998 / Received in revised form: 4 March 1999     

A Computational Study of the Giant Local Electric Field Enhancement in Al-Au-Ag Trimetallic Three-Layered Nanoshells

The surface plasmon resonance (SPR)-induced local field effect in Al-Au-Ag trimetallic three-layered nanoshells has been studied theoretically. Because of having three kinds of metal, three plasmonic bands have been observed in the absorption spectra and the local electric field factor spectra. The local electric field enhancement and the corresponding resonance wavelength for different plasmon coupling modes and spatial positions of the Al-Au-Ag nanoshells with various geometry dimensions are investigated to find the maximum local electric field enhancement. The calculation results indicate that the giant local electric field enhancement could be stimulated by the plasmon coupling in the middle Au shell or the outer Ag shell and could be optimized by increasing the Ag shell thickness and decreasing the Au shell thickness. What is more, the local electric field enhancement also nonmonotonously depends on the dielectric constant of the environment; the local electric field intensity will be weakened when the surrounding dielectric constant is too small or too large.

     

Hypoxic effects on growth of Palaemonetes vulgaris larvae and other species: Using constant exposure data to estimate cyclic exposure response

First stage larval marsh grass shrimp, Palaemonetes vulgaris, were exposed to patterns of diurnal, semidiurnal, and constant hypoxia to evaluate effects on growth and to determine if there was a consistent relationship between exposures. A comparison of growth with cyclic exposures versus constant low dissolved oxygen (D.O.) concentrations equivalent to the minima of the cycles showed the cyclic exposures resulted in less growth impairment than constant low-D.O. exposures, when compared to saturated controls. The mean extent of growth impairment of cyclic hypoxia was, however, almost 1.5 times more than would be estimated using an arithmetic time-weighted-average of the hypoxic portion of the cycle. Additional testing with other life stages and species resulted in similar patterns of response. Based on this relationship, an adjusted time-weighted-average could be used to estimate field related responses to cyclic dissolved oxygen from laboratory-derived constant exposure data.     

Weak electric fields detectability in a noisy neural network

We investigate the detectability of weak electric field in a noisy neural network based on Izhikevich neuron model systematically. The neural network is composed of excitatory and inhibitory neurons with similar ratio as that in the mammalian neocortex, and the axonal conduction delays between neurons are also considered. It is found that the noise intensity can modulate the detectability of weak electric field. Stochastic resonance (SR) phenomenon induced by white noise is observed when the weak electric field is added to the network. It is interesting that SR almost disappeared when the connections between neurons are cancelled, suggesting the amplification effects of the neural coupling on the synchronization of neuronal spiking. Furthermore, the network parameters, such as the connection probability, the synaptic coupling strength, the scale of neuron population and the neuron heterogeneity, can also affect the detectability of the weak electric field. Finally, the model sensitivity is studied in detail, and results show that the neural network model has an optimal region for the detectability of weak electric field signal.     

Role of the mean curvature in the geometry of magnetic confinement configurations

Examples are presented of how the geometric notion of the mean curvature is applied to the vector of a general magnetic field and to magnetic surfaces. It is shown that the mean curvature is related to the variation of the absolute value of the magnetic field along its lines. Magnetic surfaces of constant mean curvature are optimum for plasma confinement in multimirror open confinement systems and rippled tori.     

Testing for significance of phase synchronisation dynamics in the EEG

A number of tests exist to check for statistical significance of phase synchronisation within the Electroencephalogram (EEG); however, the majority suffer from a lack of generality and applicability. They may also fail to account for temporal dynamics in the phase synchronisation, regarding synchronisation as a constant state instead of a dynamical process. Therefore, a novel test is developed for identifying the statistical significance of phase synchronisation based upon a combination of work characterising temporal dynamics of multivariate time-series and Markov modelling. We show how this method is better able to assess the significance of phase synchronisation than a range of commonly used significance tests. We also show how the method may be applied to identify and classify significantly different phase synchronisation dynamics in both univariate and multivariate datasets.     

The Glocal Forest

Spatial ecological patterns reflect the underlying processes that shape the structure of species and communities. Mechanisms like intra- and inter-specific competition, dispersal and host-pathogen interactions can act over a wide range of scales. Yet, the inference of such processes from patterns is a challenging task. Here we call attention to a quite unexpected phenomenon in the extensively studied tropical forest at the Barro-Colorado Island (BCI): the spatial deployment of (almost) all tree species is statistically equivalent, once distances are normalized by ℓ₀, the typical distance between neighboring conspecific trees. Correlation function, cluster statistics and nearest-neighbor distance distribution become species-independent after this rescaling. Global observables (species frequencies) and local spatial structure appear to be interrelated. This "glocality" suggests a radical interpretation of recent experiments that show a correlation between species'' abundance and the negative feedback among conspecifics. For the forest to be glocal, the negative feedback must govern spatial patterns over all scales.     

Loss of synchronization in partially coupled Hodgkin-Huxley equations

We study the loss of synchronization of two partially coupled space-clamped Hodgkin-Huxley equations, with symmetric coupling. This models the coupling of two cells through an electrical synapse. For strong enough coupling it is known that all solutions of the equations approach a state where the two cells are perfectly synchronized, having the same behaviour at each moment. We describe the local bifurcations that arise when the coupling strength is reduced, using a mixture of analytical and numerical methods. We find that perfect synchrony is retained for very small positive values of the coupling strength, for almost all initial conditions. Although perfect synchrony is lost for negative values of the coupling constant, the system always retains some degree of synchronization until it becomes totally unstable. This happens in two ways: in many cases for almost all initial conditions the solutions still approach a perfectly synchronized state. Even when this is not true, the attracting solutions are still synchronized, with a half-period phase shift.     

A Universal Time Constant Operating in Human Short-term Behaviour Repetitions

In repetitive movement patterns of everyday behaviour in humans a time constant of about 3 s could be shown to prevail. This time constant was found in four independent cultures (Europeans, Trobriand Islanders, Yanomami Indians and Kalahari Bushmen) and structures behaviour into units. As Pöppel (1978, 1985) has already found such a time constant in recited verse and optical illusions, it seems that we are dealing here with a universal central nervous mechanism structuring time. Its function could be seen in creating a subjective present and in facilitating communication and synchronisation between interactants. Only 15% of patterns in the investigated behaviour repetitions do not obey the 3-s time span. These are stereotyped behaviour patterns of longer duration which seem to have a special function.     

Macroecology and people

A macroecological perspective has become recognised as an important component of ecological studies, serving particularly to crystallise the notion that processes operating at large spatial (geographic) and temporal scales often play important roles in shaping species assemblages and communities at more local scales. However, within the field, consideration has been surprisingly lacking of the influence of humans in shaping macroecological patterns, the determinants of those patterns, or their consequences for local assemblages and communities. Here I briefly review the reasons why this might be so, and the possible interactions between macroecology and people, and suggest some simple steps for exploring this issue.     

Adaptation of tick-borne encephalitis virus to BHK-21 cells results in the formation of multiple heparan sulfate binding sites in the envelope protein and attenuation in vivo

Propagation of the flavivirus tick-borne encephalitis virus in BHK-21 cells selected for mutations within the large surface glycoprotein E that increased the net positive charge of the protein. In the course of 16 independent experiments, 12 different protein E mutation patterns were identified. These were located in all three of the structural domains and distributed over almost the entire upper and lateral surface of protein E. The mutations resulted in the formation of local patches of predominantly positive surface charge. Recombinant viruses carrying some of these mutations in a defined genetic backbone showed heparan sulfate (HS)-dependent phenotypes, resulting in an increased specific infectivity and binding affinity for BHK-21 cells, small plaque formation in porcine kidney cells, and significant attenuation of neuroinvasiveness in adult mice. Our results corroborate the notion that the selection of attenuated HS binding mutants is a common and frequent phenomenon during the propagation of viruses in cell culture and suggest a major role for HS dependence in flavivirus attenuation. Recognition of this principle may be of practical value for designing attenuated flavivirus strains in the future.     

Optimised motion tracking for positron emission tomography studies of brain function in awake rats

Positron emission tomography (PET) is a non-invasive molecular imaging technique using positron-emitting radioisotopes to study functional processes within the body. High resolution PET scanners designed for imaging rodents and non-human primates are now commonplace in preclinical research. Brain imaging in this context, with motion compensation, can potentially enhance the usefulness of PET by avoiding confounds due to anaesthetic drugs and enabling freely moving animals to be imaged during normal and evoked behaviours. Due to the frequent and rapid motion exhibited by alert, awake animals, optimal motion correction requires frequently sampled pose information and precise synchronisation of these data with events in the PET coincidence data stream. Motion measurements should also be as accurate as possible to avoid degrading the excellent spatial resolution provided by state-of-the-art scanners. Here we describe and validate methods for optimised motion tracking suited to the correction of motion in awake rats. A hardware based synchronisation approach is used to achieve temporal alignment of tracker and scanner data to within 10 ms. We explored the impact of motion tracker synchronisation error, pose sampling rate, rate of motion, and marker size on motion correction accuracy. With accurate synchronisation (<100 ms error), a sampling rate of >20 Hz, and a small head marker suitable for awake animal studies, excellent motion correction results were obtained in phantom studies with a variety of continuous motion patterns, including realistic rat motion (<5% bias in mean concentration). Feasibility of the approach was also demonstrated in an awake rat study. We conclude that motion tracking parameters needed for effective motion correction in preclinical brain imaging of awake rats are achievable in the laboratory setting. This could broaden the scope of animal experiments currently possible with PET.     

Rhythmic swimming activity in Anguilla anguilla glass eels: Synchronisation to water current reversal under laboratory conditions

Synchronisation of swimming activity to water current reversal every 6.2 h was tested in the European glass eel (Anguilla anguilla L.). When presented with a change in water current direction, glass eels exhibited rhythmic patterns of activity with a period close to the tidal one. Glass eels began to swim with the current and then alternated between positive and negative rheotaxis after each change in the water current direction. Results are discussed in relation to the flood tidal transport theory. Following synchronisation to current reversal, glass eels subjected to constant conditions displayed a weak rhythmic activity suggesting that locomotor behaviour might, in the wild, synchronise to several environmental cues related to the tide. Results obtained with different densities also suggest that social cues might improve the synchronisation.