Spontaneous Synchrony Breaking

Research on synchronization of coupled oscillators has helped explain how uniform behavior emerges in populations of non-uniform systems. But explaining how uniform populations engage in sustainable non-uniform synchronization may prove to be just as fascinating

Macroscopic coherent structures in a stochastic neural network: from interface dynamics to coarse-grained bifurcation analysis

We study coarse pattern formation in a cellular automaton modelling a spatially-extended stochastic neural network. The model, originally proposed by Gong and Robinson (Phys Rev E 85(5):055,101(R), 2012), is known to support stationary and travelling bumps of localised activity. We pose the model on a ring and study the existence and stability of these patterns in various limits using a combination of analytical and numerical techniques. In a purely deterministic version of the model, posed on a continuum, we construct bumps and travelling waves analytically using standard interface methods from neural field theory. In a stochastic version with Heaviside firing rate, we construct approximate analytical probability mass functions associated with bumps and travelling waves. In the full stochastic model posed on a discrete lattice, where a coarse analytic description is unavailable, we compute patterns and their linear stability using equation-free methods. The lifting procedure used in the coarse time-stepper is informed by the analysis in the deterministic and stochastic limits. In all settings, we identify the synaptic profile as a mesoscopic variable, and the width of the corresponding activity set as a macroscopic variable. Stationary and travelling bumps have similar meso- and macroscopic profiles, but different microscopic structure, hence we propose lifting operators which use microscopic motifs to disambiguate them. We provide numerical evidence that waves are supported by a combination of high synaptic gain and long refractory times, while meandering bumps are elicited by short refractory times

Neural field models with threshold noise

The original neural field model of Wilson and Cowan is often interpreted as the averaged behaviour of a network of switch like neural elements with a distribution of switch thresholds, giving rise to the classic sigmoidal population firing-rate function so prevalent in large scale neuronal modelling. In this paper we explore the effects of such threshold noise without recourse to averaging and show that spatial correlations can have a strong effect on the behaviour of waves and patterns in continuum models. Moreover, for a prescribed spatial covariance function we explore the differences in behaviour that can emerge when the underlying stationary distribution is changed from Gaussian to non-Gaussian. For travelling front solutions, in a system with exponentially decaying spatial interactions, we make use of an interface approach to calculate the instantaneous wave speed analytically as a series expansion in the noise strength. From this we find that, for weak noise, the spatially averaged speed depends only on the choice of covariance function and not on the shape of the stationary distribution. For a system with a Mexican-hat spatial connectivity we further find that noise can induce localised bump solutions, and using an interface stability argument show that there can be multiple stable solution branches

The dynamics of neural fields on bounded domains: an interface approach for Dirichlet boundary conditions

Continuum neural field equations model the large scale spatio-temporal dynamics of interacting neurons on a cortical surface. They have been extensively studied, both analytically and numerically, on bounded as well as unbounded domains. Neural field models do not require the specification of boundary conditions. Relatively little attention has been paid to the imposition of neural activity on the boundary, or to its role in inducing patterned states. Here we redress this imbalance by studying neural field models of Amari type (posed on one- and two-dimensional bounded domains) with Dirichlet boundary conditions. The Amari model has a Heaviside nonlinearity that allows for a description of localised solutions of the neural field with an interface dynamics. We show how to generalise this reduced but exact description by deriving a normal velocity rule for an interface that encapsulates boundary effects. The linear stability analysis of localised states in the interface dynamics is used to understand how spatially extended patterns may develop in the absence and presence of boundary conditions. Theoretical results for pattern formation are shown to be in excellent agreement with simulations of the full neural field model. Furthermore, a numerical scheme for the interface dynamics is introduced and used to probe the way in which a Dirichlet boundary condition can limit the growth of labyrinthine structures

Combining spatial and parametric working memory in a dynamic neural field model

We present a novel dynamic neural field model consisting of two coupled fields of Amari-type which supports the existence of localized activity patterns or “bumps” with a continuum of amplitudes. Bump solutions have been used in the past to model spatial working memory. We apply the model to explain input-specific persistent activity that increases monotonically with the time integral of the input (parametric working memory). In numerical simulations of a multi-item memory task, we show that the model robustly memorizes the strength and/or duration of inputs. Moreover, and important for adaptive behavior in dynamic environments, the memory strength can be changed at any time by new behaviorally relevant information. A direct comparison of model behaviors shows that the 2-field model does not suffer the problems of the classical Amari model when the inputs are presented sequentially as opposed to simultaneously

The inevitable youthfulness of known high-redshift radio galaxies

Radio galaxies can be seen out to very high redshifts, where in principle they can serve as probes of the early evolution of the Universe. Here we show that for any model of radio-galaxy evolution in which the luminosity decreases with time after an initial rapid increase (that is, essentially all reasonable models), all observable high-redshift radio-galaxies must be seen when the lobes are less than 10^7 years old. This means that high-redshift radio galaxies can be used as a high-time-resolution probe of evolution in the early Universe. Moreover, this result helps to explain many observed trends of radio-galaxy properties with redshift [(i) the `alignment effect' of optical emission along radio-jet axes, (ii) the increased distortion in radio structure, (iii) the decrease in physical sizes, (iv) the increase in radio depolarisation, and (v) the increase in dust emission] without needing to invoke explanations based on cosmology or strong evolution of the surrounding intergalactic medium with cosmic time, thereby avoiding conflict with current theories of structure formation.Comment: To appear in Nature. 4 pages, 2 colour figures available on request. Also available at http://www-astro.physics.ox.ac.uk/~km

Phylogenetically related Argentinean and Australian Escherichia coli O157 isolates are distinguished by virulence clades and alternative shiga toxin 1 and 2 prophages

Shiga toxigenic Escherichia coli O157 is the leading cause of hemolytic uremic syndrome (HUS) worldwide. The frequencies of stx genotypes and the incidences of O157-related illness and HUS vary significantly between Argentina and Australia. Locusspecific polymorphism analysis revealed that lineage I/II (LI/II) E. coli O157 isolates were most prevalent in Argentina (90%) and Australia (88%). Argentinean LI/II isolates were shown to belong to clades 4 (28%) and 8 (72%), while Australian LI/II isolates were identified as clades 6 (15%), 7 (83%), and 8 (2%). Clade 8 was significantly associated with Shiga toxin bacteriophage insertion (SBI) type stx2 (locus of insertion, argW) in Argentinean isolates (P<0.0001). In Argentinean LI/II strains, stx2 is carried by a prophage inserted at argW, whereas in Australian LI/II strains the argW locus is occupied by the novel stx1 prophage. In both Argentinean and Australian LI/II strains, stx2c is almost exclusively carried by a prophage inserted at sbcB. However, alternative q933- or q21-related alleles were identified in the Australian stx2c prophage. Argentinean LI/II isolates were also distinguished from Australian isolates by the presence of the putative virulence determinant ECSP_3286 and the predominance of motile O157:H7 strains. Characteristics common to both Argentinean and Australian LI/II O157 strains included the presence of putative virulence determinants (ECSP_3620, ECSP_0242, ECSP_2687, ECSP_2870, and ECSP_2872) and the predominance of the tir255T allele. These data support further understanding of O157 phylogeny and may foster greater insight into the differential virulence of O157 lineages. © 2012, American Society for Microbiology

Large cell neuroendocrine lung carcinoma: consensus statement from The British Thoracic Oncology Group and the Association of Pulmonary Pathologists

Over the past 10 years, lung cancer clinical and translational research has been characterised by exponential progress, exemplified by the introduction of molecularly targeted therapies, immunotherapy and chemo-immunotherapy combinations to stage III and IV non-small cell lung cancer. Along with squamous and small cell lung cancers, large cell neuroendocrine carcinoma (LCNEC) now represents an area of unmet need, particularly hampered by the lack of an encompassing pathological definition that can facilitate real-world and clinical trial progress. The steps we have proposed in this article represent an iterative and rational path forward towards clinical breakthroughs that can be modelled on success in other lung cancer pathologies