Evolution of genuine cross-correlation strength of focal onset seizures

To quantify the evolution of genuine zero-lag cross-correlations of focal onset seizures, we apply a recently introduced multivariate measure to broad band and to narrow-band EEG data. For frequency components below 12.5 Hz, the strength of genuine cross-correlations decreases significantly during the seizure and the immediate postseizure period, while higher frequency bands show a tendency of elevated cross-correlations during the same period. We conclude that in terms of genuine zero-lag cross-correlations, the electrical brain activity as assessed by scalp electrodes shows a significant spatial fragmentation, which might promote seizure offset.

A BAYESIAN HIERARCHICAL FRAMEWORK FOR SPATIAL MODELING OF fMRI DATA

Functional neuroimaging techniques enable investigations into the neural basis of human cognition, emotions, and behaviors. In practice, applications of functional magnetic resonance imaging (fMRI) have provided novel insights into the neuropathophysiology of major psychiatric,neurological, and substance abuse disorders, as well as into the neural responses to their treatments. Modern activation studies often compare localized task-induced changes in brain activity between experimental groups. One may also extend voxel-level analyses by simultaneously considering the ensemble of voxels constituting an anatomically defined region of interest (ROI) or by considering means or quantiles of the ROI. In this work we present a Bayesian extension of voxel-level analyses that offers several notable benefits. First, it combines whole-brain voxel-by-voxel modeling and ROI analyses within a unified framework. Secondly, an unstructured variance/covariance for regional mean parameters allows for the study of inter-regional functional connectivity, provided enough subjects are available to allow for accurate estimation. Finally, an exchangeable correlation structure within regions allows for the consideration of intra-regional functional connectivity. We perform estimation for our model using Markov Chain Monte Carlo (MCMC) techniques implemented via Gibbs sampling which, despite the high throughput nature of the data, can be executed quickly (less than 30 minutes). We apply our Bayesian hierarchical model to two novel fMRI data sets: one considering inhibitory control in cocaine-dependent men and the second considering verbal memory in subjects at high risk for Alzheimer’s disease. The unifying hierarchical model presented in this manuscript is shown to enhance the interpretation content of these data sets.

Temporal and spatial variability of personal exposure to radio frequency electromagnetic fields

BACKGROUND: Little is known about the population's exposure to radio frequency electromagnetic fields (RF-EMF) in industrialized countries. OBJECTIVES: To examine levels of exposure and the importance of different RF-EMF sources and settings in a sample of volunteers living in a Swiss city. METHODS: RF-EMF exposure of 166 volunteers from Basel, Switzerland, was measured with personal exposure meters (exposimeters). Participants carried an exposimeter for 1 week (two separate weeks in 32 participants) and completed an activity diary. Mean values were calculated using the robust regression on order statistics (ROS) method. RESULTS: Mean weekly exposure to all RF-EMF sources was 0.13 mW/m(2) (0.22 V/m) (range of individual means 0.014-0.881 mW/m(2)). Exposure was mainly due to mobile phone base stations (32.0%), mobile phone handsets (29.1%) and digital enhanced cordless telecommunications (DECT) phones (22.7%). Persons owning a DECT phone (total mean 0.15 mW/m(2)) or mobile phone (0.14 mW/m(2)) were exposed more than those not owning a DECT or mobile phone (0.10 mW/m(2)). Mean values were highest in trains (1.16 mW/m(2)), airports (0.74 mW/m(2)) and tramways or buses (0.36 mW/m(2)), and higher during daytime (0.16 mW/m(2)) than nighttime (0.08 mW/m(2)). The Spearman correlation coefficient between mean exposure in the first and second week was 0.61. CONCLUSIONS: Exposure to RF-EMF varied considerably between persons and locations but was fairly consistent within persons. Mobile phone handsets, mobile phone base stations and cordless phones were important sources of exposure in urban Switzerland.

Changing correlation structures of the Northern Hemisphere atmospheric circulation from 1000 to 2100 AD

Atmospheric circulation modes are important concepts in understanding the variability of atmospheric dynamics. Assuming their spatial patterns to be fixed, such modes are often described by simple indices from rather short observational data sets. The increasing length of reanalysis products allows these concepts and assumptions to be scrutinised. Here we investigate the stability of spatial patterns of Northern Hemisphere teleconnections by using the Twentieth Century Reanalysis as well as several control and transient millennium-scale simulations with coupled models. The observed and simulated centre of action of the two major teleconnection patterns, the North Atlantic Oscillation (NAO) and to some extent the Pacific North American (PNA), are not stable in time. The currently observed dipole pattern of the NAO, its centre of action over Iceland and the Azores, split into a north–south dipole pattern in the western Atlantic with a wave train pattern in the eastern part, connecting the British Isles with West Greenland and the eastern Mediterranean during the period 1940–1969 AD. The PNA centres of action over Canada are shifted southwards and over Florida into the Gulf of Mexico during the period 1915–1944 AD. The analysis further shows that shifts in the centres of action of either teleconnection pattern are not related to changes in the external forcing applied in transient simulations of the last millennium. Such shifts in their centres of action are accompanied by changes in the relation of local precipitation and temperature with the overlying atmospheric mode. These findings further undermine the assumption of stationarity between local climate/proxy variability and large-scale dynamics inherent when using proxy-based reconstructions of atmospheric modes, and call for a more robust understanding of atmospheric variability on decadal timescales.

Quantitative 3D strain analysis in analogue experiments: Integration of X-ray computed tomography and digital volume correlation techniques

The combination of scaled analogue experiments, material mechanics, X-ray computed tomography (XRCT) and Digital Volume Correlation techniques (DVC) is a powerful new tool not only to examine the 3 dimensional structure and kinematic evolution of complex deformation structures in scaled analogue experiments, but also to fully quantify their spatial strain distribution and complete strain history. Digital image correlation (DIC) is an important advance in quantitative physical modelling and helps to understand non-linear deformation processes. Optical non-intrusive (DIC) techniques enable the quantification of localised and distributed deformation in analogue experiments based either on images taken through transparent sidewalls (2D DIC) or on surface views (3D DIC). X-ray computed tomography (XRCT) analysis permits the non-destructive visualisation of the internal structure and kinematic evolution of scaled analogue experiments simulating tectonic evolution of complex geological structures. The combination of XRCT sectional image data of analogue experiments with 2D DIC only allows quantification of 2D displacement and strain components in section direction. This completely omits the potential of CT experiments for full 3D strain analysis of complex, non-cylindrical deformation structures. In this study, we apply digital volume correlation (DVC) techniques on XRCT scan data of “solid” analogue experiments to fully quantify the internal displacement and strain in 3 dimensions over time. Our first results indicate that the application of DVC techniques on XRCT volume data can successfully be used to quantify the 3D spatial and temporal strain patterns inside analogue experiments. We demonstrate the potential of combining DVC techniques and XRCT volume imaging for 3D strain analysis of a contractional experiment simulating the development of a non-cylindrical pop-up structure. Furthermore, we discuss various options for optimisation of granular materials, pattern generation, and data acquisition for increased resolution and accuracy of the strain results. Three-dimensional strain analysis of analogue models is of particular interest for geological and seismic interpretations of complex, non-cylindrical geological structures. The volume strain data enable the analysis of the large-scale and small-scale strain history of geological structures.

Spatial and Temporal Melt Variability at Helheim Glacier, East Greenland, and Its Effect on Ice Dynamics

Understanding the behavior of large outlet glaciers draining the Greenland Ice Sheet is critical for assessing the impact of climate change on sea level rise. The flow of marine-terminating outlet glaciers is partly governed by calving-related processes taking place at the terminus but is also influenced by the drainage of surface runoff to the bed through moulins, cracks, and other pathways. To investigate the extent of the latter effect, we develop a distributed surface-energy-balance model for Helheim Glacier, East Greenland, to calculate surface melt and thereby estimate runoff. The model is driven by data from an automatic weather station operated on the glacier during the summers of 2007 and 2008, and calibrated with independent measurements of ablation. Modeled melt varies over the deployment period by as much as 68% relative to the mean, with melt rates approximately 77% higher on the lower reaches of the glacier trunk than on the upper glacier. We compare melt variations during the summer season to estimates of surface velocity derived from global positioning system surveys. Near the front of the glacier, there is a significant correlation (on >95% levels) between variations in runoff (estimated from surface melt) and variations in velocity, with a 1 day delay in velocity relative to melt. Although the velocity changes are small compared to accelerations previously observed following some calving events, our findings suggest that the flow speed of Helheim Glacier is sensitive to changes in runoff. The response is most significant in the heavily crevassed, fast-moving region near the calving front. The delay in the peak of the cross-correlation function implies a transit time of 12-36 h for surface runoff to reach the bed.

Standing waves as an explanation for generic stationary correlation patterns in noninvasive EEG of focal onset seizures.

Cerebral electrical activity is highly nonstationary because the brain reacts to ever changing external stimuli and continuously monitors internal control circuits. However, a large amount of energy is spent to maintain remarkably stationary activity patterns and functional inter-relations between different brain regions. Here we examine linear EEG correlations in the peri-ictal transition of focal onset seizures, which are typically understood to be manifestations of dramatically changing inter-relations. Contrary to expectations we find stable correlation patterns with a high similarity across different patients and different frequency bands. This skeleton of spatial correlations may be interpreted as a signature of standing waves of electrical brain activity constituting a dynamical ground state. Such a state could promote the formation of spatiotemporal neuronal assemblies and may be important for the integration of information stemming from different local circuits of the functional brain network.

Radiocarbon Analysis of Elemental and Organic Carbon in Switzerland during Winter-Smog Episodes from 2008 to 2012 – Part I: Source Apportionment and Spatial Variability

While several studies have investigated winter-time air pollution with a wide range of concentration levels, hardly any results are available for longer time periods covering several winter-smog episodes at various locations; e.g., often only a few weeks from a single winter are investigated. Here, we present source apportionment results of winter-smog episodes from 16 air pollution monitoring stations across Switzerland from five consecutive winters. Radiocarbon (14C) analyses of the elemental (EC) and organic (OC) carbon fractions, as well as levoglucosan, major water-soluble ionic species and gas-phase pollutant measurements were used to characterize the different sources of PM10. The most important contributions to PM10 during winter-smog episodes in Switzerland were on average the secondary inorganic constituents (sum of nitrate, sulfate and ammonium = 41 ± 15%) followed by organic matter (OM) (34 ± 13%) and EC (5 ± 2%). The non-fossil fractions of OC (fNF,OC) ranged on average from 69 to 85 and 80 to 95% for stations north and south of the Alps, respectively, showing that traffic contributes on average only up to ~ 30% to OC. The non-fossil fraction of EC (fNF,EC), entirely attributable to primary wood burning, was on average 42 ± 13 and 49 ± 15% for north and south of the Alps, respectively. While a high correlation was observed between fossil EC and nitrogen oxides, both primarily emitted by traffic, these species did not significantly correlate with fossil OC (OCF), which seems to suggest that a considerable amount of OCF is secondary, from fossil precursors. Elevated fNF,EC and fNF,OC values and the high correlation of the latter with other wood burning markers, including levoglucosan and water soluble potassium (K+) indicate that residential wood burning is the major source of carbonaceous aerosols during winter-smog episodes in Switzerland. The inspection of the non-fossil OC and EC levels and the relation with levoglucosan and water-soluble K+ shows different ratios for stations north and south of the Alps (most likely because of differences in burning technologies) for these two regions in Switzerland.

Impact of above- and below-ground invertebrates on temporal and spatial stability of grassland of different diversity

1. Recent theoretical studies suggest that the stability of ecosystem processes is not governed by diversity per se, but by multitrophic interactions in complex communities. However, experimental evidence supporting this assumption is scarce.2. We investigated the impact of plant diversity and the presence of above- and below-ground invertebrates on the stability of plant community productivity in space and time, as well as the interrelationship between both stability measures in experimental grassland communities.3. We sampled above-ground plant biomass on subplots with manipulated above- and below-ground invertebrate densities of a grassland biodiversity experiment (Jena Experiment) 1, 4 and 6 years after the establishment of the treatments to investigate temporal stability. Moreover, we harvested spatial replicates at the last sampling date to explore spatial stability.4. The coefficient of variation of spatial and temporal replicates served as a proxy for ecosystem stability. Both spatial and temporal stability increased to a similar extent with plant diversity. Moreover, there was a positive correlation between spatial and temporal stability, and elevated plant density might be a crucial factor governing the stability of diverse plant communities.5. Above-ground insects generally increased temporal stability, whereas impacts of both earthworms and above-ground insects depended on plant species richness and the presence of grasses. These results suggest that inconsistent results of previous studies on the diversity–stability relationship have in part been due to neglecting higher trophic-level interactions governing ecosystem stability.6. Changes in plant species diversity in one trophic level are thus unlikely to mirror changes in multitrophic interrelationships. Our results suggest that both above- and below-ground invertebrates decouple the relationship between spatial and temporal stability of plant community productivity by differently affecting the homogenizing mechanisms of plants in diverse plant communities.7.Synthesis. Species extinctions and accompanying changes in multitrophic interactions are likely to result not only in alterations in the magnitude of ecosystem functions but also in its variability complicating the assessment and prediction of consequences of current biodiversity loss.

Correlation of tuberculosis and human immunodeficiency virus in Harris County, Texas from 2009 through 2010 using Geographic Information Systems

A population based ecological study was conducted to identify areas with a high number of TB and HIV new diagnoses in Harris County, Texas from 2009 through 2010 by applying Geographic Information Systems to determine whether distinguished spatial patterns exist at the census tract level through the use of exploratory mapping. As of 2010, Texas has the fourth highest occurrence of new diagnoses of HIV/AIDS and TB.[31] The Texas Department of State Health Services (DSHS) has identified HIV infected persons as a high risk population for TB in Harris County.[29] In order to explore this relationship further, GIS was utilized to identify spatial trends. ^ The specific aims were to map TB and HIV new diagnoses rates and spatially identify hotspots and high value clusters at the census tract level. The potential association between HIV and TB was analyzed using spatial autocorrelation and linear regression analysis. The spatial statistics used were ArcGIS 9.3 Hotspot Analysis and Cluster and Outlier Analysis. Spatial autocorrelation was determined through Global Moran's I and linear regression analysis. ^ Hotspots and clusters of TB and HIV are located within the same spatial areas of Harris County. The areas with high value clusters and hotspots for each infection are located within the central downtown area of the city of Houston. There is an additional hotspot area of TB located directly north of I-10 and a hotspot area of HIV northeast of Interstate 610. ^ The Moran's I Index of 0.17 (Z score = 3.6 standard deviations, p-value = 0.01) suggests that TB is statistically clustered with a less than 1% chance that this pattern is due to random chance. However, there were a high number of features with no neighbors which may invalidate the statistical properties of the test. Linear regression analysis indicated that HIV new diagnoses rates (β=−0.006, SE=0.147, p=0.970) and census tracts (β=0.000, SE=0.000, p=0.866) were not significant predictors of TB new diagnoses rates. ^ Mapping products indicate that census tracts with overlapping hotspots and high value clusters of TB and HIV should be a targeted focus for prevention efforts, most particularly within central Harris County. While the statistical association was not confirmed, evidence suggests that there is a relationship between HIV and TB within this two year period.^

Competition may explain the fine-scale spatial patterns and genetic structure of two co-occurring plant congeners

1. The spatial distribution of individual plants within a population and the population’s genetic structure are determined by several factors, like dispersal, reproduction mode or biotic interactions. The role of interspecific interactions in shaping the spatial genetic structure of plant populations remains largely unknown. 2. Species with a common evolutionary history are known to interact more closely with each other than unrelated species due to the greater number of traits they share. We hypothesize that plant interactions may shape the fine genetic structure of closely related congeners. 3. We used spatial statistics (georeferenced design) and molecular techniques (ISSR markers) to understand how two closely related congeners, Thymus vulgaris (widespread species) and T. loscosii (narrow endemic) interact at the local scale. Specific cover, number of individuals of both study species and several community attributes were measured in a 10 × 10 m plot. 4. Both species showed similar levels of genetic variation, but differed in their spatial genetic structure. Thymus vulgaris showed spatial aggregation but no spatial genetic structure, while T. loscosii showed spatial genetic structure (positive genetic autocorrelation) at short distances. The spatial pattern of T. vulgaris’ cover showed significant dissociation with that of T. loscosii. The same was true between the spatial patterns of the cover of T. vulgaris and the abundance of T. loscosii and between the abundance of each species. Most importantly, we found a correlation between the genetic structure of T. loscosii and the abundance of T. vulgaris: T. loscosii plants were genetically more similar when they were surrounded by a similar number of T. vulgaris plants. 5. Synthesis. Our results reveal spatially complex genetic structures of both congeners at small spatial scales. The negative association among the spatial patterns of the two species and the genetic structure found for T. loscosii in relation to the abundance of T. vulgaris indicate that competition between the two species may account for the presence of adapted ecotypes of T. loscosii to the abundance of a competing congeneric species. This suggests that the presence and abundance of close congeners can influence the genetic spatial structure of plant species at fine scales.