Alterations of white matter integrity related to the season of birth in schizophrenia: a DTI study

In schizophrenia there is a consistent epidemiological finding of a birth excess in winter and spring. Season of birth is thought to act as a proxy indicator for harmful environmental factors during foetal maturation. There is evidence that prenatal exposure to harmful environmental factors may trigger pathologic processes in the neurodevelopment, which subsequently increase the risk of schizophrenia. Since brain white matter alterations have repeatedly been found in schizophrenia, the objective of this study was to investigate whether white matter integrity was related to the season of birth in patients with schizophrenia. Thirty-four patients with schizophrenia and 33 healthy controls underwent diffusion tensor imaging. Differences in the fractional anisotropy maps of schizophrenia patients and healthy controls born in different seasons were analysed with tract-based spatial statistics. A significant main effect of season of birth and an interaction of group and season of birth showed that patients born in summer had significantly lower fractional anisotropy in widespread white matter regions than those born in the remainder of the year. Additionally, later age of schizophrenia onset was found in patients born in winter months. The current findings indicate a relationship of season of birth and white matter alterations in schizophrenia and consequently support the neurodevelopmental hypothesis of early pathological mechanisms in schizophrenia.

Foundations of stochastic geometry and theory of random sets

The first section of this chapter starts with the Buffon problem, which is one of the oldest in stochastic geometry, and then continues with the definition of measures on the space of lines. The second section defines random closed sets and related measurability issues, explains how to characterize distributions of random closed sets by means of capacity functionals and introduces the concept of a selection. Based on this concept, the third section starts with the definition of the expectation and proves its convexifying effect that is related to the Lyapunov theorem for ranges of vector-valued measures. Finally, the strong law of large numbers for Minkowski sums of random sets is proved and the corresponding limit theorem is formulated. The chapter is concluded by a discussion of the union-scheme for random closed sets and a characterization of the corresponding stable laws.

Gibbs point process approximation: Total variation bounds using Stein's method

We obtain upper bounds for the total variation distance between the distributions of two Gibbs point processes in a very general setting. Applications are provided to various well-known processes and settings from spatial statistics and statistical physics, including the comparison of two Lennard-Jones processes, hard core approximation of an area interaction process and the approximation of lattice processes by a continuous Gibbs process. Our proof of the main results is based on Stein's method. We construct an explicit coupling between two spatial birth-death processes to obtain Stein factors, and employ the Georgii-Nguyen-Zessin equation for the total bound.

Deficit actual tool use in schizophrenia is linked to structural alterations in key regions of planning and executing of tool use and connecting fibers

Introduction: Schizophrenia patients frequently suffer from complex motor abnormalities including fine and gross motor disturbances, abnormal involuntary movements, neurological soft signs and parkinsonism. These symptoms occur early in the course of the disease, continue in chronic patients and may deteriorate with antipsychotic medication. Furthermore gesture performance is impaired in patients, including the pantomime of tool use. Whether schizophrenia patients would show difficulties of actual tool use has not yet been investigated. Human tool use is complex and relies on a network of distinct and distant brain areas. We therefore aim to test if schizophrenia patients had difficulties in tool use and to assess associations with structural brain imaging using voxel based morphometry (VBM) and tract based spatial statistics (TBSS). Methode: In total, 44 patients with schizophrenia (DSM-5 criteria; 59% men, mean age 38) underwent structural MR imaging and performed the Tool-Use test. The test examines the use of a scoop and a hammer in three conditions: pantomime (without the tool), demonstration (with the tool) and actual use (with a recipient object). T1-weighted images were processed using SPM8 and DTI-data using FSL TBSS routines. To assess structural alterations of impaired tool use we first compared gray matter (GM) volume in VBM and white matter (WM) integrity in TBSS data of patients with and without difficulties of actual tool use. Next we explored correlations of Tool use scores and VBM and TBSS data. Group comparisons were family wise error corrected for multiple tests. Correlations were uncorrected (p < 0.001) with a minimum cluster threshold of 17 voxels (equivalent to a map-wise false positive rate of alpha < 0.0001 using a Monte Carlo procedure). Results: Tool use was impaired in schizophrenia (43.2% pantomime, 11.6% demonstration, 11.6% use). Impairment was related to reduced GM volume and WM integrity. Whole brain analyses detected an effect in the SMA in group analysis. Correlations of tool use scores and brain structure revealed alterations in brain areas of the dorso-dorsal pathway (superior occipital gyrus, superior parietal lobule, and dorsal premotor area) and the ventro-dorsal pathways (middle occipital gyrus, inferior parietal lobule) the action network, as well as the insula and the left hippocampus. Furthermore, significant correlations within connecting fiber tracts - particularly alterations within the bilateral corona radiata superior and anterior as well as the corpus callosum -were associated with Tool use performance. Conclusions: Tool use performance was impaired in schizophrenia, which was associated with reduced GM volume in the action network. Our results are in line with reports of impaired tool use in patients with brain lesions particularly of the dorso-dorsal and ventro-dorsal stream of the action network. In addition an effect of tool use on WM integrity was shown within fiber tracts connecting regions important for planning and executing tool use. Furthermore, hippocampus is part of a brain system responsible for spatial memory and navigation.The results suggest that structural brain alterations in the common praxis network contribute to impaired tool use in schizophrenia.

Fast Update of Conditional Simulation Ensembles

Gaussian random field (GRF) conditional simulation is a key ingredient in many spatial statistics problems for computing Monte-Carlo estimators and quantifying uncertainties on non-linear functionals of GRFs conditional on data. Conditional simulations are known to often be computer intensive, especially when appealing to matrix decomposition approaches with a large number of simulation points. This work studies settings where conditioning observations are assimilated batch sequentially, with one point or a batch of points at each stage. Assuming that conditional simulations have been performed at a previous stage, the goal is to take advantage of already available sample paths and by-products to produce updated conditional simulations at mini- mal cost. Explicit formulae are provided, which allow updating an ensemble of sample paths conditioned on n ≥ 0 observations to an ensemble conditioned on n + q observations, for arbitrary q ≥ 1. Compared to direct approaches, the proposed formulae proveto substantially reduce computational complexity. Moreover, these formulae explicitly exhibit how the q new observations are updating the old sample paths. Detailed complexity calculations highlighting the benefits of this approach with respect to state-of-the-art algorithms are provided and are complemented by numerical experiments.

Microstructure and Cerebral Blood Flow within White Matter of the Human Brain: A TBSS Analysis.

BACKGROUND White matter (WM) fibers connect different brain regions and are critical for proper brain function. However, little is known about the cerebral blood flow in WM and its relation to WM microstructure. Recent improvements in measuring cerebral blood flow (CBF) by means of arterial spin labeling (ASL) suggest that the signal in white matter may be detected. Its implications for physiology needs to be extensively explored. For this purpose, CBF and its relation to anisotropic diffusion was analyzed across subjects on a voxel-wise basis with tract-based spatial statistics (TBSS) and also across white matter tracts within subjects. METHODS Diffusion tensor imaging and ASL were acquired in 43 healthy subjects (mean age = 26.3 years). RESULTS CBF in WM was observed to correlate positively with fractional anisotropy across subjects in parts of the splenium of corpus callosum, the right posterior thalamic radiation (including the optic radiation), the forceps major, the right inferior fronto-occipital fasciculus, the right inferior longitudinal fasciculus and the right superior longitudinal fasciculus. Furthermore, radial diffusivity correlated negatively with CBF across subjects in similar regions. Moreover, CBF and FA correlated positively across white matter tracts within subjects. CONCLUSION The currently observed findings on a macroscopic level might reflect the metabolic demand of white matter on a microscopic level involving myelination processes or axonal function. However, the exact underlying physiological mechanism of this relationship needs further evaluation.

Spatial Assessment of Erosion and its Impact on Soil Fertility in the Tajik Foothills

Efficient planning of soil conservation measures requires, first, to understand the impact of soil erosion on soil fertility with regard to local land cover classes; and second, to identify hot spots of soil erosion and bright spots of soil conservation in a spatially explicit manner. Soil organic carbon (SOC) is an important indicator of soil fertility. The aim of this study was to conduct a spatial assessment of erosion and its impact on SOC for specific land cover classes. Input data consisted of extensive ground truth, a digital elevation model and Landsat 7 imagery from two different seasons. Soil spectral reflectance readings were taken from soil samples in the laboratory and calibrated with results of SOC chemical analysis using regression tree modelling. The resulting model statistics for soil degradation assessments are promising (R2=0.71, RMSEV=0.32). Since the area includes rugged terrain and small agricultural plots, the decision tree models allowed mapping of land cover classes, soil erosion incidence and SOC content classes at an acceptable level of accuracy for preliminary studies. The various datasets were linked in the hot-bright spot matrix, which was developed to combine soil erosion incidence information and SOC content levels (for uniform land cover classes) in a scatter plot. The quarters of the plot show different stages of degradation, from well conserved land to hot spots of soil degradation. The approach helps to gain a better understanding of the impact of soil erosion on soil fertility and to identify hot and bright spots in a spatially explicit manner. The results show distinctly lower SOC content levels on large parts of the test areas, where annual crop cultivation was dominant in the 1990s and where cultivation has now been abandoned. On the other hand, there are strong indications that afforestations and fruit orchards established in the 1980s have been successful in conserving soil resources.

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.

Changes in species composition in alpine snowbeds with climate change inferred from small-scale spatial patterns

Alpine snowbeds are characterised by a very short growing season. However, the length of the snow-free period is increasingly prolonged due to climate change, so that snowbeds become susceptible to invasions from neighbouring alpine meadow communities. We hypothesised that spatial distribution of species generated by plant interactions may indicate whether snowbed species will coexist with or will be out-competed by invading alpine species – spatial aggregation or segregation will point to coexistence or competitive exclusion, respectively. We tested this hypothesis in snowbeds of the Swiss Alps using the variance ratio statistics. We focused on the relationships between dominant snowbed species, subordinate snowbed species, and potentially invading alpine grassland species. Subordinate snowbed species were generally spatially aggregated with each other, but were segregated from alpine grassland species. Competition between alpine grassland and subordinate snowbed species may have caused this segregation. Segregation between these species groups increased with earlier snowmelt, suggesting an increasing importance of competition with climate change. Further, a dominant snowbed species (Alchemilla pentaphyllea) was spatially aggregated with subordinate snowbed species, while two other dominants (Gnaphalium supinum and Salix herbacea) showed aggregated patterns with alpine grassland species. These dominant species are known to show distinct microhabitat preferences suggesting the existence of hidden microhabitats with different susceptibility to invaders. These results allow us to suggest that alpine snowbed areas are likely to be reduced as a consequence of climate change and that invading species from nearby alpine grasslands could outcompete subordinate snowbed species. On the other hand, microhabitats dominated by Gnaphalium or Salix seem to be particularly prone to invasions by non-snowbed species.

Contextualizing local-scale point sample data using global-scale spatial datasets: Lessons learnt from the analysis of large-scale land acquisitions

This paper examines how the geospatial accuracy of samples and sample size influence conclusions from geospatial analyses. It does so using the example of a study investigating the global phenomenon of large-scale land acquisitions and the socio-ecological characteristics of the areas they target. First, we analysed land deal datasets of varying geospatial accuracy and varying sizes and compared the results in terms of land cover, population density, and two indicators for agricultural potential: yield gap and availability of uncultivated land that is suitable for rainfed agriculture. We found that an increase in geospatial accuracy led to a substantial and greater change in conclusions about the land cover types targeted than an increase in sample size, suggesting that using a sample of higher geospatial accuracy does more to improve results than using a larger sample. The same finding emerged for population density, yield gap, and the availability of uncultivated land suitable for rainfed agriculture. Furthermore, the statistical median proved to be more consistent than the mean when comparing the descriptive statistics for datasets of different geospatial accuracy. Second, we analysed effects of geospatial accuracy on estimations regarding the potential for advancing agricultural development in target contexts. Our results show that the target contexts of the majority of land deals in our sample whose geolocation is known with a high level of accuracy contain smaller amounts of suitable, but uncultivated land than regional- and national-scale averages suggest. Consequently, the more target contexts vary within a country, the more detailed the spatial scale of analysis has to be in order to draw meaningful conclusions about the phenomena under investigation. We therefore advise against using national-scale statistics to approximate or characterize phenomena that have a local-scale impact, particularly if key indicators vary widely within a country.