Advancing the understanding of brain function with multivariate pattern analysis

Magdeburg, Univ., Fak. für Naturwiss., Diss., 2009

Behavior understanding in non-crowded and crowded scenes

Magdeburg, Univ., Fak. für , Diss., 2012

Understanding and monitoring attitudes of product properties over time

Magdeburg, Univ., Fak. für Informatik, Diss., 2015

Understanding sources of the change in international business cycles

Macroeconomic activity has become less volatile over the past three decades in most G7 economies. Current literature focuses on the characterization of the volatility reduction and explanations for this so called "moderation" in each G7 economy separately. In opposed to individual country analysis and individual variable analysis, this paper focuses on common characteristics of the reduction and common explanations for the moderation in G7 countries. In particular, we study three explanations: structural changes in the economy, changes in common international shocks and changes in domestic shocks. We study these explanations in a unified model structure. To this end, we propose a Bayesian factor structural vector autoregressive model. Using the proposed model, we investigate whether we can find common explanations for all G7 economies when information is pooled from multiple domestic and international sources. Our empirical analysis suggests that volatility reductions can largely be attributed to the decline in the magnitudes of the shocks in most G7 countries while only for the U.K., the U.S. and Italy they can partially be attributed to structural changes in the economy. Analyzing the components of the volatility, we also find that domestic shocks rather than common international shocks can account for a large part of the volatility reduction in most of the G7 countries. Finally, we find that after mid-1980s the structure of the economy changes substantially in five of the G7 countries: Germany, Italy, Japan, the U.K. and the U.S..

Understanding Interactions in Social Networks and Committees

While much of the literature on cross section dependence has focused mainly on estimation of the regression coefficients in the underlying model, estimation and inferences on the magnitude and strength of spill-overs and interactions has been largely ignored. At the same time, such inferences are important in many applications, not least because they have structural interpretations and provide useful interpretation and structural explanation for the strength of any interactions. In this paper we propose GMM methods designed to uncover underlying (hidden) interactions in social networks and committees. Special attention is paid to the interval censored regression model. Our methods are applied to a study of committee decision making within the Bank of England’s monetary policy committee.

Does Semantic Context Benefit Speech Understanding through "Top-Down" Processes? Evidence from Time-resolved Sparse fMRI.

When speech is degraded, word report is higher for semantically coherent sentences (e.g., her new skirt was made of denim) than for anomalous sentences (e.g., her good slope was done in carrot). Such increased intelligibility is often described as resulting from "top-down" processes, reflecting an assumption that higher-level (semantic) neural processes support lower-level (perceptual) mechanisms. We used time-resolved sparse fMRI to test for top-down neural mechanisms, measuring activity while participants heard coherent and anomalous sentences presented in speech envelope/spectrum noise at varying signal-to-noise ratios (SNR). The timing of BOLD responses to more intelligible speech provides evidence of hierarchical organization, with earlier responses in peri-auditory regions of the posterior superior temporal gyrus than in more distant temporal and frontal regions. Despite Sentence content × SNR interactions in the superior temporal gyrus, prefrontal regions respond after auditory/perceptual regions. Although we cannot rule out top-down effects, this pattern is more compatible with a purely feedforward or bottom-up account, in which the results of lower-level perceptual processing are passed to inferior frontal regions. Behavioral and neural evidence that sentence content influences perception of degraded speech does not necessarily imply "top-down" neural processes.

Understanding Liquidity and Credit Risks in the Financial Crisis

This paper develops a structured dynamic factor model for the spreads between London Interbank Offered Rate (LIBOR) and overnight index swap (OIS) rates for a panel of banks. Our model involves latent factors which reflect liquidity and credit risk. Our empirical results show that surges in the short term LIBOR-OIS spreads during the 2007-2009 fi nancial crisis were largely driven by liquidity risk. However, credit risk played a more signifi cant role in the longer term (twelve-month) LIBOR-OIS spread. The liquidity risk factors are more volatile than the credit risk factor. Most of the familiar events in the financial crisis are linked more to movements in liquidity risk than credit risk.

Understanding the vertical equity judgements underpinning health inequality measures

The choice of income-related health inequality measures in comparative studies is often determined by custom and analytical concerns, without much explicit consideration of the vertical equity judgements underlying alternative measures. This note employs an inequality map to illustrate how it these judgements that affect the ranking of populations by health inequality. In particular, it is shown that relative indices of inequality in health attainments and shortfalls embody distinct vertical equity judgments, where each may represent ethically defensible positions in specific contexts. Further research is needed to explore people’s preferences over distributions of income and health.

Developments in the scientific and clinical understanding of gout.

Gout is the most common form of inflammatory arthritis in the elderly. In the last two decades, both hyperuricemia and gout have increased markedly and similar trends in the epidemiology of the metabolic syndrome have been observed. Recent studies provide new insights into the transporters that handle uric acid in the kidney as well as possible links between these transporters, hyperuricemia, and hypertension. The treatment of established hyperuricemia has also seen new developments. Febuxostat and PEG-uricase are two novel treatments that have been evaluated and shown to be highly effective in the management of hyperuricemia, thus enlarging the therapeutic options available to lower uric acid levels. Monosodium urate (MSU) crystals are potent inducers of inflammation. Within the joint, they trigger a local inflammatory reaction, neutrophil recruitment, and the production of pro-inflammatory cytokines as well as other inflammatory mediators. Experimentally, the uptake of MSU crystals by monocytes involves interactions with components of the innate immune system, namely Toll-like receptor (TLR)-2, TLR-4, and CD14. Intracellularly, MSU crystals activate multiple processes that lead to the formation of the NALP-3 (NACHT, LRR, and pyrin domain-containing-3) inflammasome complex that in turn processes pro-interleukin (IL)-1 to yield mature IL-1 beta, which is then secreted. The inflammatory effects of MSU are IL-1-dependent and can be blocked by IL-1 inhibitors. These advances in the understanding of hyperuricemia and gout provide new therapeutic targets for the future.

The geographic understanding of snail borne disease in endemic areas using satellite surveillance

The current status of research on use of earth observing satellite sensors and geographic ifnormation systems for control program management of schistosomiais and fascioliasis is reviewed.

Understanding the low-temperature limitations to forest growth through calibration of a forest dynamics model with tree-ring data

The sensitivity of altitudinal and latitudinal tree-line ecotones to climate change, particularly that of temperature, has received much attention. To improve our understanding of the factors affecting tree-line position, we used the spatially explicit dynamic forest model TreeMig. Although well-suited because of its landscape dynamics functions, TreeMig features a parabolic temperature growth response curve, which has recently been questioned. and the species parameters are not specifically calibrated for cold temperatures. Our main goals were to improve the theoretical basis of the temperature growth response curve in the model and develop a method for deriving that curve's parameters from tree-ring data. We replaced the parabola with an asymptotic curve, calibrated for the main species at the subalpine (Swiss Alps: Pinus cembra, Larix decidua, Picea abies) and boreal (Fennoscandia: Pinus sylvestris, Betula pubescens, P. abies) tree-lines. After fitting new parameters, the growth curve matched observed tree-ring widths better. For the subalpine species, the minimum degree-day sum allowing, growth (kDDMin) was lowered by around 100 degree-days; in the case of Larix, the maximum potential ring-width was increased to 5.19 mm. At the boreal tree-line, the kDDMin for P. sylvestris was lowered by 210 degree-days and its maximum ring-width increased to 2.943 mm; for Betula (new in the model) kDDMin was set to 325 degree-days and the maximum ring-width to 2.51 mm; the values from the only boreal sample site for Picea were similar to the subalpine ones, so the same parameters were used. However, adjusting the growth response alone did not improve the model's output concerning species' distributions and their relative importance at tree-line. Minimum winter temperature (MinWiT, mean of the coldest winter month), which controls seedling establishment in TreeMig, proved more important for determining distribution. Picea, P. sylvestris and Betula did not previously have minimum winter temperature limits, so these values were set to the 95th percentile of each species' coldest MinWiT site (respectively -7, -11, -13). In a case study for the Alps, the original and newly calibrated versions of TreeMig were compared with biomass data from the National Forest Inventor), (NFI). Both models gave similar, reasonably realistic results. In conclusion, this method of deriving temperature responses from tree-rings works well. However, regeneration and its underlying factors seem more important for controlling species' distributions than previously thought. More research on regeneration ecology, especially at the upper limit of forests. is needed to improve predictions of tree-line responses to climate change further.

The contribution of aging to the understanding of the dimensionality of executive functions.

It has been reported in the literature that executive functions may be fractioned into updating, shifting, and inhibition. The present study aimed to explore whether these executive sub-components can be identified in a more age-heterogeneous sample and see if they are prone to an age-related decline. We tested the performances of 81 individuals aged from 18 to 88 years old in each executive sub-component, working memory, fluid intelligence and processing speed. Correlation analysis revealed only a slight positive relationship between the two updating measures. A linear decrement with age was observed only for two complex executive tests. Tasks indexing working memory, processing speed and fluid intelligence showed a stronger linear decline with age than executive tasks. In conclusion, our results did not replicate the executive structure known from the literature, and revealed that decrement in executive function is not an unavoidable concomitant of aging but rather concerns specific executive tasks.