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It has recently been demonstrated that the presentation of a rare target in a visual oddball paradigm induces a prolonged inhibition of microsaccades. In the field of electrophysiology, the amplitude of the P300 component in event-related potentials (ERP) has been shown to be sensitive to the stimulus category (target vs. non target) of the eliciting stimulus, its overall probability, and the preceding stimulus sequence. In the present study we further specify the functional underpinnings of the prolonged microsaccadic inhibition in the visual oddball task, showing that the stimulus category, the frequency of a stimulus and the preceding stimulus sequence influence microsaccade rate. Furthermore, by co-recording ERPs and eye-movements, we were able to demonstrate that, despite being largely sensitive to the same experimental manipulation, the amplitude of P300 and the microsaccadic inhibition predict each other very weakly, and thus constitute two independent measures of the brain’s response to rare targets in the visual oddball paradigm.
Prediction of hybrid biomass in Arabidopsis thaliana by selected parental SNP and metabolic markers
(2009)
A recombinant inbred line (RIL) population, derived from two Arabidopsis thaliana accessions, and the corresponding testcrosses with these two original accessions were used for the development and validation of machine learning models to predict the biomass of hybrids. Genetic and metabolic information of the RILs served as predictors. Feature selection reduced the number of variables (genetic and metabolic markers) in the models by more than 80% without impairing the predictive power. Thus, potential biomarkers have been revealed. Metabolites were shown to bear information on inherited macroscopic phenotypes. This proof of concept could be interesting for breeders. The example population exhibits substantial mid-parent biomass heterosis. The results of feature selection could therefore be used to shed light on the origin of heterosis. In this respect, mainly dominance effects were detected.
Prediction of hybrid biomass in Arabidopsis thaliana by selected parental SNP and metabolic markers
(2009)
A recombinant inbred line (RIL) population, derived from two Arabidopsis thaliana accessions, and the corresponding testcrosses with these two original accessions were used for the development and validation of machine learning models to predict the biomass of hybrids. Genetic and metabolic information of the RILs served as predictors. Feature selection reduced the number of variables (genetic and metabolic markers) in the models by more than 80% without impairing the predictive power. Thus, potential biomarkers have been revealed. Metabolites were shown to bear information on inherited macroscopic phenotypes. This proof of concept could be interesting for breeders. The example population exhibits substantial mid-parent biomass heterosis. The results of feature selection could therefore be used to shed light on the origin of heterosis. In this respect, mainly dominance effects were detected.
Business process management experiences a large uptake by the industry, and process models play an important role in the analysis and improvement of processes. While an increasing number of staff becomes involved in actual modeling practice, it is crucial to assure model quality and homogeneity along with providing suitable aids for creating models. In this paper we consider the problem of offering recommendations to the user during the act of modeling. Our key contribution is a concept for defining and identifying so-called action patterns - chunks of actions often appearing together in business processes. In particular, we specify action patterns and demonstrate how they can be identified from existing process model repositories using association rule mining techniques. Action patterns can then be used to suggest additional actions for a process model. Our approach is challenged by applying it to the collection of process models from the SAP Reference Model.
We examined individual differences in masked repetition priming by re-analyzing item-level response-time (RT) data from three experiments. Using a linear mixed model (LMM) with subjects and items specified as crossed random factors, the originally reported priming and word-frequency effects were recovered. In the same LMM, we estimated parameters describing the distributions of these effects across subjects. Subjects’ frequency and priming effects correlated positively with each other and negatively with mean RT. These correlation estimates, however, emerged only with a reciprocal transformation of RT (i.e., -1/RT), justified on the basis of distributional analyses. Different correlations, some with opposite sign, were obtained (1) for untransformed or logarithmic RTs or (2) when correlations were computed using within-subject analyses. We discuss the relevance of the new results for accounts of masked priming, implications of applying RT transformations, and the use of LMMs as a tool for the joint analysis of experimental effects and associated individual differences.
Two dimensional gas chromatography coupled to time-of-flight mass spectrometry (GCxGC-TOF-MS) is a promising technique to overcome limits of complex metabolome analysis using one dimensional GC-TOF-MS. Especially at the stage of data export and data mining, however, convenient procedures to cope with the complexity of GCxGC-TOF-MS data are still in development. Here, we present a high sample throughput protocol exploiting first and second retention index for spectral library search and subsequent construction of a high dimensional data matrix useful for statistical analysis. The method was applied to the analysis of 13 C-labelling experiments in the unicellular green alga Chlamydomonas reinhardtii. We developed a rapid sampling and extraction procedure for Chlamydomonas reinhardtii laboratory strain (CC503), a cell wall deficient mutant. By testing all published quenching protocols we observed dramatic metabolite leakage rates for certain metabolites. To circumvent metabolite leakage, samples were directly quenched and analyzed without separation of the medium. The growth medium was adapted to this rapid sampling protocol to avoid interference with GCxGC-TOF-MS analysis. To analyse batches of samples a new software tool, MetMax, was implemented which extracts the isotopomer matrix from stable isotope labelling experiments together with the first and second retention index (RI1 and RI2). To exploit RI1 and RI2 for metabolite identification we used the Golm metabolome database (GMD [1] with RI1/ RI2-reference spectra and new search algorithms. Using those techniques we analysed the dynamics of (CO2)-C-13 and C-13- acetate uptake in Chlamydomonas reinhardtii cells in two different steady states namely photoautotrophic and mixotrophic growth conditions.
Complex network theory provides an elegant and powerful framework to statistically investigate the topology of local and long range dynamical interrelationships, i.e., teleconnections, in the climate system. Employing a refined methodology relying on linear and nonlinear measures of time series analysis, the intricate correlation structure within a multivariate climatological data set is cast into network form. Within this graph theoretical framework, vertices are identified with grid points taken from the data set representing a region on the the Earth's surface, and edges correspond to strong statistical interrelationships between the dynamics on pairs of grid points. The resulting climate networks are neither perfectly regular nor completely random, but display the intriguing and nontrivial characteristics of complexity commonly found in real world networks such as the internet, citation and acquaintance networks, food webs and cortical networks in the mammalian brain. Among other interesting properties, climate networks exhibit the "small-world" effect and possess a broad degree distribution with dominating super-nodes as well as a pronounced community structure. We have performed an extensive and detailed graph theoretical analysis of climate networks on the global topological scale focussing on the flow and centrality measure betweenness which is locally defined at each vertex, but includes global topological information by relying on the distribution of shortest paths between all pairs of vertices in the network. The betweenness centrality field reveals a rich internal structure in complex climate networks constructed from reanalysis and atmosphere-ocean coupled general circulation model (AOGCM) surface air temperature data. Our novel approach uncovers an elaborately woven meta-network of highly localized channels of strong dynamical information flow, that we relate to global surface ocean currents and dub the backbone of the climate network in analogy to the homonymous data highways of the internet. This finding points to a major role of the oceanic surface circulation in coupling and stabilizing the global temperature field in the long term mean (140 years for the model run and 60 years for reanalysis data). Carefully comparing the backbone structures detected in climate networks constructed using linear Pearson correlation and nonlinear mutual information, we argue that the high sensitivity of betweenness with respect to small changes in network structure may allow to detect the footprints of strongly nonlinear physical interactions in the climate system. The results presented in this thesis are thoroughly founded and substantiated using a hierarchy of statistical significance tests on the level of time series and networks, i.e., by tests based on time series surrogates as well as network surrogates. This is particularly relevant when working with real world data. Specifically, we developed new types of network surrogates to include the additional constraints imposed by the spatial embedding of vertices in a climate network. Our methodology is of potential interest for a broad audience within the physics community and various applied fields, because it is universal in the sense of being valid for any spatially extended dynamical system. It can help to understand the localized flow of dynamical information in any such system by combining multivariate time series analysis, a complex network approach and the information flow measure betweenness centrality. Possible fields of application include fluid dynamics (turbulence), plasma physics and biological physics (population models, neural networks, cell models). Furthermore, the climate network approach is equally relevant for experimental data as well as model simulations and hence introduces a novel perspective on model evaluation and data driven model building. Our work is timely in the context of the current debate on climate change within the scientific community, since it allows to assess from a new perspective the regional vulnerability and stability of the climate system while relying on global and not only on regional knowledge. The methodology developed in this thesis hence has the potential to substantially contribute to the understanding of the local effect of extreme events and tipping points in the earth system within a holistic global framework.
Microsaccades are very small, involuntary flicks in eye position that occur on average once or twice per second during attempted visual fixation. Microsaccades give rise to EMG eye muscle spikes that can distort the spectrum of the scalp EEG and mimic increases in gamma band power. Here we demonstrate that microsaccades are also accompanied by genuine and sizeable cortical activity, manifested in the EEG. In three experiments, high-resolution eye movements were corecorded with the EEG: during sustained fixation of checkerboard and face stimuli and in a standard visual oddball task that required the counting of target stimuli. Results show that microsaccades as small as 0.15° generate a field potential over occipital cortex and midcentral scalp sites 100 –140 ms after movement onset, which resembles the visual lambda response evoked by larger voluntary saccades. This challenges the standard assumption of human brain imaging studies that saccade-related brain activity is precluded by fixation, even when fully complied with. Instead, additional cortical potentials from microsaccades were present in 86% of the oddball task trials and of similar amplitude as the visual response to stimulus onset. Furthermore, microsaccade probability varied systematically according to the proportion of target stimuli in the oddball task, causing modulations of late stimulus-locked event-related potential (ERP) components. Microsaccades present an unrecognized source of visual brain signal that is of interest for vision research and may have influenced the data of many ERP and neuroimaging studies.
Bundistinnen
(2009)
Pri ha-Pardes (Früchte des Obstgartens) ist eine Reihe der Vereinigung für Jüdische Studien e.V., welche in Verbindung mit dem Zentrum für Jüdische Studien der Universität Potsdam publiziert wird. Pri ha-Pardes möchte kleineren wissenschaftlichen Studien, Forschungen am Rande der großen Disziplinen und exzellenten Masterarbeiten eine Publikationsplattform bieten. Im fünften Band der Reihe Pri ha-Pardes skizziert Rebekka Denz die Geschichte von Frauen im Allgemeinen Jüdischen Arbeiterbund („Bund“) seit seiner Gründung 1897 bis zum Jahr 1939. Durch das Prisma der gewählten Hauptquelle ─ die Frauenbiographien der „Doires Bundistn“, einer jiddischsprachigen Biographiensammlung verfasst von Mitgliedern des „Bund“ ─ werden das Mitwirken und die Bedeutung von Frauen in dieser sozialistischen, jiddischistischen Bewegung Ost(mittel)europas dargestellt. Zudem wird ein erster Versuch unternommen, diesen Teil der bundischen Parteigeschichtsschreibung hinsichtlich ihrer (Re-) Konstruktionsprinzipien zu lesen. Die Arbeit gliedert sich dabei analog zum bundischen Selbstverständnis und der geographischen Verschiebung seines Hauptwirkungsfeldes in zwei Teile: Frauen im „Russischen Bund“ (1897-1917) und Frauen im „Polnischen Bund“ (1918-1939). Die Auswirkungen der unterschiedlichen historischen Kontexte auf lebensweltliche Aspekte, Tätigkeiten in Bewegung und Partei sowie Tendenzen der Lebensgestaltung der Bundistinnen werden anhand von drei Vergleichskapiteln aufgezeigt; weitere Einzelkapitel behandeln zeitspezifische Aspekte. Die Instabilität der Lebensverhältnisse für die Mitglieder im illegalen „Russischen Bund“ bzw. die größere Stabilität in der Zeit des „Bund“ in Polen als legale Partei bilden wichtige, bislang vernachlässigte Faktoren bei der Betrachtung der weiblichen Lebensmuster.