Estimating and quantifying uncertainties on level sets using the Vorob'ev expectation and deviation with Gaussian process models

Several methods based on Kriging have recently been proposed for calculating a probability of failure involving costly-to-evaluate functions. A closely related problem is to estimate the set of inputs leading to a response exceeding a given threshold. Now, estimating such a level set—and not solely its volume—and quantifying uncertainties on it are not straightforward. Here we use notions from random set theory to obtain an estimate of the level set, together with a quantification of estimation uncertainty. We give explicit formulae in the Gaussian process set-up and provide a consistency result. We then illustrate how space-filling versus adaptive design strategies may sequentially reduce level set estimation uncertainty.

Hierarchical segmentation-assisted multimodal registration for MR brain images

Information theory-based metric such as mutual information (MI) is widely used as similarity measurement for multimodal registration. Nevertheless, this metric may lead to matching ambiguity for non-rigid registration. Moreover, maximization of MI alone does not necessarily produce an optimal solution. In this paper, we propose a segmentation-assisted similarity metric based on point-wise mutual information (PMI). This similarity metric, termed SPMI, enhances the registration accuracy by considering tissue classification probabilities as prior information, which is generated from an expectation maximization (EM) algorithm. Diffeomorphic demons is then adopted as the registration model and is optimized in a hierarchical framework (H-SPMI) based on different levels of anatomical structure as prior knowledge. The proposed method is evaluated using Brainweb synthetic data and clinical fMRI images. Both qualitative and quantitative assessment were performed as well as a sensitivity analysis to the segmentation error. Compared to the pure intensity-based approaches which only maximize mutual information, we show that the proposed algorithm provides significantly better accuracy on both synthetic and clinical data.

Expectation-based types of volunteers in Swiss sports clubs

Volunteer research in sports clubs has paid hardly any attention to the individual expectations even though matching conditions to the specific volunteer’s expectations represents a major management challenge. This article presents a person-oriented approach to the expectation profiles of volunteers that delivers the basis for identifying different volunteer segments. The approach assumes explicitly that volunteers in sports clubs develop specific expectations regarding their working conditions. These expectations were determined in a sample of 441 members of 45 selected sports clubs. Proximately, a cluster analysis revealed that volunteers vary in their expectations regarding voluntary work. Four different types of volunteers could be identified: (1) recognition seekers, (2) material incentive seekers, (3) participation and communication seekers, and (4) support seekers. These “expectation-based volunteer types” could also be characterized in socioeconomic, membershiprelated, and volunteer-work-related terms. These types could serve as a basis for designing specific voluntary work conditions in sports clubs.

Proactive motivation and engagement in career behaviors: Investigating direct, mediated, and moderated effects

Proactive career behaviors become increasingly important in today's career environment, but little is known about how and when motivational patterns affect individual differences. In a six-month longitudinal study among German university students (Study 1; N = 289) it was demonstrated that motivation in terms of “can do” (self-efficacy and context beliefs), “reason to” (autonomous career goals), and “energized to” (positive affect) significantly predicted career behaviors. Contrary to expectation, negative context beliefs had a positive effect when combined with other motivational states. Study 2 replicated and extended those results by investigating whether “can do” motivation mediates the effect of proactive personality and whether those effects are conditional upon the degree of career choice decidedness. We tested a moderated multiple mediation model with a unique sample of 134 German students, assessed three times, each interval being 6 weeks apart. The results showed that effects of proactivity were partially carried through higher self-efficacy beliefs but not context beliefs. Supporting a moderation model, indirect effects through self-efficacy beliefs were not present for students with very low decidedness.

Conditional and inducible transgene expression in endothelial and hematopoietic cells using Cre/loxP and tetracycline-off systems

In the present study, the tetracycline-off and Cre/loxP systems were combined to gain temporal and spatial control of transgene expression. Mice were generated that carried three transgenes: Tie2-tTA, tet-O-Cre and either the ZEG or ZAP reporter. Tie2-tTA directs expression of tetracycline-controlled transactivator (tTA) in endothelial and hematopoietic cells under the control of the Tie2 promoter. Tet-O-Cre produces Cre recombinase from a minimal promoter containing the tet-operator (tetO). ZEG or ZAP contains a strong promoter and a loxP-flanked stop sequence, followed by an enhanced green fluorescence protein (EGFP) or human placental alkaline phosphatase (hPLAP) reporter. In the presence of tetracycline, the tTA transactivator produced by Tie-2-tTA is disabled and Cre is not expressed. In the absence of tetracycline, the tTA binds tet-O-Cre to drive the expression of Cre, which recombines the loxP sites of the ZEG or ZAP transgene and results in reporter gene expression. In the present study, the expression of the ZEG or ZAP reporter genes in embryos and adult animals with and without tetracycline treatment was examined. In the presence of tetracycline, no reporter gene expression was observed. When tetracycline was withdrawn, Cre excision was activated and the reporter genes were detected in endothelial and hematopoietic cells. These results demonstrate that this system may be used to bypass embryonic lethality and access adult phenotypes.

Postnatal Notch1 activation induces T‑cell malignancy in conditional and inducible mouse models

The Notch1 signaling pathway is essential for hematopoietic development. However, the effects of postnatal activation of Notch1 signaling on hematopoietic system is not yet fully understood. We previously generated ZEG‑IC‑Notch1 transgenic mice that have a floxed β‑geo/stop signal between a CMV promoter and intracellular domain of Notch1 (IC‑Notch1). Constitutively active IC‑Notch1 is silent until the introduction of Cre recombinase. In this study, endothelial/hematopoietic specific expression of IC‑Notch1 in double transgenic ZEG‑IC‑Notch1/Tie2‑Cre embryos induced embryonic lethality at E9.5 with defects in vascular system but not in hematopoietic system. Inducible IC‑Notch1 expression in adult mice was achieved by using tetracycline regulated Cre system. The ZEG‑IC‑Notch1/Tie2‑tTA/tet‑O‑Cre triple transgenic mice survived embryonic development when maintained on tetracycline. Post‑natal withdrawal of tetracycline induced expression of IC‑Notch1 transgene in hematopoietic cells of adult mice. The triple transgenic mice displayed extensive T‑cell infiltration in multiple organs and T‑cell malignancy of lymph nodes. In addition, the protein levels of p53 and alternative reading frame (ARF) were decreased in lymphoma‑like neoplasms from the triple transgenic mice while their mRNA expression remained unchanged, suggesting that IC‑Notch1 might repress ARF‑p53 pathway by a post‑transcriptional mechanism. This study demonstrated that activation of constitutive Notch1 signaling after embryonic development alters adult hematopoiesis and induces T‑cell malignancy.

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.

Binary recombinase systems for high-resolution conditional mutagenesis.

Conditional mutagenesis using Cre recombinase expressed from tissue specific promoters facilitates analyses of gene function and cell lineage tracing. Here, we describe two novel dual-promoter-driven conditional mutagenesis systems designed for greater accuracy and optimal efficiency of recombination. Co-Driver employs a recombinase cascade of Dre and Dre-respondent Cre, which processes loxP-flanked alleles only when both recombinases are expressed in a predetermined temporal sequence. This unique property makes Co-Driver ideal for sequential lineage tracing studies aimed at unraveling the relationships between cellular precursors and mature cell types. Co-InCre was designed for highly efficient intersectional conditional transgenesis. It relies on highly active trans-splicing inteins and promoters with simultaneous transcriptional activity to reconstitute Cre recombinase from two inactive precursor fragments. By generating native Cre, Co-InCre attains recombination rates that exceed all other binary SSR systems evaluated in this study. Both Co-Driver and Co-InCre significantly extend the utility of existing Cre-responsive alleles.

Disentangling mental imagery and perceptual expectation

Mental imagery and perception are thought to rely on similar neural circuits, and many recent behavioral studies have attempted to demonstrate interactions between actual physical stimulation and sensory imagery in the corresponding sensory modality. However, there has been a lack of theoretical understanding of the nature of these interactions, and both interferential and facilitatory effects have been found. Facilitatory effects appear strikingly similar to those that arise due to experimental manipulations of expectation. Using a self-motion discrimination task, we try to disentangle the effects of mental imagery from those of expectation by using a hierarchical drift diffusion model to investigate both choice data and response times. Manipulations of expectation are reasonably well understood in terms of their selective influence on parameters of the drift diffusion model, and in this study, we make the first attempt to similarly characterize the effects of mental imagery. We investigate mental imagery within the computational framework of control theory and state estimation. • Mental imagery and perception are thought to rely on similar neural circuits; however, on more theoretical grounds, imagery seems to be closely related to the output of forward models (sensory predictions). • We reanalyzed data from a study of imagined self-motion. • Bayesian modeling of response times may allow us to disentangle the effects of mental imagery on behavior from other cognitive (top-down) effects, such as expectation.