Experimental research: problems and opportunities in the big-data era

Experimental research in psychology, psycholinguistics or medicine provides quantitative and therefore seemingly conclusive and trustworthy evidence. However, it has been convincingly shown that most research findings are actually false. This has hardly influenced the dominant scientific evaluation system which reflects a continued trust in the unbiasedness of data by a strong reliance on simple quantifications of scientific quality and productivity, such as number of publications and number of citations. This state of affairs is remarkable in the light of a long history of strong criticism of commonly used inference methods and scientific evaluation systems, which is now backed by large-scale research projects directly questioning the reproducibility of scientific findings. This way, the large amounts of data – “big-data” – have helped to uncover some of these problematic issues, but also provided a more open attitude towards data and code sharing. In addition, novel analytic frameworks may help to better integrate empirical data with computational models

The development of an fMRI protocol to investigate vmPFC network topology underlying the generalization of behavioral control

Description: Experiencing behavioral control over stress can have long lasting and generalizing effects. The controllability of a physical threat, for example, affects the processing of subsequent social stress. Animal research has shown that the vmPFC plays a critical role in behavioral control and orchestrating subcortical responses. However, translational research on these neural systems in humans is sparse and we therefore aimed to develop a paradigm to test the generalization effect of behavioral control on vmPFC functioning. A pilot study was performed in which subjects (n=18) were first randomly assigned to one of two versions of a signal detection task, where feedback was either paired with a controllable or an uncontrollable mild shock. Subsequently, subjects underwent a social evaluative threat fMRI paradigm to measure their response to the anticipation of speaking in public. The analyses tested whether the controllability manipulation influenced behavioral and physiological responses and vmPFC network topology. Results showed that overall subjects were faster to respond to potential shock trials in the signal detection task, and there was a trend significant difference between the controllable or uncontrollable group. No significant differences between the two groups were observed on other behavioral or physiological responses. fMRI results showed higher vmPFC efficiency in the controllable threat group at baseline and recovery but similar to the uncontrollable group during speech anticipation. The current report establishes the feasibility of the protocol and adequately-powered follow-up research is needed to further evaluate the generalization effect on the behavioral, physiological and neural level

In vivo "real-time" monitoring of glucose in the brain with an amperometric enzyme-based biosensor based on gold coated tungsten (W-Au) microelectrodes

Biosensors based on Pt or Pt/Ir based needle-type microelectrodes have been successfully employed for continuous in vivo real-time brain biomonitoring of biomarkers such as glutamate and glucose. However, when implanted, these biosensors often bend, thereby damaging its surface and degrading its bioanalytical properties. In addition, downscaling of Pt and Pt/Ir needle-type biosensors, to improve the spatial resolution and decrease tissue damage, is technically challenging. In that sense, we investigated whether the use of a material with low malleability, tungsten (W), coated with a highly conductive material, gold (Au) could be as an alternative for conventional needle-type based biosensors. Therefore, we developed implantable needle-type (50 tim 0) gold coated tungsten (W-Au) amperometric microbiosensors. First, we evaluated electrochemically, the ability of W-Au microelectrodes (50 tim 0) to continuously monitor changes in H2O2. After, we functionalized, using a layer-by-layer assembly, the surface of W-Au microelectrodes. First with permselective membrane(s) (Nafion and Nafion-PPD) and after with an enzymatic hydrogel, containing an enzyme selective for glucose (glucose oxidase). Both the enzyme loading and the applied potential were optimized and the performance of functionalized W-Au microelectrodes and fully assembled biosensors was evaluated electrochemically. Additionally, the surface of bare and functionalized microelectrodes was also characterized by imaging techniques (scanning electron microscopy). In vivo experiments revealed that, W-Au based glucose biosensors, were able to accurately monitor, in real-time, changes in brain glucose in response to relevant pharmacological challenges. (C) 2018 Elsevier B.V. All rights reserved

Cost-effectiveness analysis of a first-trimester screening test for preterm preeclampsia in the Netherlands

Objectives: The risk of preterm preeclampsia (PT PE) can significantly be reduced by starting acetylsalicylic acid ≤ 16 weeks of gestational age. First trimester predictive models based on maternal risk factors to effectively start this therapy lacked sufficient power, but recent studies showed that these models can be improved by including test results of biochemical and/or -physical markers. To investigate whether testing a biochemical marker in the first trimester is cost-effective in the Netherlands, a cost-effectiveness analysis was performed in this study. Study design: The outcome of this study was expressed as an incremental cost-effectiveness ratio (ICER) with as effect prevented PT PE cases. To evaluate the impact of each model parameter and to determine model uncertainties, both univariate and probabilistic sensitivity analyses were performed. Results: When compared to the baseline strategy, the test strategy is estimated to save almost 4 million euros per year on a national scale and at the same time this would prevent an additional 228 PT PE cases. The sensitivity analyses showed that the major drivers of the result are the costs to monitor a high-risk pregnancy and the specificity and that most of the model simulations were in the southeast quadrant: cost saving and more prevented complications. Conclusions: This study showed that a first-trimester test strategy to screen for PT PE in the first trimester is potentially cost-effective in the Dutch healthcare setting. The fact that the specificity is a major driver of the ICER indicates the importance for a (new) screening model to correctly classify low-risk pregnancies.</p

i3DMM: Deep Implicit 3D Morphable Model of Human Heads

We present the first deep implicit 3D morphable model (i3DMM) of full heads. Unlike earlier morphable face models it not only captures identity-specific geometry, texture, and expressions of the frontal face, but also models the entire head, including hair. We collect a new dataset consisting of 64 people with different expressions and hairstyles to train i3DMM. Our approach has the following favorable properties: (i) It is the first full head morphable model that includes hair. (ii) In contrast to mesh-based models it can be trained on merely rigidly aligned scans, without requiring difficult non-rigid registration. (iii) We design a novel architecture to decouple the shape model into an implicit reference shape and a deformation of this reference shape. With that, dense correspondences between shapes can be learned implicitly. (iv) This architecture allows us to semantically disentangle the geometry and color components, as color is learned in the reference space. Geometry is further disentangled as identity, expressions, and hairstyle, while color is disentangled as identity and hairstyle components. We show the merits of i3DMM using ablation studies, comparisons to state-of-the-art models, and applications such as semantic head editing and texture transfer. We will make our model publicly available

Parametric, nonparametric and parametric modelling of a chaotic circuit time series

The determination of a differential equation underlying a measured time series is a frequently arising task in nonlinear time series analysis. In the validation of a proposed model one often faces the dilemma that it is hard to decide whether possible discrepancies between the time series and model output are caused by an inappropriate model or by bad estimates of parameters in a correct type of model, or both. We propose a combination of parametric modelling based on Bock's multiple shooting algorithm and nonparametric modelling based on optimal transformations as a strategy to test proposed models and if rejected suggest and test new ones. We exemplify this strategy on an experimental time series from a chaotic circuit where we obtain an extremely accurate reconstruction of the observed attractor.Comment: 19 pages, 8 Fig