Recurrent antitopographic inhibition mediates competitive stimulus selection in an attention network

Topographically organized neurons represent multiple stimuli within complex visual scenes and compete for subsequent processing in higher visual centers. The underlying neural mechanisms of this process have long been elusive. We investigate an experimentally constrained model of a midbrain structure: the optic tectum and the reciprocally connected nucleus isthmi. We show that a recurrent antitopographic inhibition mediates the competitive stimulus selection between distant sensory inputs in this visual pathway. This recurrent antitopographic inhibition is fundamentally different from surround inhibition in that it projects on all locations of its input layer, except to the locus from which it receives input. At a larger scale, the model shows how a focal top-down input from a forebrain region, the arcopallial gaze field, biases the competitive stimulus selection via the combined activation of a local excitation and the recurrent antitopographic inhibition. Our findings reveal circuit mechanisms of competitive stimulus selection and should motivate a search for anatomical implementations of these mechanisms in a range of vertebrate attentional systems.

Cell therapies for heart function recovery: focus on myocardial tissue engineering and nanotechnologies

Cell therapies have gained increasing interest and developed in several approaches related to the treatment of damaged myocardium. The results of multiple clinical trials have already been reported, almost exclusively involving the direct injection of stem cells. It has, however, been postulated that the efficiency of injected cells could possibly be hindered by the mechanical trauma due to the injection and their low survival in the hostile environment. It has indeed been demonstrated that cell mortality due to the injection approaches 90%. Major issues still need to be resolved and bed-to-bench followup is paramount to foster clinical implementations. The tissue engineering approach thus constitutes an attractive alternative since it provides the opportunity to deliver a large number of cells that are already organized in an extracellular matrix. Recent laboratory reports confirmed the interest of this approach and already encouraged a few groups to investigate it in clinical studies. We discuss current knowledge regarding engineered tissue for myocardial repair or replacement and in particular the recent implementation of nanotechnological approaches.

Optimized quantitative magnetic resonance spectroscopy for clinical routine

Several practical obstacles in data handling and evaluation complicate the use of quantitative localized magnetic resonance spectroscopy (qMRS) in clinical routine MR examinations. To overcome these obstacles, a clinically feasible MR pulse sequence protocol based on standard available MR pulse sequences for qMRS has been implemented along with newly added functionalities to the free software package jMRUI-v5.0 to make qMRS attractive for clinical routine. This enables (a) easy and fast DICOM data transfer from the MR console and the qMRS-computer, (b) visualization of combined MR spectroscopy and imaging, (c) creation and network transfer of spectroscopy reports in DICOM format, (d) integration of advanced water reference models for absolute quantification, and (e) setup of databases containing normal metabolite concentrations of healthy subjects. To demonstrate the work-flow of qMRS using these implementations, databases for normal metabolite concentration in different regions of brain tissue were created using spectroscopic data acquired in 55 normal subjects (age range 6-61 years) using 1.5T and 3T MR systems, and illustrated in one clinical case of typical brain tumor (primitive neuroectodermal tumor). The MR pulse sequence protocol and newly implemented software functionalities facilitate the incorporation of qMRS and reference to normal value metabolite concentration data in daily clinical routine. Magn Reson Med, 2013. © 2012 Wiley Periodicals, Inc.

Flattening Traits

Traits are fine-grained components that can be used to compose classes, while avoiding many of the problems of multiple inheritance and mixin-based approaches. Since most implementations of traits have focused on dynamically-typed languages, the question naturally arises, how can one best introduce traits to statically-typed languages, like Java and C#?

FAME, A Polyglot Library for Metamodeling at Runtime

Tomorrow's eternal software system will co-evolve with their context: their metamodels must adapt at runtime to ever-changing external requirements. In this paper we present FAME, a polyglot library that keeps metamodels accessible and adaptable at runtime. Special care is taken to establish causal connection between fame-classes and host-classes. As some host-languages offer limited reflection features only, not all implementations feature the same degree of causal connection. We present and discuss three scenarios: 1) full causal connection, 2) no causal connection, and 3) emulated causal connection. Of which, both Scenario 1 and 3 are suitable to deploy fully metamodel-driven applications.

Safe Reflection Through Polymorphism

Code executed in a fully reflective system switches back and forth between application and interpreter code. These two states can be seen as contexts in which an expression is evaluated. Current language implementations obtain reflective capabilities by exposing objects to the interpreter. However, in doing so these systems break the encapsulation of the application objects. In this paper we propose safe reflection through polymorphism, \ie by unifying the interface and ensuring the encapsulation of objects from both the interpreter and application context. We demonstrate a \emphhomogeneous system that defines the execution semantics in terms of itself, thus enforcing that encapsulation is not broken.

PyGirl: Generating Whole-System VMs from High-Level Prototypes Using PyPy

Virtual machines (VMs) emulating hardware devices are generally implemented in low-level languages for performance reasons. This results in unmaintainable systems that are difficult to understand. In this paper we report on our experience using the PyPy toolchain to improve the portability and reduce the complexity of whole-system VM implementations. As a case study we implement a VM prototype for a Nintendo Game Boy, called PyGirl, in which the high-level model is separated from low-level VM implementation issues. We shed light on the process of refactoring from a low-level VM implementation in Java to a high-level model in RPython. We show that our whole-system VM written with PyPy is significantly less complex than standard implementations, without substantial loss in performance.

The effect of figures in CCS communication

Illustrations are an essential part of most CCS communication materials. This article looks at the role of illustrations in communication and education in general, and in CCS communication in particular. First, literature on multimedia learning is reviewed and general guidelines for designing graphical displays deduced. This is followed by a discussion of relevant mental models and their possible implementa- tion in pictorial form. The authors then report on an interview study in which illustrations with various implementations of CCS mental models are compared. No major differences were found regarding under- standing of CCS between the different illustrations. Graphical displays alone are not powerful enough to implicitly correct typical misconceptions about CCS. Such misconceptions should be stated explicitly, along with their correction.

Drivers of RFID adoption in the automotive industry

The automotive industry is confronted with increasing competition, leading to higher cost pressures and the demand to optimize production processes and value chains. Here the RFID technology promises to improve a range of processes in logistics and manufacturing. Despite its promising potential in the automotive industry, RFID has not yet made a decisive step from pilots to real-life implementations in the supply chain. Building on existing models of technology adoption, we analyze RFID adoption dynamics in the automotive industry. Building on existing IOS adoption models tailored to RFID specifics and based on ten semi-structured interviews with OEMs and suppliers, we evaluate main drivers of RFID adoption in the automotive industry. Our key findings are that the use of a coercive approach by the OEM could be redundant because of the market-driven RFID adoption among many suppliers. Furthermore, suppliers implementing RFID can now gain an early mover competitive advantage by developing higher trust in their relationship with the OEM as well as accumulating unique expertise in this area.

Asking sensitive questions: Possibilities and limits of randomized response and other techniques in different survey modes

In our project within the DFG Priority Programme on Survey Methodology (SPP 1292) we conducted various methodological studies on survey techniques for asking sensitive questions. For example, we compared results from the randomized response technique (RRT) to true known data in a validation study, developed and evaluated implementations of the RRT for CATI and online mode, and compared the performance of the RRT to competing approaches. In our talk, we will give an overview of the studies conducted in this project and will present our key findings. Furthermore, we will identify open research questions and give guidelines for future research on asking sensitive questions.

Sensitive Questions in Online Surveys: An Experimental Comparison of the RRT and the Crosswise Model

Self-administered online surveys provide a higher level of privacy protection to respondents than surveys administered by an interviewer. Yet, studies show that asking sensitive questions is problematic also in self-administered mode. Because respondents might not be willing to reveal the truth and provide answers that are subject to social desirability bias, the validity of prevalence estimates of sensitive behaviors gained via online surveys can be challenged. A wellknown method to combat these problems is the Randomized Response Technique (RRT). However, convincing evidence that the RRT provides more valid estimates than direct questioning in online mode is still lacking. Moreover, an alternative approach called the Crosswise Model (CM) has recently been suggested to overcome some of the deficiencies of the RRT. We therefore conducted an experimental study in which different implementations of the RRT and the CM have been tested and compared to direct questioning. Our study is a large-scale online survey on sensitive behaviors by students such as cheating in exams and paper plagiarism. The results of the study reveal poor per-formance of the RRT, while the CM yielded significantly higher estimates of sensitive behaviors than direct questioning. We conclude that the CM is a promising approach for asking sensitive questions in self-administered surveys.

Asking Sensitive Questions in Online Surveys: An Experimental Comparison of the Randomized Response Technique and the Crosswise Model

Self-administered online surveys provide a higher level of privacy protection to respondents than surveys administered by an interviewer. Yet, studies show that asking sensitive questions is problematic also in self-administered mode. Because respondents might not be willing to reveal the truth and provide answers that are subject to social desirability bias, the validity of prevalence estimates of sensitive behaviors gained via online surveys can be challenged. A well-known method to combat these problems is the Randomized Response Technique (RRT). However, convincing evidence that the RRT provides more valid estimates than direct questioning in online mode is still lacking. Moreover, an alternative approach called the Crosswise Model (CM) has recently been suggested to overcome some of the deficiencies of the RRT. In the context of an online survey on plagiarism and cheating on exams among students of two Swiss universities (N = 6,494), we tested different implementations of the RRT and the CM and compared them to direct questioning using a randomized experimental design. Results reveal a poor performance of the RRT, which failed to elicit higher prevalence estimates than direct questioning. Using the CM however, significantly higher prevalence estimates were obtained making it a promising new alternative to the conventional RRT.