Neural correlates of affective contributions to lexical decisions in children and adults

The goal of the present study was to investigate whether 6–9-year old children and adults show similar neural responses to affective words. An event-related neuroimaging paradigm was used in which both age cohorts performed the same auditory lexical decision task (LDT). The results show similarities in (auditory) lexico-semantic network activation as well as in areas associated with affective information. In both age cohorts’ activations were stronger for positive than for negative words, thus exhibiting a positivity superiority effect. Children showed less activation in areas associated with affective information in response to all three valence categories than adults. Our results are discussed in the light of computational models of word recognition, and previous findings of affective contributions to LDT in adults

Replicability and comprehensibility of social research and its technical implementation

"This paper is a contribution to the methodological and technical discussion of social research infrastructure. The main question is how to store and manage data in a way that meets the increasing demand for secondary data analysis in both quantitative and qualitative social science research. The first two sections focus mainly on aspects of data documentation, in particular on the unification of various documentation requirements that have arisen across ongoing projects of the SFB 882. While the aim of documenting quantitative research processes is to ensure replicability, the aim of documenting qualitative projects is to maintain the understandability and informative value of research data. In the third section a virtual research environment (VRE) is presented that provides both a generic work platform and a project-specific research platform. The work platform bundles IT resources by bringing together various tools for administration, project management, and time- and location-independent collaboration in a single environment adapted to researchers' specific work processes. The research component combines data management with further developments in social science methodologies. It provides services for the archiving and reuse of data and enables the infrastructural and methodological coordination of data documentation. We also introduce a documentation scheme for qualitative and quantitative social research within the SFB 882. This scheme considers the specific requirements of research projects within the SFB, such as different methods (e.g. panel analysis, experimental approaches, ethnography, and interview research), project work, and requirements of longterm research." (author's abstract

A Hierarchical Diffusion Model Analysis of Age Effects on Visual Word Recognition

Reading is one of the most popular leisure activities and it is routinely performed by most individuals even in old age. Successful reading enables older people to master and actively participate in everyday life and maintain functional independence. Yet, reading comprises a multitude of subprocesses and it is undoubtedly one of the most complex accomplishments of the human brain. Not surprisingly, findings of age-related effects on word recognition and reading have been partly contradictory and are often confined to only one of four central reading subprocesses, i.e., sublexical, orthographic, phonological and lexico-semantic processing. The aim of the present study was therefore to systematically investigate the impact of age on each of these subprocesses. A total of 1,807 participants (young, N = 384; old, N = 1,423) performed four decision tasks specifically designed to tap one of the subprocesses. To account for the behavioral heterogeneity in older adults, this subsample was split into high and low performing readers. Data were analyzed using a hierarchical diffusion modeling approach, which provides more information than standard response time/accuracy analyses. Taking into account incorrect and correct response times, their distributions and accuracy data, hierarchical diffusion modeling allowed us to differentiate between age- related changes in decision threshold, non-decision time and the speed of information uptake. We observed longer non-decision times for older adults and a more conservative decision threshold. More importantly, high-performing older readers outperformed younger adults at the speed of information uptake in orthographic and lexico-semantic processing, whereas a general age- disadvantage was observed at the sublexical and phonological levels. Low- performing older readers were slowest in information uptake in all four subprocesses. Discussing these results in terms of computational models of word recognition, we propose age-related disadvantages for older readers to be caused by inefficiencies in temporal sampling and activation and/or inhibition processes

Structural gray matter features and behavioral preliterate skills predict future literacy – A machine learning approach

When children learn to read, their neural system undergoes major changes to become responsive to print. There seem to be nuanced interindividual differences in the neurostructural anatomy of regions that later become integral parts of the reading network. These differences might affect literacy acquisition and, in some cases, might result in developmental disorders like dyslexia. Consequently, the main objective of this longitudinal study was to investigate those interindividual differences in gray matter morphology that might facilitate or hamper future reading acquisition. We used a machine learning approach to examine to what extent gray matter macrostructural features and cognitive-linguistic skills measured before formal literacy teaching could predict literacy 2 years later. Forty-two native German-speaking children underwent T1-weighted magnetic resonance imaging and psychometric testing at the end of kindergarten. They were tested again 2 years later to assess their literacy skills. A leave-one-out cross-validated machine-learning regression approach was applied to identify the best predictors of future literacy based on cognitive-linguistic preliterate behavioral skills and cortical measures in a priori selected areas of the future reading network. With surprisingly high accuracy, future literacy was predicted, predominantly based on gray matter volume in the left occipito-temporal cortex and local gyrification in the left insular, inferior frontal, and supramarginal gyri. Furthermore, phonological awareness significantly predicted future literacy. In sum, the results indicate that the brain morphology of the large-scale reading network at a preliterate age can predict how well children learn to read

Differentiation of benign and malignant vertebral fractures using a convolutional neural network to extract CT-based texture features.

PURPOSE To assess the diagnostic performance of three-dimensional (3D) CT-based texture features (TFs) using a convolutional neural network (CNN)-based framework to differentiate benign (osteoporotic) and malignant vertebral fractures (VFs). METHODS A total of 409 patients who underwent routine thoracolumbar spine CT at two institutions were included. VFs were categorized as benign or malignant using either biopsy or imaging follow-up of at least three months as standard of reference. Automated detection, labelling, and segmentation of the vertebrae were performed using a CNN-based framework ( https://anduin.bonescreen.de ). Eight TFs were extracted: Varianceglobal, Skewnessglobal, energy, entropy, short-run emphasis (SRE), long-run emphasis (LRE), run-length non-uniformity (RLN), and run percentage (RP). Multivariate regression models adjusted for age and sex were used to compare TFs between benign and malignant VFs. RESULTS Skewnessglobal showed a significant difference between the two groups when analyzing fractured vertebrae from T1 to L6 (benign fracture group: 0.70 [0.64-0.76]; malignant fracture group: 0.59 [0.56-0.63]; and p = 0.017), suggesting a higher skewness in benign VFs compared to malignant VFs. CONCLUSION Three-dimensional CT-based global TF skewness assessed using a CNN-based framework showed significant difference between benign and malignant thoracolumbar VFs and may therefore contribute to the clinical diagnostic work-up of patients with VFs

Structural transformations of Li2C2 at high pressures

Structural changes of Li2C2 under pressure were studied by synchrotron x-ray diffraction in a diamond anvil cell under hydrostatic conditions and by using evolutionary search methodology for crystal structure prediction. We show that the high-pressure polymorph of Li2C2, which forms from the Immm ground-state structure (Z = 2) at around 15 GPa, adopts an orthorhombic Pnma structure with Z = 4. Acetylide C2 dumbbells characteristic of Immm Li2C2 are retained in Pnma Li2C2. The structure of Pnma Li2C2 relates closely to the anticotunnite-type structure. C2 dumbbell units are coordinated by nine Li atoms, as compared to eight in the antifluorite structure of Immm Li2C2. First-principles calculations predict a transition of Pnma Li2C2 at 32 GPa to a topologically identical phase with a higher Cmcm symmetry. The coordination of C2 dumbbell units by Li atoms is increased to 11. The structure of Cmcm Li2C2 relates closely to the Ni2 In-type structure. It is calculated that Cmcm Li2C2 becomes metallic at pressures above 40 GPa. In experiments, however, Pnma Li2C2 is susceptible to irreversible amorphization

Auditory brainstem measures and genotyping boost the prediction of literacy : a longitudinal study on early markers of dyslexia

Literacy acquisition is impaired in children with developmental dyslexia resulting in lifelong struggle to read and spell. Proper diagnosis is usually late and commonly achieved after structured schooling started, which causes delayed interventions. Legascreen set out to develop a preclinical screening to identify children at risk of developmental dyslexia. To this end we examined 93 preliterate German children, half of them with a family history of dyslexia and half of them without a family history. We assessed standard demographic and behavioral precursors of literacy, acquired saliva samples for genotyping, and recorded speech-evoked brainstem responses to add an objective physiological measure. Reading and spelling was assessed after two years of structured literacy instruction. Multifactorial regression analyses considering demographic information, genotypes, and auditory brainstem encoding, predicted children’s literacy skills to varying degrees. These predictions were improved by adding the standard psychometrics with a slightly higher impact on spelling compared to reading comprehension. Our findings suggest that gene-brain-behavior profiling has the potential to determine the risk of developmental dyslexia. At the same time our results imply the need for a more sophisticated assessment to fully account for the disparate cognitive profiles and the multifactorial basis of developmental dyslexia

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements