Generalizations of Ripley's K-function with Application to Space Curves

The intensity function and Ripley's K-function have been used extensively in the literature to describe the first and second moment structure of spatial point sets. This has many applications including describing the statistical structure of synaptic vesicles. Some attempts have been made to extend Ripley's K-function to curve pieces. Such an extension can be used to describe the statistical structure of muscle fibers and brain fiber tracks. In this paper, we take a computational perspective and construct new and very general variants of Ripley's K-function for curves pieces, surface patches etc. We discuss the method from [Chiu, Stoyan, Kendall, & Mecke 2013] and compare it with our generalizations theoretically, and we give examples demonstrating the difference in their ability to separate sets of curve pieces.Comment: 9 pages & 8 figure

Bilingualism and creativity across development: Evidence from divergent thinking and convergent thinking.

Numerous studies have demonstrated the benefits of creativity from bilingualism. Divergent thinking and convergent thinking are considered the two most important components of creativity. Various (although not all) studies have concluded that bilingual children outperform monolingual children in divergent thinking, however, no study on children or adolescents so far has explored the relation between bilingualism and convergent thinking, or the brain structural basis of interaction between bilingualism and creativity. This study aimed to explore the impact of bilingualism on both convergent and divergent thinking in children and adolescents based on neuropsychological assessments, and the possible structural basis of the effect of bilingualism on creativity by a whole-brain analysis of regional gray matter volume (rGMV) and cortical thickness in children and adolescents. 92 healthy children and adolescents of age 4-18 were recruited from public or private schools in the French-speaking side of Switzerland. Demographic data of the participants were collected, including gender, age, pedagogy, usage of language, and parents' socioeconomic status. Most of the participants underwent the neuropsychological assessments of divergent thinking, convergent thinking, and fluid intelligence. Structural image data of 75 participants were analyzed. Both voxel-based morphometry (VBM) and surface-based morphometry (SBM) were processed, to perform the analyses of rGMV and cortical thickness respectively. The outcomes indicated that convergent thinking, but not divergent thinking benefits from bilingualism in children and adolescents. However, this bilingual advantage appears to weaken across development. Unexpectedly, no significant correlation between morphometry and bilingualism was found. Neither divergent thinking scores nor convergent thinking scores showed any significant correlation with rGMV. However, the whole brain SBM showed that the cortical thickness in the right supplementary motor area (SMA) was negatively correlated with convergent thinking scores, which suggested that the children and adolescents with higher convergent thinking abilities may have thinner, more mature, and more activated cortex in the right SMA. Bilingualism and cortical thinness in the right SMA might facilitate convergent thinking independently, by enhancing this selective ability

Sparse Adaptive Parameterization of Variability in Image Ensembles

International audienceThis paper introduces a new parameterization of diffeomorphic deformations for the characterization of the variability in image ensembles. Dense diffeomorphic deformations are built by interpolating the motion of a finite set of control points that forms a Hamiltonian flow of self-interacting particles. The proposed approach estimates a template image representative of a given image set, an optimal set of control points that focuses on the most variable parts of the image, and template-to-image registrations that quantify the variability within the image set. The method automatically selects the most relevant control points for the characterization of the image variability and estimates their optimal positions in the template domain. The optimization in position is done during the estimation of the deformations without adding any computational cost at each step of the gradient descent. The selection of the control points is done by adding a L 1 prior to the objective function, which is optimized using the FISTA algorithm

Copulas, multivariate risk-neutral distributions and implied dependence functions

In this paper, we use copulas to define multivariate risk-neutral distributions. We can then derive general pricing formulas for multi-asset options and best possible bounds with given volatility smiles. Finally, we apply the copula framework to define ‘forward-looking ’ indicators of the dependence function between asset returns.

Early years autism and bilingualism: An interpretative phenomenological analysis of parent perceptions during lockdown

This is the final version. Available from SAGE Publications via the DOI in this record. Aim: This study explores how bilingual parents of autistic children made language decisions for their families, how the event of the SARS-CoV-2 pandemic and subsequent lockdown impacted the communication environment of their households, and whether these experiences affected their language habits. Method: Semi-structured interviews were conducted with five bilingual parents of autistic children who lived through lockdown in France. Data were analysed using interpretative phenomenological analysis. Demographic and background information was collected using an adapted version of the Questionnaire for Parents of Bilingual Children. Results: Participants reported conflicting advice given by a range of practitioners. Parents expressed differing beliefs about the impact of language choices on their children. Parents described active engagement with their children’s home-learning as generally positive. Parents identified an increase in children’s exposure to their first language during the lockdown. Parents reported an increase in children’s overall communication abilities. Conclusion: Parents believed that their children’s positive communication development during lockdown was related to increased exposure to their first language(s), and direct involvement in their children’s learning programs.Swiss National Science Foundatio

An eye-tracking study of selective trust development in children with and without autism spectrum disorder

The purpose of this study was to explore whether children with autism display selectivity in social learning. We investigated the processing of word mappings provided by speakers who differed on previously demonstrated accuracy and on potential degree of reliability in three groups of children (children with autism spectrum disorder, children with developmental language disorder, and typically developing children) aged 4–9 years. In Task 1, one speaker consistently misnamed familiar objects and the second speaker consistently gave correct names. In Task 2, both speakers provided correct information but differed on how they could achieve this accuracy. We analyzed how the speakers’ profiles influenced children's decisions to rely on them in order to learn novel words. We also examined how children attended to the speakers’ testimony by tracking their eye movements and comparing children’ gaze distribution across speakers’ faces and objects of their choice. Results show that children rely on associative trait attribution heuristics to selectively learn from accurate speakers. In Task 1, children in all groups preferred the novel object selected by accurate speakers and directly avoided information provided by previously inaccurate speakers, as revealed by the eye-tracking data. In Task 2, where more sophisticated reasoning about speakers’ reliability was required, only children in the typically developing group performed above chance. Nonverbal intelligence score emerged as a predictor of children's preference for more reliable informational sources. In addition, children with autism exhibited reduced attention to speakers’ faces compared with children in the comparison groups

A precision medicine initiative for Alzheimer's disease: the road ahead to biomarker-guided integrative disease modeling

After intense scientific exploration and more than a decade of failed trials, Alzheimer’s disease (AD) remains a fatal global epidemic. A traditional research and drug development paradigm continues to target heterogeneous late-stage clinically phenotyped patients with single 'magic bullet' drugs. Here, we propose that it is time for a paradigm shift towards the implementation of precision medicine (PM) for enhanced risk screening, detection, treatment, and prevention of AD. The overarching structure of how PM for AD can be achieved will be provided through the convergence of breakthrough technological advances, including big data science, systems biology, genomic sequencing, blood-based biomarkers, integrated disease modeling and P4 medicine. It is hypothesized that deconstructing AD into multiple genetic and biological subsets existing within this heterogeneous target population will provide an effective PM strategy for treating individual patients with the specific agent(s) that are likely to work best based on the specific individual biological make-up. The Alzheimer’s Precision Medicine Initiative (APMI) is an international collaboration of leading interdisciplinary clinicians and scientists devoted towards the implementation of PM in Neurology, Psychiatry and Neuroscience. It is hypothesized that successful realization of PM in AD and other neurodegenerative diseases will result in breakthrough therapies, such as in oncology, with optimized safety profiles, better responder rates and treatment responses, particularly through biomarker-guided early preclinical disease-stage clinical trials