Project description:Prosody or "melody in speech" in autism spectrum disorder (ASD) is often perceived as atypical. This study examined perception and production of statements and questions in 84 children, adolescents and adults with and without ASD, as well as participants' pitch direction discrimination thresholds. The results suggested that the abilities to discriminate (in both speech and music conditions), identify, and imitate statement-question intonation were intact in individuals with ASD across age cohorts. Sensitivity to pitch direction predicted performance on intonation processing in both groups, who also exhibited similar developmental changes. These findings provide evidence for shared mechanisms in pitch processing between speech and music, as well as associations between low- and high-level pitch processing and between perception and production of pitch.
Project description:Conrad et al. Nature 456, 344–349 (2008) have generated human adult germline stem cells (haGSCs) from human testicular tissue, which they claim have similar pluripotent properties to human embryonic stem cells (hESCs). Here we investigate the pluripotency of haGSCs by using global gene-expression analysis based on their gene array data and comparing the expression of pluripotency marker genes in haGSCs and hESCs, and in haGSCs and human fibroblast samples derived from different laboratories, including our own. We find that haGSCs and fibroblasts have a similar gene-expression profile, but that haGSCs and hESCs do not. The pluripotency of Conrad and colleagues’ haGSCs is therefore called into question.
Project description:Neural extractive summarization methods often require much labeled training data, for which headlines or lead summaries of news articles can sometimes be used. Such directly useful summaries are not always available, however, especially for user-generated content, such as questions posted on community question answering services. In this paper, we address an extractive summarization (i.e., headline extraction) task for such questions as a case study and consider how to alleviate the problem by using question-answer pairs, instead of missing-headline pairs. To this end, we propose a framework to examine how to use such unlabeled paired data from the viewpoint of training methods. Experimental results show that multi-task training performs well with undersampling and distant supervision.
Project description:Conrad et al. Nature 456, 344â349 (2008) have generated human adult germline stem cells (haGSCs) from human testicular tissue, which they claim have similar pluripotent properties to human embryonic stem cells (hESCs). Here we investigate the pluripotency of haGSCs by using global gene-expression analysis based on their gene array data and comparing the expression of pluripotency marker genes in haGSCs and hESCs, and in haGSCs and human fibroblast samples derived from different laboratories, including our own. We find that haGSCs and fibroblasts have a similar gene-expression profile, but that haGSCs and hESCs do not. The pluripotency of Conrad and colleaguesâ haGSCs is therefore called into question. RNA samples from human testicular fibroblast cells (hTFCs) were obtained and applied to global gene expression analysis using gene arrays.
Project description:We propose an extrinsic regression framework for modeling data with manifold valued responses and Euclidean predictors. Regression with manifold responses has wide applications in shape analysis, neuroscience, medical imaging and many other areas. Our approach embeds the manifold where the responses lie onto a higher dimensional Euclidean space, obtains a local regression estimate in that space, and then projects this estimate back onto the image of the manifold. Outside the regression setting both intrinsic and extrinsic approaches have been proposed for modeling i.i.d manifold-valued data. However, to our knowledge our work is the first to take an extrinsic approach to the regression problem. The proposed extrinsic regression framework is general, computationally efficient and theoretically appealing. Asymptotic distributions and convergence rates of the extrinsic regression estimates are derived and a large class of examples are considered indicating the wide applicability of our approach.
Project description:BackgroundWhen patients have multiple chronic illnesses, it is not feasible to provide disease-based care when treatments for one condition adversely affect another. Instead, health-care delivery requires a broader person-centred treatment plan based on collaborative, patient-oriented values and goals.ObjectiveWe examined the individual variability, thematic content, and sociodemographic correlates of valued life abilities and activities among multimorbid veterans diagnosed with life-altering cancer.Setting and participantsParticipants were 144 veterans in the 'Vet-Cares' study who completed a health-care values and goals scale 12 months after diagnosis of head and neck, gastro-oesophageal, or colorectal cancer. They had mean age of 65 years and one quarter identified as Hispanic and/or African American.DesignAt twelve months post-diagnosis, participants rated 16 life abilities/activities in their importance to quality of life on a 10-point Likert scale, during an in-person interview. Scale themes were validated via exploratory factor analysis and examining associations with sociodemographic variables.ResultsParticipants rated most life abilities/activities as extremely important. Variability in responses was sufficient to identify three underlying values themes in exploratory factor analysis: self-sufficiency, enjoyment/comfort, and connection to family, friends and spirituality. Veterans with a spouse/partner rated self-sufficiency as less important. African American veterans rated connection as more important than did White veterans.ConclusionsIt is feasible yet challenging to ask older, multimorbid patients to rate relative importance of values associated with life abilities/activities. Themes related to self-sufficiency, enjoyment/comfort in daily life and connection are salient and logically consistent with sociodemographic traits. Future studies should explore their role in goal-directed health care.
Project description:As people form social groups, they benefit from being able to detect socially valuable community members-individuals who act prosocially, support others, and form strong relationships. Multidisciplinary evidence demonstrates that people indeed track others' social value, but the mechanisms through which such detection occurs remain unclear. Here, we combine social network and neuroimaging analyses to examine this process. We mapped social networks in two freshman dormitories (n = 97), identifying how often individuals were nominated as socially valuable (i.e., sources of friendship, empathy, and support) by their peers. Next, we scanned a subset of dorm members ("perceivers"; n = 50) as they passively viewed photos of their dormmates ("targets"). Perceiver brain activity in regions associated with mentalizing and value computation differentiated between highly valued targets and other community members but did not differentiate between targets with middle versus low levels of social value. Cross-validation analysis revealed that brain activity from novel perceivers could be used to accurately predict whether targets viewed by those perceivers were high in social value or not. These results held even after controlling for perceivers' own ratings of closeness to targets, and even though perceivers were not directed to focus on targets' social value. Overall, these findings demonstrate that individuals spontaneously monitor people identified as sources of strong connection in the broader community.
Project description:Importance:Sight is often considered to be the sense most valued by the general public, but there are limited empirical data to support this. This study provides empirical evidence for frequent assertions made by practitioners, researchers, and funding agencies that sight is the most valued sense. Objective:To determine which senses are rated most valuable by the general public and quantify attitudes toward sight and hearing loss in particular. Design, Setting, and Participants:This cross-sectional web-based survey was conducted from March to April 2016 through a market research platform and captured a heterogeneous sample of 250 UK adults ages 22 to 80 years recruited in March 2016. The data were analyzed from October to December 2018. Main Outcomes and Measures:Participants were first asked to rank the 5 traditional senses (sight, hearing, touch, smell, and taste) plus 3 other senses (balance, temperature, and pain) in order of most valuable (8) to least valuable (1). Next, the fear of losing sight and hearing was investigated using a time tradeoff exercise. Participants chose between 10 years without sight/hearing vs varying amounts of perfect health (from 0-10 years). Results:Of 250 participants, 141 (56.4%) were women and the mean (SD) age was 49.5 (14.6) years. Two hundred twenty participants (88%) ranked sight as their most valuable sense (mean [SD] rating, 7.8 [0.9]; 95% CI, 7.6-7.9). Hearing was ranked second (mean [SD] rating, 6.2 [1.3]; 95% CI 6.1-6.4) and balance third (mean [SD] rating, 4.9 [1.7]; 95% CI, 4.7-5.1). All 3 were ranked above the traditional senses of touch, taste, and smell (F7?=?928.4; P?<?.001). The time tradeoff exercise indicated that, on average, participants preferred 4.6 years (95% CI, 4.2-5.0) of perfect health over 10 years without sight and 6.8 years (95% CI, 6.5-7.2) of perfect health over 10 years without hearing (mean difference between sight and hearing, 2.2 years; P?<?.001). Conclusions and Relevance:In a cross-sectional survey of UK adults from the general public, sight was the most valued sense, followed by hearing. These results suggest that people would on average choose 4.6 years of perfect health over 10 years of life with complete sight loss, although how this generalizes to other parts of the world is unknown.
Project description:Stein variational gradient descent (SVGD) is a particle-based inference algorithm that leverages gradient information for efficient approximate inference. In this work, we enhance SVGD by leveraging preconditioning matrices, such as the Hessian and Fisher information matrix, to incorporate geometric information into SVGD updates. We achieve this by presenting a generalization of SVGD that replaces the scalar-valued kernels in vanilla SVGD with more general matrix-valued kernels. This yields a significant extension of SVGD, and more importantly, allows us to flexibly incorporate various preconditioning matrices to accelerate the exploration in the probability landscape. Empirical results show that our method outperforms vanilla SVGD and a variety of baseline approaches over a range of real-world Bayesian inference tasks.