City University London

About: City University London is a education organization based out in London, United Kingdom. It is known for research contribution in the topics: Population & Context (language use). The organization has 5735 authors who have published 17285 publications receiving 453290 citations.

Patterns of Nonsocial and Social Cognitive Functioning in Adults With Autism Spectrum Disorder: A Systematic Review and Meta-analysis.

Abstract: Importance Many studies have investigated impairments in cognitive domains in adults with autism spectrum disorder (ASD). Yet, to date, a comprehensive overview on the patterns of cognitive functioning is lacking. Objective To provide an overview of nonsocial and social cognitive functioning in various domains in adults with ASD, allowing for comparison of the severity of deficits between different domains. Data Sources A literature search performed in an academic medical setting was conducted using PubMed, PsycINFO, Embase, and Medline databases with the combination of the following free-text and Medical Subject Headings where applicable: [cogniti* OR neurocogniti* OR neuropsycholog* OR executive function* OR IQ OR intelligence quotient OR social cognition OR emotion perception OR affect perception OR emotion recognition OR attribution OR ToM OR mentalising OR mentalizing OR prosody OR social knowledge OR mind reading OR social cue OR social judgment] AND [autis* OR ASD OR Asperger OR Asperger’s OR PDD OR pervasive developmental disorder]. The search was further limited to studies published between 1980 (first inclusion of autism diagnosis in theDSM-III) and July 2018. Study Selection Studies included were published as a primary peer-reviewed research article in English, included individuals with ASD 16 years or older, and assessed at least 1 domain of neurocognitive functioning or social cognition using standard measures. Data Extraction and Synthesis Of 9892 articles identified and screened, 75 met the inclusion criteria for the systematic review and meta-analysis. Main Outcomes and Measures Hedgesgeffect sizes were computed, and random-effects models were used for all analyses. Moderators of between-study variability in effect sizes were assessed using meta-regressions. Results The systematic review and meta-analysis included 75 studies, with a combined sample of 3361 individuals with ASD (mean [SD] age, 32.0 [9.3] years; 75.9% male) and 5344 neurotypical adults (mean [SD] age, 32.3 [9.1] years; 70.1% male). Adults with ASD showed large impairments in theory of mind (g = −1.09; 95% CI, −1.25 to −0.92; number of studies = 39) and emotion perception and processing (g = −0.80; 95% CI, −1.04 to −0.55; n = 18), followed by medium impairments in processing speed (g = −0.61; 95% CI, −0.83 to −0.38; n = 21) and verbal learning and memory (g = −0.55; 95% CI, −0.86 to −0.25; n = 12). The least altered cognitive domains were attention and vigilance (g = −0.30; 95% CI, −0.81 to 0.21; n = 5) and working memory (g = −0.23; 95% CI, −0.47 to 0.01; n = 19). Meta-regressions confirmed robustness of the results. Conclusions and Relevance Results of this systematic review and meta-analysis suggest that adults with ASD show impairments in social cognitive domains and in specific nonsocial cognitive domains. These findings contribute to the understanding of the patterns of cognitive functioning in adults with ASD and may assist in the identification of targets for cognitive interventions.

State of the Art of Sports Data Visualization

Abstract: In this report, we organize and reflect on recent advances and challenges in the field of sports data visualization. The exponentially-growing body of visualization research based on sports data is a prime indication of the importance and timeliness of this report. Sports data visualization research encompasses the breadth of visualization tasks and goals: exploring the design of new visualization techniques; adapting existing visualizations to a novel domain; and conducting design studies and evaluations in close collaboration with experts, including practitioners, enthusiasts, and journalists. Frequently this research has impact beyond sports in both academia and in industry because it is i) grounded in realistic, highly heterogeneous data, ii) applied to real-world problems, and iii) designed in close collaboration with domain experts. In this report, we analyze current research contributions through the lens of three categories of sports data: box score data (data containing statistical summaries of a sport event such as a game), tracking data (data about in-game actions and trajectories), and meta-data (data about the sport and its participants but not necessarily a given game). We conclude this report with a high-level discussion of sports visualization research informed by our analysis—identifying critical research gaps and valuable opportunities for the visualization community. More information is available at the STAR’s website: https://sportsdataviz.github.io/.

Modelling series of visual fields to detect progression in normal-tension glaucoma

Abstract: • Background: Use of statistical modelling techniques to identify models that both describe glaucomatous sensitivity decay and allow predictions of future field status. • Method: Twelve initially normal fellow eyes of untreated patients with confirmed normal-tension glaucoma were studied. All had in excess of 15 Humphrey fields (mean follow-up 5.7 years). From this cohort individual field locations were selected for analysis if they demonstrated unequivocal deterioration at the final two fields. Forty-seven locations from five eyes satisfied this criterion and were analysed using curve-fitting software which automatically applies 221 different models to sensitivity (y) against time of follow up (x). Curve-fitting was then repeated on the first five fields, followed by projection to the date of the final field to generate a predicted threshold which was compared to the actual threshold. Competing models were therefore assessed on their performance at adequately fitting the data (R2) and their potential to predict future field status. • Results: Models that provided the best fit to the data were all complex polynomial expressions (median R2 0.93). Other simple expressions fitted fewer locations and exhibited lower R2 values. However, accuracy in predicting future deterioration was superior with these less complex models. In this group a linear expression demonstrated an adequate fit to the majority of the data and generated the most accurate predictions of future field status. • Conclusions: A linear model of the pointwise sensitivity values against time of follow-up can provide a framework for detecting and forecasting glaucomatous field progression. Linear modelling allows the clinically important rate of sensitivity loss to be estimated.