Neural Underpinnings of Prosody in Autism

This study examines the processing of prosodic cues to linguistic structure and to affect, drawing on fMRI and behavioral data from 16 high-functioning adolescents with autism spectrum disorders (ASD) and 11 typically developing controls. Stimuli were carefully matched on pitch, intensity, and duration, while varying systematically in conditions of affective prosody (angry versus neutral speech) and grammatical prosody (questions versus statement). To avoid conscious attention to prosody, which normalizes responses in young people with ASD, the implicit comprehension task directed attention to semantic aspects of the stimuli. Results showed that when perceiving prosodic cues, both affective and grammatical, activation of neural regions was more generalized in ASD than in typical development, and areas recruited reflect heightened reliance on cognitive control, reading of intentions, attentional management, and visualization. This broader recruitment of executive and “mind-reading” brain areas for a relative simple language-processing task may be interpreted to suggest that speakers with high-functioning autism (HFA) have developed less automaticity in language processing and may also suggest that “mind-reading” or theory of mind deficits are intricately bound up in language processing. Data provide support for both a right-lateralized as well as a bilateral model of prosodic processing in typical individuals, depending upon the function of the prosodic information

Can soluble urokinase plasminogen receptor predict outcomes after cardiac surgery?

Acknowledgements: We thank Lisa Jolly, from the Institute of Infection, Immunity and Inflammation at the University of Glasgow who performed all lab analysis. We thank Professor John Kinsella for his contributions to this research. Funding: This work was supported by the National Institute of Academic Anaesthesia through the Royal College of Anaesthetists Research, Education and Travel grant via the Ernest Leach Fund to Dr Philip McCall. The funding body had no role in design of the study, collection, analysis and interpretation of data or writing of the manuscript.Peer reviewedPostprintPostprintPostprin

Distance-Based Analysis of Variance for Brain Connectivity

The field of neuroimaging dedicated to mapping connections in the brain is increasingly being recognized as key for understanding neurodevelopment and pathology. Networks of these connections are quantitatively represented using complex structures including matrices, functions, and graphs, which require specialized statistical techniques for estimation and inference about developmental and disorder-related changes. Unfortunately, classical statistical testing procedures are not well suited to high-dimensional testing problems. In the context of global or regional tests for differences in neuroimaging data, traditional analysis of variance (ANOVA) is not directly applicable without first summarizing the data into univariate or low-dimensional features, a process that may mask salient features of the high-dimensional distributions. In this work, we consider a general framework for two-sample testing of complex structures by studying generalized within- and between-group variances based on distances between complex and potentially high-dimensional observations. We derive an asymptotic approximation to the null distribution of the ANOVA test statistic, and conduct simulation studies with scalar and graph outcomes to study finite sample properties of the test. Finally, we apply our test to our motivating study of structural connectivity in autism spectrum disorder