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    Machine Analysis of Facial Expressions

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    Mental imagery of positive and neutral memories : a fMRI study comparing field perspective imagery to observer perspective imagery

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    Imagery perspective can influence what information is recalled, processing style, and emotionality; however, the understanding of possible mechanisms mediating these observed differences is still limited. We aimed to examine differences between memory recall from a field perspective and observer perspective at the neurobiological level, in order to improve our understanding of what is underlying the observed differences at the behavioral level. We conducted a fMRI study in healthy individuals, comparing imagery perspectives during recall of neutral and positive autobiographical memories. Behavioral results revealed field perspective imagery of positive memories, as compared to observer perspective, to be associated with more positive feelings afterwards. At the neurobiological level, contrasting observer perspective to field perspective imagery was associated with greater activity, or less decrease relative to the control visual search task, in the right precuneus and in the right temporoparietal junction (TPJ). Greater activity in the right TPJ during an observer perspective as compared to field perspective could reflect performing a greater shift of perspective and mental state during observer perspective imagery than field perspective imagery. Differential activity in the precuneus may reflect that during observer perspective imagery individuals are more likely to engage in (self-) evaluative processing and visuospatial processing. Our findings contribute to a growing understanding of how imagery perspective can influence the type of information that is recalled and the intensity of the emotional response. Observer perspective imagery may not automatically reduce emotional intensity but this could depend on how the imagined situation is evaluated in relation to the self-concept. (C) 2016 Elsevier Inc. All rights reserved

    Bayesian log-Gaussian Cox process regression: applications to meta-analysis of neuroimaging working memory studies

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    Working memory (WM) was one of the first cognitive processes studied with functional magnetic resonance imaging. With now over 20 years of studies on WM, each study with tiny sample sizes, there is a need for meta-analysis to identify the brain regions that are consistently activated by WM tasks, and to understand the interstudy variation in those activations. However, current methods in the field cannot fully account for the spatial nature of neuroimaging meta-analysis data or the heterogeneity observed among WM studies. In this work, we propose a fully Bayesian random-effects metaregression model based on log-Gaussian Cox processes, which can be used for meta-analysis of neuroimaging studies. An efficient Markov chain Monte Carlo scheme for posterior simulations is presented which makes use of some recent advances in parallel computing using graphics processing units. Application of the proposed model to a real data set provides valuable insights regarding the function of the WM
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