In action-control research, typically, stimulus sparse displays are used. This might be one reason why previous theorizing focuses on the (top-down) demands of response selection (e.g., what key to press), while often ignoring (bottom-up) demands of stimulus selection (e.g., what stimulus to attend). However, complex perceptual situations may pose selection demands that make additional, response-unrelated feature dimensions relevant for response selection. The major stimulus characteristic affecting perceptual selection is salience. In research on visual attention, there is a debate about the conditions under which salience becomes effective. We related both debates in two experiments, in which we modulated display set size as well as salience in a stimulus-response binding task. In sum, the data of these experiments (pooled N = 138) demonstrated that salience furthered the integration of stimulus features in displays with many stimuli more than in sparse displays. Our results demonstrate the neglected impact of salience on action-control when going beyond the very simplistic displays common in action-control research. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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Parasit Vectors
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Faculty of Geography, Environmental Informatics, University of Marburg, Deutschhausstraße 12, 35032, Marburg, Hessen, Germany.
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January 2025
Department of Chemistry, Yale University, New Haven, Connecticut 06520, United States.
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View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Department of Chemical and Biological Engineering, University of Colorado, Boulder, CO 80305.
Immunological interventions, like vaccinations, are enabled by the predictive control of humoral responses to novel antigens. While the development trajectories for many broadly neutralizing antibodies (bnAbs) have been measured, it is less established how human subtype-specific antibodies develop from their precursors. In this work, we evaluated the retrospective development trajectories for eight anti-SARS-CoV-2 Spike human antibodies (Abs).
View Article and Find Full Text PDFMethods
January 2025
School of Computer Science, Qufu Normal University, Rizhao 276826, China.
Brain imaging genetics aims to explore the association between genetic factors such as single nucleotide polymorphisms (SNPs) and brain imaging quantitative traits (QTs). However, most existing methods do not consider the nonlinear correlations between genotypic and phenotypic data, as well as potential higher-order relationships among subjects when identifying bi-multivariate associations. In this paper, a novel method called deep hyper-Laplacian regularized self-representation learning based structured association analysis (DHRSAA) is proposed which can learn genotype-phenotype associations and obtain relevant biomarkers.
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Exploration and Development Research Institute, PetroChina Tarim Oilfield Company, Korla, 841000, China.
The reservoir in focus has braided river delta front deposition, with multiple periods of submerged distributary channels within the reservoir. It also displays frequent cutting and stacking with local-connecting characteristics. Forecasting the sand distribution characteristics between wells in this type of reservoir brings a significant challenge for modeling.
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