15 research outputs found

    Effects of stimulus font and size on masked repetition priming: An event-related potentials (ERP) investigation

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    International audienceThe size and font of target words were manipulated in a masked repetition priming paradigm with ERP recordings. Repetition priming effects were found in four ERP components: the N/P150, N250, P325, and N400. Neither a change in font nor a change in size across prime and target were found to affect repetition priming in the N250, P325, and N400 components. Changing font was, however, found to affect repetition priming in the N/P150 component, while the interaction between repetition priming and size was not significant in this component. These results confirm our interpretation of the N/P150 as a component sensitive to feature-level processing, and suggest that the type of prelexical and lexical processing reflected in the N250, P325, and N400 components is performed on representations that are invariant to changes in both font and size

    Understanding Visualization by Understanding Individual Users

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    Visualizations are tools to support thinking. They can be used to externalize knowledge about a complex analytical task or domain, and through interaction, they can embody a reasoning process. As such, visualization cannot be fully understood without also understanding how the user of a visualization thinks. This understanding is nontrivial, and has been complicated by mounting evidence that there is no single type of visualization user. Ultimately, making sense of visualization requires understanding how users vary and why. Past research in visualization theory has focused primarily on how data can be mapped to visual forms and how people perceive them. These research endeavors have led to the identification of fundamental principles regarding how humans perceive colors and visual patterns, and have led to the establishment of general design guidelines for developing useful visualizations. Perceptual visualization theory attempts to understand and model how users perform fundamental lowleve

    From brains to bytes

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