Recent studies have found that visual working memory (VWM) for color shows a : observers typically remember colors as more prototypical to the category they belong to than they actually are. Here, we further examine color-category effects on VWM using pupillometry. Participants remembered a color for later reproduction on a color wheel. During the retention interval, a colored probe was presented, and we measured the pupil constriction in response to this probe, assuming that the strength of constriction reflects the visual saliency of the probe. We found that the pupil initially constricted most strongly for non-matching colors that were maximally different from the memorized color; this likely reflects a lack of visual adaptation for these colors, which renders them more salient than memory-matching colors (which were shown before). Strikingly, this effect reversed later in time, such that pupil constriction was more prolonged for memory-matching colors as compared to non-matching colors; this likely reflects that memory-matching colors capture attention more strongly, and perhaps for a longer time, than non-matching colors do. We found no effects of color categories on pupil constriction: after controlling for color distance, (non-matching) colors from the same category as the memory color did not result in a different pupil response as compared to colors from a different category; however, we did find that behavioral responses were biased by color categories. In summary, we found that pupil constriction to colored probes reflects both visual adaptation and VWM content, but, unlike behavioral measures, is not notably affected by color categories.
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http://dx.doi.org/10.5334/joc.208 | DOI Listing |
Atten Percept Psychophys
January 2025
Department of Psychology, The Ohio State University, 225 Psychology Building, 1835 Neil Ave, Columbus, OH, 43210, USA.
Humans can learn to attentionally suppress salient, irrelevant information when it consistently appears at a predictable location. While this ability confers behavioral benefits by reducing distraction, the full scope of its utility is unknown. As people locomote and/or shift between task contexts, known-to-be-irrelevant locations may change from moment to moment.
View Article and Find Full Text PDFJ Mol Diagn
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Clinical Research and Technological Development Division (Divisão de Pesquisa Clínica e Desenvolvimento Tecnológico), Brazilian National Cancer Institute (Instituto Nacional de Câncer), Rio de Janeiro, Brazil. Electronic address:
This article examines the frequency distribution of Tier 1 pharmacogenetic variants of the Association for Molecular Pathology Pharmacogenomics Working Group Recommendations in two large (>1.000 individuals) cohorts of the admixed Brazilian population, and in patients from the Brazilian Public Health System enrolled in pharmacogenetic trials. Three Tier 1 variants, all in DPYD, were consistently absent, which may justify their non-inclusion in genotyping panels for Brazilians; 13 variants had frequency < 1.
View Article and Find Full Text PDFEnviron Monit Assess
January 2025
Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Shollinganallur, Chennai, India.
Municipal waste classification is significant for effective recycling and waste management processes that involve the classification of diverse municipal waste materials such as paper, glass, plastic, and organic matter using diverse techniques. Yet, this municipal waste classification process faces several challenges, such as high computational complexity, more time consumption, and high variability in the appearance of waste caused by variations in color, type, and degradation level, which makes an inaccurate waste classification process. To overcome these challenges, this research proposes a novel Channel and Spatial Attention-Based Multiblock Convolutional Network for accurately classifying municipal waste that utilizes a unique attention mechanism for enhancing feature learning and waste classification accuracy.
View Article and Find Full Text PDFDiagnostics (Basel)
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Facultad de Informática, Universidad Autónoma de Querétaro, Querétaro 76230, Mexico.
: Oral diseases such as caries, gingivitis, and periodontitis are highly prevalent worldwide and often arise from plaque. This study focuses on detecting three plaque stages-new, mature, and over-mature-using state-of-the-art YOLO architectures to enhance early intervention and reduce reliance on manual visual assessments. : We compiled a dataset of 531 RGB images from 177 individuals, captured via multiple mobile devices.
View Article and Find Full Text PDFEnviron Monit Assess
January 2025
Royal Danish Library, Special Collections, Søren Kierkegaards Plads. 1, 1221, Copenhagen K, Denmark.
Historical topographical maps contain valuable, spatially and thematically detailed information about past landscapes. Yet, for analyses of landscape dynamics through geographical information systems, it is necessary to "unlock" this information via map processing. For two study areas in northern and central Jutland, Denmark, we apply object-based image analysis, vector GIS, colour image segmentation, and machine learning processes to produce machine-readable layers for the land use and land cover categories forest, wetland, heath, dune sand, and water bodies from topographic maps from the late nineteenth century.
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