This study examined the neural mechanisms underlying perceptual categorization and expertise. Participants were either exposed to or learned to classify three categories of cars (sedans, SUVs, antiques) at either the basic or subordinate level. Event-Related Potentials (ERPs) as well as accuracy and reaction time were recorded before, immediately after, and 1-week after training. Behavioral results showed that only subordinate-level training led to better discrimination of trained cars, and this ability was retained a week after training. ERPs showed an equivalent increase in the N170 across all three training conditions whereas the N250 was only enhanced in response to subordinate-level training. The behavioral and electrophysiological results distinguish category learning at the subordinate level from category learning occurring at the basic level or from simple exposure. Together with data from previous investigations, the current results suggest that subordinate-level training, but not basic-level or exposure training, leads to expert-like improvements in categorization accuracy. These improvements are mirrored by changes in the N250 rather than the N170 component, and these effects persist at least a week after training, so are conceivably related to long-term learning processes supporting perceptual expertise.
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http://dx.doi.org/10.1016/j.brainres.2008.02.054 | DOI Listing |
AIDS Behav
January 2025
Institute for Sexual and Gender Minority Health and Wellbeing, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Young men who have sex with men (YMSM) have high rates of substance use, which increases their risk for HIV. Digital Health Interventions (DHI) have the potential to address HIV risk overall and reduce harms in the context of substance use. However, there is limited research on how YMSM with different substance use patterns respond to HIV DHIs and how these programs impact participant outcomes.
View Article and Find Full Text PDFJMIR Med Inform
January 2025
School of Social Policy & Practice, University of Pennsylvania, Philadelphia, PA, United States.
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JMIR Med Educ
January 2025
Department of Pharmacy, Taipei Veterans General Hospital Hsinchu Branch, Hsinchu, Taiwan.
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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 PDFMed Educ Online
December 2025
Computer Science and Information Engineering, National Central University, Taoyuan, Taiwan.
Background: Medical Humanities (MH) curricula integrate humanities disciplines into medical education to nurture essential qualities in future physicians. However, the impact of MH on clinical competencies during formative training phases remains underexplored. This study aimed to determine the influence of MH curricula on internship performance.
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