Prior studies have shown that experts possess an excellent ability for action anticipation. However, it is not clear how experts process the discrepancies between predicted outcomes and actual outcomes. Based on Bayesian theory, Experiment 1 in the current study explored this question by categorizing unexpected outcomes into gradually increasing discrepancies and comparing the performance of experts and novices on a congruence discrimination task. Our behavioral analysis revealed that experts outperformed novices significantly in detecting these discrepancies. The following electroencephalogram study in Experiment 2 was conducted focused exclusively on experts to examine the role of theta wave oscillations within the mid-frontal cortex in processing varying levels of discrepancy. The results showed that reaction time and theta oscillations gradually increased as the magnitude of discrepancy increased. These findings indicate that compared to the novices, experts have a better ability to perceptual the discrepancy. Also, the magnitude of discrepancies induced an increase in mid-frontal theta in experts, providing greater flexibility in their response strategies.
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http://dx.doi.org/10.1080/02640414.2024.2358291 | DOI Listing |
Am J Emerg Med
January 2025
Faculty of Medicine, Universidad de Valladolid, Valladolid, Spain; Emergency Department, Hospital Clínico Universitario, Gerencia Regional de Salud de Castilla y León, Valladolid, Spain.
Background: The study of the inclusion of new variables in already existing early warning scores is a growing field. The aim of this work was to determine how capnometry measurements, in the form of end-tidal CO2 (ETCO2) and the perfusion index (PI), could improve the National Early Warning Score (NEWS2).
Methods: A secondary, prospective, multicenter, cohort study was undertaken in adult patients with unselected acute diseases who needed continuous monitoring in the emergency department (ED), involving two tertiary hospitals in Spain from October 1, 2022, to June 30, 2023.
PLoS One
January 2025
College of Business, Southern University of Science and Technology, Shenzhen, China.
In credit risk assessment, unsupervised classification techniques can be introduced to reduce human resource expenses and expedite decision-making. Despite the efficacy of unsupervised learning methods in handling unlabeled datasets, their performance remains limited owing to challenges such as imbalanced data, local optima, and parameter adjustment complexities. Thus, this paper introduces a novel hybrid unsupervised classification method, named the two-stage hybrid system with spectral clustering and semi-supervised support vector machine (TSC-SVM), which effectively addresses the unsupervised imbalance problem in credit risk assessment by targeting global optimal solutions.
View Article and Find Full Text PDFJ Neurophysiol
January 2025
KU Leuven, Department of Movement Sciences, B-3000 Leuven, Belgium.
In motor adaptation, learning is thought to rely on a combination of several processes. Two of these are implicit learning (incidental updating of the movement due to sensory prediction error) and explicit learning (intentional adjustment to reduce target error). The explicit component is thought to be fast adapting, while the implicit one is slow.
View Article and Find Full Text PDFExpert Opin Drug Metab Toxicol
January 2025
Institute of Psychology, University of Innsbruck, Austria.
Introduction: The prevalence of polypharmacy and the increasing availability of pharmacogenetic information in clinical practice have raised the prospect of data-driven clinical decision making when addressing the issues of drug-drug interactions and genetic polymorphisms in metabolizing enzymes. Inhibition of metabolizing enzymes in drug interactions can lead to genotype-phenotype discrepancies (phenoconversion) that reduce the relevance of individual pharmacogenetic information.
Areas Covered: The aim of this review is to provide an overview on existing models of phenoconversion and we discuss how phenoconversion models may be developed to estimate joint drug-interactions and genetic effects.
APMIS
January 2025
Department of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
This study prospectively collected the clinical data, information on respiratory pathogens, and laboratory findings of children with Mycoplasma pneumoniae (M. pneumonia) infection who were hospitalized at the First Affiliated Hospital of Anhui Medical University during the M. pneumoniae outbreak in Hefei City, Anhui Province, China, between October 2023 and December 2023.
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