When seeing people perform actions, we are able to quickly predict the action's outcomes. These predictions are not solely based on the observed actions themselves but utilize our prior knowledge of others. It has been suggested that observed outcomes that are not in line with these predictions result in prediction errors, which require additional processing to be integrated or updated. However, there is no consensus on whether this is indeed the case for the kind of high-level social-cognitive processes involved in action observation. In this fMRI study, we investigated whether observation of unexpected outcomes causes additional activation in line with the processing of prediction errors and, if so, whether this activation overlaps with activation in brain areas typically associated with social-cognitive processes. In the first part of the experiment, participants watched animated movies of two people playing a bowling game, one experienced and one novice player. In cases where the player's score was higher or lower than expected based on their skill level, there was increased BOLD activity in areas that were also activated during a theory of mind task that participants performed in the second part of the experiment. These findings are discussed in the light of different theoretical accounts of human social-cognitive processing.
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http://dx.doi.org/10.1162/jocn_a_01381 | DOI Listing |
Bioresour Technol
December 2024
School of Resources and Environment, Northeast Agricultural University, Harbin 150030, China. Electronic address:
Evaluating compost maturity, e.g. via manual seed germination index (GI) measurement, is both time-consuming and costly during composting.
View Article and Find Full Text PDFInt J Antimicrob Agents
December 2024
Department of Pharmacy, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510163, China. Electronic address:
Despite the widespread use of voriconazole in antifungal treatment, its high pharmacokinetic and pharmacodynamic variability may lead to suboptimal efficacy, especially in intensive care unit (ICU) patients. Machine learning (ML), an artificial intelligence modeling approach, is increasingly being applied to personalized medicine. The effectiveness of ML models for predicting voriconazole blood concentrations in ICU patients, compared to traditional population pharmacokinetics (popPK) models, has been uncertain until now.
View Article and Find Full Text PDFJ Food Sci
December 2024
College of Computer and Information Engineering, Inner Mongolia Agricultural University, Hohhot, China.
As consumers increasingly prioritize food safety and nutritional value, the dairy industry faces a pressing need for rapid and accurate methods to detect essential nutritional components in milk, such as fat, protein, and lactose. Hyperspectral imaging (HSI) technology, known for its non-destructive, fast, and precise nature, shows great promise in food quality assessment. However, the high dimensionality of HSI data poses challenges for effective band selection and model optimization.
View Article and Find Full Text PDFBiodegradation
December 2024
Department of Civil engineering, Islamic Azad university, Mashhad Branch, Iran.
The widespread use of pesticides, including diazinon, poses an increased risk of environmental pollution and detrimental effects on biodiversity, food security, and water resources. In this study, we investigated the impact of Potentially Toxic Elements (PTE) including Zn, Cd, V, and Mn on the degradation of diazinon in three different soils. We investigated the capability and performance of four machine learning models to predict residual pesticide concentration, including adaptive neuro-fuzzy inference system (ANFIS), support vector regression (SVR), radial basis function (RBF), and multi-layer perceptron (MLP).
View Article and Find Full Text PDFGraefes Arch Clin Exp Ophthalmol
December 2024
Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, No. 83 Fenyang Road, Shanghai, 200031, China.
Purpose: To compare the precision of the arithmetic mean of surgically induced astigmatism (M-SIA) and the centroid of surgically induced astigmatism (C-SIA) in estimating SIA when predicting the power and axis of toric IOLs under different circumstances.
Methods: 120 eyes of 99 patients undergoing toric IOL replacement in a simple cataract surgery were included in the retrospective study. The predicted position of toric IOL was calculated by Z Calc online calculator and Barrett Toric Calculator with M-SIA (0.
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