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Events are a fundamentally important part of our understanding of the world. How lexical concepts denoting events are represented in the brain remains controversial. We conducted two experiments using event and object nouns matched on a range of psycholinguistic variables, including concreteness, to examine spatial and temporal characteristics of event concepts. Both experiments used magnitude and valence tasks on event and object nouns. The fMRI experiment revealed a distributed set of regions for events, including the angular gyrus, anterior temporal lobe, and posterior cingulate across tasks. In the EEG experiment, events and objects differed in amplitude within the 300-500 ms window. Together these results shed light into the spatiotemporal characteristics of event concept representation and show that event concepts are represented in the putative hubs of the semantic system. While these hubs are typically associated with object semantics, they also represent events, and have a likely role in temporal integration.
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http://dx.doi.org/10.1016/j.bandl.2023.105328 | DOI Listing |
Patient
September 2025
PPD Evidera Patient-Centered Research, Thermo Fisher Scientific, Waltham, MA, USA.
Background: Migraine care is often suboptimal owing to undertreatment, variation in clinical outcomes and administration methods among existing treatments, and between- and within-individual heterogeneity in the clinical course of migraine. In response to these challenges, preference studies have been increasingly conducted to inform treatment decision-making and development. However, gaps remain in understanding how treatment preferences have been assessed across different migraine studies.
View Article and Find Full Text PDFEpilepsia
September 2025
Department of Pharmacology and Neuroscience, Creighton University School of Medicine, Omaha, Nebraska, USA.
The rate of sudden unexpected death in epilepsy (SUDEP) is ~1 per 1000 patients each year. Terminal events reportedly involve repeated and prolonged apnea, suggesting a failure to autoresuscitate. To better understand the mechanisms and identify novel therapeutics, standardized tests to screen for autoresuscitation efficacy are needed in preclinical SUDEP.
View Article and Find Full Text PDFAPMIS
September 2025
Laboratory of Parasitology, Department of Bacteria, Parasites and Fungi, Infectious Disease Preparedness, Statens Serum Institut, Copenhagen, Denmark.
Clinical microbiology involves the detection and differentiation of primarily bacteria, viruses, parasites and fungi in patients with infections. Billions of people may be colonised by one or more species of common luminal intestinal parasitic protists (CLIPPs) that are often detected in clinical microbiology laboratories; still, our knowledge on these organisms' impact on global health is very limited. The genera Blastocystis, Dientamoeba, Entamoeba, Endolimax and Iodamoeba comprise CLIPPs species, the life cycles of which, as opposed to single-celled pathogenic intestinal parasites (e.
View Article and Find Full Text PDFFront Psychol
August 2025
School of Economics and Management, Chengdu Sport University, Chengdu, China.
Introduction: Although marathon events have gained global popularity and align closely with public health objectives, limited research has explored how individuals perceive the attractiveness of these events and how such perceptions influence participation intention. This study introduces the concept of "perceived attractiveness" as a multidimensional evaluation encompassing emotional, symbolic, cultural, and convenience facets related to participation. Drawing upon self-determination theory and self-efficacy theory, the study investigates how perceived attractiveness predicts participation intention, mediated by exercise-related self-efficacy.
View Article and Find Full Text PDFNat Sci Sleep
August 2025
Flinders Health and Medical Research Institute-- Sleep Health (Adelaide Institute for Sleep Health), College of Medicine and Public Health, Flinders University, Bedford Park, SA, 5042, Australia.
Introduction: Type 2 diabetes (T2D) shows bidirectional relationships with polysomnographic measures. However, no studies have searched systematically for novel polysomnographic biomarkers of T2D. We therefore investigated if state-of-the-art explainable machine learning (ML) models could identify new polysomnographic biomarkers predictive of incident T2D.
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