Semantic organization, an aspect of semantic processing, requires a pre-existing network of semantic knowledge that relies on a widely distributed neural network. The inferior prefrontal cortex (IPFC) has been identified as a vital structure for processing competing semantic information when making a decision about the meaning of a stimulus. However, the precise role of the IPFC in maintaining or creating a consistent semantic organizational structure is unclear. In this study, a semantic triadic decision-making task (Tallent, K.A., Weinberger, D.R., and Goldberg, T.E. 2001. Associating semantic space abnormalities with formal thought disorder in schizophrenia: use of triadic comparisons. J. Clin. Exp. Neuropsychol. 285-296) was used during functional magnetic resonance imaging to test the hypothesis that the degree of activation in the IPFC correlates with the consistency of semantic organization in healthy subjects. In this sample, subjects who had greater activation in the IPFC also demonstrated smaller stress coefficients in a two-dimensional "semantic space", indicating a greater organization of words along semantic dimensions. This finding is consistent with the role of the IPFC in establishing self-generated semantic relationships between stimuli.
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http://dx.doi.org/10.1016/j.neuroimage.2005.05.029 | DOI Listing |
PLoS One
January 2025
Dipartimento di Informatica, Bioingegneria, Robotica e Ingegneria dei Sistemi, Università di Genova, Genova, Italy.
In this paper, we explore the application of Artificial Intelligence and network science methodologies in characterizing interdisciplinary disciplines, with a specific focus on the field of Italian design, taken as a paradigmatic example. Exploratory data analysis and the study of academic collaboration networks highlight how the field is evolving towards increased collaboration. Text analysis and semantic topic modelling identified the evolution of research interest over time, defining a ranking of pairs of keywords and three prominent research topics: User-Centric Experience Design, Innovative Product Design and Sustainable Service Design.
View Article and Find Full Text PDFSci Rep
January 2025
EIAS Data Science Lab, College of Computer and Information Sciences, Prince Sultan University, 11586, Riyadh, Saudi Arabia.
During the Covid-19 pandemic, the widespread use of social media platforms has facilitated the dissemination of information, fake news, and propaganda, serving as a vital source of self-reported symptoms related to Covid-19. Existing graph-based models, such as Graph Neural Networks (GNNs), have achieved notable success in Natural Language Processing (NLP). However, utilizing GNN-based models for propaganda detection remains challenging because of the challenges related to mining distinct word interactions and storing nonconsecutive and broad contextual data.
View Article and Find Full Text PDFMicrosc Microanal
January 2025
Fritz-Haber-Institut der Max-Planck-Gesellschaft, Berlin 14195, Germany.
In catalysis research, the amount of microscopy data acquired when imaging dynamic processes is often too much for nonautomated quantitative analysis. Developing machine learned segmentation models is challenged by the requirement of high-quality annotated training data. We thus substitute expert-annotated data with a physics-based sequential synthetic data model.
View Article and Find Full Text PDFJ Exp Psychol Learn Mem Cogn
December 2024
Basque Center on Cognition, Brain and Language.
The present study uses event-related potentials (ERPs) to investigate lexicosemantic prediction in native speakers (L1) of English and advanced second language (L2) learners of English with Swedish as their L1. The main goal of the study was to examine whether learners recruit predictive mechanisms to the same extent as L1 speakers when a change in the linguistic environment renders prediction a useful strategy to pursue. The study, which uses a relatedness proportion paradigm adapted from Lau et al.
View Article and Find Full Text PDFPsychol Aging
January 2025
Department of Psychology, National Taiwan University.
The Socioemotional Selectivity Theory (SST) posits that older and younger adults have different life goals due to differences in perceived remaining lifetime. Younger adults focus more on future-oriented knowledge exploration and forming new friendships, while older adults prioritize present-focused emotional regulation and maintaining close relationships. While previous research has found these age differences manifest in autobiographical textual expressions, their presence in verbal communication remains unexplored.
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