The present findings show the existence of significant differences in latency and amplitude of some waves of ERPs to three subclasses of nouns or verbs. Latency LP3 of ERPs to action verbs was shorter than latency of the same wave to abstract verbs. In nouns the relation was a similar (manipulable objects versus abstract ones). The amplitude of early positive components (P1, P2) and BN3 wave also depended on semantic attributes of nouns and verbs. Some waves of ERPs to motion verbs in our experiment had significantly higher amplitude than the same waves of ERPs to nonmanipulable objects. Also revealed was interaction between some ERP features and the subject's gender. It was primarily the amplitude of BP2, the size of which depended on gender in all cases--BP2 amplitude was significantly higher in females then in males. In the other components (BP1, BP4, BN2 and BN4) there were fewer significant differences and if they do occurred, then their amplitude was higher in males than in females. In some cases, gender also affected latency of waves LP2, LN1 and LN4 of ERPs to the same noun or verb subclass--latencies of these waves were shorter in females.
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http://dx.doi.org/10.5507/bp.2004.028 | DOI Listing |
Int J Neural Syst
January 2025
Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China, Huzhou 313001, P. R. China.
Visual semantic decoding aims to extract perceived semantic information from the visual responses of the human brain and convert it into interpretable semantic labels. Although significant progress has been made in semantic decoding across individual visual cortices, studies on the semantic decoding of the ventral and dorsal cortical visual pathways remain limited. This study proposed a graph neural network (GNN)-based semantic decoding model on a natural scene dataset (NSD) to investigate the decoding differences between the dorsal and ventral pathways in process various parts of speech, including verbs, nouns, and adjectives.
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December 2024
Cognitive Neuroscience Centre, University of San Andres, Victoria, Buenos Aires, Argentina.
Background: Dementia impacts the way individuals perceive and describe everyday events. Alzheimer's disease (AD) notably affects processing of entities manifested by nouns, while behavioral variant frontotemporal dementia (bvFTD) often presents a detached, third-person perspective. Yet, the potential of natural language processing tools (NLP) to detect these variations in spontaneous speech remains explored.
View Article and Find Full Text PDFBackground: Identifying language variation in healthy aging speakers is important for understanding normal cognitive aging. Setting a baseline of normal aging languages in the first place is necessary for the evaluation of language performances of old adults. Lexical concreteness, a well-studied psycholinguistic parameter, has been used to detect semantic memory-related deficits.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
National University of Singapore, Singapore, Singapore.
Comput Inform Nurs
December 2024
Author Affiliations: Data Driven WV, John Chambers College of Business and Economics (Ms Bailey), and School of Nursing, West Virginia University (Dr Carter-Templeton), Morgantown; School of Library and Information Sciences, North Carolina Central University, Durham (Dr Peterson); Duke University School of Nursing, Durham, NC (Dr Oermann); Dwight Schar College of Nursing and Health Sciences, Ashland University, OH (Dr Owens).
All disciplines, including nursing, may be experiencing significant changes with the advent of free, publicly available generative artificial intelligence tools. Recent research has shown the difficulty in distinguishing artificial intelligence-generated text from content that is written by humans, thereby increasing the probability for unverified information shared in scholarly works. The purpose of this study was to determine the extent of generative artificial intelligence usage in published nursing articles.
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