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| http://dx.doi.org/10.1371/journal.pntd.0004455 | DOI Listing |
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A shared serial order system for verbal working memory and language production: evidence from aphasia.
Cogn Neuropsychol
January 2025
Department of Psychological Sciences, Rice University, Houston, Texas, USA.
Many aspects of human performance require producing sequences of items in serial order. The current study takes a multiple-case approach to investigate whether the system responsible for serial order is shared across cognitive domains, focusing on working memory (WM) and word production. Serial order performance in three individuals with post-stroke language and verbal WM disorders (hereafter persons with aphasia, PWAs) were assessed using recognition and recall tasks for verbal and visuospatial WM, as well as error analyses in spoken and written production tasks to assess whether there was a tendency to produce the correct phonemes/letters in the wrong order.
View Article and Find Full Text PDFToward a Free-Response Paradigm of Decision-Making in Spiking Neural Networks.
Neural Comput
January 2025
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200437, China
Spiking neural networks (SNNs) have attracted significant interest in the development of brain-inspired computing systems due to their energy efficiency and similarities to biological information processing. In contrast to continuous-valued artificial neural networks, which produce results in a single step, SNNs require multiple steps during inference to achieve a desired accuracy level, resulting in a burden in real-time response and energy efficiency. Inspired by the tradeoff between speed and accuracy in human and animal decision-making processes, which exhibit correlations among reaction times, task complexity, and decision confidence, an inquiry emerges regarding how an SNN model can benefit by implementing these attributes.
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Department of Computer Science, City University of Hong Kong, Hong Kong, China.
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Intensive longitudinal data, increasingly common in social and behavioral sciences, often consist of multivariate time series from multiple individuals. Dynamic factor analysis, combining factor analysis and time series analysis, has been used to uncover individual-specific processes from single-individual time series. However, integrating these processes across individuals is challenging due to estimation errors in individual-specific parameter estimates.
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College of Education and Professional Studies, University of South Alabama, 75 S University Blvd #3600, Mobile, AL, 36618, USA.
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