This study investigated the computational cost associated with grammatical planning in sentence production. We measured people's pupillary responses as they produced spoken descriptions of depicted events. We manipulated the syntactic structure of the target by training subjects to use different types of sentences following a colour cue. The results showed higher increase in pupil size for the production of passive and object dislocated sentences than for active canonical subject-verb-object sentences, indicating that more cognitive effort is associated with more complex noncanonical thematic order. We also manipulated the time at which the cue that triggered structure-building processes was presented. Differential increase in pupil diameter for more complex sentences was shown to rise earlier as the colour cue was presented earlier, suggesting that the observed pupillary changes are due to differential demands in relatively independent structure-building processes during grammatical planning. Task-evoked pupillary responses provide a reliable measure to study the cognitive processes involved in sentence production.
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http://dx.doi.org/10.1080/17470218.2014.911925 | DOI Listing |
Health Informatics J
January 2025
Department of Computer Science and Information Technology, La Trobe University, Melbourne, VIC, Australia.
The HIV epidemic in Indonesia is one of the fastest growing in Southeast Asia and is characterised by a number of geographic and sociocultural challenges. Can large language models (LLMs) be integrated with telehealth (TH) to address cost and quality of care? A literature review was performed using the PRISMA-ScR (2018) guidelines between Jan 2017 and June 2024 using the PubMed, ArXiv and semantic scholar databases. Of the 694 records identified, 12 studies met the inclusion criteria.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
Faculty of Medicine and Pharmacy of Rabat, Mohammed V University of Rabat, Rabat, 10000, Morocco.
Gastrointestinal (GI) disease examination presents significant challenges to doctors due to the intricate structure of the human digestive system. Colonoscopy and wireless capsule endoscopy are the most commonly used tools for GI examination. However, the large amount of data generated by these technologies requires the expertise and intervention of doctors for disease identification, making manual analysis a very time-consuming task.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy.
The current gold standard for the study of human movement is the marker-based motion capture system that offers high precision but constrained by costs and controlled environments. Markerless pose estimation systems emerge as ecological alternatives, allowing unobtrusive data acquisition in natural settings. This study compares the performance of two popular markerless systems, OpenPose (OP) and DeepLabCut (DLC), in assessing locomotion.
View Article and Find Full Text PDFTransl Psychiatry
January 2025
Department of Psychology, Goldsmiths University of London, London, UK.
Bipolar disorder (BD) involves altered reward processing and decision-making, with inconsistencies across studies. Here, we integrated hierarchical Bayesian modelling with magnetoencephalography (MEG) to characterise maladaptive belief updating in this condition. First, we determined if previously reported increased learning rates in BD stem from a heightened expectation of environmental changes.
View Article and Find Full Text PDFMethods
January 2025
School of Computer Science and Engineering, Central South University, Changsha 410083, China; Hunan Provincial Key Lab on Bioinformatics, Central South University, Changsha 410083, China.
Compound-protein interaction (CPI) prediction is critical in the early stages of drug discovery, narrowing the search space for CPIs and reducing the cost and time required for traditional high-throughput screening. However, CPI-related data are usually distributed across different institutions and their sharing is restricted because of data privacy and intellectual property rights. Constructing a scheme that enhances multi-institutional collaboration to improve prediction accuracy while protecting data privacy is essential.
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