While part of the left ventral occipito-temporal cortex (left-vOT), known as the Visual Word Form Area, plays a central role in reading, the area also responds to speech. This cross-modal activation has been explained by three competing hypotheses. Firstly, speech is converted to orthographic representations that activate, in a top-down manner, written language coding neurons in the left-vOT. Secondly, the area contains multimodal neurons that respond to both language modalities. Thirdly, the area comprises functionally segregated neuronal populations that selectively encode different language modalities. A transcranial magnetic stimulation (TMS)-adaptation protocol was used to disentangle these hypotheses. During adaptation, participants were exposed to spoken or written words in order to tune the initial state of left-vOT neurons to one of the language modalities. After adaptation, they performed lexical decisions on spoken and written targets with TMS applied to the left-vOT. TMS showed selective facilitatory effects. It accelerated lexical decisions only when the adaptors and the targets shared the same modality, i.e., when left-vOT neurons had initially been adapted to the modality of the target stimuli. Since this within-modal adaptation was observed for both input modalities and no evidence for cross-modal adaptation was found, our findings suggest that the left-vOT contains neurons that selectively encode written and spoken language rather than purely written language coding neurons or multimodal neurons encoding language regardless of modality.
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http://dx.doi.org/10.1016/j.neuroimage.2018.11.014 | DOI Listing |
Cities
February 2025
Department of Geography & Environmental Studies, University of New Mexico, Albuquerque, New Mexico, 87131, USA.
Historical redlining practices in the United States date back to the 1930s and have continued to impact cities socially, environmentally, and economically since then. This study explores current social vulnerability inequity among former HOLC (Home Owners' Loan Corporation) neighborhoods with four color-coded grades in 196 U.S.
View Article and Find Full Text PDFInt J Nurs Stud Adv
June 2025
Research Group Healthy Ageing, Allied Health Care and Nursing and FAITH Research, Hanze University of Applied Sciences, Petrus Driessenstraat 3, 9714, CA, Groningen, The Netherlands.
Introduction: Oral health care of older people in long-term care facilities is insufficient, stressing the need for clear evidence-based implementation strategies to improve oral care. In 2013, a systematic review was performed and new evidence was published. This study aimed to gain insights into implementation strategies used to promote or improve oral health care for older people in long-term care facilities, explore their effectiveness and uncover strategy content in behavioral change techniques, and report the differences between the current results and those of the 2013 study.
View Article and Find Full Text PDFJMIR Med Inform
January 2025
School of Social Policy & Practice, University of Pennsylvania, Philadelphia, PA, United States.
Background: Prediction models have demonstrated a range of applications across medicine, including using electronic health record (EHR) data to identify hospital readmission and mortality risk. Large language models (LLMs) can transform unstructured EHR text into structured features, which can then be integrated into statistical prediction models, ensuring that the results are both clinically meaningful and interpretable.
Objective: This study aims to compare the classification decisions made by clinical experts with those generated by a state-of-the-art LLM, using terms extracted from a large EHR data set of individuals with mental health disorders seen in emergency departments (EDs).
Nat Commun
January 2025
Department of Civil and Systems Engineering, Johns Hopkins University, Baltimore, MD, USA.
Direct Ink Writing, an extrusion-based 3D printing technique, has attracted growing interest due to its ability to process a broad range of materials and integrate multifunctional printheads with features such as shape-changing nozzles, in-situ curing, material switching, and material mixing. Despite these advancements, incorporating auxiliary controls into Geometry Code (G-Code), the standard programming language for these printers, remains challenging. G-Code's line-by-line execution requires auxiliary control commands to interrupt the print path motion, causing defects in the printed structure.
View Article and Find Full Text PDFJ Biomed Inform
January 2025
University of Manchester, United Kingdom.
Objective: Extracting named entities from clinical free-text presents unique challenges, particularly when dealing with discontinuous entities-mentions that are separated by unrelated words. Traditional NER methods often struggle to accurately identify these entities, prompting the development of specialised computational solutions. This paper systematically reviews and presents the methodologies developed for Discontinuous Named Entity Recognition in clinical texts, highlighting their effectiveness and the challenges they face.
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