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Language production involves action sequencing to produce fluent speech in real time, placing a computational burden on working memory that leads to sequencing biases in production. Here we examine whether these biases extend beyond language to constrain one of the most complex human behaviors: music improvisation. Using a large corpus of improvised solos from eminent jazz musicians, we test for a production bias observed in language termed -a tendency for more accessible sequences to occur at the beginning of a phrase, allowing incremental planning later in the same phrase. Our analysis shows consistent evidence of easy first in improvised music, with the beginning of musical phrases containing both more frequent and less complex sequences. The findings indicate that expert jazz musicians, known for spontaneous creative performance, reliably retrieve easily accessed melodic sequences before creating more complex sequences, suggesting that a domain-general sequencing system may support multiple forms of complex human behavior, from language production to music improvisation. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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http://dx.doi.org/10.1037/xge0001107 | DOI Listing |
Ann Biomed Eng
September 2025
Department of Midwifery, Faculty of Health Sciences, Sakarya University, 54100, Sakarya, Turkey.
The incorporation of AI-supported language models into the healthcare sector holds significant potential to revolutionize nursing education, research, and clinical practice. Within this framework, ChatGPT has emerged as a valuable tool for personalizing educational materials, enhancing academic productivity, expediting clinical decision-making processes, and optimizing research efficiency. In the realm of nursing education, ChatGPT offers numerous advantages, including the preparation of course content, facilitation of student assessments, and the development of simulation-based learning environments.
View Article and Find Full Text PDFJ Speech Lang Hear Res
September 2025
University of the Witwatersrand, Johannesburg, South Africa.
Background: The integration of digital health care technologies into speech-language pathology and audiology is rapidly transforming service delivery. In South Africa and other low- and middle-income countries (LMICs), digital tools offer significant opportunities to address access challenges and enhance patient outcomes. However, the adoption of these technologies requires careful consideration of contextual factors.
View Article and Find Full Text PDFMedicine (Baltimore)
September 2025
School of Sports Science and Technology, Guangzhou College of Applied Science and Technology, Guangdong, China.
Objective: This study combines a bibliometric analysis with an umbrella review to delineate the research landscape, hotspots, and emerging trends in the application of artificial intelligence to the clinical diagnosis and treatment of mild cognitive impairment.
Methods: We searched the Web of Science Core Collection for literature published between 2004 and 2024. Bibliometric analysis of the retrieved publications was performed using CiteSpace and VOSviewer to map publication trends, international collaboration networks, key contributors, and keyword co-occurrence.
Nat Comput Sci
September 2025
PGI-15, Forschungszentrum Jülich, Jülich, Germany.
Transformer networks, driven by self-attention, are central to large language models. In generative transformers, self-attention uses cache memory to store token projections, avoiding recomputation at each time step. However, graphics processing unit (GPU)-stored projections must be loaded into static random-access memory for each new generation step, causing latency and energy bottlenecks.
View Article and Find Full Text PDFNat Comput Sci
September 2025
Department of Electronic Engineering, Tsinghua University, Beijing, China.
City plans are the product of integrating human creativity with emerging technologies, which continuously evolve and reshape urban morphology and environments. Here we argue that large language models hold large untapped potential in addressing the growing complexities of urban planning and enabling a more holistic, innovative and responsive approach to city design. By harnessing their advanced generation and simulation capabilities, large language models can contribute as an intelligent assistant for human planners in synthesizing conceptual ideas, generating urban designs and evaluating the outcomes of planning efforts.
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