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The activities of the human brain vary across different timescales, exhibiting scale-free dynamics. Previous research has highlighted the psychological and physiological significance of brain dynamical fluctuations across the Delta to Gamma bands. However, there has been less focus on infra-slow scale-free dynamics, e.g. power law exponent (PLE), and neural variability, e.g. standard deviation (SD), and sample entropy (SE), in mediating brain-behavior connection during attention. In this study, we recruited 49 participants and recorded functional magnetic resonance imaging (fMRI) resting-state and task data during a sustained attention task paradigm to investigate how the three measures-SD, SE, and PLE-modulate the dynamics of behavioral performance. Our findings demonstrate the following: (i) PLE, SD, and SE exhibit differential topographic distribution with a hierarchical structure from sensory to associative networks, during their rest-task modulation. (ii) PLE, SD, and SE show different topographic extensions from visual cortex to default-mode network in their relationship with behavioral variability. (iii) The relationship between SD and SE is mediated by PLE in the empirical data, which (iv) is further confirmed in simulation. Collectively, our results highlight the topographically- and dynamically-layered mechanisms of distinct neurodynamical features during attention processing: scale-free dynamics modulate neural and behavioral variability.
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http://dx.doi.org/10.1038/s42003-025-08448-3 | DOI Listing |
Bull Math Biol
September 2025
Universidad Tecnológica Metropolitana, Las Palmeras 3360, Ñuñoa, 7800003, Santiago de Chile, Santiago de Chile, Chile.
We introduce two mathematical models for the spread of an SIR-type infectious disease, incorporating direct (person-to-person) and indirect (environment-to-person) transmissions, latent periods, asymptomatic infections, and different isolation rates for exposed, asymptomatic and symptomatic individuals. The first model employs the classical homogeneous mixing approach, while the second uses the edge-based compartmental approach to consider heterogeneity in the number of contacts within the population through a random contact network. Key epidemiological metrics, including the basic reproduction number and final epidemic size, are derived and illustrated through simulations for both models.
View Article and Find Full Text PDFSci Total Environ
August 2025
State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China. Electronic address:
Research on urban soils has traditionally neglected two significant dimensions: the spatial heterogeneity emerging within megacity resulting from varying urbanization rates, and the dynamic responses of soil microbial communities to ongoing urban expansion processes. To address these research gaps, we propose a new approach to study soil bacterial communities based on urbanization gradients. Beijing is divided into three regions according to urbanization gradient by machine learning method.
View Article and Find Full Text PDFSci Rep
August 2025
Business School, University of Shanghai for Science and Technology, Shanghai, 200093, China.
Rumor spreading has been posing a significant threat to maintain the normal social order. In this paper, we propose a ISDR rumor propagation model on scale-free networks that considers fractional-order and refutation mechanism. we acquire basic reproduction number [Formula: see text] based on the rumor equilibrium point [Formula: see text], which thoroughly characterizes the dynamics of rumor propagation.
View Article and Find Full Text PDFSci Rep
August 2025
Department of Mathematics, University of Tennessee at Chattanooga, Chattanooga, TN, 37403, USA.
Gaining insight into the mechanisms of zoonotic disease transmission in both animal and human populations is essential for implementing effective measures to control the disease spread and mitigate its impact. This paper employs an evolutionary game theory framework to analyze the intricate dynamics of Monkeypox (mpox) epidemics across diverse networks, including scale-free and random regular networks with four network settings (BA-BA, ER-ER, BA-ER, and ER-BA) in both humans and animals. We investigate how individual behaviors and interactions influence the spread of diseases in different populations by combining network structures with evolutionary game dynamics.
View Article and Find Full Text PDFCommun Biol
August 2025
Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health Research, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada.