It is known that features of stimuli in the environment affect the strength of functional connectivity in the human brain. However, investigations to date have not converged in determining whether these also impact functional networks' global features, such as modularity strength, number of modules, partition structure, or degree distributions. We hypothesized that one environmental attribute that may strongly impact global features is the temporal regularity of the environment, as prior work indicates that differences in regularity impact regions involved in sensory, attentional and memory processes. We examined this with an fMRI study, in which participants passively listened to tonal series that had identical physical features and differed only in their regularity, as defined by the strength of transition structure between tones. We found that series-regularity induced systematic changes to global features of functional networks, including modularity strength, number of modules, partition structure, and degree distributions. In tandem, we used a novel node-level analysis to determine the extent to which brain regions maintained their within-module connectivity across experimental conditions. This analysis showed that primary sensory regions and those associated with default-mode processes are most likely to maintain their within-module connectivity across conditions, whereas prefrontal regions are least likely to do so. Our work documents a significant capacity for global-level brain network reorganization as a function of context. These findings suggest that modularity and other core, global features, while likely constrained by white-matter structural brain connections, are not completely determined by them.
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http://dx.doi.org/10.1016/j.neuroimage.2015.05.025 | DOI Listing |
Brain Struct Funct
January 2025
Department of Biomedical Engineering, College of Chemistry and Life Sciences, Beijing University of Technology, Beijing, 100124, China.
The brain undergoes atrophy and cognitive decline with advancing age. The utilization of brain age prediction represents a pioneering methodology in the examination of brain aging. This study aims to develop a deep learning model with high predictive accuracy and interpretability for brain age prediction tasks.
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Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
The incidence of type 2 diabetes has risen globally, in parallel with the obesity epidemic and environments promoting a sedentary lifestyle and low-quality diet. There has been scrutiny of ultra-processed foods (UPFs) as a driver of type 2 diabetes, underscored by their increasing availability and intake worldwide, across countries of all incomes. This narrative review addresses the accumulated evidence from investigations of the trends in UPF consumption and the relationship with type 2 diabetes incidence.
View Article and Find Full Text PDFProteins
January 2025
Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India.
Vector-borne diseases pose a severe threat to human life, contributing significantly to global mortality. Understanding the structure-function relationship of the vector proteins is pivotal for effective insecticide development due to their involvement in drug resistance and disease transmission. This study reports the structural and dynamic features of D1-like dopamine receptors (DARs) in disease-causing mosquito species, such as Aedes aegypti, Culex quinquefasciatus, Anopheles gambiae, and Anopheles stephensi.
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Guangdong Key Laboratory of Animal Conservation and Resource Utilization, Institute of Zoology, Guangdong Academy of Sciences, Guangzhou, Guangdong, China.
Rhinolophus bats have been identified as natural reservoirs for viruses with global health implications, including severe acute respiratory syndrome-related coronaviruses (SARSr-CoV) and swine acute diarrhoea syndrome-related coronavirus (SADSr-CoV). In this study, we characterised the individual viromes of 603 bats to systematically investigate the diversity, abundance and geographic distribution of viral communities within R. affinis, R.
View Article and Find Full Text PDFAnal Methods
November 2017
Centre de Recherche sur la Conservation (CRC), MNHN, Sorbonne-Universités CNRS, MCC, USR 3224, CP21, 36 rue Geoffroy Saint Hilaire, 75005 Paris, France.
Reflectance spectral imaging is a powerful tool for the non-invasive study of cultural heritage objects. Particular visible to short wave infrared (400-2500 nm) spectral features are linked to compositional information. Spectral images can hence be used to generate useful chemical maps.
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