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Although functional connectivity has been extensively studied in MS, robust estimates of both stationary (static connectivity at the time) and dynamic (connectivity variation across time) functional connectivity has not been commonly evaluated and neither has its association to cognition. In this study, we focused on interhemispheric connections as previous research has shown links between anatomical homologous connections and cognition. We examined functional interhemispheric connectivity (IC) in MS during resting-state functional MRI using both stationary and dynamic strategies and related connectivity measures to processing speed performance. Twenty-five patients with relapsing-remitting MS and 41 controls were recruited. Stationary functional IC was assessed between homologous Regions of Interest (ROIs) using correlation. For dynamic IC, a sliding window approach was used to quantify changes between homologous ROIs across time. We related IC measures to cognitive performance with correlation and regression. Compared to control subjects, MS demonstrated increased IC across homologous regions, which accurately predicted performance on the symbol digit modalities test (SDMT) ( = 0.96) and paced auditory serial addition test (PASAT) ( = 0.59). Dynamic measures were not different between the 2 groups, but dynamic IC was related to PASAT scores. The associations between stationary/dynamic connectivity and cognitive tests demonstrated that different aspects of functional IC were associated with cognitive processes. Processing speed measured in SDMT was associated with static interhemispheric connections and better PASAT performance, which requires working memory, sustain attention, and processing speed, was more related to rigid IC, underlining the neurophysiological mechanism of cognition in MS.
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http://dx.doi.org/10.3389/fneur.2020.00407 | DOI Listing |
ISA Trans
September 2025
State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, No. 95 ZhongGuanCun East Road, HaiDian District, Beijing, PR China. Electronic address:
This work investigates the problem of collaborative target tracking by multiple unmanned aerial vehicles (UAVs) in maritime search and rescue. A class of time-varying (TV) convex optimization problems with inequality constraints is presented. In contrast to existing studies that address UAV-based maritime search and rescue under fixed wind speed conditions, this study also explores collaborative target tracking by UAVs under varying wind speed conditions.
View Article and Find Full Text PDFComput Methods Programs Biomed
September 2025
Laboratory of Image Science and Technology, School of Computer Science and Engineering, Southeast University, Nanjing, 210096, China; Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing, Southeast University, Nanjing, 210096, China. Electronic address: xuji@s
Background: Photon counting computed tomography (PCCT) has emerged as a potential technology that is revolutionizing clinical CT imaging. Using photon counting detectors (PCDs), the PCCT counts each X-ray event and measures the corresponding energy above the noise floor with significantly higher spatial resolution. However, the multiple-energy-bin setting and much smaller pixels increase the raw data size of PCCT by 20-100 times compared to traditional CT.
View Article and Find Full Text PDFPhys Rev Lett
August 2025
California Institute of Technology, TAPIR, Division of Physics, Mathematics, and Astronomy, Pasadena, California 91125, USA.
In the gravitational-wave analysis of pulsar-timing-array datasets, parameter estimation is usually performed using Markov chain Monte Carlo methods to explore posterior probability densities. We introduce an alternative procedure that instead relies on stochastic gradient-descent Bayesian variational inference, whereby we obtain the weights of a neural-network-based approximation of the posterior by minimizing the Kullback-Leibler divergence of the approximation from the exact posterior. This technique is distinct from simulation-based inference with normalizing flows since we train the network for a single dataset, rather than the population of all possible datasets, and we require the computation of the data likelihood and its gradient.
View Article and Find Full Text PDFGerontologist
September 2025
Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, 60612United States.
Background And Objectives: Cognition may be influenced by health-related factors such as blood pressure (BP). However, variations in BP may differentially affect cognition across race. This study investigates BP and cognitive decline in older Black and White adults.
View Article and Find Full Text PDFJ Biomed Opt
September 2025
Fraunhofer Institute for Microelectronic Circuits and Systems IMS, Duisburg, Germany.
Significance: The spatial and temporal distribution of fluorophore fractions in biological and environmental systems contains valuable information about the interactions and dynamics of these systems. To access this information, fluorophore fractions are commonly determined by means of their fluorescence emission spectrum (ES) or lifetime (LT). Combining both dimensions in temporal-spectral multiplexed data enables more accurate fraction determination while requiring advanced and fast analysis methods to handle the increased data complexity and size.
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