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Empirical studies reporting low test-retest reliability of individual blood oxygen-level dependent (BOLD) signal estimates in functional magnetic resonance imaging (fMRI) data have resurrected interest among cognitive neuroscientists in methods that may improve reliability in fMRI. Over the last decade, several individual studies have reported that modeling decisions, such as smoothing, motion correction and contrast selection, may improve estimates of test-retest reliability of BOLD signal estimates. However, it remains an empirical question whether certain analytic decisions improve individual and group level reliability estimates in an fMRI task across multiple large, independent samples. This study used three independent samples (s: 60, 81, 119) that collected the same task (Monetary Incentive Delay task) across two runs and two sessions to evaluate the effects of analytic decisions on the individual (intraclass correlation coefficient [ICC(3,1)]) and group (Jaccard/Spearman ) reliability estimates of BOLD activity of task fMRI data. The analytic decisions in this study vary across four categories: smoothing kernel (five options), motion correction (four options), task parameterizing (three options) and task contrasts (four options), totaling 240 different pipeline permutations. Across all 240 pipelines, the median ICC estimates are consistently low, with a maximum median ICC estimate of .43 - .55 across the three samples. The analytic decisions with the greatest impact on the median ICC and group similarity estimates are the contrast, Cue Model parameterization and a larger smoothing kernel. Using an in a contrast condition meaningfully increased group similarity and ICC estimates as compared to using the cue. This effect was largest for the Cue Model parameterization; however, improvements in reliability came at the cost of interpretability. This study illustrates that estimates of reliability in the MID task are consistently low and variable at small samples, and a higher test-retest reliability may not always improve interpretability of the estimated BOLD signal.
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http://dx.doi.org/10.1101/2024.03.19.585755 | DOI Listing |
Front Vet Sci
August 2025
Department of Pathology, Microbiology and Immunology, University of California Davis School of Veterinary Medicine, Davis, CA, United States.
Mast cell tumors (MCTs) are the most common skin neoplasms in dogs and exhibit highly variable biological behavior. Metastasis primarily affects the lymph nodes, though less frequently, MCTs can infiltrate the spleen, liver, peripheral blood, and bone marrow. Flow cytometry of fine needle aspirate samples represents a non-invasive diagnostic procedure that has shown promise for detecting and quantifying mast cells in primary tumors and lymph nodes.
View Article and Find Full Text PDFRisk Anal
September 2025
US Army Engineer Research and Development Center, Concord, Massachusetts, USA.
The COVID-19 pandemic has exposed critical gaps in our management of systemic risks within complex, interconnected systems. This review examines 10 key areas where artificial intelligence (AI) and data analytics can significantly enhance pandemic preparedness, response, and recovery. Inadequate early warning systems, insufficient real-time data on resource needs, and the limitations of traditional epidemiological models in capturing complex disease dynamics are among the challenges analyzed.
View Article and Find Full Text PDFComput Biol Chem
September 2025
School of Mathematics, Statistics and Computer Science, Durban 4000, KwaZulu-Natal, South Africa; National Institute for Theoretical and Computational Sciences, NITheCS, South Africa. Electronic address:
Food insecurity and the spread of infectious disease are among the two major problems facing the world today especially in poor rural communities. Unfortunately, these two problems are related as many poor rural communities with food insecurity issues are also endemic to some food and waterborne diseases. A mathematical model that takes into consideration the major factors affecting food insecurity and disease is developed and used to analyse the problems.
View Article and Find Full Text PDFPatient
September 2025
PPD Evidera Patient-Centered Research, Thermo Fisher Scientific, Waltham, MA, USA.
Background: Migraine care is often suboptimal owing to undertreatment, variation in clinical outcomes and administration methods among existing treatments, and between- and within-individual heterogeneity in the clinical course of migraine. In response to these challenges, preference studies have been increasingly conducted to inform treatment decision-making and development. However, gaps remain in understanding how treatment preferences have been assessed across different migraine studies.
View Article and Find Full Text PDFJ Robot Surg
September 2025
Department of Research and Innovation, Medway NHS Foundation Trust, Gillingham, ME7 5NY, UK.
Robotic surgery has transformed the field of surgery, offering enhanced precision, minimal invasiveness, and improved patient outcomes. This narrative review explores the multifaceted aspects of robotic surgery, examining the challenges, recent advances, and future prospects for its integration into healthcare. Our comprehensive analysis of 48 studies reveals significant geographic disparities in robotic surgery research and implementation, with 68.
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