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Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging technique that enables in vivo reconstruction of the brain's white matter connections at macro scale. It provides an important tool for quantitative mapping of the brain's structural connectivity using measures of connectivity or tissue microstructure. Over the last two decades, the study of brain connectivity using dMRI tractography has played a prominent role in the neuroimaging research landscape. In this paper, we provide a high-level overview of how tractography is used to enable quantitative analysis of the brain's structural connectivity in health and disease. We focus on two types of quantitative analyses of tractography, including: 1) tract-specific analysis that refers to research that is typically hypothesis-driven and studies particular anatomical fiber tracts, and 2) connectome-based analysis that refers to research that is more data-driven and generally studies the structural connectivity of the entire brain. We first provide a review of methodology involved in three main processing steps that are common across most approaches for quantitative analysis of tractography, including methods for tractography correction, segmentation and quantification. For each step, we aim to describe methodological choices, their popularity, and potential pros and cons. We then review studies that have used quantitative tractography approaches to study the brain's white matter, focusing on applications in neurodevelopment, aging, neurological disorders, mental disorders, and neurosurgery. We conclude that, while there have been considerable advancements in methodological technologies and breadth of applications, there nevertheless remains no consensus about the "best" methodology in quantitative analysis of tractography, and researchers should remain cautious when interpreting results in research and clinical applications.
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http://dx.doi.org/10.1016/j.neuroimage.2021.118870 | DOI Listing |
JMIR Hum Factors
September 2025
KK Women's and Children's Hospital, Singapore, Singapore.
Background: Breast cancer treatment, particularly during the perioperative period, is often accompanied by significant psychological distress, including anxiety and uncertainty. Mobile health (mHealth) interventions have emerged as promising tools to provide timely psychosocial support through convenient, flexible, and personalized platforms. While research has explored the use of mHealth in breast cancer prevention, care management, and survivorship, few studies have examined patients' experiences with mobile interventions during the perioperative phase of breast cancer treatment.
View Article and Find Full Text PDFJAMA Psychiatry
September 2025
School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia.
Importance: Cannabis is the most commonly used illicit drug, with 10% to 30% of regular users developing cannabis use disorder (CUD), a condition linked to altered hippocampal integrity. Evidence suggests high-intensity interval training (HIIT) enhances hippocampal structure and function, with this form of physical exercise potentially mitigating CUD-related cognitive and mental health impairments.
Objective: To determine the impact of a 12-week HIIT intervention on hippocampal integrity (ie, structure, connectivity, biochemistry) compared with 12 weeks of strength and resistance (SR) training in CUD.
Genetica
September 2025
Faculty of Fisheries and Aquaculture Sciences, Universiti Malaysia Terengganu, Kuala Nerus, Terengganu, Malaysia.
Population genetics plays a critical role in creating policies for managing fisheries, conservation, and development of aquaculture. The golden snapper, Lutjanus johnii (Bloch, 1792), is a highly commercial and aquaculture important snapper species. This study used mitochondrial markers D-loop (151 specimens) and Cytochrome b (Cyt-b, 120 specimens) from 10 populations, including populations from the east South China Sea, the west South China Sea and the Strait of Malacca to investigate the genetic diversity, population connectivity, and historical demography of L.
View Article and Find Full Text PDFPsychopharmacology (Berl)
September 2025
Instituto de Biología Celular y Neurociencias "Prof. De Robertis" (IBCN), CONICET-Universidad de Buenos Aires, Buenos Aires, Argentina.
Rationale: Autism spectrum disorders (ASD) are a group of neurodevelopmental and multifactorial conditions with cognitive manifestations. The valproic acid (VPA) rat model is a well-validated model that successfully reproduces the behavioral and neuroanatomical alterations of ASD. Previous studies found atypical brain connectivity and metabolic patterns in VPA animals: local glucose hypermetabolism in the prefrontal cortex, with no metabolic changes in the hippocampus.
View Article and Find Full Text PDFChaos
September 2025
School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
Although many real-world time series are complex, developing methods that can learn from their behavior effectively enough to enable reliable forecasting remains challenging. Recently, several machine-learning approaches have shown promise in addressing this problem. In particular, the echo state network (ESN) architecture, a type of recurrent neural network where neurons are randomly connected and only the read-out layer is trained, has been proposed as suitable for many-step-ahead forecasting tasks.
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