Parcellations of resting-state functional magnetic resonance imaging (rs-fMRI) data are widely used to create topographical maps of functional networks in the human brain. While such network maps are highly useful for studying brain organization and function, they usually require large sample sizes to make them, thus creating practical limitations for researchers that would like to carry out parcellations on data collected in their labs. Furthermore, it can be difficult to quantitatively evaluate the results of a parcellation since networks are usually identified using a clustering algorithm, like principal components analysis, on the results of a single group-averaged connectivity map.
View Article and Find Full Text PDFPurpose: High resolution fMRI is a rapidly growing research field focused on capturing functional signal changes across cortical layers. However, the data acquisition is limited by low spatial frequency EPI artifacts; termed here as Fuzzy Ripples. These artifacts limit the practical applicability of acquisition protocols with higher spatial resolution, faster acquisition speed, and they challenge imaging in lower brain areas.
View Article and Find Full Text PDFEndocr Metab Immune Disord Drug Targets
June 2024
Aim: This guideline (GL) is aimed at providing a clinical practice reference for the management of adult patients with overweight or obesity associated with metabolic complications who are resistant to lifestyle modification.
Methods: Surgeons, endocrinologists, gastroenterologists, psychologists, pharmacologists, a general practitioner, a nutritionist, a nurse and a patients' representative acted as multi-disciplinary panel. This GL has been developed following the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach.