Site differences, or systematic differences in feature distributions across multiple data-
acquisition sites, are a known source of heterogeneity that may adversely affect large-scale …

The basal ganglia and thalami are paired deep grey matter structures with extensive
metabolic activity that renders them susceptible to injury by various diseases. Most …

Background Microstructural changes in deep gray matter (DGM) nuclei are related to
physiological behavior, cognition, and memory. Therefore, it is critical to study age …

In recent years, several studies have demonstrated that machine learning and deep learning
systems can be very useful to accurately predict brain age. In this work, we propose a novel …

Putative MRI markers of iron in deep gray matter have demonstrated age related changes
during discrete periods of healthy childhood or adulthood, but few studies have included …

The thalamus is a central integration structure in the brain, receiving and distributing
information among the cerebral cortex, subcortical structures, and the peripheral nervous …

Brain ageing is a complex neurobiological process associated with morphological changes
that can be assessed on MRI scans. Recently, Deep learning (DL)-based approaches have …

The striatum is a major subcortical connection hub that has been heavily implicated in a
wide array of motor and cognitive functions. Here, we developed a normative multimodal …

The study of the hippocampus across the healthy adult lifespan has rendered inconsistent
findings. While volumetric measurements have often been a popular technique for analysis …

Statistical effects of cortical metrics derived from standard T1‐and T2‐weighted magnetic
resonance imaging (MRI) images, such as gray–white matter contrast (GWC), boundary …