Previous structural and functional neuroimaging studies have implicated distributed brain
regions and networks in depression. However, there are no robust imaging biomarkers that …

Background Schizophrenia (SZ) and bipolar disorder (BD) share substantial
neurodevelopmental components affecting brain maturation and architecture. This …

Background Conduct disorder (CD), which is characterized by severe aggressive and
antisocial behavior, is linked to emotion processing and regulation deficits. However, the …

Maternal depression during pregnancy is associated with elevated risk of anxiety and
depression in offspring, but the mechanisms are incompletely understood. Here we …

Introduction Both maternal depression problems during pregnancy and prenatal exposure to
air pollution have been associated with changes in the brain as well as worse mood and …

Graphical models such as brain connectomes derived from functional magnetic resonance
imaging (fMRI) data are considered a prime gateway to understanding network-type …

Background Brain atrophy occurs in both normal ageing and in multiple sclerosis (MS), but it
occurs at a faster rate in MS, where it is the major driver of disability progression. Here, we …

Objectives Define a clinically usable preprocessing pipeline for MRI data Predict brain age
using various machine learning and deep learning algorithms Define Caveat against …

Key Points Question Is the gap between brain age predicted from MRI and chronological
age associated with incident dementia in a general population of Dutch adults? Findings …

Abstract Machine learning algorithms trained to recognize age-related structural changes in
magnetic resonance images (MRIs) of healthy individuals can be used to predict biological …