This manuscript introduces a set of analyses, that rely on linear mixed models to perform association and prediction, while being suited to tackle the challenges of big-data in neuroimaging. Our fram....

Molecular Psychiatry - Classification of major depressive disorder using vertex-wise brain sulcal depth, curvature, and thickness with a deep and a shallow learning model

Translational Psychiatry - Applying machine-learning and deep-learning to predict depression from brain MRI and identify depression-related brain biology

The growing availability of large neuroimaging datasets, such as the UK Biobank, provides new opportunities to improve robustness and reproducibility in brain imaging research. However, little is known about the extent to which MRI processing pipelines influence results. Using 39,655 T1-weighted MRI …

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We meta-analysed results from 11 neuroimaging cohorts of elderly participants, to estimate the morphometricity (total association with brain measurements) of 17 traits of interest, and to identify th...

Many studies have investigated early predictors for Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS). Howev…