Hugo Gerard Schnack

This study links sulcal widening in schizophrenia to network hubs and genes involved in synaptic signaling and energy metabolism.

The paper examines morphometric similarity networks in health and schizophrenia, finding reduced default mode network similarity in schizophrenia but minimal individual deviations over time.

The paper identifies 617 novel genomic loci and pathways associated with structural covariance patterns in the human brain using a stochastic multivariate factorization method.

The paper examines longitudinal allometric scaling of sulcal morphology in health and schizophrenia, finding steeper age-related declines in SZ compared to healthy individuals.

This paper introduces MAGIC, a multi-scale semi-supervised clustering method for brain imaging data to identify disease subtypes, and evaluates its performance on simulated and clinical datasets.

The paper examines sex differences in lifespan trajectories and variability of human sulcal and gyral morphology using longitudinal neuroimaging data.

This study compares machine learning algorithms for predicting brain age in schizophrenia, finding that most linear methods perform similarly but OLS regression is less accurate, leading to variability in brainPAD estimates.

The paper identifies a subgroup of schizophrenia patients with extreme cognitive deficits by analyzing sulcal width dissimilarity using the PBSI-SW metric.

This study reports longitudinal changes in intracranial volume (ICV) from early adulthood to the sixth decade, finding increases until the fourth decade followed by decreases, with cross-sectional results showing larger changes.

This study identifies genetic variants linked to longitudinal brain structure changes across the lifespan using MRI data from 15,640 individuals.