Manuel Blesa

The paper introduces dGAMLSS, a distributed algorithm for fitting GAMLSS models to construct population reference charts without sharing patient data.

This study identifies two ASD subgroups with distinct brain morphology using cross-cultural datasets, highlighting key brain regions associated with subgroup characteristics and autistic traits.

This study uses the Vogt-Bailey index to analyze cortical microstructure gradients in preterm and term infants, finding spatially distributed alterations in preterm infants.

The paper introduces a longitudinal dataset of school-age children and adolescents in China, detailing its design, sampling, and neuroimaging measurements.

The paper introduces brain charts as a standardized resource for benchmarking brain morphology across the human lifespan using MRI data from a large and diverse cohort.

The paper uses DTI and NODDI metrics from 16 white matter tracts in preterm and term infants to identify general factors that capture shared variance and predict preterm birth outcomes.

The paper identifies cognitive stages in MEG data using a novel method and develops a whole-brain model to simulate cortical synchrony during a task, showing thalamic bursts drive state transitions.

This study finds that maternal cortisol levels are linked to differences in neonatal amygdala microstructure and connectivity, with sex-specific effects observed in girls and boys.

This study examines hierarchical complexity in neonatal and adult brain networks, finding greater complexity in term-born neonates compared to preterms, linked to connectivity patterns in intermediate tiers.

The paper investigates associations between polygenic risk scores for schizophrenia, psychotic-like experiences, and structural brain network properties in healthy UK Biobank participants.

The paper uses morphometric similarity networks derived from MRI data to predict brain age and identify neuroanatomic variations in preterm and term neonates.