Ariosky Areces-González

The paper introduces {xi}-Net, a generative model of cortical activity that estimates EEG components and connectivity across lifespan using rsEEG 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.

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

This paper develops multinational qEEG norms using Hermitian Riemannian methods, showing improved diagnostic accuracy for brain dysfunction and providing harmonization tools.

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.

This study compares EEG connectivity in full-term and preterm infants during their first year, finding age-related trends and differences between groups.

The paper compares EEG and MEG source spectra using BC-VARETA and finds no differences in reconstructed sources between the two modalities.

This paper introduces a method to control leakage in electrophysiological source imaging using structured sparse Bayesian learning and evaluates its performance against existing methods.