Yasser Alemán‐Gómez

MRSIPrep provides a standardized post-quantification framework for whole-brain MRSI to improve reproducibility across datasets and applications.

The paper uses longitudinal spectroscopic imaging to show sex-specific hormone-metabolite coupling in adolescent brains, revealing age and sex-dependent neurochemical changes.

This study evaluates microstructure-weighted connectomes using diffusion MRI data and finds that DePerp provides the most consistent structure-function coupling across spatial scales.

The paper uses magnetic resonance spectroscopic imaging to identify sex differences in brain metabolites across multiple cohorts, finding a consistent male higher tNAA/tCr ratio in gray and white matter.

This paper introduces directed connectomics using bicommunities to reveal asymmetric pathways in brain networks and validates them with electrophysiological data.

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

This study uses high-resolution 3D-MRSI to assess neurometabolite differences in youth at risk for psychosis compared to controls, finding elevated tNAA and Ins in specific brain regions.

This paper develops a whole-brain model to predict conduction velocity from MRI-derived microstructural features, explaining 29% of variance in neurophysiological conduction velocity.

This paper identifies optimal graph signal processing features for subject identification through large-scale comparative analysis of parameter choices and feature types.

This study uses whole-brain models to analyze brain connectivity differences between remitting and non-remitting early psychosis patients, finding altered functional connectivity and potential compensatory mechanisms.

The paper constructs the first human brain metabolic connectome using MR spectroscopic imaging, revealing distinct topological features and alignment with cytoarchitectonic and genetic patterns.

This study assesses how defacing structural MRI images affects quality assessments by humans and automated tools, finding significant human bias and minimal impact on MRIQC metrics.

This paper introduces CSET, a method that reconstructs electrical brain source-networks with high spatial resolution using diffusion MRI and EEG data.

The paper introduces an algorithm to estimate vertex-wise sulcal width maps on cortical surfaces, validated against simulations and showing correlations with age in an aging population.

ABLE extracts sulcal fundi and gyral crown lines from brain surfaces using Laplacian surface collapse, validated on HCP data to show reliable and accurate sulcal topology representation.

This paper uses an autoencoder to enhance through-plane resolution in fetal brain diffusion MRI, outperforming interpolation methods on pre-term newborn data.