Sebastian M. Benavidez

This paper identifies widespread gray and white matter volume differences in autism using a large voxel-based morphometry analysis of 3,051 participants.

This paper develops a lifespan normative model of brain white matter microstructure using diffusion MRI data from 54,583 individuals, enabling detection of microstructural deviations in diseases like Alzheimer's and 22q11.2 deletion syndrome.

This study uses BUAN and TDF to analyze white matter microstructure in autism, finding region-specific reductions in integrity and increases in diffusivity in the corpus callosum.

This study uses BUAN and TDF to map white matter microstructural differences in autism, finding altered fractional anisotropy and diffusivity in specific regions of major tracts.

This study introduces MINT, a framework that jointly models white matter microstructure and macrostructure to better detect anomalies in MCI and dementia, showing improved sensitivity compared to traditional diffusion metrics.

This study uses diffusion MRI and tractometry to analyze how amyloid, tau, and APOE genetic variants affect white matter microstructure in Alzheimer's disease.

The paper assesses sex differences in white matter microstructure during development using diffusion MRI models and finds the TDF model is most sensitive in detecting these differences.

This paper applies data harmonization techniques to 3D diffusion MRI tractometry to improve reliability and comparability across multiple scanning protocols.

This paper introduces DNT, a variational autoencoder framework for detecting white matter abnormalities in Alzheimer's disease using macro- and microstructural data.