Juan Domingo Gispert

This paper introduces Tau-CTFP, a model for forecasting regional tau PET abnormality onset in Alzheimer's disease using connectome-informed continuous-time first-passage modeling, achieving high precision and recall in predicting abnormality onset.

The paper identifies lipid-related genetic mechanisms contributing to white matter hyperintensities in middle-aged individuals at low risk for late-life dementia.

The paper identifies brain structure signatures linked to Alzheimer's genetic risk across disease stages using compositional data analysis.

The paper characterizes the genetic profiles of ALFA participants, showing high AD genetic risk and similarity to clinical groups along the AD continuum.

The paper uses computational modeling to identify key brain regions for personalized neurostimulation strategies to improve cognitive interventions in Alzheimer's disease.

The paper identifies shared transcriptome alterations across neurodegenerative and psychiatric disorders using post-mortem brain samples.

The paper describes an MRI dataset and processing pipeline for the EPAD study, identifying quality control features and image-derived phenotypes related to aging and dementia.

The paper investigates how amyloid and tau levels in CSF affect eigenvector centrality during hippocampal down-regulation using real-time fMRI neurofeedback.

This study links APOE genotype and hippocampal structure to neurofeedback performance in preclinical Alzheimer's disease risk individuals.

This paper identifies disease-stage-specific patterns of functional degradation and compensation in Alzheimer’s disease using eigenvector centrality mapping and CSF biomarkers.