The BrainLat project, a multimodal neuroimaging dataset of neurodegeneration from underrepresented backgrounds

Abstract The Latin American Brain Health Institute (BrainLat) has released a unique multimodal neuroimaging dataset of 780 participants from Latin American. The dataset includes 530 patients with neurodegenerative diseases such as Alzheimer’s disease (AD), behavioral variant frontotemporal dementia...

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Bibliographic Details
Main Authors: Pavel Prado, Vicente Medel, Raul Gonzalez-Gomez, Agustín Sainz-Ballesteros, Victor Vidal, Hernando Santamaría-García, Sebastian Moguilner, Jhony Mejia, Andrea Slachevsky, Maria Isabel Behrens, David Aguillon, Francisco Lopera, Mario A. Parra, Diana Matallana, Marcelo Adrián Maito, Adolfo M. Garcia, Nilton Custodio, Alberto Ávila Funes, Stefanie Piña-Escudero, Agustina Birba, Sol Fittipaldi, Agustina Legaz, Agustín Ibañez
Format: Article
Language:English
Published: Nature Portfolio 2023-12-01
Series:Scientific Data
Online Access:https://doi.org/10.1038/s41597-023-02806-8
Description
Summary:Abstract The Latin American Brain Health Institute (BrainLat) has released a unique multimodal neuroimaging dataset of 780 participants from Latin American. The dataset includes 530 patients with neurodegenerative diseases such as Alzheimer’s disease (AD), behavioral variant frontotemporal dementia (bvFTD), multiple sclerosis (MS), Parkinson’s disease (PD), and 250 healthy controls (HCs). This dataset (62.7 ± 9.5 years, age range 21–89 years) was collected through a multicentric effort across five Latin American countries to address the need for affordable, scalable, and available biomarkers in regions with larger inequities. The BrainLat is the first regional collection of clinical and cognitive assessments, anatomical magnetic resonance imaging (MRI), resting-state functional MRI (fMRI), diffusion-weighted MRI (DWI), and high density resting-state electroencephalography (EEG) in dementia patients. In addition, it includes demographic information about harmonized recruitment and assessment protocols. The dataset is publicly available to encourage further research and development of tools and health applications for neurodegeneration based on multimodal neuroimaging, promoting the assessment of regional variability and inclusion of underrepresented participants in research.
ISSN:2052-4463