dc.contributor.author | Machado, Alejandra | |
dc.contributor.author | Barroso Ribal, José Domingo | |
dc.contributor.author | Molina Rodsríguez, Yaiza | |
dc.contributor.author | Nieto Barco, Antonieta | |
dc.contributor.author | Díaz Flores, Lucio | |
dc.contributor.author | Westman, Eric | |
dc.contributor.author | Ferreira Padilla, Daniel | |
dc.contributor.other | Psicología Clínica, Psicobiología y Metodología | |
dc.contributor.other | Grupo de investigación ULL: Neuropsicología
Facultad de Psicología y Logopedia
Instituto Universitario de Neurociencia | |
dc.date.accessioned | 2024-01-16T21:06:30Z | |
dc.date.available | 2024-01-16T21:06:30Z | |
dc.date.issued | 2018 | |
dc.identifier.uri | http://riull.ull.es/xmlui/handle/915/35396 | |
dc.description | https://doi.org/10.1016/j.neurobiolaging.2018.07.017 | |
dc.description.abstract | Cognitive aging is highly complex. We applied a data-driven statistical method to investigate aging from
a hierarchical, multidimensional, and multivariate approach. Orthogonal partial least squares to latent
structures and hierarchical models were applied for the first time in a study of cognitive aging. The
association between age and a total of 316 demographic, clinical, cognitive, and neuroimaging measures
was simultaneously analyzed in 460 cognitively normal individuals (35e85 years). Age showed a strong
association with brain structure, especially with cortical thickness in frontal and parietal association
regions. Age also showed a fairly strong association with cognition. Although a strong association of age
with executive functions and processing speed was captured as expected, the association of age with
visual memory was stronger. Clinical measures were less strongly associated with age. Hierarchical and
correlation analyses further showed these associations in a neuroimaging-cognitive-clinical order of
importance. We conclude that orthogonal partial least square and hierarchical models are a promising
approach to better understand the complexity in cognitive aging. | en |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | |
dc.relation.ispartofseries | Neurobiology of Aging, 71 (2018) | |
dc.rights | No autorizo la publicación del documento | |
dc.title | Proposal for a hierarchical, multidimensional, and multivariate approach to investigate cognitive aging. | |
dc.type | info:eu-repo/semantics/article | |
dc.identifier.doi | 10.1016/j.neurobiolaging.2018.07.017 | |
dc.subject.keyword | Aging | en |
dc.subject.keyword | Multivariate analysis | en |
dc.subject.keyword | OPLS | en |
dc.subject.keyword | Hierarchical | en |
dc.subject.keyword | Cognition | en |
dc.subject.keyword | Magnetic resonance imaging | en |