title: Structural brain connectivity and cognitive ability differences: A multivariate distance matrix regression analysis.
abstract: Neuroimaging research involves analyses of huge amounts of biological data that might or might not be related with cognition. This relationship is usually approached using univariate methods, and, therefore, correction methods are mandatory for reducing false positives. Nevertheless, the probability of false negatives is also increased. Multivariate frameworks have been proposed for helping to alleviate this balance. Here we apply multivariate distance matrix regression for the simultaneous analysis of biological and cognitive data, namely, structural connections among 82 brain regions and several latent factors estimating cognitive performance. We tested whether cognitive differences predict distances among individuals regarding their connectivity pattern. Beginning with 3,321 connections among regions, the 36 edges better predicted by the individuals' cognitive scores were selected. Cognitive scores were related to connectivity distances in both the full (3,321) and reduced (36) connectivity patterns. The selected edges connect regions distributed across the entire brain and the network defined by these edges supports high-order cognitive processes such as (a) (fluid) executive control, (b) (crystallized) recognition, learning, and language processing, and (c) visuospatial processing. This multivariate study suggests that one widespread, but limited number, of regions in the human brain, supports high-level cognitive ability differences. Hum Brain Mapp 38:803-816, 2017. © 2016 Wiley Periodicals, Inc.
authors.affiliation: Facultad de Psicología, Universidad Autónoma de Madrid, Madrid, Spain.
authors.forename: Vicente
authors.initials: V
authors.lastname: Ponsoda
authors.affiliation: Facultad de Psicología, Universidad Autónoma de Madrid, Madrid, Spain.|Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón (Madrid, Spain) and Instituto de Investigación Sanitaria Gregorio Marañón (IISGM) (Madrid, Spain) and Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM) (Madrid, Spain) and Universidad Europea de Madrid, Madrid, Spain.
authors.forename: Kenia
authors.initials: K
authors.lastname: Martínez
authors.affiliation: CINAC (Centro Integral de Neurociencias AC), HM Puerta del Sur, Hospitales de Madrid (Móstoles, Madrid, Spain) and CEU San Pablo University, Madrid, Spain.
authors.forename: José A
authors.initials: JA
authors.lastname: Pineda-Pardo
authors.affiliation: Facultad de Psicología, Universidad Autónoma de Madrid, Madrid, Spain.
authors.forename: Francisco J
authors.initials: FJ
authors.lastname: Abad
authors.affiliation: Facultad de Psicología, Universidad Autónoma de Madrid, Madrid, Spain.
authors.forename: Julio
authors.initials: J
authors.lastname: Olea
authors.affiliation: Facultad de Psicología, Universidad Autónoma de Madrid, Madrid, Spain.|Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana.
authors.forename: Francisco J
authors.initials: FJ
authors.lastname: Román
authors.affiliation: Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana.
authors.forename: Aron K
authors.initials: AK
authors.lastname: Barbey
authors.affiliation: Facultad de Psicología, Universidad Autónoma de Madrid, Madrid, Spain.
authors.forename: Roberto
authors.initials: R
authors.lastname: Colom
mesh_terms: D000293:Adolescent; D001921:Brain / Q000000981:diagnostic imaging* / Q000502:physiology*; D001931:Brain Mapping; D003071:Cognition / Q000502:physiology*; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional; D008279:Magnetic Resonance Imaging; D008297:Male; D015999:Multivariate Analysis; D009434:Neural Pathways / Q000000981:diagnostic imaging / Q000502:physiology; D009483:Neuropsychological Tests; D012044:Regression Analysis; D015203:Reproducibility of Results; D055815:Young Adult
keywords: cognitive differences; multivariate distance matrix regression; structural connectivity