María Dolores Figueroa-Jimenez1, Cristina Cañete-Massé2,3, María Carbó-Carreté4,5, Daniel Zarabozo-Hurtado6, Maribel Peró-Cebollero2,3,4, José Guadalupe Salazar-Estrada1, Joan Guàrdia-Olmos2,3,4. 1. Department of Health Sciences, Centro Universitario de los Valles, University of Guadalajara, Guadalajara, Mexico. 2. Department of Social Psychology & Quantitative Psychology, Faculty of Psychology, University of Barcelona, Barcelona, Spain. 3. UB Institute of Complex Systems, University of Barcelona, Barcelona, Spain. 4. Institute of Neuroscience, University of Barcelona, Barcelona, Spain. 5. Department of Cognition, Developmental Psychology and Education, Faculty of Psychology, University of Barcelona, Barcelona, Spain. 6. RIO Group Clinical Laboratory, Center for Research in Advanced Functional Neuro-Diagnosis CINDFA, Guadalajara, México.
Abstract
BACKGROUND: Down syndrome (DS) is a chromosomal disorder that causes intellectual disability. Few studies have been conducted on functional connectivity using resting-state fMRI (functional magnetic resonance imaging) signals or more specifically, on the relevant structure and density of the default mode network (DMN). Although data on this issue have been reported in adult DS individuals (age: >45 years), the DMN properties in young DS individuals have not been studied. The aim of this study was to describe the density and structure of the DMN network from fMRI signals in young DS (age: <36 years). METHOD: A sample of 22 young people with DS between the ages of 16 and 35 (M = 25.5 and SD = 5.1) was recruited in various centers for people with intellectual disability (ID). In addition to sociodemographic data, a six-minute fMRI session was recorded with a 3. T Philips Ingenia scanner. A control group of 22 young people, matched by age and gender, was obtained from the Human Connectome Project (to compare the networks properties between groups). RESULTS: The values of the 48 ROIs that configured the DMN were obtained, and the connectivity graphs for each subject, the average connectivity graph for each group, the clustering and degree values for each ROI, and the average functional connectivity network were estimated. CONCLUSIONS: A higher density of overactivation was identified in DS group in the ventral, sensorimotor, and visual DMN networks, although within a framework of a wide variability of connectivity patterns in comparison with the control group network. These results extend our understanding of the functional connectivity networks pattern and intrasubject variability in DS.
BACKGROUND: Down syndrome (DS) is a chromosomal disorder that causes intellectual disability. Few studies have been conducted on functional connectivity using resting-state fMRI (functional magnetic resonance imaging) signals or more specifically, on the relevant structure and density of the default mode network (DMN). Although data on this issue have been reported in adult DS individuals (age: >45 years), the DMN properties in young DS individuals have not been studied. The aim of this study was to describe the density and structure of the DMN network from fMRI signals in young DS (age: <36 years). METHOD: A sample of 22 young people with DS between the ages of 16 and 35 (M = 25.5 and SD = 5.1) was recruited in various centers for people with intellectual disability (ID). In addition to sociodemographic data, a six-minute fMRI session was recorded with a 3. T Philips Ingenia scanner. A control group of 22 young people, matched by age and gender, was obtained from the Human Connectome Project (to compare the networks properties between groups). RESULTS: The values of the 48 ROIs that configured the DMN were obtained, and the connectivity graphs for each subject, the average connectivity graph for each group, the clustering and degree values for each ROI, and the average functional connectivity network were estimated. CONCLUSIONS: A higher density of overactivation was identified in DS group in the ventral, sensorimotor, and visual DMN networks, although within a framework of a wide variability of connectivity patterns in comparison with the control group network. These results extend our understanding of the functional connectivity networks pattern and intrasubject variability in DS.
Authors: Laia Farras-Permanyer; Núria Mancho-Fora; Marc Montalà-Flaquer; David Bartrés-Faz; Lídia Vaqué-Alcázar; Maribel Peró-Cebollero; Joan Guàrdia-Olmos Journal: Neural Regen Res Date: 2019-09 Impact factor: 5.135
Authors: Annette Karmiloff-Smith; Tamara Al-Janabi; Hana D'Souza; Jurgen Groet; Esha Massand; Kin Mok; Carla Startin; Elizabeth Fisher; John Hardy; Dean Nizetic; Victor Tybulewicz; Andre Strydom Journal: F1000Res Date: 2016-03-23
Authors: María Dolores Figueroa-Jimenez; Cristina Cañete-Massé; María Carbó-Carreté; Daniel Zarabozo-Hurtado; Maribel Peró-Cebollero; José Guadalupe Salazar-Estrada; Joan Guàrdia-Olmos Journal: Brain Behav Date: 2020-11-12 Impact factor: 2.708
Authors: María Dolores Figueroa-Jimenez; María Carbó-Carreté; Cristina Cañete-Massé; Daniel Zarabozo-Hurtado; Maribel Peró-Cebollero; José Guadalupe Salazar-Estrada; Joan Guàrdia-Olmos Journal: Brain Sci Date: 2021-03-02