Deutsch
 
Benutzerhandbuch Datenschutzhinweis Impressum Kontakt
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Zeitschriftenartikel

Networks of myelin covariance

MPG-Autoren
/persons/resource/persons19617

Draganski,  Bogdan
Laboratoire de Recherche en Neuroimagerie (LREN), Centre hospitalier universitaire vaudois, Lausanne, Switzerland;
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

Externe Ressourcen
Es sind keine Externen Ressourcen verfügbar
Volltexte (frei zugänglich)

Melie-Garcia_Slater_2017.pdf
(Verlagsversion), 3MB

Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Melie-Garcia, L., Slater, D., Ruef, A., Sanabria-Diaz, G., Preisig, M., Kherif, F., et al. (2018). Networks of myelin covariance. Human Brain Mapping, 39(4), 1532-1554. doi:10.1002/hbm.23929.


Zitierlink: http://hdl.handle.net/21.11116/0000-0000-02E6-A
Zusammenfassung
Networks of anatomical covariance have been widely used to study connectivity patterns in both normal and pathological brains based on the concurrent changes of morphometric measures (i.e., cortical thickness) between brain structures across subjects (Evans, 2013). However, the existence of networks of microstructural changes within brain tissue has been largely unexplored so far. In this article, we studied in vivo the concurrent myelination processes among brain anatomical structures that gathered together emerge to form nonrandom networks. We name these “networks of myelin covariance” (Myelin-Nets). The Myelin-Nets were built from quantitative Magnetization Transfer data—an in-vivo magnetic resonance imaging (MRI) marker of myelin content. The synchronicity of the variations in myelin content between anatomical regions was measured by computing the Pearson's correlation coefficient. We were especially interested in elucidating the effect of age on the topological organization of the Myelin-Nets. We therefore selected two age groups: Young-Age (20–31 years old) and Old-Age (60–71 years old) and a pool of participants from 48 to 87 years old for a Myelin-Nets aging trajectory study. We found that the topological organization of the Myelin-Nets is strongly shaped by aging processes. The global myelin correlation strength, between homologous regions and locally in different brain lobes, showed a significant dependence on age. Interestingly, we also showed that the aging process modulates the resilience of the Myelin-Nets to damage of principal network structures. In summary, this work sheds light on the organizational principles driving myelination and myelin degeneration in brain gray matter and how such patterns are modulated by aging.