Many reasons exist why a child may develop developmental delay (DD) and we do not know yet if they share similar underlying neural conditions, such as deficits in neural circuits. This project aims to characterize the macroscale neuronal circuit structure in children who present mild to moderate DD. We focus on a group of children with mixed reasons for DD, such as congenital heart disorders, prematurity, or congenital central nervous system disorders. We analyze existing structural and diffusion tensor magnetic resonance imaging (DT-MRI) data from newborns and associate the results with cognitive outcomes. The goal is to implement in collaboration with the Platform SEED HDDA analysis techniques that enable us to reveal connectome features that might separate groups (normal vs. pathological).
Once established, this analysis pipeline could be applied to additional datasets in the URPP, such as cases from the Developmental Delay Database. Moreover, the connectomic framework would offer a way for cross-species comparisons, where the anatomical correspondence of regions and networks between species is ambiguous.
Principal investigator: Andras Jakab, Bea Latal, Michael von Rhein, Valerio Mante
PhD student: Anna Speckert