Understanding rate and variability of connectivity in
normal brain development can offer insight into the
developmental origin of childhood and adult brain
disorders. Indeed, there is increasing interest towards
assessing the development of white matter (WM) fibers
underlying the complex brain connectivity [1], since the
development of functional connections is clearly
dependent on the establishment of cortical fiber pathways
[2,3], their appropriate maturation and myelination.
However, correlation of structural connectivity with
specific brain cognitive and behavioral brain functioning
can open the way to define quantitative and qualitative
MRI biomarkers with the final scope of understanding
brain organization and function. To goal of this work is
to study the brain connectivity and network model based
segregation of structural connectivity associated with
cognitive and behavioral scores in prematurely born
children. We used graph theory-based connectivity
analysis and stepwise linear regression models to assess
the contribution of brain connectivity as well as
subjects co-variates as gestational age (GA) and birth
weight (BW) in cognitive and behavioral performance of
young children.