Characterizing normal perinatal development of the human brain
  structural connectivity
Yihan Wu Lana Vasung Camilo Calixto Ali Gholipour Davood Karimi
Early brain development is characterized by the formation of a highly
organized structural connectome. The interconnected nature of this connectome
underlies the brain's cognitive abilities and influences its response to
diseases and environmental factors. Hence, quantitative assessment of
structural connectivity in the perinatal stage is useful for studying normal
and abnormal neurodevelopment. However, estimation of the connectome from
diffusion MRI data involves complex computations. For the perinatal period,
these computations are further challenged by the rapid brain development and
imaging difficulties. Combined with high inter-subject variability, these
factors make it difficult to chart the normal development of the structural
connectome. As a result, there is a lack of reliable normative baselines of
structural connectivity metrics at this critical stage in brain development. In
this study, we developed a computational framework, based on spatio-temporal
averaging, for determining such baselines. We used this framework to analyze
the structural connectivity between 33 and 44 postmenstrual weeks using data
from 166 subjects. Our results unveiled clear and strong trends in the
development of structural connectivity in perinatal stage. Connection weighting
based on fractional anisotropy and neurite density produced the most consistent
results. We observed increases in global and local efficiency, a decrease in
characteristic path length, and widespread strengthening of the connections
within and across brain lobes and hemispheres. We also observed asymmetry
patterns that were consistent between different connection weighting
approaches. The new computational method and results are useful for assessing
normal and abnormal development of the structural connectome early in life.