Abstract
The architecture of the human connectome changes with brain maturation. Pivotal to understanding these changes is defining developmental periods when transitions in network topology occur. Here, using 110 resting-state functional connectivity data sets from healthy fetuses between 19 and 40 gestational weeks, we estimated optimal gestational-age (GA) cut points for dichotomizing fetuses into ‘young’ and ‘old’ groups based on global network features. We computed the small-world index, normalized clustering and path length, global and local efficiency, and modularity from connectivity matrices comprised 200 regions and their corresponding pairwise connectivity. We modeled the effect of GA at scan on each metric using separate repeated-measures generalized estimating equations. Our modeling strategy involved stratifying fetuses into ‘young’ and ‘old’ based on the scan occurring before or after a selected GA (i.e., 28 to 33). We then used the quasi-likelihood independence criterion statistic to compare model fit between ‘old’ and ‘young’ cohorts and determine optimal cut points for each graph metric. Trends for all metrics, except for global efficiency, decreased with increasing gestational age. Optimal cut points fell within 30–31 weeks for all metrics coinciding with developmental events that include a shift from endogenous neuronal activity to sensory-driven cortical patterns.
Highlights
Recent advances in brain imaging have enabled researchers to investigate in vivo human brain development
Cut points were defined for global functional network metrics that we have recently described; these metrics are normalized clustering and path length, global and local efficiency, modularity, and the small-world index, metrics we have previously described in this fetal cohort [5]
We modeled the effect of GA at scan on connectivity metrics using separate repeatedmeasures generalized estimating equations (GEE)
Summary
Recent advances in brain imaging have enabled researchers to investigate in vivo human brain development. While fetal imaging is a nascent field, findings over the past decade have begun to shed light on patterns of neural circuitry formation: connectivity follows a mediolateral, posteroanterior timing [4,7,8], occipital and sensorimotor circuits develop earlier than parietal connections [4], lateralization appears in superior temporal cortices in utero [3], and intraand interhemispheric connectivity strength increase with maturity [9]. Studies have shown the emergence of small-world network topology as early as the second trimester and reduced segregation with advancing GA based on decreasing modularity, normalized clustering, and local efficiency [5,12,13]. While trends have been described, it is unclear when the transition to mature network patterns occurs
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