Global Network Organization of the Fetal Functional Connectome

Abstract

Recent advances in brain imaging have enabled non-invasive in vivo assessment of the fetal brain. Characterizing brain development in healthy fetuses provides baseline measures for identifying deviations in brain function in high-risk clinical groups. We examined 110 resting state MRI data sets from fetuses at 19 to 40 weeks' gestation. Using graph-theoretic techniques, we characterized global organizational features of the fetal functional connectome and their prenatal trajectories. Topological features related to network integration (i.e., global efficiency) and segregation (i.e., clustering) were assessed. Fetal networks exhibited small-world topology, showing high clustering and short average path length relative to reference networks. Likewise, fetal networks' quantitative small world indices met criteria for small-worldness (σ > 1, ω = [-0.5 0.5]). Along with this, fetal networks demonstrated global and local efficiency, economy, and modularity. A right-tailed degree distribution, suggesting the presence of central areas that are more highly connected to other regions, was also observed. Metrics, however, were not static during gestation; measures associated with segregation-local efficiency and modularity-decreased with advancing gestational age. Altogether, these suggest that the neural circuitry underpinning the brain's ability to segregate and integrate information exists as early as the late 2nd trimester of pregnancy and reorganizes during the prenatal period. Significance statement. Mounting evidence for the fetal origins of some neurodevelopmental disorders underscores the importance of identifying features of healthy fetal brain functional development. Alterations in prenatal brain connectomics may serve as early markers for identifying fetal-onset neurodevelopmental disorders, which in turn provide improved surveillance of at-risk fetuses and support the initiation of early interventions.

Keywords: fetal brain development; fetal connectome; global network organization; graph theory; resting state MRI.

Figure 1

Global network features of the fetal functional connectome. Top shows small world properties of fetal RSNs (Fet). Indices s and w met criteria for small-worldness, marked by the black dashed line. Fetal metrics shown relative to values from reference random (Ran) and lattice networks (Lat).

Figure 2

Economy of fetal RSNs. Global and local efficiency of fetal networks, as a function of network cost, are shown relative to random and lattice networks. Fetal RSNs are cost efficient (right); CE values >0 at all costs tested. Maximum cost efficiency denoted by dashed vertical line.

Figure 3

Degree distribution of fetal RSNs. Right tailed distribution at cost (edge density) = 10% is shown (left). A few nodes that have high degree occupy the right side of the distribution. Right show log–log plots of degree vs cumulative distribution; different model fits are presented with truncated power law showing the bestfit.

Figure 4

Normalized clustering, modularity, small world index (σ), and local efficiency decrease with advancing gestational age. Males (dot); females (diamond).