Variable functional connectivity architecture of the preterm human brain: Impact of developmental cortical expansion and maturation

Abstract

Functional connectivity (FC) is known to be individually unique and to reflect cognitive variability. Although FC can serve as a valuable correlate and potential predictor of (patho-) physiological nervous function in high-risk constellations, such as preterm birth, templates for individualized FC analysis are lacking, and knowledge about the capacity of the premature brain to develop FC variability is limited. In a cohort of prospectively recruited, preterm-born infants undergoing magnetic resonance imaging close to term-equivalent age, we show that the overall pattern could be reliably detected with a broad range of interindividual FC variability in regions of higher-order cognitive functions (e.g., association cortices) and less interindividual variability in unimodal regions (e.g., visual and motor cortices). However, when comparing the preterm and adult brains, some brain regions showed a marked shift in variability toward adulthood. This shift toward greater variability was strongest in cognitive networks like the attention and frontoparietal networks and could be partially predicted by developmental cortical expansion. Furthermore, FC variability was reflected by brain tissue characteristics indicating cortical maturation. Brain regions with high functional variability (e.g., the inferior frontal gyrus and temporoparietal junction) displayed lower cortical maturation at birth compared with somatosensory cortices. In conclusion, the overall pattern of interindividual variability in FC is already present preterm; however, some brain regions show increased variability toward adulthood, identifying characteristic patterns, such as in cognitive networks. These changes are related to postnatal cortical expansion and maturation, allowing for environmental and developmental factors to translate into marked individual differences in FC.

A simple permutation-based test of intermodal correspondence

“…Since the advent of the spin test, numerous neuroimaging experiments have adopted it to corroborate claims about intermodal similarities (Lefèvre et al 2018;Paquola et al 2019;Schmitt et al 2019;Shafiei et al 2020;Cui et al 2020;Stoecklein et al 2020) and have extended its implementation to regionally parcellated maps (Váša et al 2018;Vázquez-Rodríguez et al 2019;Cornblath et al 2020).…”

Hierarchical complexity of the macro-scale neonatal brain

“…Several metrics that are found ubiquitously in real-world networks have been used to model brain connectivity in the neonatal brain, including local and global efficiency, small-worldness, clustering coefficient, characteristic path length and rich club coefficient [7,8,9,11,13], and often they reveal remarkable structural and functional architectural facsimiles between the newborn and adult brain [13,14,15]. Hierarchical complexity (HC) is a measure of the diversity of connectivity patterns found across hierarchically equivalent (same degree) network nodes, and it reflects the hierarchical and functionally diverse capacities of the human brain.…”

Disentangling cortical functional connectivity strength and topography reveals divergent roles of genes and environment

“…Differences in individual experience may contribute to measurable diversity as well. Inter-subject variability in preterm neonates and healthy adults exhibit overall similar patterns 13 , but variability increases for parts of the fronto-parietal and dorsal attention network during maturation. At the same time, genes contribute significantly to the variability of functional 14,15 , and structural 16,17 cortical networks.…”