Dysconnectivity of neurocognitive networks at rest in very-preterm born adults

Abstract

Advances in neonatal medicine have resulted in a larger proportion of preterm-born individuals reaching adulthood. Their increased liability to psychiatric illness and impairments of cognition and behaviour intimate lasting cerebral consequences; however, the central physiological disturbances remain unclear. Of fundamental importance to efficient brain function is the coordination and contextually-relevant recruitment of neural networks. Large-scale distributed networks emerge perinatally and increase in hierarchical complexity through development. Preterm-born individuals exhibit systematic reductions in correlation strength within these networks during infancy. Here, we investigate resting-state functional connectivity in functional magnetic resonance imaging data from 29 very-preterm (VPT)-born adults and 23 term-born controls. Neurocognitive networks were identified with spatial independent component analysis conducted using the Infomax algorithm and employing Icasso procedures to enhance component robustness. Network spatial focus and spectral power were not generally significantly affected by preterm birth. By contrast, Granger-causality analysis of the time courses of network activity revealed widespread reductions in between-network connectivity in the preterm group, particularly along paths including salience-network features. The potential clinical relevance of these Granger-causal measurements was suggested by linear discriminant analysis of topological representations of connection strength, which classified individuals by group with a maximal accuracy of 86%. Functional connections from the striatal salience network to the posterior default mode network informed this classification most powerfully. In the VPT-born group it was additionally found that perinatal factors significantly moderated the relationship between executive function (which was reduced in the VPT-born as compared with the term-born group) and generalised partial directed coherence. Together these findings show that resting-state functional connectivity of preterm-born individuals remains compromised in adulthood; and present consistent evidence that the striatal salience network is preferentially affected. Therapeutic practices directed at strengthening within-network cohesion and fine-tuning between-network inter-relations may have the potential to mitigate the cognitive, behavioural and psychiatric repercussions of preterm birth.

Keywords: Executive function; Functional connectivity; Neurocognitive networks; Preterm birth; Resting-state.

Fig. 1

Ranked goodness-of-fit (GOF) scores for each component with pre-specified functionally-derived masks, for: (A) insular salience network; (B) striatal salience network; (C) left central executive network; (D) right central executive network; (E) frontal default mode network; and (F) posterior default mode network. In each sub-figure, the component chosen for subsequent extended analysis is depicted by a black circle and all other components are represented by white circles. The insets depict the binary mask for each network in yellow overlaid on sections of a standardised T1-weighted image.

Fig. 2

Components of interest, showing (A) insular salience network (B) striatal salience network; (C) left central executive network; (D) right central executive network; (E) frontal default mode network; and (F) posterior default mode network. Results depicted represent clusters with significant positive loadings (P < .05, family-wise error corrected) on the basis of one-sample T-tests including all study participants. Results are overlaid on standardised T₁-weighted image and scaled according to the T-value colour-bar shown.

Fig. 3

Group-averaged periodograms, depicting power spectrum density for the six components of interest. SN, salience network; CEN, central executive network; DMN, default mode network; VPT, very preterm.

Fig. 4

Group-averaged histograms showing the percentage of connections as a function of generalised partial directed coherence (GPDC). Dotted black line shows term-group distribution when hidden by VPT-group results. Other vertical lines represent boundaries for low (0.05–0.20), mid (0.20–0.35) and high (0.35–0.55) GPDC. Inset: Bar diagram shows grand-average connection strength for each connectivity window (CW). Asterisk denotes significant between-group difference in CW3.

Fig. 5

Classification by whole-network topology, using linear discriminant analysis of binarised networks according to variable generalised partial direct coherence (GPDC) thresholds, showing: (A) classification accuracy as a function of GPDC threshold; (B) scatterplot of classification at a GPDC threshold of 0.35; and (C) ranked LDA weights for each path for classification at a GPDC threshold of 0.35.

Fig. 6

Pathways influential for accurate classification, showing critical pathways by projection weight. Arrow breadth denotes path-specific weights from linear discriminant analysis according to the scale depicted. DMN, default mode network; CEN, central executive network; SN, salience network.