Functional Neural Network Connectivity at 3 Months Predicts Infant-Mother Dyadic Flexibility at 6 Months

• In Event: Infant learning and brain development

Abstract

Early functioning of neural networks related to the “social brain” (Atzil et al., 2018; Ciarrusta et al., 2020), particularly the default mode network (DMN; involved in allostasis, self-referential thoughts, and memory retrieval) and salience network (SN; involved in integrating internal and external information to detect socially salient stimuli and allocate attention), likely supports infants’ flexible interactions with mothers. Such dyadic flexibility is operationalized as the extent to which dyad members demonstrate a variety of behaviors and modify them smoothly in response to each other’s changing behaviors over time. Higher infant-mother dyadic flexibility denotes greater structural variability in their interactions and may help facilitate infant’s development of self-regulation (Busuito & Moore, 2017; Provenzi et al., 2015). However, little is known about patterns of synchronization within and interaction between these functional neural networks during early infancy and their contributions to infant-mother interactions. In this multimethod longitudinal study, we examined associations between infants’ functional neural networks at 3 months and infant-mother dyadic flexibility observed during the play episode of the Still-Face Paradigm (SFP) at 3, 6, and 9 months. We hypothesized that greater functional connectivity (FC) within the DMN and SN, as well as the anticorrelation between the two – all of which indicate greater brain maturation – would predict greater dyadic flexibility at each time point.

Participants were thirty-five infants (37% girls) and their mothers (87% White). At 3 months, infants participated in a resting-state functional magnetic resonance imaging session, and within- and between-network FC in the DMN and SN were derived using a seed-based approach. When infants were 3, 6, and 9 months, infant-mother interaction was assessed in the SFP. Individuals’ facial expressions, vocalizations, and directions of gaze were micro-coded in real-time and used to quantify dyadic flexibility via state space analysis.

Group-level FC maps (Figure 1a) showed that the DMN and SN at 3 months included most key nodes in their adult forms, and regional-level FC maps (Figure 1b) featured clear positive FC within each network and negative FC between the two networks. Consistent with our hypotheses, Pearson’s correlations revealed that greater within-DMN and within-SN FC, as well as greater DMN-SN anticorrelations, at 3 months were each associated with greater dyadic flexibility at 6 months (Figure 2). Correlations with 3- or 9-month flexibility, however, were nonsignificant.

Extending scarce research on infant functional networks and their links with infant-mother interactions, we found that the DMN and SN showed meaningful within-network synchronization and between-network interaction at 3 months of age. Greater functional connectivity within the DMN and SN may underlie the infant’s ability to engage in efficient processing of internal states and detection of salient events, respectively, while stronger DMN-SN anticorrelations may indicate a greater capacity to disengage introspective activities in the face of environmental demands. Further, our findings suggest that such connectivity patterns in these key neural networks at 3 months support infants’ increasing responsiveness to, as well as coordination between, internal (from themselves) and external (from mothers) cues, leading to more flexible interactions with mothers three months later.

Authors

• Xiaomei Li, University of Illinois at Urbana-Champaign
  Presenting Author

• Haitao Chen, Cedars Sinai Medical Center

• Yannan Hu, University of Illinois at Urbana-Champaign

• Ryan J. Larson, University of Illinois at Urbana-Champaign

• Bradley P. Sutton, University of Illinois at Urbana-Champaign

• Nancy McElwain, University of Illinois at Urbana-Champaign

• Wei Gao, Cedars Sinai Medical Center