Functional neural network connectivity at 3 months predicts infant-mother dyadic flexibility during play at 6 months

Autor: Xiaomei Li, Haitao Chen, Yannan Hu, Ryan J Larsen, Bradley P Sutton, Nancy L McElwain, Wei Gao
Rok vydání: 2023
Předmět:
Zdroj: Cerebral Cortex.
ISSN: 1460-2199
1047-3211
DOI: 10.1093/cercor/bhad117
Popis: Early functioning of neural networks likely underlies the flexible switching between internal and external orientation and may be key to the infant’s ability to effectively engage in social interactions. To test this hypothesis, we examined the association between infants’ neural networks at 3 months and infant-mother dyadic flexibility (denoting the structural variability of their interaction dynamics) at 3, 6, and 9 months. Participants included 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 functional connectivity (FC) within the default mode (DMN) and salience (SN) networks, as well as DMN-SN internetwork FC, were derived using a seed-based approach. When infants were 3, 6, and 9 months, infant-mother dyads completed the Still-Face Paradigm where their individual engagement behaviors were observed and used to quantify dyadic flexibility using state space analysis. Results revealed that greater within-DMN FC, within-SN FC, and DMN-SN anticorrelation at 3 months predicted greater dyadic flexibility at 6 months, but not at 3 and 9 months. Findings suggest that early synchronization and interaction between neural networks underlying introspection and salience detection may support infants’ flexible social interactions as they become increasingly active and engaged social partners.
Databáze: OpenAIRE