| Literature DB >> 32946557 |
Yuanyuan Chen1, Shuxin Liu1,2, Andrew Salzwedel1, Rebecca Stephens3, Emil Cornea3, Barbara D Goldman4, John H Gilmore3, Wei Gao1,5.
Abstract
The presence of heterogeneity/subgroups in infants and older populations against single-domain brain or behavioral measures has been previously characterized. However, few attempts have been made to explore heterogeneity at the brain-behavior relationship level. Such a hypothesis posits that different subgroups of infants may possess qualitatively different brain-behavior relationships that could ultimately contribute to divergent developmental outcomes even with relatively similar brain phenotypes. In this study, we aimed to explore such relationship-level heterogeneity and delineate the subgrouping structure of newborns with differential brain-behavior associations based on a typically developing sample of 81 infants with 3-week resting-state functional magnetic resonance imaging scans and 4-year intelligence quotient (IQ) measures. Our results not only confirmed the existence of relationship-level heterogeneity in newborns but also revealed divergent developmental outcomes associated with two subgroups showing similar brain functional connectivity but contrasting brain-behavior relationships. Importantly, further analyses unveiled an intriguing pattern that the subgroup with higher 4-year IQ outcomes possessed brain-behavior relationships that were congruent to their functional connectivity pattern in neonates while the subgroup with lower 4-year IQ not, providing potential explanations for the observed IQ differences. The characterization of heterogeneity at the brain-behavior relationship level may not only improve our understanding of the patterned intersubject variability during infancy but could also pave the way for future development of heterogeneity-inspired, personalized, subgroup-specific models for better prediction.Entities:
Keywords: brain–behavior relationship; infant subgrouping; intersubject variability; relational heterogeneity; resting-state functional connectivity
Mesh:
Year: 2021 PMID: 32946557 PMCID: PMC7727359 DOI: 10.1093/cercor/bhaa226
Source DB: PubMed Journal: Cereb Cortex ISSN: 1047-3211 Impact factor: 5.357