Short-term asymmetric functional oscillations support long-term nonlinear infant connectome growth
Poster No:
969
Submission Type:
Abstract Submission
Authors:
Liang Ma1, Sarah Shultz2, Zening Fu3, Masoud Seraji4, Armin Iraji3, Vince Calhoun5
Institutions:
1TReNDS, Altanta, GA, 2Emory University, Atlanta, GA, 3GSU, Atlanta, GA, 4Tri-Institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State, Atlanta, GA, 5GSU/GATech/Emory, Atlanta, GA
First Author:
Co-Author(s):
Masoud Seraji
Tri-Institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State
Atlanta, GA
Tri-Institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State
Atlanta, GA
Introduction:
The first six months of human life are marked by extraordinary growth of brain structure and function and rapid neurological changes, which culminate in a nonlinear trajectory of brain development(Gilmore, Knickmeyer, & Gao, 2018). Understanding the underlying mechanisms driving these nonlinear pathways in brain development could elucidate potential developmental milestones and the emergence of neurodevelopmental disorders.
Methods:
We analyzed data from seventy-four typically-developing infants enrolled in prospective longitudinal studies at the Marcus Autism Center in Atlanta, GA, USA. The functional preprocessing followed an established functional MRI pipeline (Fu et al., 2024) and obtain subject-specific functional components using the NeuroMark pipeline (Du et al., 2020). We first identify trajectories of each static functional connectivity, connectivity growth rate and growth acceleration using a generalized additive model. We then identify five spontaneous oscillation patterns in the combined infant dynamic functional connectivity after individual functional network connectivity mean removal. Finally we calculate the fluctuation asymmetry (FA) for the time series of each oscillation, and estimated its trajectory across all infants. Fluctuation asymmetry is calculated as the ratio of the mean of square of positive series value to the mean of square of negative series value minus 1.
Results:
We found there exist a transition period in the first-six-month brain development, which leads the nonlinear trajectory of connectivity growth. In the transition period from 90-120 days, the growth rate and growth acceleration reach their lowest level between the 115th and 97th day respectively. The two periods separated by the transition show markedly different growth patterns. For example, the former period has a significant growth pattern of increasing within-domain modularity for visual and cognitive domains respectively. The latter period has a significant growth pattern of increasing between-domain modularity for visual and cognitive domains.
In addition to providing long-term evidence of functional connectome growth transitions, we find that the fluctuation asymmetry (FA) of short-term oscillations may play a key role in supporting these transitions. Specifically, the sign of FA for an oscillation predicts relative changes in within- and between-domain modularity. Positive FA is associated with increased between-domain modularity and decreased within-domain modularity, while negative FA indicates the opposite pattern. The shift in FA sign between two periods appears to explain changes in the static growth pattern across most regions. For instance, states 2 and 3 are linked to both the visual and cognitive domains. During the first period, the negative FA of states 2 and 3 suggests that visual and cognitive domains are predominantly activated within their respective domains independently. Conversely, during the second period, the positive FA in both states indicates frequent co-activation between these two domains.
Moreover, the lowest point in the trajectory of mean absolute FA occurs prior to the trajectory of connectivity growth rates. This finding suggests that FA may serve as an early biomarker for the developmental transition observed in infant brain development.
In addition to providing long-term evidence of functional connectome growth transitions, we find that the fluctuation asymmetry (FA) of short-term oscillations may play a key role in supporting these transitions. Specifically, the sign of FA for an oscillation predicts relative changes in within- and between-domain modularity. Positive FA is associated with increased between-domain modularity and decreased within-domain modularity, while negative FA indicates the opposite pattern. The shift in FA sign between two periods appears to explain changes in the static growth pattern across most regions. For instance, states 2 and 3 are linked to both the visual and cognitive domains. During the first period, the negative FA of states 2 and 3 suggests that visual and cognitive domains are predominantly activated within their respective domains independently. Conversely, during the second period, the positive FA in both states indicates frequent co-activation between these two domains.
Moreover, the lowest point in the trajectory of mean absolute FA occurs prior to the trajectory of connectivity growth rates. This finding suggests that FA may serve as an early biomarker for the developmental transition observed in infant brain development.
Conclusions:
We highlight a pivotal transition period in early brain development that drives nonlinear changes in functional connectome growth. Long-term growth patterns are influenced by short-term oscillatory dynamics, with fluctuation asymmetry serving as a key predictor of modularity shifts. These findings provide insights into the mechanisms underlying early brain development and offer a potential biomarker for identifying critical developmental phases.
Lifespan Development:
Early life, Adolescence, Aging 1
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural)
fMRI Connectivity and Network Modeling 2
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Normal Development
Novel Imaging Acquisition Methods:
BOLD fMRI
Keywords:
Cortex
Development
FUNCTIONAL MRI
Plasticity
1|2Indicates the priority used for review
·Figure 1. The growth trajectory of infant functional connectome
·Figure 2. Short-term brain oscillatory state patterns and their fluctuation asymmetry trajectories
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Provide references using APA citation style.
Fu, Z., Batta, I., Wu, L., Abrol, A., Agcaoglu, O., Salman, M. S., . . . Calhoun, V. D. (2024). Searching Reproducible Brain Features using NeuroMark: Templates for Different Age Populations and Imaging Modalities. NeuroImage, 292, 120617. doi:10.1016/j.neuroimage.2024.120617
Gilmore, J. H., Knickmeyer, R. C., & Gao, W. (2018). Imaging structural and functional brain development in early childhood. Nat Rev Neurosci, 19(3), 123-137. doi:10.1038/nrn.2018.1