Developmental Patterns of Individual Differences in Brain Function During Youth
Poster No:
963
Submission Type:
Abstract Submission
Authors:
Zekun Yang1, Debin Zeng1,2, Xiuying Wang3, Shuyu Li1
Institutions:
1State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China, 2Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science & Medical Engineering, Beihang University, Beijing, China, 3School of Computer Science, The University of Sydney, Sydney, Australia
First Author:
Zekun Yang
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, China
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, China
Co-Author(s):
Debin Zeng
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University|Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science & Medical Engineering, Beihang University
Beijing, China|Beijing, China
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University|Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science & Medical Engineering, Beihang University
Beijing, China|Beijing, China
Shuyu Li
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, China
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, China
Introduction:
The human brain exhibits significant individual differences in both structure and function. MRI-based personalized brain functional network parcellation methods enable the identification of each individual's functional network map that represents an individual's unique functional topography (H. Li et al., 2017; M. Li et al., 2019; Wang et al., 2015). The overall pattern of inter-individual variability in brain function is present from early life (Mueller et al., 2013; Stoecklein et al., 2020). Throughout different stages of lifespan, the brain's structure and function undergo substantial changes. In particular, childhood, adolescence, and young adulthood are crucial stages of human brain development (Cui et al., 2020; Keller et al., 2023). However, the spatiotemporal patterns of inter-individual differences during this period remain to be explored.
Methods:
Our study utilized 23 minutes of high-quality functional MRI data from the Human Connectome Project Development (HCP-D), including 601 participants (5-21 years). We calculated voxel-level inter-individual functional variability based on functional connectivity (Mueller et al., 2013). Using an iterative parcellation method, we identified individuals' functional networks, comprising 87 functional regions (M. Li et al., 2019). ROI-level inter-individual functional variability was defined as the centroid distance of the same functional regions across different individuals. To analyze changes in inter-individual functional differences before and after adolescence, we conducted two-sample t-tests between adults (over 18 years old) and children (under 11 years old). Finally, we employed a sliding window approach across individuals to analyze the relationship between individual differences and age, with a bin size of 10 and a step size of 5. We used Generalized Additive Models (GAM) to fit the trajectories of individual differences with age.
Results:
The voxel-level results indicate that the overall pattern of inter-individual variability aligns with the sensorimotor-association axis. This pattern is established in childhood and increases overall during adolescence (Figure 1a). The strength of developmental effects exhibits hierarchical pattern(Figure 1b), providing the new developmental evidence for the brain's hierarchy. Notably, unimodal regions show more significant and faster developmental effects, whereas association area displays the opposite trend (Figure 1b). Moreover, the ROI-level results demonstrate that inter-individual differences in brain function do not follow a simple linear trajectory from childhood through adolescence to young adulthood but instead exhibit a fluctuating developmental trend. In several brain regions (cuneus, supramarginal, and occipitotemporal areas), inter-individual differences with age changes include at least two inflection points, the first near age 12 and the second near age 18 (Fig. b, c). These findings confirm that the development of inter-individual differences follows a nonlinear pattern, with significant shifts in the rate of change occurring at specific age stages. Recent studies have indicated that brain functional architecture may undergo significant reorganization from childhood to adulthood(Dong et al., 2024). Our findings are likely to further substantiate this transition in terms of inter-individual differences.
Conclusions:
This study reveals the dynamic developmental patterns of individual differences in brain function during puberty, likely associated with the transition of functional architecture anchors from unimodal to multimodal regions. It underscores puberty as a critical period for the further complexity and individualization of brain functional organization. These findings provide new evidence on the developmental mechanisms of the human brain, especially regarding individual differences and functional network reorganization.
Lifespan Development:
Early life, Adolescence, Aging 1
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural)
fMRI Connectivity and Network Modeling 2
Segmentation and Parcellation
Novel Imaging Acquisition Methods:
BOLD fMRI
Keywords:
Cortex
Development
FUNCTIONAL MRI
1|2Indicates the priority used for review
Abstract Information
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