Developmental and aging resting functional magnetic resonance imaging brain state adaptations in adolescents and adults: A large <i>N</i> (&gt;<scp>47K</scp>) study

Abrol, Anees; Fu, Zening; Du, Yuhui; Wilson, Tony W.; Wang, Yuping; Stephen, Julia M.; Calhoun, Vince D.

doi:10.1002/hbm.26200

Cited by 10 publications

(3 citation statements)

References 62 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…During early adulthood, the range of the SA and MR axes are stable, however the SA axis undergoes more rapid contraction during mid and late adult-hood compared to the MR axis, which only contracts modestly. Both SA and MR axes exhibit inverted U-shaped development previously observed in lifespan FC development 36 . In contrast, the VS axis, which differentiates between the primary unimodal processing centers, increases rapidly during infancy and early childhood, reaching its maximum range at 0.77 years (95% CI 0.27-1.8 years), undergoing gradual contraction throughout the remainder of the lifespan.…”

Section: Resultssupporting

confidence: 54%

Functional Hierarchy of the Human Neocortex from Cradle to Grave

Taylor,

Thung,

Huynh

et al. 2024

Preprint

View full text Add to dashboard Cite

Recent evidence indicates that the organization of the human neocortex is underpinned by smooth spatial gradients of functional connectivity (FC). These gradients provide crucial in-sight into the relationship between the brain’s topographic organization and the texture of human cognition. However, no studies to date have charted how intrinsic FC gradient architecture develops across the entire human lifespan. In this work, we model developmental trajectories of the three primary gradients of FC using a large, high-quality, and temporally-dense functional MRI dataset spanning from birth to 100 years of age. The gradient axes, denoted as sensorimotor-association (SA), visual-somatosensory (VS), and modulation-representation (MR), encode crucial hierarchical organizing principles of the brain in development and aging. By tracking their evolution throughout the human lifespan, we provide the first ever comprehensive low-dimensional normative reference of global FC hierarchical architecture. We observe significant age-related changes in global network features, with global markers of hierarchical organization increasing from birth to early adulthood and decreasing there-after. During infancy and early childhood, FC organization is shaped by primary sensory processing, dense short-range connectivity, and immature association and control hierarchies. Functional differentiation of transmodal systems supported by long-range coupling drives a convergence toward adult-like FC organization during late childhood, while adolescence and early adulthood are marked by the expansion and refinement of SA and MR hierarchies. While gradient topographies remain stable during late adulthood and aging, we observe decreases in global gradient measures of FC differentiation and complexity from 30 to 100 years. Examining cortical microstructure gradients alongside our functional gradients, we observed that structure-function gradient coupling undergoes differential lifespan trajectories across multiple gradient axes.

show abstract

Section: Resultssupporting

confidence: 54%

Functional Hierarchy of the Human Neocortex from Cradle to Grave

Taylor,

Thung,

Huynh

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…While many studies directly examine age-related effects, age is often treated as a nuisance covariate (Hyatt et al, 2020). With increasing awareness of the importance of replicability in neuroimaging studies (Poldrack et al, 2017), it is becoming more common to leverage multiple consortium-based datasets to examine brain structure and function in neurotypical and neurodivergent populations (Abrol et al, 2023; Grotzinger et al, 2023; Marek et al, 2022; Nicolaisen-Sobesky et al, 2022; Romer et al, 2019; Vandewouw et al, 2023). However, these datasets differ in composition in terms factors which may influence age-related effects, such as participants’ demographics (e.g., age, sex and gender, race and ethnicity, socioeconomic status), diagnosis, co-occurring conditions, and other phenotypic variables.…”

Section: Introductionmentioning

confidence: 99%

Dataset factors influencing age-related changes in brain structure and function in neurodevelopmental conditions

Vandewouw,

Ye,

Crosbie

et al. 2024

Preprint

View full text Add to dashboard Cite

With brain structure and function undergoing complex changes throughout childhood and adolescence, age is a critical consideration in neuroimaging studies, particularly for those of individuals with neurodevelopmental conditions. However, despite the increasing use of large, consortium-based datasets to examine brain structure and function in neurotypical and neurodivergent populations, it is unclear whether age-related changes are consistent between datasets, and whether inconsistencies related to differences in sample characteristics, such as demographics and phenotypic features, exist. To address this, we built models of age-related changes of brain structure (cortical thickness and surface area; N=1,579) and function (resting-state functional connectivity strength; N=1,792) in two neurodiverse datasets: the Province of Ontario Neurodevelopmental network (POND) and the Healthy Brain Network (HBN). We examined whether deviations from these models differed between the datasets, and explored whether these deviations were associated with demographic and clinical variables. We found significant differences between the two datasets for measures of cortical surface area and functional connectivity strength throughout the brain. For cortical surface area, the patterns of differences were associated with intelligence, while for functional connectivity strength, positive associations were observed with head motion. Our findings highlight that patterns of age-related changes in the brain may be influenced by demographic and phenotypic characteristics, and thus future studies should consider these when examining or controlling forage effects in analyses.

show abstract

“…Further, FC between frontal and subcortical regions appear to strengthen from childhood to adulthood (7,8). A recent study combined rsFC data from several large-scale datasets (e.g., UK Biobank, Adolescent Brain Cognitive Development, Human Connectome Project, and the Developmental Chronnecto-Genomics) to characterize brain state adaptations in human adolescent and adult subjects, showing greater strengthening, modularity, and integration of the brain's functional connections beyond adolescence (9). Consequently, rsFC has been proposed as a tool to identify biomarkers associated with risk for psychiatric disorders such as autism spectrum disorder (10), adolescent-onset schizophrenia (11), and depression (12) among others.…”

Section: Introductionmentioning

confidence: 99%

Age-related development in prefrontal-subcortical resting-state functional connectivity in nonhuman primates

Deshpande

Kohut

2023

Preprint

View full text Add to dashboard Cite

Introduction: Understanding age related changes in functional connectivity (FC) with regards to the maturation trajectories of cortical subcortical circuits is critical for identifying biomarkers for disease vulnerability. The present study investigated resting state FC in adolescent and adult nonhuman primates to characterize developmentally sensitive functional brain circuits. Methods: Resting-state fMRI data were acquired in adolescent (33.3 (sd=1.59) months; n=22) and adult (117.29 (sd=2.86) months; n=15) squirrel monkeys and FC was compared in seven prefrontal and ten subcortical regions of interest (ROIs). The effect of subject age on FC between each pair of ROIs was evaluated to identify nodes with the most age sensitive connections (hubs) which were then used in seed-to-whole brain FC analyses. A subset of adolescents (n=7) was also assessed over 3 longitudinal scans to track changes in hub connectivity throughout adolescence. Results: A significant effect of age on ROI to ROI FC was found for adolescent (p<0.001), but not adult, subjects (p=0.8). Evaluation of parameter estimates (beta) for each ROI to ROI pair found three within-prefrontal (dorsolateral (dlPFC), dorsomedial (dmPFC), and medial orbitofrontal cortices), two within-subcortical (R amygdala and L hippocampus), and three between prefrontal-subcortical (dlPFC, dmPFC, L caudate) hubs with the highest number of age-related connections. Large scale organizational differences were also observed between the adolescent and adult groups. Longitudinal scans found within subject changes in FC consistent with group effect. Conclusions: The relationship between changes in FC and age during adolescence indicates dynamic maturation of several prefrontal to subcortical circuits in nonhuman primates. These findings provide specificity in our understanding of the development of functional brain circuits during and into late adolescence.

show abstract

Developmental and aging resting functional magnetic resonance imaging brain state adaptations in adolescents and adults: A large N (>47K) study

Cited by 10 publications

References 62 publications

Functional Hierarchy of the Human Neocortex from Cradle to Grave

Functional Hierarchy of the Human Neocortex from Cradle to Grave

Dataset factors influencing age-related changes in brain structure and function in neurodevelopmental conditions

Age-related development in prefrontal-subcortical resting-state functional connectivity in nonhuman primates

Contact Info

Product

Resources

About