Functional connectome through the human life span

Abstract

The functional connectome of the human brain represents the fundamental network architecture of functional interdependence in brain activity, but its normative growth trajectory across the life course remains unknown. Here, we aggregate the largest, quality-controlled multimodal neuroimaging dataset from 119 global sites, including 33,809 task-free fMRI and structural MRI scans from 32,328 individuals ranging in age from 32 postmenstrual weeks to 80 years. Lifespan growth charts of the connectome are quantified at the whole cortex, system, and regional levels using generalized additive models for location, scale, and shape. We report critical inflection points in the non-linear growth trajectories of the whole-brain functional connectome, particularly peaking in the fourth decade of life. Having established the first fine-grained, lifespan-spanning suite of system-level brain atlases, we generate person-specific parcellation maps and further show distinct maturation timelines for functional segregation within different subsystems. We identify a spatiotemporal gradient axis that governs the life-course growth of regional connectivity, transitioning from primary sensory cortices to higher-order association regions. Using the connectome-based normative model, we demonstrate substantial individual heterogeneities at the network level in patients with autism spectrum disorder and patients with major depressive disorder. Our findings shed light on the life-course evolution of the functional connectome and serve as a normative reference for quantifying individual variation in patients with neurological and psychiatric disorders.

Protective role of parenthood on age-related brain function in mid- to late-life

“…We find a highly consistent effect of parity on functional connectivity between the sexes, both at the edge (𝑟 = .67; 𝑝 < .001; Fig1C) and network level (𝑟 = .90; 𝑝 < .001; Fig2C), suggesting that parenthood may have consistent neurobiological impacts across females and males 15 . This high-level of consistency between the sexes has also previously been demonstrated in age-related structural 14 and functional 15 alterations across the life span.…”

“…Decades of research charting age-related brain changes across the lifespan have provided great strides in mapping the normative trajectories of structural 14 and functional 15 neural reorganization from early development through late life. Aging in adulthood is associated with a progressive series of functional alterations across sensorimotor and 'higher-order' cognitive systems.…”

“…Typically, connectivity within networks, such as the default, salience/ventral attention, and somato/motor networks, decrease with age 15,16 , while connectivity between networks increases with age 17,18 . Recent evidence suggests that these network trajectories show different inflection points; for example, compared to higher-order networks, sensorimotor networks reach maturity earlier in life and show a steeper decline in function after the fourth decade of life 14,15 . Although age-related alterations in brain function are broadly consistent across the population, and between males and females 19 , differences in lifelong exposure to biological and environmental factors can impact the timing and rate of these changes, altering aging trajectories.…”

Dynamics of White Matter Architecture in Lexical Production among Middle-Aged Adults

“…At a functional level, data from resting-state and task-activation fMRI suggest that aging influences activation dynamics within large brain networks, reorganizing them to maintain cognitive performance (Deery et al, 2023; Sun et al, 2023). With aging, cerebral networks exhibit reduced functional specialization, as seen by decreased within-network connectivity (Chan et al, 2014; Edde et al, 2021; Jockwitz et al, 2017).…”

Beyond homogeneity: Charting the landscape of heterogeneity in psychiatric electroencephalography

“…to map lifespan age-related changes in brain structure (Bethlehem et al 2022; Rutherford, Fraza, et al 2022; Rutherford et al 2023) and characterize structural heterogeneity in psychiatric disorders (Segal et al 2023) such as ADHD (Wolfers et al 2020), Autism (Zabihi et al 2020), Schizophrenia and Bipolar disorder (Wolfers et al 2018), as well as in neurodegenerative disease as Alzheihmer’s disease (Verdi et al 2023). Additionally, there has been a development of normative models for functional MRI, although to a lesser extent (Rutherford, Kia, et al 2022; Sun et al 2023). However, to our knowledge, similar research focusing on the electrophysiological aspects of psychiatric disorders and the underlying substrates of heterogeneity remains unexplored.…”