Developmental Maturation of the Precuneus as a Functional Core of the Default Mode Network

Abstract

Efforts to map the functional architecture of the developing human brain have shown that connectivity between and within functional neural networks changes from childhood to adulthood. Although prior work has established that the adult precuneus distinctively modifies its connectivity during task versus rest states [Utevsky, A. V., Smith, D. V., & Huettel, S. A. Precuneus is a functional core of the default-mode network. Journal of Neuroscience, 34, 932–940, 2014], it remains unknown how these connectivity patterns emerge over development. Here, we use fMRI data collected at two longitudinal time points from over 250 participants between the ages of 8 and 26 years engaging in two cognitive tasks and a resting-state scan. By applying independent component analysis to both task and rest data, we identified three canonical networks of interest—the rest-based default mode network and the task-based left and right frontoparietal networks (LFPN and RFPN, respectively)—which we explored for developmental changes using dual regression analyses. We found systematic state-dependent functional connectivity in the precuneus, such that engaging in a task (compared with rest) resulted in greater precuneus–LFPN and precuneus–RFPN connectivity, whereas being at rest (compared with task) resulted in greater precuneus–default mode network connectivity. These cross-sectional results replicated across both tasks and at both developmental time points. Finally, we used longitudinal mixed models to show that the degree to which precuneus distinguishes between task and rest states increases with age, due to age-related increasing segregation between precuneus and LFPN at rest. Our results highlight the distinct role of the precuneus in tracking processing state, in a manner that is both present throughout and strengthened across development.

Changes in electrophysiological static and dynamic human brain functional architecture from childhood to late adulthood

“…Taken together, these HMM data suggest that the progress from childhood to adulthood is associated with a maturation of the resting-state transient brain dynamics characterized by an increase in the temporal stability of (i) transient activated networks encompassing associative frontal, inferior parietal and sensorimotor neocortical regions, and (ii) transient deactivation of the precunei. These age-related changes might relate to the previously described developmental increase in the segregation between the precuneus and fronto-parietal networks at rest 59 . The dissociation of the precuneus from the rest of the DMN in a specific deactivated transient state is also probably in line with the recognized DMN functional-anatomic fractionation 60,61 .…”

Functional connectome fingerprinting accuracy in youths and adults is similar when examined on the same day and 1.5‐years apart

“…For all subjects, we calculated a quality control measure with respect to head motion, namely volume-to-volume frame displacement (FD). Consistent with recent developmental cognitive neuroscience publications (Bathelt, Johnson, Zhang, & Astle, 2019;Calabro et al, 2019;Hafeman et al, 2019;Li et al, 2019), subjects were removed from rsfMRI analyses if the average frame displacement across the run was >0.5 mm (N = 5). Note: Detailed exclusion criteria are provided in Figure S1.…”

Modeling Individual Differences in Brain Development

“…These studies illustrate considerable variability in the taskbased MRI measures of neural responsivity to a variety of tasks across childhood and into young adulthood ( Figure 1B) (21)(22)(23). Further, longitudinal examinations of resting-state functional connectivity MRI also demonstrate individual variability of connectivity estimates in childhood and across adolescence ( Figure 1C) (24)(25)(26). The substantial individual variability present across development in functional MRI measures demonstrates the necessity of collecting longitudinal data to establish individual-level developmental patterns of brain activity and connectivity.…”