Trajectories of brain system maturation from childhood to older adulthood: Implications for lifespan cognitive functioning
Introduction
Substantial evidence suggests that the human brain is organized into dissociable anatomical networks (Fox and Raichle, 2007), which provide a latent functional architecture that is readily recruited during goal-directed cognition (Laird et al., 2011, Smith et al., 2009). Inter-individual variations in this intrinsic neural architecture carry significant implications for optimal functioning not only in adulthood (e.g., Alavash et al., 2015, Grady et al., 2016, Hampson et al., 2006, Li et al., 2009, Stevens et al., 2012, van den Heuvel et al., 2009), but also during earlier development (e.g., Church et al., 2009, Fair et al., 2010, Graham et al., 2015, Vega et al., 2015).
The brain's intrinsic functional architecture is regarded as partly reflecting an individual's behavioural history, since it indicates the neural configurations consistently recruited to manage specific cognitive demands, presumably both cumulatively and with respect to the more recent past (Wig et al., 2011). To the extent that this is indeed the case, a better understanding of shared developmental trajectories of intra- and internetwork connectivity at the whole-brain level may lead to valuable insights into the neural mechanisms underlying age-related differences in cognitive performance (Park and Reuter-Lorenz, 2009). Nonetheless, extant research on the inter-relationships among large-scale intrinsic networks, derived from whole-brain parcellations, has involved younger and older adults (e.g., Chan et al., 2014, Geerligs et al., 2015a, Geerligs et al., 2015b). In contrast, most investigations of typical age-related functional connectivity differences during childhood and adolescence focused either on a small number of networks or on whole-brain (i.e., not network-specific) connectivity patterns (Fair et al., 2007, Fair et al., 2008, Sato et al., 2015, Song et al., 2015, van Duijvenvoorde et al., 2016; for exceptions, see Betzel et al., 2014, Jolles et al., 2011, Wang et al., 2012). Thus, relatively little is known about lifespan (i.e., childhood through older adulthood) differences in patterns of whole-brain network connectivity and their implications for cognitive functioning.
To probe this issue, we used resting state data from a large lifespan sample and tested the interactions among ten intrinsic neural systems, derived from a well-established whole-brain parcellation into functional networks (Power et al., 2011). The atlas included seven processing/non-control networks and three networks linked either to cognitive-behavioural control initiation (top-down: frontoparietal vs. bottom-up: salience) or its maintenance (i.e., cingulo-opercular) (Craig, 2002, Dosenbach et al., 2007, Eisenberger et al., 2003, Grinband et al., 2006, Seeley et al., 2007, Spreng et al., 2010). The seven processing networks have been previously associated with action/perception (somatomotor, visual, auditory), externally oriented attention (top-down: dorsal attention [DAN] vs. bottom-up: ventral attention [VAN]), internally oriented/generated representations (default mode [DMN]) and feedback-based learning or processing of personally relevant information (subcortical) (Andrews-Hanna et al., 2014a, Corbetta and Shulman, 2002, Fox et al., 2006, Grady et al., 2012, Power et al., 2011, van Duijvenvoorde et al., 2016).
Our main goal was to identify functional systems with common developmental trajectories of within- and/or between-network connectivity and, then, using data from a comprehensive behavioural battery, investigate their role in the expression of age-related differences in cognitive functioning. Recruitment of behavioural control-relevant networks to compensate for the structural and functional decline of perceptual processing systems, which can no longer meet environmental demands, is considered a hallmark of neurocognitive aging (for a review of relevant findings, see Park and Reuter-Lorenz, 2009). We thus reasoned that identifying lifespan patterns of control-to-processing system connections may provide important insights in the neural mechanisms supporting age-related compensatory processes. Complementarily, a characterization of the developmental trajectory of processing-to-processing network connections could offer a better understanding of the neural resources that are most malleable to change across the lifespan and, thus, potentially, most vulnerable to decline through aging.
Section snippets
Participants
The present study included 586 participants (259 males) who were tested at the Hospital for Sick Children (Sample 1: N = 171) or Rotman Research Institute (Sample 2: N = 113) in Toronto (Canada), or who were part of the enhanced Nathan Kline Institute-Rockland Sample (NKI-RS/Sample 3: N = 302) (Nooner et al., 2012). Table 1 contains the relevant demographic details on all three samples.
The majority of participants (N = 522) were right-handed. All participants were screened for physical
Brain-age associations
In the youngest age group (5–11 years; N = 106), all ten within-network connectivity indices were significantly positive at a p-value < 0.05, based on 1,000 bootstrap samples, an effect that was replicated in the oldest age group (65 + years; N = 107). Hence, any reported age differences in within-network connectivity indicate weaker or stronger positive correlations. For between-network connectivity, the youngest and oldest age groups showed a mix of significantly positive, significantly
Discussion
The present study employed resting state and behavioural data from a large lifespan sample to investigate age-related differences in patterns of whole-brain network connectivity and their implications for cognitive functioning. Our results revealed three distinguishable profiles, which showed a linear relationship with age and characterized connectivity patterns within the ten scrutinized systems, among the non-control networks and between the control and non-control systems, respectively. All
Acknowledgements
This work was supported by the Canadian Institutes of Health Research (MOP14036 to C.L.G.; MOP119541, MOP106582 and MOP142379 to M.J.T.), the Canada Research Chairs program, the Ontario Research Fund, the Canadian Foundation for Innovation, and the Heart and Stroke Foundation Centre for Stroke Recovery. The authors also would like to thank the following people for their generosity in support of the imaging centre at Baycrest: Jack & Anne Weinbaum, Sam & Ida Ross, Joseph & Sandra Rotman. The
References (132)
- et al.
Is functional integration of resting state brain networks an unspecific biomarker for working memory performance?
NeuroImage
(2015) - et al.
Contributions of episodic retrieval and mentalizing to autobiographical thought: evidence from functional neuroimaging, resting state connectivity, and fMRI meta-analyses
Neuroimage
(2014) - et al.
A component based noise correction method (CompCor) for BOLD and perfusion based fMRI
NeuroImage
(2007) - et al.
Differential motor and prefrontal cerebello-cortical network development: evidence from multimodal neuroimaging
NeuroImage
(2016) - et al.
Changes in structural and functional connectivity among resting-state networks across the human lifespan
NeuroImage
(2014) - et al.
Dynamic fluctuations coincide with periods of high and low modularity in resting-state functional brain networks
NeuroImage
(2016) AFNI: software for analysis and visualization of functional magnetic resonance neuroimages
Comput. Biomed. Res.
(1996)- et al.
Harmonic biases in child learners: in support of language universals
Cognition
(2015) - et al.
Atypical default network connectivity in youth with attention-deficit/hyperactivity disorder
Biol. Psychiatry
(2010) Community detection in graphs
Phys. Rep.
(2010)
Neural correlates of intelligence as revealed by fMRI of fluid analogies
NeuroImage
Re-evaluating the role of TPJ in attentional control: contextual updating?
Neurosci. Biobehav. Rev.
Structural MRI of pediatric brain development: what have we learned and where are we going?
Neuron
Age differences in default and reward networks during processing of personally relevant information
Neuropsychologia
Age differences in the functional interactions among the default, frontoparietal control, and dorsal attention networks
Neurobiol. Aging
A neural representation of categorization uncertainty in the human brain
Neuron
Lateralized changes in regional cerebral blood flow during performance of verbal and facial recognition tasks: correlations with performance and ”Effort”
Brain Cognit.
Computerized neurocognitive scanning: I. Methodology and validation in healthy people
Neuropsychopharmacology
Processes of change in brain and cognitive development
Trends Cognit. Sci.
Linking planning performance and gray matter density in mid-dorsolateral prefrontal cortex: moderating effects of age and sex
NeuroImage
Competition between functional brain networks mediates behavioural variability
NeuroImage
Dissociating the roles of the default-mode, dorsal, and ventral networks in episodic memory retrieval
NeuroImage
Defining functional SMA and pre-SMA subregions in human MFC using resting state fMRI: functional connectivity-based parcellation method
Neuroimage
The effect of aging on fronto-striatal reactive and proactive inhibitory control
NeuroImage
Comparison of the continuous performance test with and without working memory demands in healthy controls and patients with schizophrenia
Schizophrenia Res.
The Penn Conditional Exclusion Test: a new measure of executive-function with alternate forms for repeat administration
Arch. Clin. Neuropsychol.
Reduction of motion-related artifacts in resting state fMRI using aCompCor
NeuroImage
Reduced functional segregation between the default mode network and the executive control network in healthy older adults: a longitudinal study
NeuroImage
Functional network organization of the human brain
Neuron
Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion
NeuroImage
Recent progress and outstanding issues in motion correction in resting state fMRI
NeuroImage
Complex network measures of brain connectivity: uses and interpretations
NeuroImage
Decreased centrality of subcortical regions during the transition to adolescence: a functional connectivity study
NeuroImage
Impact of in-scanner head motion on multiple measures of functional connectivity: relevance for studies of neurodevelopment in youth
NeuroImage
An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data
NeuroImage
Heterogeneous impact of motion on fundamental patterns of developmental changes in functional connectivity during youth
NeuroImage
A genome screen for quantitative trait loci influencing schizophrenia and neurocognitive phenotypes
Am. J. Psychiatry
Cognitive control in adolescence: neural underpinnings and relation to self-report behaviors
PLoS One
The default network and self-generated thought: component processes, dynamic control, and clinical relevance
Ann. N. Y. Acad. Sci. - Year Cognit. Neurosci. Special Issue
A Monte Carlo study of the stability of canonical correlations, canonical weights, and canonical variate-variable correlations
Multivar. Behav. Res.
Distraction can reduce age-related forgetting
Psychol. Sci.
How similar are fluid cognition and general intelligence? A developmental neuroscience perspective on fluid cognition as an aspect of human cognitive ability
Behav. Brain Sci.
Hemispheric asymmetry reduction in older adults: the HAROLD model
Psychol. Aging
Age differences in the intrinsic functional connectivity of default network subsystems
Front. Aging Neurosci.
Selective development of anticorrelated networks in the intrinsic functional organization of the human brain
J. Cognit. Neurosci.
Decreased segregation of brain systems across the healthy adult lifespan
Proc. Natl. Acad. Sci.
Control networks in paediatric Tourette Syndrome show immature and anomalous patterns of functional connectivity
Brain A J. Neurol.
An automated, adaptive framework for optimizing preprocessing pipelines in task-based Functional MRI
PLoS One
The segregation and integration of distinct brain networks and their relationship to cognition
J. Neurosci.
Comparison of the Halstead-Reitan and infrared light beam finger tappers
Assessment
Cited by (27)
Bilingual language entropy influences executive functions through functional connectivity and signal variability
2021, Brain and LanguageCitation Excerpt :The extracted LVs would reflect putative brain functional patterns that were associated with faster global RTs (in both Stroop and color-shape switching tasks), lower Stroop conflict costs, and lower switching and mixing costs (or vice versa). We chose to model both ET tasks simultaneously to extract a set of LVs, each representing a divergent EF measurement profile (c.f. Petrican et al., 2017; Xia et al., 2018), while respecting the potential overlapping aspects of different ET tasks and indices (e.g., task impurity; see review in Hartano & Yang, 2020). Furthermore, if there were robust task-specific widespread brain-EF patterns, we expected PLS to yield more than one statistically reliable LV.
Warped rhythms: Epileptic activity during critical periods disrupts the development of neural networks for human communication
2021, Behavioural Brain ResearchCitation Excerpt :In contrast, high-order networks showed relatively less within-network connectivity than sensorimotor systems, the better to flexibly fractionalize into specialized subsystems [43]. Beyond adolescence, in a lifespan sample of 586 individuals, Petrician and colleagues [44] found that intra-network connectivity profiles for ventral attention and auditory networks showed the expected increase in connectivity from childhood to young adulthood. However, such connectivity began to decrease in late middle age.
Brain Oscillations, Synchrony, and Plasticity: Basic Principles and Application to Auditory-Related Disorders
2021, Brain Oscillations, Synchrony and Plasticity: Basic Principles and Application to Auditory-Related DisordersDeep learning identifies morphological determinants of sex differences in the pre-adolescent brain
2020, NeuroImageCitation Excerpt :Beyond sex-linked risks for disease (Brie et al., 2019; Egloff et al., 2018; Jahanshad and Thompson, 2017; Lind et al., 2017; Retico et al., 2016; Vogeley et al., 2000), this search is motivated by adolescence being a period of particular vulnerability to the emergence of sex-linked neuropsychiatric disorders such as schizophrenia (Vogeley et al., 2000; Womer et al., 2016) and autism (Golarai et al., 2006; Liu et al., 2016; Pierce et al., 2019; Retico et al., 2016; Strickler et al., 2020), which have a higher prevalence in boys than girls, and depression, which girls by age 15 develop twice as likely as boys (Breslau et al., 2017; Cyranowski et al., 2000). In vivo structural magnetic resonance imaging (MRI) studies characterize brain development as following heterogeneous growth trajectories (Giedd, 2004; Petrican et al., 2017) during which sex-specific behaviors emerge (Johnson and Meade, 1987). While physical signs of sex differences are present at birth (Gilmore et al., 2007), brain structural and functional differences between the sexes continue to develop over childhood through late adolescence (Giedd et al., 2015; Mankiw et al., 2017; Pfefferbaum et al., 2016, 2018; Tamnes et al., 2017).
5.26 - The Development of the Nociceptive System and Childhood Pain
2020, The Senses: A Comprehensive Reference: Volume 1-7, Second EditionGenetic contribution to the phenotypic correlation between trait impulsivity and resting-state functional connectivity of the amygdala and its subregions
2019, NeuroImageCitation Excerpt :However, not much is known about the neural correlates of trait impulsivity in late adolescence and early adulthood. The rsFC continues to change across the lifespan (Zuo et al., 2017), even during this time period (Petrican et al., 2017; Richmond et al., 2016; Stevens, 2016; Zhang et al., 2016). Therefore, the neural correlates of trait impulsivity remain to be determined in late adolescence and early adulthood, which is a critical development period for both the healthy population and patients with psychiatric disorders (Havighurst, 1972; Kessler et al., 2005).