Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature
Open accessAbstract
The development of human cognition results from the emergence of coordinated activity between distant brain areas. Network science, combined with non-invasive functional imaging, has generated unprecedented insights regarding the adult brain's functional organization, and promises to help elucidate the development of functional architectures supporting complex behavior. Here we review what is known about functional network development from birth until adulthood, particularly as understood through the use of resting-state functional connectivity MRI (rs-fcMRI). We attempt to synthesize rs-fcMRI findings with other functional imaging techniques, with macro-scale structural connectivity, and with knowledge regarding the development of micro-scale structure. We highlight a number of outstanding conceptual and technical barriers that need to be addressed, as well as previous developmental findings that may need to be revisited. Finally, we discuss key areas ripe for future research in order to (1) better characterize normative developmental trajectories, (2) link these trajectories to biologic mechanistic events, as well as component behaviors and (3) better understand the clinical implications and pathophysiological basis of aberrant network development.
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- Premisecitation
Resting-state networks are highly reproducible in the adult brain.
“RSNs have proven to be highly reproducible in the adult brain (Doucet et al., 2011; Gordon et al., 2016; Power et al., 2011; Yeo et al., 2011)”
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Neonatal hubs primarily involve early sensorimotor, visual, and limbic regions.
“whereas neonatal hubs primarily involve early sensorimotor, visual, and limbic regions (De Asis-Cruz et al., 2015; Fransson et al., 2011; Gao et al., 2011).”
- Also stated in: § Regional hub metrics · plain
“whereas neonatal hubs primarily involve early sensorimotor, visual, and limbic regions (De Asis-Cruz et al., 2015; Fransson et al., 2011; Gao et al., 2011)”
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- Premisecitation
Functional connectivity patterns within and between major resting-state networks are associated with task-relevant behavioral performance.
“and are associated with task-relevant behavioral performance (Cole et al., 2012; Lewis et al., 2009).”
Quote in the paperNot a substantial claim0 of 2 sources checked - Interpretationcitation
Functional connectivity aberrations may indicate the etiological bases of neuropsychiatric disorders.
“and that FC aberrations may point towards the etiological bases of neuropsychiatric disorders (e.g. (Swartz and Monk, 2014; van den Heuvel et al., 2016a)).”
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- cites van den Heuvel et al., 2016a
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Individual cognitive abilities generally depend on distributed networks rather than one localized region.
“First, most individual cognitive abilities arise not solely from a particular brain area, but from networks of activity spanning multiple distributed regions (Petersen and Sporns, 2015).”
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- Interpretationreasoning
The development of functional networks likely reflects programmed neurodevelopmental events.
“This intricate structural-functional interplay underscores that the ontogeny of functional networks likely reflects programmed neurodevelopmental events (e.g. neurogenesis, cell death, myelination, pruning, synaptic plasticity, and glial development) (Innocenti and Price, 2005; Stiles and Jernigan, 2010)”
Quote in the paperSubstantial claim0 of 2 sources checked - Premisecitation
These properties undergo experience-dependent and activity-dependent modulation over the lifespan.
“properties that, in turn, undergo experience-dependent and activity-dependent modulation over the lifespan (Huttenlocher, 2002; Markham and Greenough, 2004; Scholz et al., 2009).”
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Functional connectivity patterns within and between major resting-state networks strongly predict interregional co-activation across tasks.
“Patterns of functional connectivity (FC) within and between the major RSNs are increasingly understood as intrinsic properties of brain function, given that they strongly predict patterns of interregional co-activation across different tasks (Cole et al., 2014; Smith et al., 2009)”
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Cognitive capacities change together with network-level effects inside and across resting-state networks over postnatal development.
“specific cognitive capacities co-evolve with complex network effects within and between different RSNs, throughout postnatal development”
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Adult brains show several coarse modules that remain highly consistent across studies despite small methodological variations.
“The adult brain has several modules at the coarsest level that are remarkably reproducible despite slight methodological differences across studies (Doucet et al., 2011; Gordon et al., 2016; Power et al., 2011; Yeo et al., 2011).”
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Segregated and integrated neural processing are interwoven features of cognition.
“Furthermore, these distinct network effects, i.e. segregated versus integrated neural processing, are interwoven features of cognition.”
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In healthy young adults, higher global efficiency in structural and functional networks is associated with better IQ, attention, and working memory.
“Greater global efficiency in structural and functional networks has been linked to higher IQ, attentional capacity, and working memory in healthy young adults (Cohen and D’Esposito, 2016; Kitzbichler et al., 2011; Li et al., 2009; Stanley et al., 2015; van den Heuvel et al., 2009)”
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- cites Kitzbichler et al., 2011 source
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- cites Li et al., 2009
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Structural connectivity shapes and constrains functional networks throughout life.
“Second, structural connectivity shapes and constrains functional networks across the lifespan (Betzel et al., 2014; Hagmann et al., 2012; Vertes and Bullmore, 2015).”
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The dorsal attention, salience, and frontoparietal executive networks follow comparable spatial and temporal courses as distributed connectivity emerges.
“Similar spatial and temporal properties characterize the emergence of distributed connectivity in the dorsal attention (Gao et al., 2013), salience (Alcauter et al., 2015a; Gao et al., 2015a; Gao et al., 2015b) and frontoparietal executive (Gao et al., 2015a; Gao et al., 2015b) networks.”
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- cites Alcauter et al., 2015a
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A node's structural hub status has been associated with global integration of brain activity.
“Similarly, structural hubness has been linked to integration of global brain activity (Grayson et al., 2016).”
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Adult task-positive cognition involves three large distributed modules: dorsal attention, cingulo-opercular salience, and frontoparietal executive.
“3) three large, distributed modules for task-positive cognition: a) dorsal attention, involved in eye movements and attentional orienting, b) the cingulo-opercular salience module, involved primarily in attentional maintenance, and c) the frontoparietal executive module, important for task-switching.”
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Experimentally induced local perturbations produce broad neurophysiological changes that can be partly accounted for by global network interactions.
“recent studies have found that even purely local, experimentally induced perturbations (e.g. exogenous stimulation or inactivation) result in widespread, complex neurophysiological changes, which are at least partly explainable as local interactions with global network structure (Andoh et al., 2015; Grayson et al., 2016; Gu et al., 2015a; Misic et al., 2015).”
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Mammalian structural networks display rich-club organization, where high-strength nodes link disproportionately with other high-strength nodes.
“Structural networks in the mammalian brain exhibit an important phenomenon known as “rich-club” organization, whereby hubs (i.e. nodes with high strength) link disproportionately to other hubs.”
Quote in the paperNot a substantial claim0 of 2 sources checked - Interpretationcitation
Evidence indicates that infants have a clear community structure, though in an immature form.
“The current nascent literature on infant network topology (see Figure 2B) suggests that a robust community structure does exist, albeit in a primitive form.”
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Infant brains contain strong bilateral segregated networks for sensorimotor, auditory, primary visual, and extrastriate visual regions.
“Seed-based and component-based approaches demonstrate the existence of robust, bilateral segregated networks for somatomotor, primary auditory, primary visual, and extrastriate visual cortex (Fransson et al., 2007; Gao et al., 2015a; Kiviniemi et al., 2000; Lin et al., 2008; Liu et al., 2008; Smyser et al., 2010).”
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A core property of human brain activity is modularity: unexpectedly strong functional connectivity within resting-state networks compared with between them.
“A defining feature of human brain activity is “modularity,” which refers to an unexpectedly high level of within-RSN FC relative to between-RSN FC (Lohse et al., 2014).”
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Across the first two years, default-mode regions progressively become integrated into an online network.
“Over the course of the first two years of life, these regions undergo a precise evolution to gradually bring the network ‘online’ (Damaraju et al., 2014; Gao et al., 2013; Gao et al., 2009).”
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During infancy, structural growth and regression happen concurrently even as overall volume and connectivity increase.
“It is also worth noting that both progressive and regressive changes in structure occur simultaneously during infancy (Gilmore et al., 2012; Scott et al., 2015), despite overall growth in volume and connectivity.”
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Infant heteromodal association cortex contains separate components considered precursors of adult distributed higher-order cognitive networks.
“Distinct components throughout heteromodal association cortex have also been described in infants, and are believed to represent prototypical elements of distributed, higher-order cognitive networks identifiable in adults (Graham et al., 2015).”
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- Interpretationcitation
Networks for sensory processing mature earlier than those underlying higher cognitive functions.
“Collectively, these findings suggest that sensory networks become established at a much earlier age relative to those implicated in higher-level cognition (Gao et al., 2016).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Gao et al., 2016
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Several infant modules align with subdivisions of adult salience, frontoparietal, default-mode, dorsal attention, and ventral attention networks.
“Many of these modules clearly reflect anterior/posterior/temporal subdivisions of the adult salience, frontoparietal, DMN, dorsal attention, and ventral attention modules.”
Quote in the paperSubstantial claim - Study design and conductnone given
A crucial caveat to infant observations is the potential for unidentified sources of artifact in infant studies.
“A crucial caveat to the above observations is the potential for unidentified sources of artifact in infant studies”
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Human and animal studies indicate differences in stimulus-evoked neurovascular coupling between infants and older individuals.
“Human and animal studies indeed indicate differences in stimulus-evoked neurovascular coupling between infants and older individuals, but whether these differences impact rs-fcMRI measurements has yet to be determined (Graham et al., 2015).”
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- Study design and conductcitation
Infant imaging studies are predominantly done during natural sleep or sedation.
“Infant imaging studies are also predominantly done during natural sleep (e.g. (Liu et al., 2008)) or sedation (e.g. (Fransson et al., 2007)).”
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Infant modules often combine nearby regions that later serve different functions in adults.
“Another distinction seen is that infant modules tend to group together anatomically proximate ROIs that have divergent roles in adulthood.”
Quote in the paperSubstantial claim - Premisecitation
With age, regions gradually became more defined by their respective functional roles.
“With age, regions gradually became more defined by their respective functional roles (Power et al., 2011; Power et al., 2010).”
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Hub configurations are robustly evident after birth.
“Hub configurations are robustly evident after birth (De Asis-Cruz et al., 2015; Fransson et al., 2011; Gao et al., 2011)”
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The pattern of hub strengthening spatially and temporally overlaps with increasing within-module synchronization.
“This pattern of hub strengthening bears substantial spatial and temporal overlap with the pattern of increasing within-module synchronization.”
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Different sleep stages correspond with different neurophysiological phenomena that impact rs-fcMRI measurements.
“Different sleep stages also correspond with different neurophysiological phenomena, which impact rs-fcMRI measurements (Laumann et al., 2016; Spoormaker et al., 2010).”
Quote in the paperSubstantial claim0 of 2 sources checked - Interpretationreasoning
Development of small-world architecture and capacity for globally efficient communication and integration largely occurs during the first year of life and prenatally.
“These findings suggest that the development of a small-world architecture, as well as the capacity for globally efficient communication and integration, largely occurs during the first year of life and prenatally, a finding that is supported by multimodal structural and functional network analysis in preterm infants (Ball et al., 2014; van den Heuvel et al., 2015b).”
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- cites van den Heuvel et al., 2015b
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- Premisecitation
Similar global functional network topology is found in conscious versus unconscious adults.
“This concern is partly mitigated by findings of similar global functional network topology in conscious versus unconscious state in adults (Spoormaker et al., 2010)”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Spoormaker et al., 2010 source
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- Interpretationnone given
Many network changes seen during infancy reflect long-term trajectories that extend into childhood and adolescence.
“Many of the network changes seen during infancy reflect long-term trajectories that extend into childhood and adolescence.”
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Altered state of arousal and consciousness might pose important confounds when comparing network findings to those in conscious children or adults.
“However, altered state of arousal and consciousness might pose important confounds when comparing network findings to those seen in conscious children or adults.”
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One of the more reproducible findings of child and adolescent development had been an apparent shift from local to global organization.
“More generally, one of the more reproducible findings of child and adolescent development (until very recently) had been an apparent shift from a local to global organization.”
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This modular structure undergoes rapid postnatal refinement, leading to stronger coupling between distributed links that facilitate modular specialization.
“2) this structure undergoes rapid postnatal refinement, leading to progressively stronger coupling between distributed links that facilitate modular specialization”
Quote in the paperSubstantial claim - Interpretationreasoning
These enhancements establish stable primary sensory networks well before higher-level cognitive networks appear substantially adult-like.
“3) these enhancements result in the establishment of stable, primary sensory networks well before networks involved in higher-level cognition appear substantially adult-like.”
Quote in the paperSubstantial claim - Interpretationreasoning
Node strength and betweenness in functional networks may serve as proxies for modular size and synchronization.
“This is consistent with the notion that node strength and betweenness in functional networks may serve, at least to some extent, as proxies for modular size and synchronization (Power et al., 2013).”
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- Interpretationreasoning
This early developmental trajectory contrasts with a more protracted progression toward increasingly segregated and refined modular architecture that continues into early childhood and beyond.
“This (very) early developmental trajectory stands in contrast to the more protracted progression towards increasingly segregated and refined modular architecture which continues into early childhood and beyond.”
Quote in the paperSubstantial claim - Premisecitation
Several prenatal factors, such as immune and endocrine systems, strongly affect postnatal network trajectories.
“It is also clear that several prenatal factors (e.g. immune and endocrine systems) strongly affect postnatal network trajectories (Canetta et al., 2016; Scheinost et al., 2016b).”
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Key differences have been found in corticocortical and thalamocortical connectivity between conscious and unconscious states.
“but key differences have been found in corticocortical (Heine et al., 2012; Horovitz et al., 2009; Spoormaker et al., 2010) and thalamocortical (Spoormaker et al., 2010) connectivity.”
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In adulthood, high strength and betweenness hubs are largely located within default mode, attentional, sensorimotor, and visual areas.
“high strength and betweenness hubs in adulthood are largely located within within the default mode, attentional, sensorimotor, and visual areas (Cao et al., 2014; Fransson et al., 2011; Grayson et al., 2014; Hwang et al., 2013)”
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In childhood, regional modular assignments appeared to strongly depend on local anatomy.
“In childhood, regional assignments appeared to strongly depend on local anatomy.”
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Hub configurations undergo substantial changes postnatally.
“but undergo substantial changes postnatally.”
Quote in the paperSubstantial claim - Interpretationreasoning
Modular patterns at birth are coarse and primitive, heavily influenced by local anatomy.
“1) modular patterns at birth take a coarse, primitive form that is heavily influenced by local anatomy”
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Infancy is accompanied by specific changes in neurovascular coupling.
“there is good reason to suspect that infancy is accompanied by specific changes in neurovascular coupling (Hagmann et al., 2012).”
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In neonates, two separate resting-state fMRI studies reported modules composed mainly of anatomically adjacent regions.
“In neonates, two independent rs-fcMRI studies found evidence for modules comprised largely of anatomically proximate areas (De Asis-Cruz et al., 2015; van den Heuvel et al., 2015b).”
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- cites van den Heuvel et al., 2015b
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Connectivity between adult DMN areas and within other cognitive RSNs continues to strengthen from early childhood throughout development, especially long-range anterior-posterior links.
“Seed and component approaches have consistently found that connectivity between these areas (and indeed, connectivity within other cognitive RSNs) continues to strengthen from early childhood throughout development, especially with respect to long-range anterior-posterior links (de Bie et al., 2012; Fair et al., 2008; Sato et al., 2014; Sherman et al., 2014; Supekar et al., 2010).”
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Spectral power decreases continually from 5-30 years of age across most frequency bands, particularly in the slow-wave (0.5-7Hz).
“One of the classical and well-reproduced findings is that spectral power (i.e. amplitude of activity within different temporal frequency bands) decreases continually from 5–30 years of age across most frequency bands, but particularly in the slow-wave (0.5–7Hz) (Miskovic et al., 2015; Rodriguez-Martinez et al., 2015; Smit et al., 2012; Whitford et al., 2007).”
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Systems with different functional roles are characterized by substantially different developmental trajectories.
“Much of this new work is finding that systems with different functional roles are characterized by substantially different trajectories (Gu et al., 2015b; Marek et al., 2015).”
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There is convergent evidence that locations of high-strength and high-betweenness hub regions are stable after 5 years of age.
“Returning to the MRI literature, there is convergent evidence that the locations of high-strength and high-betweenness hub regions appear to be stable after 5 years of age (Cao et al., 2014; Grayson et al., 2014; Hwang et al., 2013; Wang et al., 2012; Wu et al., 2013; Zuo et al., 2012).”
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Motion increases non-specific local coupling and decreases long-range coupling in ways similar to differences found between children and adults.
“it has been revealed that motion increases non-specific local coupling and decreases long-range coupling in ways that are similar to differences found between children and adults (Fair et al., 2012b; Power et al., 2012; Satterthwaite et al., 2012; Yan et al., 2013).”
Quote in the paperSubstantial claim0 of 3 sources checked - Study design and conductcitation
When motion-removal techniques are applied, developmental effects on local versus distributed coupling and modular assignments are substantially attenuated but still present to a limited extent.
“When processing techniques intended to remove motion artifact are applied, developmental effects of this type – both in terms of overall local versus distributed coupling and in terms of changing modular assignments – are substantially attenuated, though still present to a limited extent (Fair et al., 2012b; Power et al., 2012; Satterthwaite et al., 2012).”
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Functional network maturation likely follows more precise spatiotemporal trajectories than previously understood.
“It is likely, however, that functional network maturation follows more precise spatiotemporal trajectories than previously understood.”
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There is a progressive shift in peak amplitude towards higher frequency activity.
“There is also a progressive shift in peak amplitude towards higher frequency activity (Miskovic et al., 2015; Rodriguez-Martinez et al., 2015; Smit et al., 2012; Whitford et al., 2007).”
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At least three reports suggest that network structure in children as defined by community detection is largely similar to the adult.
“Indeed, there are now at least 3 reports that suggest the network structure in children as defined by community detection (see Figure 3) are largely similar to the adult (Fair et al., 2012b; Marek et al., 2015; Power et al., 2012).”
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Regional properties exhibit nonlinear relationships with age.
“Regional properties have also been found to exhibit nonlinear relationships with age (Wang et al., 2012), emphasizing the importance of mapping trajectories with more detailed temporal precision.”
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Distance-dependent effects were strong enough to enable reasonably accurate predictions of an individual subject's age from a single resting-state scan.
“Distance-dependent effects were even strong enough to enable reasonably accurate predictions of an individual subject’s age on the basis of a single resting-state scan (Dosenbach et al., 2010).”
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Network structure becomes increasingly non-random across this timespan.
“There is also consensus that network structure becomes increasingly non-random across this timespan (Boersma et al., 2011; Miskovic et al., 2015; Smit et al., 2012).”
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Sensorimotor systems, already well-segregated in childhood, display little change into adulthood.
“For example, (Gu et al., 2015b) found that sensorimotor systems, already well-segregated in childhood, displayed little change into adulthood.”
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- Study design and conductcitation
Recent concerns about head-motion artifact have raised doubts about the interpretability of broad developmental trends.
“However, recent concerns about the influence of head-motion artifact have raised some doubts about the interpretability of such broad trends.”
Quote in the paperSubstantial claim - Interpretationreasoning
These coincident trajectories support the hypothesis that developmental changes in baseline electrophysiological signatures may primarily be subserved by reduction of neuropil and progressive synapse elimination.
“These coincident trajectories have provided key support for the hypothesis that developmental changes in baseline electrophysiological signatures may primarily be subserved by reduction of neuropil and progressive synapse elimination (Buchmann et al., 2011; Smit et al., 2012; Whitford et al., 2007).”
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There is evidence for regional refinement of hub properties.
“However, there is also evidence for regional refinement of hub properties.”
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Node strength and centrality of subcortical regions decrease in late childhood and adolescence.
“Node strength and centrality of subcortical regions have both been reported to decrease in late childhood and adolescence (Sato et al., 2015; Supekar et al., 2009).”
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From roughly 5 years of age until adulthood, theta, alpha, and beta oscillation networks exhibit concurrent increases in clustering coefficient and strength of long-range anterior-posterior and interhemispheric connections.
“From roughly 5 years of age until adulthood, theta (~4Hz), alpha (~10Hz), and beta (~20Hz) oscillation networks exhibit concurrent increases in clustering coefficient (Boersma et al., 2011; Smit et al., 2012) and strength of long-range anterior-posterior and interhemispheric connections (Barry et al., 2004; Miskovic et al., 2015; Smit et al., 2012; Srinivasan, 1999).”
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Much of the observed dynamics in rs-fcMRI networks primarily reflects noise, especially movement.
“Laumann et al. (Laumann et al., 2016) has recently provided strong evidence that much of the observed dynamics in rs-fcMRI networks primarily reflects noise (especially movement).”
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Both highly parameterized simulations and sparser analytic predictions of FC appear comparably effective.
“Models can involve highly parameterized simulations of regional activity (Hansen et al., 2015; Messe et al., 2014; Sanz-Leon et al., 2015), or sparser analytic predictions of FC using graph metrics of mutual communication (Goni et al., 2014; Grayson et al., 2016) (although, both approaches appear to be comparably effective; see Figure 1D).”
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Macroscale FC is modulated by interareal correlated gene expression, areal densities of excitatory and inhibitory receptors, and other microscale architectural features that vary across brain structures.
“macroscale FC is known to be modulated by interareal correlated gene expression, areal densities of excitatory and inhibitory receptors, and other features of microscale architecture that vary across brain structures (Richiardi et al., 2015; Scholtens et al., 2014; Turk et al., 2016; van den Heuvel et al., 2016b)”
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SC-FC correspondence is higher in older adolescents than in young children.
“Hagmann et al. (Hagmann et al., 2010) reported that SC-FC correspondence was higher in older teens versus in young children.”
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Autism Spectrum Disorder is characterized by increased subject-to-subject variability relative to the general population.
“recent work suggests that Autism Spectrum Disorder is characterized by increased subject-to-subject variability relative to the general population (Hahamy et al., 2015).”
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Multiple structural network configurations can theoretically give rise to the same apparent aberrations in function.
“multiple structural network configurations can theoretically give rise to the same apparent aberrations in function – this is essentially the ‘many-to-many mappings’ problem very nicely described in (Pessoa, 2014).”
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Site-specific pathology can be deduced from distributed functional network disturbances.
“This work also provides evidence that site-specific pathology can be deduced from distributed functional network disturbances (Grayson et al., 2016).”
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Head motion has become a substantial concern since 2012, when a trio of papers pointed to systematic motion-related artifacts in rs-fcMRI.
“head motion has become a substantial concern since 2012 when a trio of papers pointed to systematic motion-related artifacts in rs-fcMRI (Power et al., 2012; Satterthwaite et al., 2012; Van Dijk et al., 2012).”
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The functional connectome exhibits temporal instability that allows flexible switching between multiple configurations within a scanning session.
“Mounting evidence suggests that the functional connectome exhibits temporal instability that allows it to flexibly switch between multiple different configurations within a scanning session (Allen et al., 2014; Chang and Glover, 2010; Kang et al., 2011; Shen et al., 2015).”
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There is an abundance of research demonstrating a correlation between DWI-tractography connection weights and FC in adults.
“There is an abundance of research demonstrating a correlation between DWI-tractography connection weights and FC in adults (Hagmann et al., 2008; Hagmann et al., 2010; Honey et al., 2009).”
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Neonates at 40 weeks gestational age have substantially greater SC-FC coupling than neonates born at 30 weeks.
“neonates at 40 weeks gestational age have substantially greater SC-FC coupling than neonates born at 30 weeks.”
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- Study design and conductcitation
Common statistical approaches to assessing dynamic FC may not test against null models that properly account for random noise.
“Other work has called into question some of the common statistical approaches to assessing dynamic FC (Hindriks et al., 2016; Leonardi and Van De Ville, 2015), which may not test against null models that properly account for random noise.”
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Even the best-performing SC-FC models generally account for less than 50% of the variance in FC across the brain in both humans and non-human primates.
“Even the best-performing SC-FC models generally account for less than 50% of the variance in FC across the brain in both humans and non-human primates (Grayson et al., 2016; Messe et al., 2014; Misic et al., 2015).”
Quote in the paperSubstantial claim0 of 3 sources checked - Premisecitation
The fMRI signal is susceptible to spurious sources of variance due to hardware instabilities, respiratory and cardiac signals, and head motion artifacts.
“the fMRI signal is susceptible to a number of spurious sources of variance due to hardware instabilities, respiratory and cardiac signals, and head motion artifacts (Jo et al., 2010; Power et al., 2016).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Jo et al., 2010
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- cites Power et al., 2016
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- Interpretationcitation
Disease processes localized to one part of the brain can cause widespread neurophysiological disturbances in areas distant and unconnected from the pathology.
“These data empirically suggest that in a broad context, disease processes localized to one part of the brain can cause widespread neurophysiological disturbances in areas distant and unconnected from the pathology.”
Quote in the paperSubstantial claim - Premisecitation
Individual brains, even among typical subjects, are distinguishable via their functional connectomes.
“individual brains, even among typical subjects, are distinguishable via their functional connectomes (Finn et al., 2015; Laumann et al., 2015; Miranda-Dominguez et al., 2014b).”
Quote in the paperSubstantial claim0 of 3 sources checked - Premisereasoning
SC networks can be combined with modeling approaches to predict FC networks, allowing exploration of how the structural connectome gives rise to complex neural interactions.
“More generally, SC networks can be combined with various modeling approaches to predict FC networks, allowing for detailed exploration of how the structural connectome gives rise to complex neural interactions.”
Quote in the paperNot a substantial claim - Premisecitation
Focal pharmacogenetic inactivation and cortical transcranial magnetic stimulation demonstrate a causal effect on distributed resting-state connectivity and other neurophysiological signatures, driven by cascading neuronal interactions.
“In our recent paper, we presented experimental validation of these ideas through focal pharmacogenetic inactivation (Grayson et al., 2016), and similar findings were presented by (Andoh et al., 2015) using cortical transcranial magnetic stimulation. Both works demonstrate a causal effect on distributed resting-state connectivity and other neurophysiological signatures, driven by cascading neuronal”
Quote in the paperSubstantial claim0 of 2 sources checked - Premisecitation
This temporal instability property is important for executive functioning, learning, and switching between challenging task demands.
“There is evidence that this property is important for executive functioning, learning, and switching between challenging task demands (Bassett et al., 2011; Braun et al., 2015; Chen et al., 2016).”
Quote in the paperNot a substantial claim0 of 3 sources checked - Premisecitation
In the monkey, whole-brain tract-tracer connection networks and tractography networks show a significant but only moderately high correspondence.
“In the monkey, whole-brain tract-tracer connection networks and tractography networks demonstrate a significant, but only moderately high correspondence.”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Donahue et al., 2016 source
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- cites van den Heuvel et al., 2015a
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- Premisecitation
Complex, distributed disruptions in resting-state networks are consistently implicated in Schizophrenia, ADHD, and Autism.
“Complex, distributed disruptions in resting-state networks are consistently implicated in Schizophrenia (Baker et al., 2014; Khadka et al., 2013; Satterthwaite et al., 2015), ADHD (Castellanos and Aoki, 2016; Fair et al., 2012b), and Autism (Kessler et al., 2016; Moseley et al., 2015; Supekar et al., 2013)”
Quote in the paperNot a substantial claim0 of 3 sources checked - Premisecitation
Simulation experiments using structure-function models predict that purely focal and transient perturbations in activity result in diffuse network reorganization affecting distant brain systems.
“simulation experiments using structure-function models have predicted that even purely focal and transient perturbations in activity should result in diffuse network reorganization that affects distant brain systems (Alstott et al., 2009; Honey and Sporns, 2008; Misic et al., 2015).”
Quote in the paperSubstantial claim0 of 3 sources checked - Premisecitation
Animal models are proving to be an important and necessary bridge for identifying ground-truth structure-to-function principles.
“animal models are proving to be an important and necessary “bridge” for identifying ground-truth structure-to-function principles (Deco et al., 2014; Grayson et al., 2016; Miranda-Dominguez et al., 2014b; Stafford et al., 2014).”
Quote in the paperNot a substantial claim0 of 3 sources checked - Premisecitation
With functional connectivity data, some parcellation schemes can obscure known community structure.
“with functional connectivity data some parcellation schemes can obscure known community structure.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Power et al., 2011 source
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- Premisecitation
Recent data reinforces concerns about artifactual contributions to the global signal in conventional 3T rs-fcMRI acquisitions sensitive to BOLD contrast.
“Recent data reinforces concerns about artifactual contributions to the global signal in conventional 3T rs-fcMRI acquisitions sensitive to BOLD contrast (Grayson et al., 2016; Power et al., 2016)”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Grayson et al., 2016 source
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- cites Power et al., 2016
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- Premisecitation
Functional areal boundaries of heteromodal association areas are variable with respect to sulcal and gyral anatomy.
“functional areal boundaries (see Parcellation Choice) of heteromodal association areas are variable with respect to sulcal and gyral anatomy (Fischl et al., 2008).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Fischl et al., 2008 source
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- Interpretationnone given
Across all stages of postnatal development, functional brain networks exhibit non-trivial properties such as community structure, hub organization, cross-module integration, and global efficiency.
“Across all stages of postnatal development, functional brain networks exhibit non-trivial properties such as community structure, hub organization, cross-module integration, and global efficiency.”
Quote in the paperSubstantial claim - Premisecitation
There is currently no consensus regarding an optimal set of criteria for defining an areal parcellation.
“There is currently no consensus regarding an optimal set of criteria for defining an areal parcellation (Craddock et al., 2013; Glasser et al., 2016a; Gordon et al., 2016)”
Quote in the paperNot a substantial claim0 of 3 sources checked - Premisecitation
Structure-function modeling using MRI data suffers from inherent limitations in DWI-tractography that have not been overcome by state-of-the-art acquisition and processing approaches.
“structure-function modeling using MRI data suffers from a number of inherent limitations in DWI-tractography that have not been overcome by state-of-the-art acquisition and processing approaches (Calabrese et al., 2015; Donahue et al., 2016; Reveley et al., 2015; Thomas et al., 2014).”
Quote in the paperSubstantial claim0 of 3 sources checked - Premisecitation
Some of the techniques currently being used to remove motion artifacts are non-optimal.
“Some of the techniques currently being used to remove these artifacts are non-optimal (Burgess et al., 2016; Goto et al., 2016).”
Quote in the paperSubstantial claim0 of 2 sources checked - Premisecitation
Each cortical area is thought to make a distinct contribution to information processing.
“each area is thought to make a distinct contribution to information processing (Cohen et al., 2008; Felleman and Van Essen, 1991; Fuster, 2002; O’Leary and Nakagawa, 2002; Sur and Rubenstein, 2005).”
Quote in the paperSubstantial claim0 of 3 sources checked - Premisecitation
Without those efforts, critical structure-function relationships were much degraded.
“Without these efforts (which are not feasible in the large majority of human studies), critical structure-function relationships were much degraded.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Grayson et al., 2016 source
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- Premisecitation
Areal boundaries appear very early in development.
“These areal boundaries appear very early in development (Kostovic et al., 1995)”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Kostovic et al., 1995 source
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- Premisecitation
Surface-based registrations that take into account sulcal and gyral anatomy also help mitigate confounds from developmental changes.
“Surface based registrations that take into account the sulcal and gyral anatomy also help mitigate these confounds, and may be the future direction of the field (Fischl, 2012; Van Essen, 2012).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Fischl, 2012 source
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- cites Van Essen, 2012
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- Interpretationcitation
Other factors outside of macro-anatomical connectivity likely affect FC measurements.
“other factors outside of macro-anatomical connectivity likely affect FC measurements.”
Quote in the paperSubstantial claim - Premisecitation
In animal studies, comprehensive histologically and functionally defined whole-brain areal parcellations are feasible.
“In animal studies (rodents and non-human primates), this is feasible through the use of comprehensive, histologically and functionally defined whole-brain areal parcellations (Bezgin et al., 2012; Lein et al., 2007; Paxinos et al., 2000; Saleem and Logothetis, 2007; Swanson, 2015; Van Essen et al., 2012).”
Quote in the paperNot a substantial claim0 of 3 sources checked - Premisecitation
Recent data partly substantiates concerns regarding global signal regression under less conventional, high signal-to-noise scenarios where motion can be physically restricted.
“but also partly substantiates concerns regarding GSR under less conventional, high signal-to-noise scenarios where motion can be physically restricted (Grayson et al., 2016).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Grayson et al., 2016 source
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- Premisecitation
There is strong consensus about the importance of preventing head motion during acquisition and rigorously quantifying motion effects in study data.
“there is strong consensus about the importance of preventing head motion during acquisition and rigorously quantifying motion effects in study data (Goto et al., 2016; Power et al., 2015; Siegel et al., 2016).”
Quote in the paperNot a substantial claim0 of 3 sources checked - Premisecitation
Multiple studies have found evidence for limited test-retest reliability using a multitude of conventional rs-fcMRI network characteristics and analytic approaches.
“Multiple studies have found evidence for limited test-retest reliability using a multitude of conventional rs-fcMRI network characteristics and analytic approaches (Braun et al., 2012; Wang et al., 2011; Wisner et al., 2013; Zuo et al., 2010; Zuo and Xing, 2014).”
Quote in the paperSubstantial claim0 of 3 sources checked - Premisecitation
These reliability effects may largely result from insufficient data acquisition.
“Recent evidence suggests that these effects may largely result from insufficient data acquisition.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Laumann et al., 2015 source
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- Premisecitation
Functional areas possess unique internal structure, such as architectonics and topography.
“Functional areas possess unique internal structure (e.g. architectonics and topography).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Felleman and Van Essen, 1991 source
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- Interpretationreasoning
This length of scan time for each individual is likely prohibitive in most developmental rs-fcMRI studies.
“However, this length of scan time for each individual is likely prohibitive in most developmental rs-fcMRI studies, underscoring the importance of internal study replication.”
Quote in the paperNot a substantial claim - Interpretationnone given
Network refinement continues through childhood and adolescence, strengthening connections particularly among functional hubs.
“The most dramatic changes appear to occur in the first two years of life, though network refinement continues through childhood and adolescence, strengthening connections particularly among functional hubs.”
Quote in the paperSubstantial claim - Premisecitation
Network properties and structure-function relationships supporting sensory and cognitive function are attainable across species.
“network properties and structure-function relationships supporting sensory and cognitive function (see Figure 5) are attainable across species (Grayson et al., 2016; Miranda-Dominguez et al., 2014b; Stafford et al., 2014).”
Quote in the paperSubstantial claim0 of 3 sources checked - Interpretationnone given
The most dramatic changes in functional brain networks appear to occur in the first two years of life.
“The most dramatic changes appear to occur in the first two years of life, though network refinement continues through childhood and adolescence, strengthening connections particularly among functional hubs.”
Quote in the paperNot a substantial claim - Premisecitation
The cerebral cortex is anatomically and functionally organized at many physical scales, from single neurons to functional systems.
“The cerebral cortex is both anatomically and functionally organized at many physical scales - starting at the level of single neurons and extending up to functional systems (Churchland and Sejnowski, 1992).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Churchland and Sejnowski, 1992
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- Premisecitation
Regions or parcels that are overly large may encompass multiple distinct functional areas in ways that make community/network organization non-recognizable.
“regions or parcels that are overly large may encompass multiple distinct functional areas in ways that make community/network organization non-recognizable (Power et al., 2011).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Power et al., 2011 source
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- Premisereasoning
In humans, there is much less clarity regarding potential areal boundaries because comprehensive data have not been readily available in a common reference space.
“In humans, there is much less clarity regarding potential areal boundaries (outside of elementary cytoarchitectonic divisions described, for example, by (Brodmann, 1909) and (Economo and Koskinas, 1925)) since a comparable amount of comprehensive data has not been readily available in a common reference space.”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Brodmann, 1909
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- cites Economo and Koskinas, 1925
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- Premisecitation
The use of high-contrast, age-specific and study-specific template brain images for image registration is a well-validated approach to help overcome confounds from developmental changes.
“The use of high-contrast, age-specific and study-specific template brain images for image registration is a well-validated approach to help overcome some of these confounds (Avants et al., 2010; Fonov et al., 2011)”
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PremisecitationSmall-worldness, global efficiency, and average clustering coefficient are already high in neonates.
“Small-worldness (De Asis-Cruz et al., 2015; Fransson et al., 2011; Gao et al., 2011), as well as its constituent properties of global efficiency and average clustering coefficient, are already high in neonates.”
Quote in the paperNot a substantial claim1 of 3 sources checked- cites De Asis-Cruz et al., 2015 sourceExperimental — accuracy not yet measured
- cites Fransson et al., 2011
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Gao et al., 2011
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Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationLater studies found comparable bilateral correlations in early visual and early auditory cortex.
“followed soon after by similar findings of bilaterally correlated activity in early visual and early auditory cortex (Cordes et al., 2001; Kiviniemi et al., 2000; Lowe et al., 1998).”
Quote in the paperNot a substantial claim0 of 3 sources checkedMay combine two claims.
PremisecitationIndependent component analysis reliably identifies early visual, early auditory, and primary sensory/motor maps, along with distributed association-cortex components.
“ICA maps reproducibly reveal early visual, early auditory, and primary sensory/motor components, as well as other components comprising distributed portions of the frontal, parietal, and temporal association cortices (Damoiseaux et al., 2006).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Damoiseaux et al., 2006 source
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PremisecitationInterregional functional connectivity arises from anatomical projection strengths, correlated gene expression, and synaptic receptor densities.
“Interregional FC arises from anatomical projection strengths (Messe et al., 2014; Shen et al., 2012), correlated gene expression (Richiardi et al., 2015), and synaptic receptor densities (Turk et al., 2016; van den Heuvel et al., 2016b)”
Quote in the paperNot a substantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe first observation of correlated resting-state activity was in bilateral sensorimotor cortex.
“Correlated resting-state activity was first identified in bilateral sensorimotor cortex by (Biswal et al., 1995)”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Biswal et al., 1995 source
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PremisecitationSmall-world organization appears across brain scales and is proposed to reflect a biological compromise between efficient integration and the expense of long-distance connections.
“This property, which is ubiquitous across vastly different scales of investigation in the brain, is thought to emerge from a biological need to balance the benefits of integration against the costs of long-range wiring (Collin et al., 2013; Vertes and Bullmore, 2015).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Collin et al., 2013
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- cites Vertes and Bullmore, 2015 source
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InterpretationcitationThe observed sequence fits the presence of basic touch and vision at birth and findings that primary sensory cortex matures earliest.
“These trends are consistent with the presence of basic somatosensory and visual functions at birth, and help contextualize findings that primary sensory regions are generally the first cortical areas to reach plateaus or peaks in growth (Geng et al., 2016; Gilmore et al., 2012; Lyall et al., 2015; Scott et al., 2015).”
Quote in the paperSubstantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationRich-club nodes tend to span multiple resting-state networks, aiding integration among them.
“Rich-club nodes tend to span multiple RSNs, thereby facilitating integration between them (Sporns, 2013; van den Heuvel and Sporns, 2013).”
Quote in the paperNot a substantial claim0 of 2 sources checkedMay combine two claims.
PremisecitationDuring the first two years, sensory networks mature and strengthen, becoming substantially adult-like by age two.
“These sensory networks undergo subtle refinements and strengthening over the first two years of life, and by age two bear substantial resemblance to their adult counterparts (Gao et al., 2015a; Lin et al., 2008).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Gao et al., 2015a
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- cites Lin et al., 2008 source
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PremisecitationAt age two, the default-mode network resembles the adult form, but long-range anterior-posterior coupling is still relatively weak.
“By two years of age, the network bears adult-like qualities, although coupling between distant anterior and posterior nodes of the network remain relatively low.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationThe default-mode network is viewed as task-negative, associated with internal thought, and shows reduced activity during external tasks.
“the DMN is considered “task-negative” as it has been linked to internal mentation and is known to deactivate during processing of external stimuli (Buckner et al., 2008)”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Buckner et al., 2008 source
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PremisecitationResting-state networks are present in infancy and possibly to some degree before birth.
“RSNs are already present during infancy, and potentially to some extent in utero (Thomason et al., 2013).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Thomason et al., 2013 source
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PremisecitationSegregation and integration together are involved in cognitive control and executive function, and relate differently to simple motor versus complex working memory performance.
“Both effects in tandem are crucially involved in cognitive control (Dwyer et al., 2014) and executive functioning (Reineberg et al., 2015), and are differentially associated with performance on simple motor tasks versus complex working memory tasks (Cohen and D’Esposito, 2016).”
Quote in the paperSubstantial claim0 of 3 sources checkedMay combine two claims.
PremisecitationDefault-mode network subregions in neonates and young infants are locally correlated but not yet synchronized as one coherent network.
“In neonates and very young infants, these individual compartments demonstrate locally correlated activity, but fail to synchronize into a coherent network (Damaraju et al., 2014; Fransson et al., 2007; Gao et al., 2009; Smyser et al., 2010; Wylie et al., 2014).”
Quote in the paperSubstantial claim0 of 3 sources checkedMay combine two claims.
PremisecitationAdult modular organization includes separate sensory/motor systems and the default-mode network.
“These modules include 1) segregated, non-distributed modules for sensory/motor activity, such as in early visual cortex and in somatomotor cortex, 2) the default-mode network (DMN), comprising the medial prefrontal, posterior cingulate/precuneus, angular gyrus, and medial temporal cortex”
Quote in the paperNot a substantial claim0 of 3 sources checkedMay combine two claims.
PremisecitationThe brain doubles in volume during year one and attains 80-90% of adult size by age three.
“doubling in volume during the first year and reaching 80–90% of adult volume by age 3 (Courchesne et al., 2000; Knickmeyer et al., 2008).”
Quote in the paperNot a substantial claim0 of 2 sources checkedMay combine two claims.
PremisecitationMajor fiber pathways are consolidated by myelination, but they are largely present before birth.
“The brain’s major fiber pathways become consolidated through myelination, though their presence is largely established prenatally (Stiles and Jernigan, 2010).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Stiles and Jernigan, 2010 source
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InterpretationreasoningNormal and pathological developmental changes in functional connectivity are best interpreted using an integrated structural-functional network approach.
“By extension, one could reason that developmental modifications in brain FC, whether normative or pathological, are also best understood via an emerging network science that merges structural and functional connectivity data.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationThe first years include widespread rapid synapse formation, then a long phase of synapse removal and cell loss that extends into adulthood.
“This same time period is marked by rapid and widespread cortical synaptogenesis, followed by a protracted period of synapse elimination and cell loss which carries into adulthood (Huttenlocher, 2002; Innocenti and Price, 2005).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Huttenlocher, 2002
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- cites Innocenti and Price, 2005 source
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PremisecitationTwo-year-olds show separate auditory, sensorimotor, and visual modules, and perhaps early versions of salience, frontoparietal, and default-mode networks.
“Community structure assessed at two years of age (Alcauter et al., 2015b; Gao et al., 2015b) indicates the presence of distinct modules encompassing early auditory, early somatomotor, and early visual areas, and potentially, other prototypical modules similar to the canonical salience, frontoparietal, and DMN seen in adults.”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Alcauter et al., 2015b
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- cites Gao et al., 2015b
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PremisecitationLong-distance links are preferentially strengthened during the first year and level off thereafter.
“Concomitantly, long-distance links are preferentially strengthened during the first year of life, leveling off thereafter (Gao et al., 2011).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Gao et al., 2011 source
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Study design and conductreasoningEarly postnatal changes in cerebral vasculature and altered state of consciousness when scanning very young participants are considerations in infant rs-fcMRI.
“Other considerations include early postnatal changes in cerebral vasculature, and altered state of consciousness when scanning very young participants.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationPrior to 2012, multiple studies found that functional connectivity between anatomically proximate ROIs gradually decreased, while long-range functional connections, especially anterior-posterior links, gradually increased until adulthood.
“Prior to 2012, multiple studies had found that functional connectivity between anatomically proximate ROIs gradually decreased, whereas long-range functional connections, especially anterior-posterior links, gradually increased until adulthood (Dosenbach et al., 2010; Fair et al., 2009; Kelly et al., 2009; Supekar et al., 2009).”
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Study design and conductcitationDifferent community detection algorithms can provide unique results and not all are appropriate for any given experimental condition.
“different community detection algorithms can provide unique results and all are not appropriate for any given experimental condition (Gates et al., 2016).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Gates et al., 2016 source
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PremisecitationFrom birth through the first two years of life, synchronization and homotopic coupling increase while between-module connectivity decreases, indicating greater functional specialization.
“synchronization and homotopic coupling from birth through the first two years of life (Gao et al., 2015b; Homae et al., 2010), concomitant with decreasing between-module connectivity (i.e. greater functional specialization).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Gao et al., 2015b
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- cites Homae et al., 2010 source
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Study design and conductnone givenNatural sleep or sedation attenuates micromovements and their attendant signal artifacts.
“A natural benefit is the attenuation of micromovements and their attendant signal artifacts.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationA recent study using matched methods in adults and 1-2 year olds first directly showed many localized infant modules and how they map onto adult organization.
“One recent report compared community structure in adults against that in 1–2 year olds using closely matched methods (Eggebrecht et al., 2017), providing the first direct evidence for numerous anatomically localized modules in the infant brain and their relationship to adult functional organization (Figure 2C).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Eggebrecht et al., 2017 source
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PremisecitationRich clubs are evident in both structural and functional networks in neonates, along with high functional modularity and integration capacity between modules.
“Rich clubs are also evident in both structural and functional networks in neonates along with both high functional modularity and integration capacity between modules (Ball et al., 2014; Scheinost et al., 2016a; van den Heuvel et al., 2015b).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Ball et al., 2014 source
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- cites Scheinost et al., 2016a
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- cites van den Heuvel et al., 2015b
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InterpretationcitationAnatomical areas involved in integrating different information processing streams are likely critical for complex cognitive and social abilities and potentially uniquely susceptible to early environmental influences.
“Such anatomical areas are likely critical for the development of complex cognitive and social abilities, and are potentially uniquely susceptible to early environmental influences (Graham et al., 2015).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Graham et al., 2015 source
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PremisecitationFrom birth through age two, these modules markedly increase distributed synchronization and homotopic coupling.
“These latter modules also exhibit substantial growth of distributed synchronization and homotopic coupling from birth through the first two years of life (Gao et al., 2015b; Homae et al., 2010), concomitant”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Gao et al., 2015b
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- cites Homae et al., 2010 source
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PremisecitationThese properties marginally increase during the first year and plateau until at least the end of the second year.
“These properties only appear to marginally increase during the first year of life, plateauing thereafter until at least the end of the second year (Gao et al., 2011).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Gao et al., 2011 source
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PremisecitationDuring the first two years, hubness of sensorimotor areas gradually decreases and involvement of association cortical areas increases, especially medial frontal and parietal default mode portions.
“The first two years of life reflect a gradual decrease in the hubness of sensorimotor areas and increased involvement of various association cortical areas, especially the medial frontal and parietal portions of the default mode (Gao et al., 2011).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Gao et al., 2011 source
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PremisecitationThe DMN exhibits increasingly synchronized within-network and between-network connections.
“The DMN was found to exhibit both increasingly synchronized within-network and between-network connections.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Gu et al., 2015b
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PremisecitationAmong cortical areas, some report increasing hubness of frontal nodes, while other lobes show mixed reports of increasing, decreasing, or stable hubness.
“Among cortical areas, some have reported increasing hubness of frontal nodes (Cao et al., 2014; Wu et al., 2013) while in other lobes there have been mixed reports of increasing (Cao et al., 2014; Grayson et al., 2014) and decreasing (Wu et al., 2013; Zuo et al., 2012), or stable (Hwang et al., 2013) hubness.”
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InterpretationreasoningThese trends pointed to dampening of non-specific local spread of activity and strengthening of long-range links, facilitating cognitive development through modular specialization and selective cross-network integration.
“These trends pointed to coherent changes that involved a dampening of non-specific local spread of activity and strengthening of long-range links, facilitating cognitive development through modular specialization and selective cross-network integration (Bunge and Wright, 2007; Fair et al., 2009; Uddin, 2011; Uddin et al., 2011).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Bunge and Wright, 2007 source
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- cites Fair et al., 2009
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- cites Uddin, 2011
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PremisecitationIncreased cross-network integration between cingulo-opercular/salience and somatomotor modules occurs over age 10-26 and is associated with cognitive control development.
“Similar, albeit not identical developmental findings, are observed by (Marek et al., 2015)), who found increased cross-network integration between the cingulo-opercular/salience and somatomotor modules over the age of 10–26, which they showed to be associated with the development of cognitive control.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Marek et al., 2015 source
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PremisecitationSpecific connections to cortical hub regions increase during childhood and adolescence, resulting in increased rich club coefficients in adulthood.
“More detailed network analyses have revealed that specific connections to cortical hub regions increase during childhood and adolescence (Grayson et al., 2014; Hwang et al., 2013) resulting in increased rich club coefficients in adulthood (Cao et al., 2014; Grayson et al., 2014).”
Quote in the paperSubstantial claim0 of 3 sources checkedMay combine two claims.
PremisecitationFrontal and parietal cortical gray matter volume decreases across 5-30 years and exhibits curvilinear trajectories closely correlated with loss of slow-wave power in the same areas.
“Interestingly, frontal and parietal cortical gray matter (but not white matter) volume decreases across this same age bracket, and exhibits curvilinear trajectories that are closely correlated to the loss of slow-wave power in these same areas (Buchmann et al., 2011; Smit et al., 2012; Whitford et al., 2007).”
Quote in the paperSubstantial claim0 of 3 sources checkedMay combine two claims.
PremisecitationDespite adult-like organization, refinements within and between systems occur over time.
“Despite this “adult like” level of organization, refinements within and between systems does appear to occur over time, although details to this end are still being worked out (Fair et al., 2012b; Gu et al., 2015b; Marek et al., 2015).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Fair et al., 2012b
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- cites Gu et al., 2015b
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- cites Marek et al., 2015 source
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PremisecitationTwo reports found path length increases with age, while more recent work demonstrates age-related reductions.
“Somewhat unexpectedly, two reports found path length to also increase with age (Boersma et al., 2011; Smit et al., 2012), although more recent work demonstrates age-related reductions (Miskovic et al., 2015).”
Quote in the paperNot a substantial claim0 of 3 sources checkedMay combine two claims.
PremisereasoningEEG/MEG resting-state networks provide greater temporal resolution than rs-fMRI and offer complementary insights about functional development.
“Resting-state networks obtained using electrophysiological recording (EEG or MEG) provide greater temporal resolution (<100Hz) relative to rs-fMRI (<0.1Hz) and therefore offer complementary insights about functional development.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningThese mixed or non-significant findings might suggest that regional properties of cortical hubs are largely established during very early development.
“At first glance, these mixed or non-significant findings might suggest that regional properties of cortical hubs are largely established during very early development.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningRecent convergence of data suggests that network structure continues to evolve after late childhood in ways not primarily distance-dependent, with complex specific changes coinciding with development of specific cognitive abilities.
“Therefore, there is recent convergence of data suggesting that network structure continues to evolve after late childhood in ways that are not primarily distance-dependent; rather, complex but specific changes may coincide with the development of specific cognitive abilities.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationNetworks involved in task-positive cognitive function (salience, frontoparietal executive, attentional) became increasingly segregated and exhibited increasingly variable spatial structure.
“On the other hand, networks involved in task-positive cognitive function (e.g. salience, frontoparietal executive, and attentional networks), being generally well-connected with other systems, became increasingly segregated and exhibited increasingly variable spatial structure.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Gu et al., 2015b
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Study design and conductreasoningEEG/MEG studies are generally unable to map activity to precise brain areas due to source localization challenges and often treat scalp sensors as network nodes.
“It is important to note that these studies are generally unable to map activity to precise brain areas due to challenges in source localization, and often treat the scalp sensors as the network nodes.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationAge-related changes in functional connectivity disproportionately impact polysynaptic connections, though the study spanned the lifespan and may reflect aging.
“Another study found that age-related changes in FC disproportionately impacts polysynaptic connections (Betzel et al., 2014), although this study was performed across the lifespan and may reflect an effect of aging.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Betzel et al., 2014 source
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PremisecitationGlobal signal regression is arguably the most effective motion-denoising technique currently available.
“The most contentious debate probably concerns the use of global signal regression (GSR) – arguably the most effective motion-denoising technique currently available (Burgess et al., 2016; Power et al., 2015; Yan et al., 2013).”
Quote in the paperNot a substantial claim0 of 3 sources checkedMay combine two claims.
InterpretationcitationPredictive models have been extensively validated on both rs-fcMRI and EEG data, suggesting that SC strongly shapes and constrains activity across temporal scales.
“Predictive models have been extensively validated on both rs-fcMRI and EEG data (Chu et al., 2015), suggesting that SC strongly shapes and constrains activity across temporal scales.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Chu et al., 2015 source
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PremisecitationOver development, rs-fcMRI networks show increased within-subject variability, consistent with EEG studies showing increased signal complexity.
“Over development, rs-fcMRI networks show increased within-subject variability (Hutchison and Morton, 2015; Marusak et al., 2016; Qin et al., 2015), consistent with EEG studies showing that signal complexity increases over development (McIntosh et al., 2008; Vakorin et al., 2011).”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites Hutchison and Morton, 2015
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- cites Marusak et al., 2016
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- cites Qin et al., 2015 source
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PremisecitationThe highest reported correlation between monkey tract-tracer and tractography networks is r = 0.59, though it is often much lower.
“Currently, the highest reported correlation stands at r = 0.59 (Donahue et al., 2016), though it is often much lower (van den Heuvel et al., 2015a).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Donahue et al., 2016 source
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- cites van den Heuvel et al., 2015a
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Study design and conductcitationInstability exists in the form of measurable state transitions (e.g., awake to sleep, eyes open versus closed), and there is considerably less evidence for intrinsic dynamics otherwise.
“The authors note that instability is not absent, but that it exists in the form of measurable state transitions (e.g. from awake to sleep, or eyes open verus closed), and that there is considerably less evidence for intrinsic dynamics otherwise.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Laumann et al., 2016 source
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PremisecitationHead motion increases functional correlations between spatially proximal nodes and decreases correlations between distant nodes.
“head motion increases functional correlations between spatially proximal nodes and decreases correlations between distant nodes (Power et al., 2012).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Power et al., 2012 source
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PremisecitationSchizophrenia, ADHD, Autism, and potentially other DSM-defined disorders each constitute a highly heterogeneous set of etiologies.
“The first challenge is the ever-expanding evidence that Schizophrenia (Meda et al., 2014; Satterthwaite and Baker, 2015), ADHD (Costa Dias et al., 2015; Fair et al., 2012a; Gates et al., 2014; Karalunas et al., 2014), Autism (Jeste and Geschwind, 2014; Rudie et al., 2012), and potentially other DSM defined disorders, each constitutes a highly heterogeneous set of etiologies.”
Quote in the paperSubstantial claim0 of 3 sources checkedMay combine two claims.
InterpretationcitationNew multimodal approaches that anchor surface-based registrations to other structural or functional characteristics of an individual are likely to improve subject-to-subject registrations and reduce intersubject variability.
“New multimodal approaches that also anchor surface-based registrations to other structural or functional characteristics of an individual are likely to improve subject to subject registrations, and hence reduce intersubject variability, even more (e.g.(Glasser et al., 2016b; Robinson et al., 2014).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Glasser et al., 2016b
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- cites Robinson et al., 2014 source
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PremisecitationProbing cellular and molecular markers across the whole human brain at high-throughput is exceptionally difficult and cannot be done under strict experimental conditions.
“probing cellular and molecular markers across the whole human brain at high-throughput is exceptionally difficult (Richiardi et al., 2015) and cannot be done under strict experimental conditions.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Richiardi et al., 2015 source
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Interpretationnone givenCommunity structure at birth is coarse and primitive, but gradually evolves into a denser, more spatially structured, and distributed organization.
“Community structure at birth is coarse and primitive, but gradually evolves into a denser, more spatially structured, and distributed organization.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationTight control of functional imaging conditions was needed in Grayson et al. to reveal novel structure-function relationships and maximize model performance.
“One interesting aspect of the work in (Grayson et al., 2016) is how tightly functional imaging conditions had to be controlled in order to reveal novel structure-function relationships and in order to maximize model performance”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Grayson et al., 2016 source
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PremisecitationFunctional areas contain distinct combinations of inputs and outputs, which group related areas into specialized networks.
“They also contain distinct combinations of inputs and outputs, which in turn group related areas into specialized networks (Felleman and Van Essen, 1991).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Felleman and Van Essen, 1991 source
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PremisecitationFC networks in one highly sampled individual converged as a function of the timeseries length used to extract correlations and were extremely reproducible using approximately 1 hour of motion-free data.
“FC networks in one highly sampled individual converged as a function of the timeseries length used to extract correlations and were extremely reproducible using approximately 1 hour of motion-free data (Laumann et al., 2015).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Laumann et al., 2015 source
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Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenA very large portion of the current human developmental literature is in dire need of re-examination in light of recent developments regarding systematic artifacts in the imaging signals.
“a very large portion of the current human developmental literature is in dire need of re-examination in light of recent developments regarding systematic artifacts in the imaging signals.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationGlobal topological metrics for structural and functional networks show stability across different parcellation schema of similar density, but vary considerably as a function of network size.
“Global topological metrics for structural and functional networks show stability across different parcellation schema of similar density, but vary considerably as a function of network size (de Reus and van den Heuvel, 2013; Fornito et al., 2010; Zalesky et al., 2010).”
Quote in the paperNot a substantial claim0 of 3 sources checkedMay combine two claims.
PremisecitationMotion artifacts appear to be tightly related to clinical factors and a whole host of behavioral phenotypes and metrics.
“Motion artifacts appear to be tightly related to clinical factors (Fair et al., 2012b) and a whole host of behavioral phenotypes and metrics (Siegel et al., 2016).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Fair et al., 2012b
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- cites Siegel et al., 2016
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PremisecitationStrong artifacts due to motion have been noted in diffusion weighted imaging and cortical thickness measurements.
“Strong artifacts due to motion, in addition to their relevance for fMRI, have been noted in diffusion weighted imaging (Roalf et al., 2016; Yendiki et al., 2014) and cortical thickness measurements (Reuter et al., 2015; Savalia et al., 2017).”
Quote in the paperSubstantial claim0 of 3 sources checkedMay combine two claims.
InterpretationreasoningFindings of increased subject-to-subject variability in ASD are consistent with different pathologies in brain function leading to related clinical outcomes and underscore the importance of identifying individualized abnormalities.
“Such findings are consistent with the notion that different pathologies in brain function may lead to related clinical outcomes, and underscore the importance of identifying individualized abnormalities.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningExperimental animal models should remain indispensable for probing cellular and molecular markers across the whole human brain.
“Experimental animal models should therefore remain indispensable for this purpose the foreseeable future.”
Quote in the paperNot a substantial claim
The paper relies on this without support.
Coordinated activity across distant brain regions is fundamental to human brain function.
“Coordinated neuronal activity between anatomically disparate regions is an essential feature of human brain function.”
The paper relies on this without support.
The functional connectivity measures used in the reviewed studies reflect neural connectivity rather than non-neural artifacts.
“A crucial caveat to the above observations is the potential for unidentified sources of artifact in infant studies”
The paper relies on this without support.
Developmental trajectories observed in cross-sectional studies reflect true longitudinal development.
“Many of the network changes seen during infancy reflect long-term trajectories that extend into childhood and adolescence.”
The paper relies on this without support.
Adult network organization is a valid reference for assessing infant and child network maturity.
“Indeed, there are now at least 3 reports that suggest the network structure in children as defined by community detection (see Figure 3) are largely similar to the adult (Fair et al., 2012b; Marek et al., 2015; Power et al., 2012).”
The paper relies on this without support.
The studies reviewed are sufficiently comparable to synthesize trends across them.
“Taken together, these studies point towards several trends that are consistent with results from seed and component based approaches”
The paper relies on this without support.
Microscale architectural features such as gene expression and receptor densities evolve with age.
“and undoubtedly evolve with age.”
The paper relies on this without support.
Motion tends to be greater in patient populations and younger children.
“Motion tends to be greater in patient populations and younger children, posing a fundamentally important challenge for developmental research.”
The paper relies on this without support.
Even less is known about the stability of areal parcellations at younger ages.
“and even less known about the stability of these parcellations at younger ages.”
The paper relies on this without support.
Cortical folding patterns change continually from birth into adulthood, especially during infancy.
“Cortical folding patterns change continually from birth into adulthood, and especially during infancy.”
The paper relies on this without support.
Infancy is a time during which image contrasts in various MR acquisitions change dramatically.
“Infancy is also a time during which the image contrasts in various MR acquisitions changes dramatically.”
The paper relies on this without support.
Invasive tract-tracer injections remain the gold standard for identifying and quantifying interareal connection weights.
“Invasive tract-tracer injections, a method that is only feasible in animal models, remains the “gold standard” for identifying and quantifying interareal connection weights.”
Cites
1 retracted
Karalunas, S. L., Fair, D., Musser, E. D., Aykes, K., Iyer, S. P., & Nigg, J. T. (2014) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2014.763 · Cited by 340 · cited 4× · see citing works
“Complex, distributed disruptions in resting-state networks are consistently implicated in Schizophrenia (Baker et al., 2014; Khadka et al., 2013; Satterthwaite et al., 2015), ADHD (Castellanos and Aoki, 2016; Fair et al., 2012b), and Autism (Kessler et al., 2016; Moseley et al., 2015; Supekar et al., 2013) – though a…”
BackgroundInfluentialSelf-citationRetractedCollective dynamics of ‘small-world’ networks
Watts, D. J., & Strogatz, S. H. (1998) · Nature · doi:10.1038/30918 · Cited by 43,060 · cited 1× · see citing works
“When networks exhibit both high global efficiency and high average clustering coefficients, they exhibit “small-world” organization (Watts and Strogatz, 1998).”
BackgroundFunctional connectivity in the motor cortex of resting human brain using echo‐planar mri
Biswal, B., Zerrin Yetkin, F., Haughton, V. M., & Hyde, J. S. (1995) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910340409 · Cited by 9,812 · cited 1× · see citing works
“…to functional connectivity are evolving rapidly Correlated resting-state activity was first identified in bilateral sensorimotor cortex by Biswal et al. (1995), followed soon after by similar findings of bilaterally correlated activity in early visual and early auditory cortex (Cordes et…”
Background<i>The Brain's Default Network</i>: <i>Anatomy, Function, and Relevance to Disease</i>
Buckner, R. L., Andrews‐Hanna, J. R., & Schacter, D. L. (2008) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1440.011 · Cited by 9,761 · see citing works
Distributed hierarchical processing in the primate cerebral cortex
Felleman, D. J., & Van Essen, D. C. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.1.1 · Cited by 7,783 · see citing works
Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.10.018 · Cited by 7,429 · see citing works
The organization of the human cerebellum estimated by intrinsic functional connectivity
Buckner, R. L., Krienen, F. M., Castellanos, A., Diaz, J. C., & Yeo, B. T. T. (2011) · Journal of Neurophysiology · doi:10.1152/jn.00339.2011 · Cited by 7,304 · see citing works
Genome-wide atlas of gene expression in the adult mouse brain
Lein, E. S., Hawrylycz, M. J., Ao, N., Ayres, M., Bensinger, A., Bernard, A., Boe, A. F., Boguski, M. S., Brockway, K. S., Byrnes, E. J., et al. (2007) · Nature · doi:10.1038/nature05453 · Cited by 5,572 · cited 2× · see citing works
“In animal studies (rodents and non-human primates), this is feasible through the use of comprehensive, histologically and functionally defined whole-brain areal parcellations (Bezgin et al., 2012; Lein et al., 2007; Paxinos et al., 2000; Saleem and Logothetis, 2007; Swanson, 2015; Van Essen et al., 2012).”
MethodA New Initiative on Precision Medicine
Collins, F. S., & Varmus, H. (2015) · New England Journal of Medicine · doi:10.1056/nejmp1500523 · Cited by 5,202 · see citing works
Correspondence of the brain's functional architecture during activation and rest
Smith, S. M., Fox, P. T., Miller, K. L., Glahn, D. C., Fox, P. M., Mackay, C. E., Filippini, N., Watkins, K. E., Toro, R., Laird, A. R., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0905267106 · Cited by 5,150 · cited 2× · see citing works
“…understood as intrinsic properties of brain function, given that they strongly predict patterns of interregional co-activation across different tasks (Cole et al., 2014; Smith et al., 2009) and are associated with task-relevant behavioral performance (Cole et al., 2012; Lewis et al., 2009).”
BackgroundA multi-modal parcellation of human cerebral cortex
Glasser, M. F., Coalson, T. S., Robinson, E. C., Hacker, C. D., Harwell, J., Yacoub, E., Ugurbil, K., Andersson, J., Beckmann, C. F., Jenkinson, M., et al. (2016) · Nature · doi:10.1038/nature18933 · Cited by 5,111 · see citing works
Consistent resting-state networks across healthy subjects
Damoiseaux, J. S., Rombouts, S. A. R. B., Barkhof, F., Scheltens, P., Stam, C. J., Smith, S. M., & Beckmann, C. F. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0601417103 · Cited by 4,326 · cited 1× · see citing works
“ICA maps reproducibly reveal early visual, early auditory, and primary sensory/motor components, as well as other components comprising distributed portions of the frontal, parietal, and temporal association cortices (Damoiseaux et al., 2006).”
BackgroundMapping the structural core of human cerebral cortex
Hagmann, P., Cammoun, L., Gigandet, X., Meuli, R., Honey, C. J., Wedeen, V. J., & Sporns, O. (2008) · PLoS Biology · doi:10.1371/journal.pbio.0060159 · Cited by 4,173 · cited 1× · see citing works
“There is an abundance of research demonstrating a correlation between DWI-tractography connection weights and FC in adults (Hagmann et al., 2008; Hagmann et al., 2010; Honey et al., 2009).”
BackgroundFunctional Network Organization of the Human Brain
Power, J. D., Cohen, A. L., Nelson, S. M., Wig, G. S., Barnes, K. A., Church, J. A., Vogel, A. C., Laumann, T. O., Miezin, F. M., Schlaggar, B. L., et al. (2011) · Neuron · doi:10.1016/j.neuron.2011.09.006 · Cited by 4,124 · see citing works
Functional cartography of complex metabolic networks
Guimerà, R., & Nunes Amaral, L. A. (2005) · Nature · doi:10.1038/nature03288 · Cited by 3,983 · see citing works
Methods to detect, characterize, and remove motion artifact in resting state fMRI
Power, J. D., Mitra, A., Laumann, T. O., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.08.048 · Cited by 3,748 · cited 1× · see citing works
“Considerable work and debate is now ongoing to determine the optimal ‘denoising’ approaches during data processing (Patriat et al., 2016; Power et al., 2014).”
BackgroundPreface: Cerebral Cortex Has Come of Age
Goldman, P. S., & RAKIC, P. T. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.1.1-a · Cited by 3,412 · see citing works
Tracking whole-brain connectivity dynamics in the resting state
Allen, E. A., Damaraju, E., Plis, S. M., Erhardt, E. B., Eichele, T., & Calhoun, V. D. (2014) · Cerebral Cortex · doi:10.1093/cercor/bhs352 · Cited by 2,992 · see citing works
Functional connectome fingerprinting: Identifying individuals using patterns of brain connectivity
Finn, E. S., Shen, X., Scheinost, D., Rosenberg, M. D., Huang, J., Chun, M. M., Papademetris, X., & Constable, R. T. (2015) · Nature Neuroscience · doi:10.1038/nn.4135 · Cited by 2,747 · see citing works
Probabilistic Independent Component Analysis for Functional Magnetic Resonance Imaging
Beckmann, C. F., & Smith, S. M. (2004) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2003.822821 · Cited by 2,707 · cited 2× · see citing works
“More data-driven approaches were developed based on the concept of independent components analysis (Beckmann and Smith, 2004), which decomposes brain activity into a set of spatial maps (i.”
Method(1909) · Cited by 2,575 · see citing works
The influence of head motion on intrinsic functional connectivity MRI
Van Dijk, K. R. A., Sabuncu, M. R., & Buckner, R. L. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.07.044 · Cited by 2,344 · see citing works
Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging
Behrens, T. E. J., Johansen-Berg, H., Woolrich, M. W., Smith, S. M., Wheeler-Kingshott, C. A. M., Boulby, P. A., Barker, G. J., Sillery, E. L., Sheehan, K., Ciccarelli, O., et al. (2003) · Nature Neuroscience · doi:10.1038/nn1075 · Cited by 2,330 · cited 1× · see citing works
“Several groups, however, are finding ways to utilize today's non-invasive imaging tools to bring us closer to realizing these goals (Behrens et al., 2003; Glasser et al., 2016a; Gordon et al., 2016; Wig et al., 2014a, 2014b; Zhang et al., 2010).”
BackgroundUnbiased average age-appropriate atlases for pediatric studies
Fonov, V., Evans, A. C., Botteron, K., Almli, C. R., McKinstry, R. C., & Collins, D. L. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.07.033 · Cited by 2,290 · cited 4× · see citing works
“…a well-validated approach to help overcome some of these confounds (Avants et al., 2010; Fonov et al., 2011), and is increasingly adopted in both structural and functional studies of (especially early) development (Eggebrecht et al., 2017; Fonov et al., 2011; Gao et al., 2015a; Scott et al., 2015).”
BackgroundInfluentialPrediction of individual brain maturity using fMRI
Dosenbach, N. U. F., Nardos, B., Cohen, A. L., Fair, D. A., Power, J. D., Church, J. A., Nelson, S. M., Wig, G. S., Vogel, A. C., Lessov-Schlaggar, C. N., et al. (2010) · Science · doi:10.1126/science.1194144 · Cited by 2,183 · cited 3× · see citing works
“…had found that functional connectivity between anatomically proximate ROIs gradually decreased, whereas long-range functional connections, especially anterior-posterior links, gradually increased until adulthood (Dosenbach et al., 2010; Fair et al., 2009; Kelly et al., 2009; Supekar et al., 2009).”
BackgroundSelf-citationThe basics of brain development
Stiles, J., & Jernigan, T. L. (2010) · Neuropsychology Review · doi:10.1007/s11065-010-9148-4 · Cited by 2,009 · cited 3× · see citing works
“…events (e.g. neurogenesis, cell death, myelination, pruning, synaptic plasticity, and glial development) (Innocenti and Price, 2005; Stiles and Jernigan, 2010) and that FC aberrations may point towards the etiological bases of neuropsychiatric disorders (e.g. (Swartz and Monk,…”
BackgroundTime–frequency dynamics of resting-state brain connectivity measured with fMRI
Chang, C., & Glover, G. H. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.12.011 · Cited by 1,808 · cited 1× · see citing works
“Mounting evidence suggests that the functional connectome exhibits temporal instability that allows it to flexibly switch between multiple different configurations within a scanning session (Allen et al., 2014; Chang and Glover, 2010; Kang et al., 2011; Shen et al., 2015).”
BackgroundChurchland, P. S., & Sejnowski, T. J. (1992) · doi:10.7551/mitpress/2010.001.0001 · Cited by 1,757 · cited 1× · see citing works
“The cerebral cortex is both anatomically and functionally organized at many physical scales - starting at the level of single neurons and extending up to functional systems (Churchland and Sejnowski, 1992).”
BackgroundDynamic reconfiguration of human brain networks during learning
Bassett, D. S., Wymbs, N. F., Porter, M. A., Mucha, P. J., Carlson, J. M., & Grafton, S. T. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1018985108 · Cited by 1,705 · cited 2× · see citing works
“The authors contend that these changes potentially support the ability to traverse through more diverse cognitive states in order to accomplish increasingly complex task demands (Bassett et al., 2011; Braun et al., 2015).”
BackgroundTononi, G., Sporns, O., & Edelman, G. M. (1994) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.91.11.5033 · Cited by 1,626 · cited 1× · see citing works
“Similar to the participation coefficient of a given node, one can compute the network's global integrative capacity by taking into account the network modules and the interdependencies between them (de Reus and van den Heuvel, 2014; Tononi et al., 1994).”
BackgroundIntrinsic and task-evoked network architectures of the human brain
Cole, M. W., Bassett, D. S., Power, J. D., Braver, T. S., & Petersen, S. E. (2014) · Neuron · doi:10.1016/j.neuron.2014.05.014 · Cited by 1,564 · see citing works
Functional brain networks develop from a local to distributed organization
Fair, D. A., Cohen, A. L., Power, J. D., Dosenbach, N. U. F., Church, J. A., Miezin, F. M., Schlaggar, B. L., & Petersen, S. E. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000381 · Cited by 1,530 · cited 4× · see citing works
“These trends pointed to coherent changes that involved a dampening of non-specific local spread of activity and strengthening of long-range links, thereby facilitating cognitive development (Bunge and Wright, 2007; Fair et al., 2009; Uddin, 2011; Uddin et al., 2011).”
BackgroundInfluentialSelf-citationTraining induces changes in white-matter architecture
Scholz, J., Klein, M. C., Behrens, T. E. J., & Johansen-Berg, H. (2009) · Nature Neuroscience · doi:10.1038/nn.2412 · Cited by 1,508 · cited 2× · see citing works
“…expression (Richiardi et al., 2015), and synaptic receptor densities (Turk et al., 2016; van den Heuvel et al., 2016b) – properties that, in turn, undergo experience-dependent and activity-dependent modulation over the lifespan (Huttenlocher, 2002; Markham and Greenough, 2004; Scholz et al., 2009).”
BackgroundGeneration and evaluation of a cortical area parcellation from resting-state correlations
Gordon, E. M., Laumann, T. O., Adeyemo, B., Huckins, J. F., Kelley, W. M., & Petersen, S. E. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhu239 · Cited by 1,463 · cited 8× · see citing works
“Functional network analyses that strongly relate to known network organization may therefore find signal homogeneity within parcels to be a useful optimization criterion for choosing a parcellation (e.g. see Gordon et al. (2016) and Glasser et al. (2016a)).”
BackgroundInfluentialYan, C.-G., Cheung, B., Kelly, C., Colcombe, S., Craddock, R. C., Di Martino, A., Li, Q., Zuo, X.-N., Castellanos, F. X., & Milham, M. P. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.03.004 · Cited by 1,461 · cited 2× · see citing works
“In particular, it has been revealed that motion increases non-specific local coupling and decreases long-range coupling in ways that are similar to differences found between children and adults (Fair et al., 2012b; Power et al., 2012; Satterthwaite et al., 2012; Yan et al., 2013).”
BackgroundResultFrequencies contributing to functional connectivity in the cerebral cortex in "resting-state" data.
Cordes, D., Haughton, V. M., Arfanakis, K., Carew, J. D., Turski, P. A., Moritz, C. H., Quigley, M., & Meyerand, M. E. (2001) · PubMed Central · Cited by 1,402 · see citing works
Functional connectivity in single and multislice echoplanar imaging using resting-state fluctuations
Lowe, M. J., Mock, B. J., & Sorenson, J. A. (1998) · NeuroImage · doi:10.1006/nimg.1997.0315 · Cited by 1,394 · cited 2× · see citing works
“(1995), followed soon after by similar findings of bilaterally correlated activity in early visual and early auditory cortex (Cordes et al., 2001; Kiviniemi et al., 2000; Lowe et al., 1998).”
BackgroundThe maturing architecture of the brain's default network
Fair, D. A., Cohen, A. L., Dosenbach, N. U. F., Church, J. A., Miezin, F. M., Barch, D. M., Raichle, M. E., Petersen, S. E., & Schlaggar, B. L. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0800376105 · Cited by 1,314 · cited 2× · see citing works
“…areas (and indeed, connectivity within other cognitive RSNs) continues to strengthen from early childhood throughout development, especially with respect to long-range anterior-posterior links (de Bie et al., 2012; Fair et al., 2008; Sato et al., 2014; Sherman et al., 2014; Supekar et al., 2010).”
BackgroundSelf-citationDie Cytoarchitektonik der Hirnrinde des erwachsenen Menschen
Economo, C. V., & Koskinas, G. N. (1925) · Springer eBooks · Cited by 1,234 · see citing works
Whole-brain anatomical networks: does the choice of nodes matter?
Zalesky, A., Fornito, A., Harding, I. H., Cocchi, L., Yücel, M., Pantelis, C., & Bullmore, E. T. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.12.027 · Cited by 1,169 · cited 1× · see citing works
“Global topological metrics for structural and functional networks show stability across different parcellation schema of similar density, but vary considerably as a function of network size (de Reus and van den Heuvel, 2013; Fornito et al., 2010; Zalesky et al., 2010).”
BackgroundNetwork Centrality in the Human Functional Connectome
Zuo, X., Ehmke, R. C., Mennes, M., Imperati, D., Castellanos, F. X., Sporns, O., & Milham, M. P. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhr269 · Cited by 1,169 · cited 5× · see citing works
“Returning to the MRI literature, there is convergent evidence that the locations of high-strength and high-betweenness hub regions appear to be stable after 5 years of age (Cao et al., 2014; Grayson et al., 2014; Hwang et al., 2013; Wang et al., 2012; Wu et al., 2013; Zuo et al., 2012).”
BackgroundInfluentialA Structural MRI Study of Human Brain Development from Birth to 2 Years
Knickmeyer, R. C., Gouttard, S., Kang, C., Evans, D., Wilber, K., Smith, J. K., Hamer, R. M., Lin, W., Gerig, G., & Gilmore, J. H. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.3479-08.2008 · Cited by 1,151 · cited 2× · see citing works
“2A), doubling in volume during the first year and reaching 80–90% of adult volume by age 3 (Courchesne et al., 2000; Knickmeyer et al., 2008).”
BackgroundSatterthwaite, T. D., Wolf, D. H., Loughead, J., Ruparel, K., Elliott, M. A., Hakonarson, H., Gur, R. C., & Gur, R. E. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.12.063 · Cited by 1,125 · see citing works
Efficiency of Functional Brain Networks and Intellectual Performance
van den Heuvel, M. P., Stam, C. J., Kahn, R. S., & Hulshoff Pol, H. E. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.1443-09.2009 · Cited by 1,078 · see citing works
The Rhesus Monkey Brain in Stereotaxic Coordinates
Paxinos, G., Huang, X., & Toga, A. W. (1999) · Research Online (University of Wollongong) · Cited by 1,070 · see citing works
Network attributes for segregation and integration in the human brain
Sporns, O. (2013) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2012.11.015 · Cited by 1,067 · cited 1× · see citing works
“Rich-club nodes tend to span multiple RSNs, thereby facilitating integration between them (Sporns, 2013; van den Heuvel and Sporns, 2013).”
BackgroundCourchesne, E., Chisum, H. J., Townsend, J., Cowles, A., Covington, J., Egaas, B., Harwood, M., Hinds, S., & Press, G. A. (2000) · Radiology · doi:10.1148/radiology.216.3.r00au37672 · Cited by 1,049 · cited 2× · see citing works
“2A), doubling in volume during the first year and reaching 80–90% of adult volume by age 3 (Courchesne et al., 2000; Knickmeyer et al., 2008).”
BackgroundPrecuneus shares intrinsic functional architecture in humans and monkeys
Margulies, D. S., Vincent, J. L., Kelly, C., Lohmann, G., Uddin, L. Q., Biswal, B. B., Villringer, A., Castellanos, F. X., Milham, M. P., & Petrides, M. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0905314106 · Cited by 965 · see citing works
Recent progress and outstanding issues in motion correction in resting state fMRI
Power, J. D., Schlaggar, B. L., & Petersen, S. E. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.10.044 · Cited by 957 · cited 2× · see citing works
“Moving forward, there is strong consensus about the importance of preventing head motion during acquisition and rigorously quantifying motion effects in study data (Goto et al., 2016; Power et al., 2015; Siegel et al., 2016).”
BackgroundControllability of structural brain networks
Gu, S., Pasqualetti, F., Cieslak, M., Telesford, Q. K., Yu, A. B., Kahn, A. E., Medaglia, J. D., Vettel, J. M., Miller, M. B., Grafton, S. T., et al. (2015) · Nature Communications · doi:10.1038/ncomms9414 · Cited by 912 · see citing works
Functional system and areal organization of a highly sampled individual human brain
Laumann, T. O., Gordon, E. M., Adeyemo, B., Snyder, A. Z., Joo, S. J., Chen, M.-Y., Gilmore, A. W., McDermott, K. B., Nelson, S. M., Dosenbach, N. U. F., et al. (2015) · Neuron · doi:10.1016/j.neuron.2015.06.037 · Cited by 911 · cited 2× · see citing works
“Cutting-edge work in resting-state fMRI acquisition and network analysis suggests that individual brains, even among typical subjects, are distinguishable via their functional connectomes (Finn et al., 2015; Laumann et al., 2015; Miranda-Dominguez et al., 2014b).”
BackgroundMethodOn spurious and real fluctuations of dynamic functional connectivity during rest
Leonardi, N., & Van De Ville, D. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.09.007 · Cited by 828 · see citing works
Betzel, R. F., Byrge, L., He, Y., Goñi, J., Zuo, X.-N., & Sporns, O. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.07.067 · Cited by 807 · cited 2× · see citing works
“Another study found that age-related changes in FC disproportionately impacts polysynaptic connections (Betzel et al., 2014), although this study was performed across the lifespan and may reflect an effect of aging.”
BackgroundDevelopment of large-scale functional brain networks in children
Supekar, K., Musen, M., & Menon, V. (2009) · PLoS Biology · doi:10.1371/journal.pbio.1000157 · Cited by 807 · cited 3× · see citing works
“…had found that functional connectivity between anatomically proximate ROIs gradually decreased, whereas long-range functional connections, especially anterior-posterior links, gradually increased until adulthood (Dosenbach et al., 2010; Fair et al., 2009; Kelly et al., 2009; Supekar et al., 2009).”
BackgroundDynamic reconfiguration of frontal brain networks during executive cognition in humans
Braun, U., Schäfer, A., Walter, H., Erk, S., Romanczuk-Seiferth, N., Haddad, L., Schweiger, J. I., Grimm, O., Heinz, A., Tost, H., et al. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1422487112 · Cited by 791 · cited 2× · see citing works
“The authors contend that these changes potentially support the ability to traverse through more diverse cognitive states in order to accomplish increasingly complex task demands (Bassett et al., 2011; Braun et al., 2015).”
BackgroundLongitudinal Analysis of Neural Network Development in Preterm Infants
Smyser, C. D., Inder, T. E., Shimony, J. S., Hill, J. E., Degnan, A. J., Snyder, A. Z., & Neil, J. J. (2010) · Cerebral Cortex · doi:10.1093/cercor/bhq035 · Cited by 791 · cited 3× · see citing works
“…componentbased approaches demonstrate the existence of robust, bilateral segregated networks for somatomotor, primary auditory, primary visual, and extrastriate visual cortex (Fransson et al., 2007; Gao et al., 2015a; Kiviniemi et al., 2000; Lin et al., 2008; Liu et al., 2008; Smyser et al., 2010).”
BackgroundLearning sculpts the spontaneous activity of the resting human brain
Lewis, C. M., Baldassarre, A., Committeri, G., Romani, G. L., & Corbetta, M. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0902455106 · Cited by 777 · cited 2× · see citing works
“, 2009) and are associated with task-relevant behavioral performance (Cole et al., 2012; Lewis et al., 2009).”
BackgroundThe development of human functional brain networks
Power, J. D., Fair, D. A., Schlaggar, B. L., & Petersen, S. E. (2010) · Neuron · doi:10.1016/j.neuron.2010.08.017 · Cited by 751 · see citing works
Self-citationZuo, X.-N., Kelly, C., Adelstein, J. S., Klein, D. F., Castellanos, F. X., & Milham, M. P. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.10.080 · Cited by 744 · cited 1× · see citing works
“Multiple studies have found evidence for limited test-retest reliability using a multitude of conventional rs-fcMRI network characteristics and analytic approaches (Braun et al., 2012; Wang et al., 2011; Wisner et al., 2013; Zuo et al., 2010; Zuo and Xing, 2014).”
BackgroundContributions and challenges for network models in cognitive neuroscience
Sporns, O. (2014) · Nature Neuroscience · doi:10.1038/nn.3690 · Cited by 743 · cited 1× · see citing works
“The network's behavior can thus be modeled as a set of properties that emerge from the network's unique global structure and local features (Sporns, 2014).”
BackgroundCortical folding patterns and predicting cytoarchitecture
Fischl, B., Rajendran, N., Busa, E., Augustinack, J., Hinds, O., Yeo, B. T. T., Mohlberg, H., Amunts, K., & Zilles, K. (2008) · Cerebral Cortex · doi:10.1093/cercor/bhm225 · Cited by 737 · cited 1× · see citing works
“On top of these issues, functional areal boundaries (see Parcellation Choice) of heteromodal association areas are variable with respect to sulcal and gyral anatomy (Fischl et al., 2008).”
BackgroundThomas, C., Ye, F. Q., Irfanoglu, M. O., Modi, P., Saleem, K. S., Leopold, D. A., & Pierpaoli, C. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1405672111 · Cited by 725 · cited 4× · see citing works
“Unfortunately, follow-up work on this topic in humans has been relatively scant, and this work was prior to new information regarding tractography artifacts (Calabrese et al., 2015; Donahue et al., 2016; Reveley et al., 2015; Thomas et al., 2014), and prior to systematic motion artifacts being demonstrated in diffusio…”
BackgroundMethodInfluentialEvidence for hubs in human functional brain networks
Power, J. D., Schlaggar, B. L., Lessov-Schlaggar, C. N., & Petersen, S. E. (2013) · Neuron · doi:10.1016/j.neuron.2013.07.035 · Cited by 716 · see citing works
White matter maturation reshapes structural connectivity in the late developing human brain
Hagmann, P., Sporns, O., Madan, N., Cammoun, L., Pienaar, R., Wedeen, V. J., Meuli, R., Thiran, J.-P., & Grant, P. E. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1009073107 · Cited by 700 · cited 2× · see citing works
“There is an abundance of research demonstrating a correlation between DWI-tractography connection weights and FC in adults (Hagmann et al., 2008; Hagmann et al., 2010; Honey et al., 2009).”
BackgroundResting-state networks in the infant brain
Fransson, P., Skiöld, B., Horsch, S., Nordell, A., Blennow, M., Lagercrantz, H., & Åden, U. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0704380104 · Cited by 696 · cited 4× · see citing works
“…componentbased approaches demonstrate the existence of robust, bilateral segregated networks for somatomotor, primary auditory, primary visual, and extrastriate visual cortex (Fransson et al., 2007; Gao et al., 2015a; Kiviniemi et al., 2000; Lin et al., 2008; Liu et al., 2008; Smyser et al., 2010).”
BackgroundInfluentialDecoupling of the brain's default mode network during deep sleep
Horovitz, S. G., Braun, A. R., Carr, W. S., Picchioni, D., Balkin, T. J., Fukunaga, M., & Duyn, J. H. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0901435106 · Cited by 685 · cited 2× · see citing works
“…global functional network topology in conscious versus unconscious state in adults (Spoormaker et al., 2010), but key differences have been found in corticocortical (Heine et al., 2012; Horovitz et al., 2009; Spoormaker et al., 2010) and thalamocortical (Spoormaker et al., 2010) connectivity.”
BackgroundPatterning and plasticity of the cerebral cortex
Sur, M., & Rubenstein, J. L. R. (2005) · Science · doi:10.1126/science.1112070 · Cited by 677 · cited 2× · see citing works
“These areal boundaries appear very early in development (Kostovic et al., 1995) and each area is thought to make a distinct contribution to information processing (Cohen et al., 2008; Felleman and Van Essen, 1991; Fuster, 2002; O'Leary and Nakagawa, 2002; Sur and Rubenstein, 2005).”
BackgroundZuo, X., & Xing, X.-X. (2014) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2014.05.009 · Cited by 657 · cited 1× · see citing works
“Multiple studies have found evidence for limited test-retest reliability using a multitude of conventional rs-fcMRI network characteristics and analytic approaches (Braun et al., 2012; Wang et al., 2011; Wisner et al., 2013; Zuo et al., 2010; Zuo and Xing, 2014).”
BackgroundDisentangling the heterogeneity of autism spectrum disorder through genetic findings
Jeste, S. S., & Geschwind, D. H. (2014) · Nature Reviews Neurology · doi:10.1038/nrneurol.2013.278 · Cited by 644 · cited 6× · see citing works
“DSG was supported by an Autism Speaks Dennis Weatherstone Predoctoral Fellowship (#9591).”
BackgroundInfluentialMSM: a new flexible framework for Multimodal Surface Matching
Robinson, E. C., Jbabdi, S., Glasser, M. F., Andersson, J., Burgess, G. C., Harms, M. P., Smith, S. M., Van Essen, D. C., & Jenkinson, M. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.05.069 · Cited by 640 · cited 1× · see citing works
“New multimodal approaches that also anchor surface-based registrations to other structural or functional characteristics of an individual are likely to improve subject to subject registrations, and hence reduce intersubject variability, even more (e.g. (Glasser et al., 2016b; Robinson et al., 2014).”
BackgroundThe optimal template effect in hippocampus studies of diseased populations
Avants, B. B., Yushkevich, P., Pluta, J., Minkoff, D., Korczykowski, M., Detre, J., & Gee, J. C. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.09.062 · Cited by 640 · cited 2× · see citing works
“…age-specific and study-specific template brain images for image registration is a well-validated approach to help overcome some of these confounds (Avants et al., 2010; Fonov et al., 2011), and is increasingly adopted in both structural and functional studies of (especially early) development…”
BackgroundCorrelated gene expression supports synchronous activity in brain networks
Richiardi, J., Altmann, A., Milazzo, A.-C., Chang, C., Chakravarty, M. M., Banaschewski, T., Barker, G. J., Bokde, A. L. W., Bromberg, U., Büchel, C., et al. (2015) · Science · doi:10.1126/science.1255905 · Cited by 625 · see citing works
Global Connectivity of Prefrontal Cortex Predicts Cognitive Control and Intelligence
Cole, M. W., Yarkoni, T., Repovs, G., Anticevic, A., & Braver, T. S. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.0536-12.2012 · Cited by 613 · cited 2× · see citing works
“, 2009) and are associated with task-relevant behavioral performance (Cole et al., 2012; Lewis et al., 2009).”
BackgroundGao, W., Zhu, H., Giovanello, K. S., Smith, J. K., Shen, D., Gilmore, J. H., & Lin, W. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0811221106 · Cited by 601 · cited 2× · see citing works
“In neonates and very young infants, these individual compartments demonstrate locally correlated activity, but fail to synchronize into a coherent network (Damaraju et al., 2014; Fransson et al., 2007; Gao et al., 2009; Smyser et al., 2010; Wylie et al., 2014).”
BackgroundBrain Anatomical Network and Intelligence
Li, Y., Liu, Y., Li, J., Qin, W., Li, K., Yu, C., & Jiang, T. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000395 · Cited by 597 · cited 2× · see citing works
“Greater global efficiency in structural and functional networks has been linked to higher IQ, attentional capacity, and working memory in healthy young adults (Cohen and D'Esposito, 2016; Kitzbichler et al., 2011; Li et al., 2009; Stanley et al., 2015; van den Heuvel et al., 2009), supporting the notion that it confer…”
BackgroundDefining functional areas in individual human brains using resting functional connectivity MRI
Cohen, A. L., Fair, D. A., Dosenbach, N. U. F., Miezin, F. M., Dierker, D., Van Essen, D. C., Schlaggar, B. L., & Petersen, S. E. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.01.066 · Cited by 582 · cited 2× · see citing works
“These areal boundaries appear very early in development (Kostovic et al., 1995) and each area is thought to make a distinct contribution to information processing (Cohen et al., 2008; Felleman and Van Essen, 1991; Fuster, 2002; O'Leary and Nakagawa, 2002; Sur and Rubenstein, 2005).”
BackgroundSelf-citationZhang, Z., Liao, W., Chen, H., Mantini, D., Ding, J.-R., Xu, Q., Wang, Z., Yuan, C., Chen, G., Jiao, Q., et al. (2011) · Brain · doi:10.1093/brain/awr223 · Cited by 580 · see citing works
Resting-brain functional connectivity predicted by analytic measures of network communication
Goñi, J., van den Heuvel, M. P., Avena‐Koenigsberger, A., de Mendizábal, N. V., Betzel, R. F., Griffa, A., Hagmann, P., Corominas‐Murtra, B., Thiran, J., & Sporns, O. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1315529111 · Cited by 579 · cited 2× · see citing works
“, 2015), or sparser analytic predictions of FC using graph metrics of mutual communication (Goni et al., 2014; Grayson et al., 2016) (although, both approaches appear to be comparably effective; see Fig.”
BackgroundDevelopment of Anterior Cingulate Functional Connectivity from Late Childhood to Early Adulthood
Kelly, A. M. C., Di Martino, A., Uddin, L. Q., Shehzad, Z., Gee, D. G., Reiss, P. T., Margulies, D. S., Castellanos, F. X., & Milham, M. P. (2009) · Cerebral Cortex · doi:10.1093/cercor/bhn117 · Cited by 572 · cited 2× · see citing works
“…had found that functional connectivity between anatomically proximate ROIs gradually decreased, whereas long-range functional connections, especially anterior-posterior links, gradually increased until adulthood (Dosenbach et al., 2010; Fair et al., 2009; Kelly et al., 2009; Supekar et al., 2009).”
BackgroundModeling the impact of lesions in the human brain
Alstott, J., Breakspear, M., Hagmann, P., Cammoun, L., & Sporns, O. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000408 · Cited by 561 · cited 1× · see citing works
“As an example, simulation experiments using structure-function models have predicted that even purely focal and transient perturbations in activity should result in diffuse network reorganization that affects distant brain systems (Alstott et al., 2009; Honey and Sporns, 2008; Misic et al., 2015).”
MethodBrain networks and cognitive architectures
Petersen, S. E., & Sporns, O. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.027 · Cited by 553 · see citing works
The functional architecture of the infant brain as revealed by resting-state fMRI
Fransson, P., Åden, U., Blennow, M., & Lagercrantz, H. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhq071 · Cited by 542 · cited 6× · see citing works
“…and betweenness hubs in adulthood are largely located within the default mode, attentional, sensorimotor, and visual areas (Cao et al., 2014; Fransson et al., 2011; Grayson et al., 2014; Hwang et al., 2013), whereas neonatal hubs primarily involve early sensorimotor, visual, and limbic…”
BackgroundInfluentialBrain hyperconnectivity in children with autism and its links to social deficits
Supekar, K., Uddin, L. Q., Khouzam, A., Phillips, J., Gaillard, W. D., Kenworthy, L. E., Yerys, B. E., Vaidya, C. J., & Menon, V. (2013) · Cell Reports · doi:10.1016/j.celrep.2013.10.001 · Cited by 538 · cited 6× · see citing works
“DSG was supported by an Autism Speaks Dennis Weatherstone Predoctoral Fellowship (#9591).”
BackgroundInfluentialFunctional connectivity dynamics: modeling the switching behavior of the resting state
Hansen, E. C. A., Battaglia, D., Spiegler, A., Deco, G., & Jirsa, V. K. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.11.001 · Cited by 528 · cited 2× · see citing works
“Models can involve highly parameterized simulations of regional activity (Hansen et al., 2015; Messe et al., 2014; Sanz-Leon et al., 2015), or sparser analytic predictions of FC using graph metrics of mutual communication (Goni et al., 2014; Grayson et al., 2016) (although, both approaches appear…”
BackgroundSupekar, K., Uddin, L. Q., Prater, K. E., Amin, H., Greicius, M. D., & Menon, V. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.04.009 · Cited by 524 · cited 2× · see citing works
“…areas (and indeed, connectivity within other cognitive RSNs) continues to strengthen from early childhood throughout development, especially with respect to long-range anterior-posterior links (de Bie et al., 2012; Fair et al., 2008; Sato et al., 2014; Sherman et al., 2014; Supekar et al., 2010).”
BackgroundUddin, L. Q., Supekar, K. S., Ryali, S., & Menon, V. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.4465-11.2011 · Cited by 520 · cited 2× · see citing works
“These trends pointed to coherent changes that involved a dampening of non-specific local spread of activity and strengthening of long-range links, thereby facilitating cognitive development (Bunge and Wright, 2007; Fair et al., 2009; Uddin, 2011; Uddin et al., 2011).”
BackgroundExuberance in the development of cortical networks
Innocenti, G. M., & Price, D. J. (2005) · Nature Reviews Neuroscience · doi:10.1038/nrn1790 · Cited by 512 · cited 3× · see citing works
“This same time period is marked by rapid and widespread cortical synaptogenesis, followed by a protracted period of synapse elimination and cell loss which carries into adulthood (Huttenlocher, 2002; Innocenti and Price, 2005).”
BackgroundMapping sources of correlation in resting state FMRI, with artifact detection and removal
Jo, H. J., Saad, Z. S., Simmons, W. K., Milbury, L. A., & Cox, R. W. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.04.246 · Cited by 509 · cited 2× · see citing works
“There is ongoing debate regarding the adequacy of these techniques (Jo et al., 2010; Power et al., 2016), and more work may be warranted to determine optimal ways to account for age-related physiological confounds.”
BackgroundSpurious group differences due to head motion in a diffusion MRI study
Yendiki, A., Koldewyn, K., Kakunoori, S., Kanwisher, N., & Fischl, B. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.11.027 · Cited by 508 · cited 4× · see citing works
“Strong artifacts due to motion, in addition to their relevance for fMRI, have been noted in diffusion weighted imaging (Roalf et al., 2016; Yendiki et al., 2014) and cortical thickness measurements (Reuter et al.”
BackgroundInfluentialEigenvector Centrality Mapping for Analyzing Connectivity Patterns in fMRI Data of the Human Brain
Lohmann, G., Margulies, D. S., Horstmann, A., Pleger, B., Lepsien, J., Goldhahn, D., Schloegl, H., Stümvoll, M., Villringer, A., & Turner, R. (2010) · PLoS ONE · doi:10.1371/journal.pone.0010232 · Cited by 505 · cited 2× · see citing works
“By far, strength and betweenness have been the most popular hub metrics within neuroimaging, although others such as eigenvector centrality (Lohmann et al., 2010; Zuo et al., 2012) and node communicability (de Reus and van den Heuvel, 2014; Mantzaris et al., 2013) have seen useful application as…”
BackgroundFair, D. A., Bathula, D., Nikolas, M. A., & Nigg, J. T. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1115365109 · Cited by 464 · cited 8× · see citing works
“…consistently implicated in Schizophrenia (Baker et al., 2014; Khadka et al., 2013; Satterthwaite et al., 2015), ADHD (Castellanos and Aoki, 2016; Fair et al., 2012b), and Autism (Kessler et al., 2016; Moseley et al., 2015; Supekar et al., 2013) – though a thorough examination of this literature…”
BackgroundResultInfluentialSelf-citationUnderstanding brain networks and brain organization
Pessoa, L. (2014) · Physics of Life Reviews · doi:10.1016/j.plrev.2014.03.005 · Cited by 464 · cited 1× · see citing works
“The network's behavior can thus be modeled as a set of properties that emerge from the network's unique global structure and local features (Sporns, 2014).”
BackgroundFair, D. A., Nigg, J. T., Iyer, S., Bathula, D., Mills, K. L., Dosenbach, N. U. F., Schlaggar, B. L., Mennes, M., Gutman, D., Bangaru, S., et al. (2013) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2012.00080 · Cited by 463 · cited 8× · see citing works
“…consistently implicated in Schizophrenia (Baker et al., 2014; Khadka et al., 2013; Satterthwaite et al., 2015), ADHD (Castellanos and Aoki, 2016; Fair et al., 2012b), and Autism (Kessler et al., 2016; Moseley et al., 2015; Supekar et al., 2013) – though a thorough examination of this literature…”
BackgroundResultInfluentialSelf-citationHead motion during MRI acquisition reduces gray matter volume and thickness estimates
Reuter, M., Tisdall, M. D., Qureshi, A., Buckner, R. L., van der Kouwe, A. J. W., & Fischl, B. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.12.006 · Cited by 457 · cited 2× · see citing works
“, 2014) and cortical thickness measurements (Reuter et al., 2015; Savalia et al., 2017).”
BackgroundLongitudinal Development of Cortical and Subcortical Gray Matter from Birth to 2 Years
Gilmore, J. H., Shi, F., Woolson, S. L., Knickmeyer, R. C., Short, S. J., Lin, W., Zhu, H., Hamer, R. M., Styner, M., & Shen, D. (2012) · Cerebral Cortex · doi:10.1093/cercor/bhr327 · Cited by 456 · see citing works
A Combined MRI and Histology Atlas of the Rhesus Monkey Brain: In Stereotaxic Coordinates
Saleem, K. S., & Logothetis, N. K. (2012) · Max Planck Digital Library · Cited by 446 · see citing works
Topological organization of the human brain functional connectome across the lifespan
Cao, M., Wang, J.-H., Dai, Z.-J., Cao, X.-Y., Jiang, L.-L., Fan, F.-M., Song, X.-W., Xia, M.-R., Shu, N., Dong, Q., et al. (2014) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2013.11.004 · Cited by 440 · see citing works
Network scaling effects in graph analytic studies of human resting-state fMRI data
Fornito, A. (2010) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2010.00022 · Cited by 439 · see citing works
Experience-driven brain plasticity: Beyond the synapse
MARKHAM, J. A., & GREENOUGH, W. T. (2004) · Neuron Glia Biology · doi:10.1017/s1740925x05000219 · Cited by 437 · cited 2× · see citing works
“…expression (Richiardi et al., 2015), and synaptic receptor densities (Turk et al., 2016; van den Heuvel et al., 2016b) – properties that, in turn, undergo experience-dependent and activity-dependent modulation over the lifespan (Huttenlocher, 2002; Markham and Greenough, 2004; Scholz et al., 2009).”
BackgroundIncreased Brain Signal Variability Accompanies Lower Behavioral Variability in Development
McIntosh, A. R., Kovacevic, N., & Itier, R. J. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000106 · Cited by 431 · cited 2× · see citing works
“Over development, rs-fcMRI networks show increased within-subject variability (Hutchison and Morton, 2015; Marusak et al., 2016; Qin et al., 2015), consistent with EEG studies showing that signal complexity increases over development (McIntosh et al., 2008; Vakorin et al., 2011).”
BackgroundCognitive effort drives workspace configuration of human brain functional networks
Kitzbichler, M. G., Henson, R. N. A., Smith, M. L., Nathan, P. J., & Bullmore, E. T. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.0440-11.2011 · Cited by 427 · cited 1× · see citing works
“…and functional networks has been linked to higher IQ, attentional capacity, and working memory in healthy young adults (Cohen and D'Esposito, 2016; Kitzbichler et al., 2011; Li et al., 2009; Stanley et al., 2015; van den Heuvel et al., 2009), supporting the notion that it confers advantages for…”
BackgroundBraun, U., Plichta, M. M., Esslinger, C., Sauer, C., Haddad, L., Grimm, O., Mier, D., Mohnke, S., Heinz, A., Erk, S., et al. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.08.044 · Cited by 424 · cited 1× · see citing works
“Multiple studies have found evidence for limited test-retest reliability using a multitude of conventional rs-fcMRI network characteristics and analytic approaches (Braun et al., 2012; Wang et al., 2011; Wisner et al., 2013; Zuo et al., 2010; Zuo and Xing, 2014).”
BackgroundNeural Plasticity: The Effects of Environment on the Development of the Cerebral Cortex
Huttenlocher, P. R. (2002) · doi:10.4159/9780674038936 · Cited by 421 · see citing works
Imaging human connectomes at the macroscale
Craddock, R. C., Jbabdi, S., Yan, C.-G., Vogelstein, J. T., Castellanos, F. X., Di Martino, A., Kelly, C., Heberlein, K., Colcombe, S., & Milham, M. P. (2013) · Nature Methods · doi:10.1038/nmeth.2482 · Cited by 419 · cited 1× · see citing works
“There is currently no consensus regarding an optimal set of criteria for defining an areal parcellation (Craddock et al., 2013; Glasser et al., 2016a; Gordon et al., 2016), and even less known about the stability of these parcellations at younger ages.”
BackgroundReveley, C., Seth, A. K., Pierpaoli, C., Silva, A. C., Yu, D., Saunders, R. C., Leopold, D. A., & Ye, F. Q. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1418198112 · Cited by 417 · cited 2× · see citing works
“For example, structure-function modeling using MRI data suffers from a number of inherent limitations in DWI-tractography that have not been overcome by state-of-the-art acquisition and processing approaches (Calabrese et al., 2015; Donahue et al., 2016; Reveley et al., 2015; Thomas et al., 2014).”
BackgroundThe idiosyncratic brain: distortion of spontaneous connectivity patterns in autism spectrum disorder
Hahamy, A., Behrmann, M., & Malach, R. (2015) · Nature Neuroscience · doi:10.1038/nn.3919 · Cited by 416 · cited 1× · see citing works
“Indeed, recent work suggests that Autism Spectrum Disorder is characterized by increased subject-to-subject variability relative to the general population (Hahamy et al., 2015).”
BackgroundWang, J.-H., Zuo, X.-N., Gohel, S., Milham, M. P., Biswal, B. B., & He, Y. (2011) · PLoS ONE · doi:10.1371/journal.pone.0021976 · Cited by 416 · cited 1× · see citing works
“Multiple studies have found evidence for limited test-retest reliability using a multitude of conventional rs-fcMRI network characteristics and analytic approaches (Braun et al., 2012; Wang et al., 2011; Wisner et al., 2013; Zuo et al., 2010; Zuo and Xing, 2014).”
BackgroundAn anatomical substrate for integration among functional networks in human cortex
van den Heuvel, M. P., & Sporns, O. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.2128-13.2013 · Cited by 404 · cited 1× · see citing works
“Rich-club nodes tend to span multiple RSNs, thereby facilitating integration between them (Sporns, 2013; van den Heuvel and Sporns, 2013).”
BackgroundBrain maturation in adolescence: concurrent changes in neuroanatomy and neurophysiology
Whitford, T. J., Rennie, C. J., Grieve, S. M., Clark, C. R., Gordon, E., & Williams, L. M. (2007) · Human Brain Mapping · doi:10.1002/hbm.20273 · Cited by 391 · cited 8× · see citing works
“There is also a progressive shift in peak amplitude towards higher frequency activity (Miskovic et al., 2015; Rodriguez-Martinez et al., 2015; Smit et al., 2012; Whitford et al., 2007).”
BackgroundInfluentialThe Neonatal Connectome During Preterm Brain Development
van den Heuvel, M. P., Kersbergen, K. J., de Reus, M. A., Keunen, K., Kahn, R. S., Groenendaal, F., de Vries, L. S., & Benders, M. J. N. L. (2015) · Cerebral Cortex · doi:10.1093/cercor/bhu095 · Cited by 386 · cited 5× · see citing works
“In neonates, two independent rs-fcMRI studies found evidence for modules comprised largely of anatomically proximate areas (De Asis-Cruz et al., 2015; van den Heuvel et al., 2015b).”
BackgroundResultInfluentialNeurodevelopmental changes in working memory and cognitive control
Bunge, S. A., & Wright, S. B. (2007) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2007.02.005 · Cited by 381 · cited 2× · see citing works
“These trends pointed to coherent changes that involved a dampening of non-specific local spread of activity and strengthening of long-range links, thereby facilitating cognitive development (Bunge and Wright, 2007; Fair et al., 2009; Uddin, 2011; Uddin et al., 2011).”
BackgroundGao, W., Alcauter, S., Elton, A., Hernandez-Castillo, C. R., Smith, J. K., Ramirez, J., & Lin, W. (2015) · Cerebral Cortex · doi:10.1093/cercor/bhu088 · Cited by 380 · cited 6× · see citing works
“…componentbased approaches demonstrate the existence of robust, bilateral segregated networks for somatomotor, primary auditory, primary visual, and extrastriate visual cortex (Fransson et al., 2007; Gao et al., 2015a; Kiviniemi et al., 2000; Lin et al., 2008; Liu et al., 2008; Smyser et al., 2010).”
BackgroundInfluentialDynamic Development of Regional Cortical Thickness and Surface Area in Early Childhood
Lyall, A. E., Shi, F., Geng, X., Woolson, S., Li, G., Wang, L., Hamer, R. M., Shen, D., & Gilmore, J. H. (2015) · Cerebral Cortex · doi:10.1093/cercor/bhu027 · Cited by 376 · cited 2× · see citing works
“These trends are consistent with the presence of basic somatosensory and visual functions at birth, and help contextualize findings that primary sensory regions are generally the first cortical areas to reach plateaus or peaks in growth (Geng et al., 2016; Gilmore et al., 2012; Lyall et al., 2015; Scott et al., 2015).”
BackgroundRich-club organization of the newborn human brain
Ball, G., Aljabar, P., Zebari, S., Tusor, N., Arichi, T., Merchant, N., Robinson, E. C., Ogundipe, E., Rueckert, D., Edwards, A. D., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1324118111 · Cited by 360 · cited 3× · see citing works
“These findings suggest that the development of a small-world architecture, as well as the capacity for globally efficient communication and integration, largely occurs during the first year of life and prenatally, a finding that is supported by multimodal structural and functional network analysis in preterm infants (…”
BackgroundResultMathematical framework for large-scale brain network modeling in The Virtual Brain
Sanz-Leon, P., Knock, S. A., Spiegler, A., & Jirsa, V. K. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.01.002 · Cited by 356 · cited 3× · see citing works
“Given that macroscale FC is modulated by both interregional connectivity strength as well as local population dynamics (Sanz-Leon et al., 2015), alterations in SC-FC coupling could potentially point to important shifts in the underlying drivers of various network phenomena.”
BackgroundDevelopment of human brain cortical network architecture during infancy
Gao, W., Alcauter, S., Smith, J. K., Gilmore, J. H., & Lin, W. (2015) · Brain Structure and Function · doi:10.1007/s00429-014-0710-3 · Cited by 356 · cited 6× · see citing works
“…componentbased approaches demonstrate the existence of robust, bilateral segregated networks for somatomotor, primary auditory, primary visual, and extrastriate visual cortex (Fransson et al., 2007; Gao et al., 2015a; Kiviniemi et al., 2000; Lin et al., 2008; Liu et al., 2008; Smyser et al., 2010).”
BackgroundInfluentialDynamical consequences of lesions in cortical networks
Honey, C. J., & Sporns, O. (2008) · Human Brain Mapping · doi:10.1002/hbm.20579 · Cited by 353 · cited 1× · see citing works
“As an example, simulation experiments using structure-function models have predicted that even purely focal and transient perturbations in activity should result in diffuse network reorganization that affects distant brain systems (Alstott et al., 2009; Honey and Sporns, 2008; Misic et al., 2015).”
MethodEEG correlates of time-varying BOLD functional connectivity
Chang, C. E., Liu, Z., Chen, M. C., Liu, X., & Duyn, J. H. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.01.049 · Cited by 344 · cited 2× · see citing works
“These data agree with notions that temporal variability in very low frequency correlations is an emergent, hidden property of higher frequency power spectra (Chang et al., 2013; Tagliazucchi et al., 2012), which is known to change continuously throughout development (Miskovic et al.”
BackgroundNoninvasive Functional and Structural Connectivity Mapping of the Human Thalamocortical System
Zhang, D., Snyder, A. Z., Shimony, J. S., Fox, M., & Raichle, M. E. (2009) · Cerebral Cortex · doi:10.1093/cercor/bhp182 · Cited by 344 · cited 1× · see citing works
“Several groups, however, are finding ways to utilize today's non-invasive imaging tools to bring us closer to realizing these goals (Behrens et al., 2003; Glasser et al., 2016a; Gordon et al., 2016; Wig et al., 2014a, 2014b; Zhang et al., 2010).”
BackgroundCooperative and competitive spreading dynamics on the human connectome
Mišić, B., Betzel, R. F., Nematzadeh, A., Goñi, J., Griffa, A., Hagmann, P., Flammini, A., Ahn, Y.-Y., & Sporns, O. (2015) · Neuron · doi:10.1016/j.neuron.2015.05.035 · Cited by 342 · cited 6× · see citing works
“Even the best-performing SC-FC models generally account for less than 50% of the variance in FC across the brain in both humans and non-human primates (Grayson et al., 2016; Messe et al., 2014; Misic et al., 2015).”
BackgroundMethodInfluentialEmergence of system roles in normative neurodevelopment
Gu, S., Satterthwaite, T. D., Medaglia, J. D., Yang, M., Gur, R. E., Gur, R. C., & Bassett, D. S. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1502829112 · Cited by 338 · cited 5× · see citing works
“Despite this “adult like” level of organization, refinements within and between systems do appear to occur over time, although details to this end are still being worked out (Fair et al., 2012b; Gu et al., 2015b; Marek et al., 2015).”
BackgroundInfluentialThe contribution of network organization and integration to the development of cognitive control
Marek, S., Hwang, K., Foran, W., Hallquist, M. N., & Luna, B. (2015) · PLOS Biology · doi:10.1371/journal.pbio.1002328 · Cited by 337 · see citing works
Sherman, L. E., Rudie, J. D., Pfeifer, J. H., Masten, C. L., McNealy, K., & Dapretto, M. (2014) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2014.08.002 · Cited by 325 · see citing works
Brain activity at rest: a multiscale hierarchical functional organization
Doucet, G., Naveau, M., Petit, L., Delcroix, N., Zago, L., Crivello, F., Jobard, G., Tzourio-Mazoyer, N., Mazoyer, B., Mellet, E., et al. (2011) · Journal of Neurophysiology · doi:10.1152/jn.00895.2010 · Cited by 319 · cited 4× · see citing works
“At finer resolutions, several other modules can be identified (Doucet et al., 2011; Gordon et al., 2016; Power et al., 2011; Yeo et al., 2011), including hierarchical visual subdivisions, topographical somatomotor subdivisions, an auditory module, a limbic module, a ventral attention module, and other smaller subdivis…”
BackgroundInfluentialDynamic BOLD functional connectivity in humans and its electrophysiological correlates
Tagliazucchi, E., von Wegner, F., Morzelewski, A., Brodbeck, V., & Laufs, H. (2012) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2012.00339 · Cited by 285 · cited 2× · see citing works
“These data agree with notions that temporal variability in very low frequency correlations is an emergent, hidden property of higher frequency power spectra (Chang et al., 2013; Tagliazucchi et al., 2012), which is known to change continuously throughout development (Miskovic et al.”
BackgroundThe parcellation-based connectome: limitations and extensions
de Reus, M. A., & van den Heuvel, M. P. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.03.053 · Cited by 282 · see citing works
O’Leary, D. D. M., & Nakagawa, Y. (2002) · Current Opinion in Neurobiology · doi:10.1016/s0959-4388(02)00285-4 · Cited by 277 · cited 2× · see citing works
“These areal boundaries appear very early in development (Kostovic et al., 1995) and each area is thought to make a distinct contribution to information processing (Cohen et al., 2008; Felleman and Van Essen, 1991; Fuster, 2002; O'Leary and Nakagawa, 2002; Sur and Rubenstein, 2005).”
BackgroundDevelopment of a large-scale functional brain network during human non-rapid eye movement sleep
Spoormaker, V. I., Schröter, M. S., Gleiser, P. M., Andrade, K. C., Dresler, M., Wehrle, R., Sämann, P. G., & Czisch, M. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.2015-10.2010 · Cited by 273 · cited 6× · see citing works
“, 2010) and thalamocortical (Spoormaker et al., 2010) connectivity.”
BackgroundInfluentialEEG sleep slow-wave activity as a mirror of cortical maturation
Buchmann, A., Ringli, M., Kurth, S., Schaerer, M., Geiger, A., Jenni, O. G., & Huber, R. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhq129 · Cited by 273 · cited 4× · see citing works
“These coincident trajectories have provided key support for the hypothesis that developmental changes in baseline electrophysiological signatures may primarily be subserved by reduction of neuropil and progressive synapse elimination (Buchmann et al., 2011; Smit et al., 2012; Whitford et al., 2007).”
BackgroundInfluentialTemporal and spatial evolution of brain network topology during the first two years of life
Gao, W., Gilmore, J. H., Giovanello, K. S., Smith, J. K., Shen, D., Zhu, H., & Lin, W. (2011) · PLoS ONE · doi:10.1371/journal.pone.0025278 · Cited by 272 · cited 7× · see citing works
“The first two years of life reflect a gradual decrease in the hubness of sensorimotor areas and increased involvement of various association cortical areas, especially the medial frontal and parietal portions of the default mode (Gao et al., 2011).”
BackgroundInfluentialResting State Networks and Consciousness
Heine, L., Soddu, A., Gómez, F., Vanhaudenhuyse, A., Tshibanda, L., Thonnard, M., Charland-Verville, V., Kirsch, M., Laureys, S., & Demertzi, A. (2012) · Frontiers in Psychology · doi:10.3389/fpsyg.2012.00295 · Cited by 272 · cited 2× · see citing works
“…global functional network topology in conscious versus unconscious state in adults (Spoormaker et al., 2010), but key differences have been found in corticocortical (Heine et al., 2012; Horovitz et al., 2009; Spoormaker et al., 2010) and thalamocortical (Spoormaker et al., 2010) connectivity.”
BackgroundNeural Plasticity: The Effects of Environment on the Development of the Cerebral Cortex
Huttenlocher, P. R. (2002) · Cited by 269 · see citing works
The effects of SIFT on the reproducibility and biological accuracy of the structural connectome
Smith, R. E., Tournier, J.-D., Calamante, F., & Connelly, A. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.10.004 · Cited by 266 · cited 1× · see citing works
“Future work could probably improve these relationships substantially by imposing rigorous anatomical constraints in the tractography process (Smith et al., 2015), but such efforts have not seen extensive validation yet.”
BackgroundMeda, S. A., Ruaño, G., Windemuth, A., O’Neil, K., Berwise, C., Dunn, S. M., Boccaccio, L. E., Narayanan, B., Kocherla, M., Sprooten, E., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1313093111 · Cited by 242 · cited 4× · see citing works
“The first challenge is the ever-expanding evidence that Schizophrenia (Meda et al., 2014; Satterthwaite and Baker, 2015), ADHD (Costa Dias et al., 2015; Fair et al., 2012a; Gates et al., 2014; Karalunas et al., 2014), Autism (Jeste and Geschwind, 2014; Rudie et al., 2012), and potentially other DSM…”
BackgroundInfluentialNetwork analysis of resting state EEG in the developing young brain: structure comes with maturation
Boersma, M., Smit, D. J. A., de Bie, H. M. A., Van Baal, G. C. M., Boomsma, D. I., de Geus, E. J. C., Delemarre‐van de Waal, H. A., & Stam, C. J. (2011) · Human Brain Mapping · doi:10.1002/hbm.21030 · Cited by 235 · cited 5× · see citing works
“Somewhat unexpectedly, two reports found path length to also increase with age (Boersma et al., 2011; Smit et al., 2012), although more recent work demonstrates age-related reductions (Miskovic et al.”
BackgroundResultInfluentialLarge-scale topology and the default mode network in the mouse connectome
Stafford, J. M., Jarrett, B. R., Miranda-Dominguez, O., Mills, B. D., Cain, N., Mihalas, S., Lahvis, G. P., Lattal, K. M., Mitchell, S. H., David, S. V., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1404346111 · Cited by 229 · cited 2× · see citing works
“5) are attainable across species (Grayson et al., 2016; Miranda-Dominguez et al., 2014b; Stafford et al., 2014; Hutchison et al., 2015; Hutchison and Everling, 2012; Margulies et al., 2009).”
BackgroundSelf-citationCross-hemispheric functional connectivity in the human fetal brain
Thomason, M. E., Dassanayake, M. T., Shen, S., Katkuri, Y., Alexis, M., Anderson, A. L., Yeo, L., Mody, S., Hernandez-Andrade, E., Hassan, S. S., et al. (2013) · Science Translational Medicine · doi:10.1126/scitranslmed.3004978 · Cited by 225 · cited 1× · see citing works
“RSNs are already present during infancy, and potentially to some extent in utero (Thomason et al., 2013).”
BackgroundFunctional connectivity MR imaging reveals cortical functional connectivity in the developing brain
Lin, W., Zhu, Q., Gao, W., Chen, Y., Toh, C.-H., Styner, M., Gerig, G., Smith, J. K., Biswal, B., & Gilmore, J. H. (2008) · American Journal of Neuroradiology · doi:10.3174/ajnr.a1256 · Cited by 222 · cited 3× · see citing works
“These sensory networks undergo subtle refinements and strengthening over the first two years of life, and by age two bear substantial resemblance to their adult counterparts (Gao et al., 2015a; Lin et al., 2008).”
BackgroundKhadka, S., Meda, S. A., Stevens, M. C. G., Glahn, D. C., Calhoun, V. D., Sweeney, J. A., Tamminga, C. A., Keshavan, M. S., O'Neil, K. M., Schretlen, D. J., et al. (2013) · Biological Psychiatry · doi:10.1016/j.biopsych.2013.04.024 · Cited by 219 · cited 4× · see citing works
“Complex, distributed disruptions in resting-state networks are consistently implicated in Schizophrenia (Baker et al., 2014; Khadka et al., 2013; Satterthwaite et al., 2015), ADHD (Castellanos and Aoki, 2016; Fair et al., 2012b), and Autism (Kessler et al., 2016; Moseley et al., 2015; Supekar et al., 2013) – though a…”
BackgroundInfluentialMessé, A., Rudrauf, D., Benali, H., & Marrelec, G. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003530 · Cited by 215 · cited 6× · see citing works
“Interregional FC arises from anatomical projection strengths (Messe et al., 2014; Shen et al., 2012), correlated gene expression (Richiardi et al., 2015), and synaptic receptor densities (Turk et al., 2016; van den Heuvel et al., 2016b) – properties that, in turn, undergo experience-dependent and…”
BackgroundInfluentialTracking the Brain's Functional Coupling Dynamics over Development
Hutchison, R. M., & Morton, J. B. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.4638-14.2015 · Cited by 214 · cited 2× · see citing works
“Over development, rs-fcMRI networks show increased within-subject variability (Hutchison and Morton, 2015; Marusak et al., 2016; Qin et al., 2015), consistent with EEG studies showing that signal complexity increases over development (McIntosh et al., 2008; Vakorin et al., 2011).”
BackgroundReineberg, A. E., Andrews-Hanna, J. R., Depue, B. E., Friedman, N. P., & Banich, M. T. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.09.045 · Cited by 206 · cited 2× · see citing works
“, 2014) and executive functioning (Reineberg et al., 2015), and are differentially associated with performance on simple motor tasks versus complex working memory tasks (Cohen and D'Esposito, 2016).”
BackgroundDevelopment of global cortical networks in early infancy
Homae, F., Watanabe, H., Otobe, T., Nakano, T., Go, T., Konishi, Y., & Taga, G. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.5618-09.2010 · Cited by 206 · cited 2× · see citing works
“These latter modules also exhibit substantial growth of distributed synchronization and homotopic coupling from birth through the first two years of life (Gao et al., 2015b; Homae et al., 2010), concomitant with decreasing between-module connectivity (i.e. greater functional specialization).”
BackgroundCanetta, S., Bolkan, S., Padilla-Coreano, N., Song, L. J., Sahn, R., Harrison, N. L., Gordon, J. A., Brown, A., & Kellendonk, C. (2016) · Molecular Psychiatry · doi:10.1038/mp.2015.222 · Cited by 201 · see citing works
Connectotyping: Model Based Fingerprinting of the Functional Connectome
Miranda-Dominguez, O., Mills, B. D., Carpenter, S. D., Grant, K. A., Kroenke, C. D., Nigg, J. T., & Fair, D. A. (2014) · PLoS ONE · doi:10.1371/journal.pone.0111048 · Cited by 197 · cited 5× · see citing works
“Cutting-edge work in resting-state fMRI acquisition and network analysis suggests that individual brains, even among typical subjects, are distinguishable via their functional connectomes (Finn et al., 2015; Laumann et al., 2015; Miranda-Dominguez et al., 2014b).”
BackgroundInfluentialSelf-citationVértes, P. E., & Bullmore, E. T. (2015) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12365 · Cited by 197 · cited 3× · see citing works
“Past reviews have already written eloquently about the rationales for applying this approach to study development (Power et al., 2010; Vertes and Bullmore, 2015), which we will only briefly summarize and expand upon here.”
BackgroundAn approach for parcellating human cortical areas using resting-state correlations
Wig, G. S., Laumann, T. O., & Petersen, S. E. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.07.035 · Cited by 187 · cited 1× · see citing works
“Several groups, however, are finding ways to utilize today's non-invasive imaging tools to bring us closer to realizing these goals (Behrens et al., 2003; Glasser et al., 2016a; Gordon et al., 2016; Wig et al., 2014a, 2014b; Zhang et al., 2010).”
BackgroundStructural and functional rich club organization of the brain in children and adults
Grayson, D. S., Ray, S., Carpenter, S., Iyer, S., Dias, T. G. C., Stevens, C., Nigg, J. T., & Fair, D. A. (2014) · PLoS ONE · doi:10.1371/journal.pone.0088297 · Cited by 187 · cited 11× · see citing works
“Returning to the MRI literature, there is convergent evidence that the locations of high-strength and high-betweenness hub regions appear to be stable after 5 years of age (Cao et al., 2014; Grayson et al., 2014; Hwang et al., 2013; Wang et al., 2012; Wu et al., 2013; Zuo et al., 2012).”
BackgroundInfluentialSelf-citationCortical Parcellations of the Macaque Monkey Analyzed on Surface-Based Atlases
Essen, D. C. V., Glasser, M. F., Dierker, D. L., & Harwell, J. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhr290 · Cited by 182 · cited 8× · see citing works
“Surface based registrations that take into account the sulcal and gyral anatomy also help mitigate these confounds, and may be the future direction of the field (Fischl, 2012; Van Essen, 2012).”
MethodInfluentialWu, K., Taki, Y., Sato, K., Hashizume, H., Sassa, Y., Takeuchi, H., Thyreau, B., Yong He, A., Evans, A. C., Li, X., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0055347 · Cited by 176 · cited 5× · see citing works
“Returning to the MRI literature, there is convergent evidence that the locations of high-strength and high-betweenness hub regions appear to be stable after 5 years of age (Cao et al., 2014; Grayson et al., 2014; Hwang et al., 2013; Wang et al., 2012; Wu et al., 2013; Zuo et al., 2012).”
BackgroundInfluentialMiskovic, V., Ma, X., Chou, C.-A., Fan, M., Owens, M., Sayama, H., & Gibb, B. E. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.06.013 · Cited by 175 · cited 10× · see citing works
“There is also a progressive shift in peak amplitude towards higher frequency activity (Miskovic et al., 2015; Rodriguez-Martinez et al., 2015; Smit et al., 2012; Whitford et al., 2007).”
BackgroundResultInfluentialStructural and Maturational Covariance in Early Childhood Brain Development
Geng, X., Li, G., Lu, Z., Gao, W., Wang, L., Shen, D., Zhu, H., & Gilmore, J. H. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw022 · Cited by 175 · see citing works
Grayson, D. S., Bliss-Moreau, E., Machado, C. J., Bennett, J., Shen, K., Grant, K. A., Fair, D. A., & Amaral, D. G. (2016) · Neuron · doi:10.1016/j.neuron.2016.06.005 · Cited by 172 · see citing works
Self-citationNetwork structure shapes spontaneous functional connectivity dynamics
Shen, K., Hutchison, R. M., Bezgin, G., Everling, S., & McIntosh, A. R. (2015) · The Journal of Neuroscience · doi:10.1523/jneurosci.4903-14.2015 · Cited by 171 · cited 1× · see citing works
“Mounting evidence suggests that the functional connectome exhibits temporal instability that allows it to flexibly switch between multiple different configurations within a scanning session (Allen et al., 2014; Chang and Glover, 2010; Kang et al., 2011; Shen et al., 2015).”
BackgroundVakorin, V. A., Lippé, S., & McIntosh, A. R. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.3153-10.2011 · Cited by 171 · cited 2× · see citing works
“Over development, rs-fcMRI networks show increased within-subject variability (Hutchison and Morton, 2015; Marusak et al., 2016; Qin et al., 2015), consistent with EEG studies showing that signal complexity increases over development (McIntosh et al., 2008; Vakorin et al., 2011).”
BackgroundLi, G., Lin, W., Gilmore, J. H., & Shen, D. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.4107-14.2015 · Cited by 164 · see citing works
Identification of optimal structural connectivity using functional connectivity and neural modeling
Deco, G., McIntosh, A. R., Shen, K., Hutchison, R. M., Menon, R. S., Everling, S., Hagmann, P., & Jirsa, V. K. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.4423-13.2014 · Cited by 162 · cited 1× · see citing works
“In the meantime, animal models are proving to be an important and necessary “bridge” for identifying ground-truth structure-to-function principles (Deco et al., 2014; Grayson et al., 2016; Miranda-Dominguez et al., 2014b; Stafford et al., 2014).”
BackgroundScholtens, L. H., Schmidt, R., de Reus, M. A., & van den Heuvel, M. P. (2014) · The Journal of Neuroscience · doi:10.1523/jneurosci.0752-14.2014 · Cited by 160 · cited 2× · see citing works
“More to the point, macroscale FC is known to be modulated by interareal correlated gene expression, areal densities of excitatory and inhibitory receptors, and other features of microscale architecture that vary across brain structures (Richiardi et al., 2015; Scholtens et al., 2014; Turk et al., 2016; van den Heuvel…”
BackgroundResting-state networks in awake five- to eight-year old children
de Bie, H. M. A., Boersma, M., Adriaanse, S., Veltman, D. J., Wink, A. M., Roosendaal, S. D., Barkhof, F., Stam, C. J., Oostrom, K. J., Delemarre‐van de Waal, H. A., et al. (2012) · Human Brain Mapping · doi:10.1002/hbm.21280 · Cited by 143 · cited 1× · see citing works
“…areas (and indeed, connectivity within other cognitive RSNs) continues to strengthen from early childhood throughout development, especially with respect to long-range anterior-posterior links (de Bie et al., 2012; Fair et al., 2008; Sato et al., 2014; Sherman et al., 2014; Supekar et al., 2010).”
BackgroundThe brain matures with stronger functional connectivity and decreased randomness of its network
Smit, D. J. A., Boersma, M., Schnack, H. G., Micheloyannis, S., Boomsma, D. I., Hulshoff Pol, H. E., Stam, C. J., & de Geus, E. J. C. (2012) · PLoS ONE · doi:10.1371/journal.pone.0036896 · Cited by 143 · cited 15× · see citing works
“There is also a progressive shift in peak amplitude towards higher frequency activity (Miskovic et al., 2015; Rodriguez-Martinez et al., 2015; Smit et al., 2012; Whitford et al., 2007).”
BackgroundResultInfluentialLarge-scale brain network dynamics supporting adolescent cognitive control
Dwyer, D. B., Harrison, B. J., Yücel, M., Whittle, S., Zalesky, A., Pantelis, C., Allen, N. B., & Fornito, A. (2014) · The Journal of Neuroscience · doi:10.1523/jneurosci.1634-14.2014 · Cited by 143 · cited 4× · see citing works
“Both effects in tandem are crucially involved in cognitive control (Dwyer et al., 2014) and executive functioning (Reineberg et al.”
BackgroundInfluentialAutism-Associated Promoter Variant in MET Impacts Functional and Structural Brain Networks
Rudie, J. D., Hernandez, L. M., Brown, J. A., Beck-Pancer, D., Colich, N. L., Gorrindo, P., Thompson, P. M., Geschwind, D. H., Bookheimer, S. Y., Levitt, P., et al. (2012) · Neuron · doi:10.1016/j.neuron.2012.07.010 · Cited by 142 · cited 1× · see citing works
“…studies (rodents and non-human primates), this is feasible through the use of comprehensive, histologically and functionally defined whole-brain areal parcellations (Bezgin et al., 2012; Lein et al., 2007; Paxinos et al., 2000; Saleem and Logothetis, 2007; Swanson, 2015; Van Essen et al., 2012).”
MethodNeural correlates of expected risks and returns in risky choice across development
van Duijvenvoorde, A. C. K., Huizenga, H. M., Somerville, L. H., Delgado, M. R., Powers, A., Weeda, W. D., Casey, B. J., Weber, E. U., & Figner, B. (2015) · The Journal of Neuroscience · doi:10.1523/jneurosci.1924-14.2015 · Cited by 141 · see citing works
Hutchison, R. M., & Everling, S. (2012) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2012.00029 · Cited by 140 · cited 1× · see citing works
“5) are attainable across species (Grayson et al., 2016; Miranda-Dominguez et al., 2014b; Stafford et al., 2014; Hutchison et al., 2015; Hutchison and Everling, 2012; Margulies et al., 2009).”
Ontogenesis of goal-directed behavior: anatomo-functional considerations
Kostović, I., Judaš, M., Petanjek, Z., & Šimić, G. (1995) · International Journal of Psychophysiology · doi:10.1016/0167-8760(94)00081-o · Cited by 139 · cited 2× · see citing works
“These areal boundaries appear very early in development (Kostovic et al., 1995) and each area is thought to make a distinct contribution to information processing (Cohen et al.”
BackgroundEEG functional connectivity is partially predicted by underlying white matter connectivity
Chu, C. J., Tanaka, N., Diaz, J., Edlow, B. L., Wu, O., Hämäläinen, M., Stufflebeam, S., Cash, S. S., & Kramer, M. A. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.12.033 · Cited by 135 · cited 1× · see citing works
“Predictive models have been extensively validated on both rsfcMRI and EEG data (Chu et al., 2015), suggesting that SC strongly shapes and constrains activity across temporal scales.”
Backgroundvan den Heuvel, M. P., de Reus, M. A., Feldman Barrett, L., Scholtens, L. H., Coopmans, F. M. T., Schmidt, R., Preuss, T. M., Rilling, J. K., & Li, L. (2015) · Human Brain Mapping · doi:10.1002/hbm.22828 · Cited by 131 · cited 5× · see citing works
“In neonates, two independent rs-fcMRI studies found evidence for modules comprised largely of anatomically proximate areas (De Asis-Cruz et al., 2015; van den Heuvel et al., 2015b).”
BackgroundResultInfluentialCharacterizing heterogeneity in children with and without ADHD based on reward system connectivity
Costa Dias, T. G., Iyer, S. P., Carpenter, S. D., Cary, R. P., Wilson, V. B., Mitchell, S. H., Nigg, J. T., & Fair, D. A. (2015) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2014.12.005 · Cited by 130 · cited 1× · see citing works
“The first challenge is the ever-expanding evidence that Schizophrenia (Meda et al., 2014; Satterthwaite and Baker, 2015), ADHD (Costa Dias et al., 2015; Fair et al., 2012a; Gates et al., 2014; Karalunas et al., 2014), Autism (Jeste and Geschwind, 2014; Rudie et al., 2012), and potentially other DSM…”
BackgroundSelf-citationMiranda-Dominguez, O., Mills, B. D., Grayson, D., Woodall, A., Grant, K. A., Kroenke, C. D., & Fair, D. A. (2014) · The Journal of Neuroscience · doi:10.1523/jneurosci.4229-13.2014 · Cited by 130 · cited 5× · see citing works
“Cutting-edge work in resting-state fMRI acquisition and network analysis suggests that individual brains, even among typical subjects, are distinguishable via their functional connectomes (Finn et al., 2015; Laumann et al., 2015; Miranda-Dominguez et al., 2014b).”
BackgroundInfluentialSelf-citationChanges in Brain Network Efficiency and Working Memory Performance in Aging
Stanley, M. L., Simpson, S. L., Dagenbach, D., Lyday, R. G., Burdette, J. H., & Laurienti, P. J. (2015) · PLoS ONE · doi:10.1371/journal.pone.0123950 · Cited by 129 · cited 2× · see citing works
“Greater global efficiency in structural and functional networks has been linked to higher IQ, attentional capacity, and working memory in healthy young adults (Cohen and D'Esposito, 2016; Kitzbichler et al., 2011; Li et al., 2009; Stanley et al., 2015; van den Heuvel et al., 2009), supporting the notion that it confer…”
BackgroundWig, G. S., Laumann, T. O., Cohen, A. L., Power, J. D., Nelson, S. M., Glasser, M. F., Miezin, F. M., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2013) · Cerebral Cortex · doi:10.1093/cercor/bht056 · Cited by 123 · cited 1× · see citing works
“Several groups, however, are finding ways to utilize today's non-invasive imaging tools to bring us closer to realizing these goals (Behrens et al., 2003; Glasser et al., 2016a; Gordon et al., 2016; Wig et al., 2014a, 2014b; Zhang et al., 2010).”
BackgroundInformation processing architecture of functionally defined clusters in the macaque cortex
Shen, K., Bezgin, G., Hutchison, R. M., Gati, J. S., Menon, R. S., Everling, S., & McIntosh, A. R. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.2709-12.2012 · Cited by 123 · cited 2× · see citing works
“Interregional FC arises from anatomical projection strengths (Messe et al., 2014; Shen et al., 2012), correlated gene expression (Richiardi et al., 2015), and synaptic receptor densities (Turk et al., 2016; van den Heuvel et al., 2016b) – properties that, in turn, undergo experience-dependent and…”
BackgroundCortical cartography and Caret software
Essen, D. C. V. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.10.077 · Cited by 121 · cited 7× · see citing works
“Surface based registrations that take into account the sulcal and gyral anatomy also help mitigate these confounds, and may be the future direction of the field (Fischl, 2012; Van Essen, 2012).”
BackgroundInfluentialPredicting individual brain maturity using dynamic functional connectivity
Qin, J., Chen, S.-G., Hu, D., Zeng, L.-L., Fan, Y.-M., Chen, X.-P., & Shen, H. (2015) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2015.00418 · Cited by 117 · cited 2× · see citing works
“Over development, rs-fcMRI networks show increased within-subject variability (Hutchison and Morton, 2015; Marusak et al., 2016; Qin et al., 2015), consistent with EEG studies showing that signal complexity increases over development (McIntosh et al., 2008; Vakorin et al., 2011).”
BackgroundDecoding lifespan changes of the human brain using resting-state functional connectivity MRI
Wang, L., Su, L., Shen, H., & Hu, D. (2012) · PLoS ONE · doi:10.1371/journal.pone.0044530 · Cited by 115 · cited 2× · see citing works
“Returning to the MRI literature, there is convergent evidence that the locations of high-strength and high-betweenness hub regions appear to be stable after 5 years of age (Cao et al., 2014; Grayson et al., 2014; Hwang et al., 2013; Wang et al., 2012; Wu et al., 2013; Zuo et al., 2012).”
BackgroundConnectome-wide network analysis of youth with Psychosis-Spectrum symptoms
Satterthwaite, T. D., Vandekar, S., Wolf, D. H., Bassett, D. S., Ruparel, K., Shehzad, Z. E., Craddock, R. C., Shinohara, R. T., Moore, T. M., Gennatas, E. D., et al. (2015) · Molecular Psychiatry · doi:10.1038/mp.2015.66 · Cited by 114 · see citing works
The potential of infant fMRI research and the study of early life stress as a promising exemplar
Graham, A. M., Pfeifer, J. H., Fisher, P. A., Lin, W., Gao, W., & Fair, D. A. (2015) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2014.09.005 · Cited by 114 · see citing works
Self-citationSrinivasan, R. (1999) · Clinical Neurophysiology · doi:10.1016/s1388-2457(99)00080-2 · Cited by 112 · cited 2× · see citing works
“, 2012) and strength of long-range anterior-posterior and interhemispheric connections (Barry et al., 2004; Miskovic et al., 2015; Smit et al., 2012; Srinivasan, 1999).”
BackgroundKang, J., Wang, L., Yan, C., Wang, J., Liang, X., & He, Y. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.03.033 · Cited by 111 · cited 1× · see citing works
“Mounting evidence suggests that the functional connectome exhibits temporal instability that allows it to flexibly switch between multiple different configurations within a scanning session (Allen et al., 2014; Chang and Glover, 2010; Kang et al., 2011; Shen et al., 2015).”
BackgroundFunctional connectivity of the sensorimotor area in naturally sleeping infants
Liu, W.-C., Flax, J. F., Guise, K. G., Sukul, V., & Benasich, A. A. (2008) · Brain Research · doi:10.1016/j.brainres.2008.05.054 · Cited by 110 · cited 3× · see citing works
“…componentbased approaches demonstrate the existence of robust, bilateral segregated networks for somatomotor, primary auditory, primary visual, and extrastriate visual cortex (Fransson et al., 2007; Gao et al., 2015a; Kiviniemi et al., 2000; Lin et al., 2008; Liu et al., 2008; Smyser et al., 2010).”
BackgroundAndoh, J., Matsushita, R., & Zatorre, R. J. (2015) · The Journal of Neuroscience · doi:10.1523/jneurosci.2333-15.2015 · Cited by 109 · cited 3× · see citing works
“…induced perturbations (e.g. exogenous stimulation or inactivation) result in widespread, complex neurophysiological changes, which are at least partly explainable as local interactions with global network structure (Andoh et al., 2015; Grayson et al., 2016; Gu et al., 2015a; Misic et al., 2015).”
BackgroundMethodGates, K. M., Molenaar, P. C. M., Iyer, S. P., Nigg, J. T., & Fair, D. A. (2014) · PLoS ONE · doi:10.1371/journal.pone.0091322 · Cited by 107 · cited 4× · see citing works
“Complex, distributed disruptions in resting-state networks are consistently implicated in Schizophrenia (Baker et al., 2014; Khadka et al., 2013; Satterthwaite et al., 2015), ADHD (Castellanos and Aoki, 2016; Fair et al., 2012b), and Autism (Kessler et al., 2016; Moseley et al., 2015; Supekar et al., 2013) – though a…”
BackgroundInfluentialSelf-citationA Monte Carlo evaluation of weighted community detection algorithms
Gates, K. M., Henry, T., Steinley, D., & Fair, D. A. (2016) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2016.00045 · Cited by 106 · cited 1× · see citing works
“In the case of identified networks in infants it is important to note that different community detection algorithms can provide unique results and all are not appropriate for any given experimental condition (Gates et al., 2016).”
BackgroundSelf-citationScott, J. A., Grayson, D. S., Fletcher, E., Lee, A., Bauman, M. D., Schumann, C. M., Buonocore, M. H., & Amaral, D. G. (2015) · Brain Structure and Function · doi:10.1007/s00429-015-1076-x · Cited by 104 · cited 5× · see citing works
“…a well-validated approach to help overcome some of these confounds (Avants et al., 2010; Fonov et al., 2011), and is increasingly adopted in both structural and functional studies of (especially early) development (Eggebrecht et al., 2017; Fonov et al., 2011; Gao et al., 2015a; Scott et al., 2015).”
BackgroundInfluentialSelf-citationAge and gender effects in EEG coherence: i. Developmental trends in normal children
Barry, R. J., Clarke, A. R., McCarthy, R., Selikowitz, M., Johnstone, S. J., & Rushby, J. A. (2004) · Clinical Neurophysiology · doi:10.1016/j.clinph.2004.05.004 · Cited by 104 · cited 2× · see citing works
“, 2012) and strength of long-range anterior-posterior and interhemispheric connections (Barry et al., 2004; Miskovic et al., 2015; Smit et al., 2012; Srinivasan, 1999).”
BackgroundFunctional connectivity in the developing brain: a longitudinal study from 4 to 9months of age
Damaraju, E., Caprihan, A., Lowe, J. R., Allen, E. A., Calhoun, V. D., & Phillips, J. P. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.08.038 · Cited by 103 · cited 2× · see citing works
“In neonates and very young infants, these individual compartments demonstrate locally correlated activity, but fail to synchronize into a coherent network (Damaraju et al., 2014; Fransson et al., 2007; Gao et al., 2009; Smyser et al., 2010; Wylie et al., 2014).”
BackgroundFransson, P., Metsäranta, M., Blennow, M., Ådén, U., Lagercrantz, H., & Vanhatalo, S. (2012) · Cerebral Cortex · doi:10.1093/cercor/bhs047 · Cited by 103 · cited 1× · see citing works
“Recent simultaneous EEG-fMRI work (Fransson et al., 2013) links developmental differences (infants versus adults) in rs-fcmri network dynamics with differences in EEG power spectra.”
BackgroundMR connectomics: a conceptual framework for studying the developing brain
Hagmann, P., Grant, P. E., & Fair, D. A. (2012) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2012.00043 · Cited by 96 · cited 4× · see citing works
“…changes in cerebral vasculature, and altered state of consciousness when scanning very young participants. fMRI relies on hemodynamic measurements (usually BOLD), and there is good reason to suspect that infancy is accompanied by specific changes in neurovascular coupling (Hagmann et al., 2012).”
BackgroundResultInfluentialSelf-citationSimulated rich club lesioning in brain networks: a scaffold for communication and integration?
de Reus, M. A., & van den Heuvel, M. P. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00647 · Cited by 89 · see citing works
Consistent Anterior–Posterior Segregation of the Insula During the First 2 Years of Life
Alcauter, S., Lin, W., Smith, J. K., Gilmore, J. H., & Gao, W. (2013) · Cerebral Cortex · doi:10.1093/cercor/bht312 · Cited by 89 · cited 2× · see citing works
“Community structure assessed at two years of age (Alcauter et al., 2015b; Gao et al., 2015b) indicates the presence of distinct modules encompassing early auditory, early somatomotor, and early visual areas, and potentially, other prototypical modules similar to the canonical salience,…”
BackgroundPreterm birth alters neonatal, functional rich club organization
Scheinost, D., Kwon, S. H., Shen, X., Lacadie, C., Schneider, K. C., Dai, F., Ment, L. R., & Constable, R. T. (2015) · Brain Structure and Function · doi:10.1007/s00429-015-1096-6 · Cited by 87 · cited 2× · see citing works
“It is also clear that several prenatal factors (e.g. immune and endocrine systems) strongly affect postnatal network trajectories (Canetta et al., 2016; Scheinost et al., 2016b).”
BackgroundFunctional properties of resting state networks in healthy full-term newborns
De Asis-Cruz, J., Bouyssi-Kobar, M., Evangelou, I., Vezina, G., & Limperopoulos, C. (2015) · Scientific Reports · doi:10.1038/srep17755 · Cited by 85 · cited 4× · see citing works
“…default mode, attentional, sensorimotor, and visual areas (Cao et al., 2014; Fransson et al., 2011; Grayson et al., 2014; Hwang et al., 2013), whereas neonatal hubs primarily involve early sensorimotor, visual, and limbic regions (De Asis-Cruz et al., 2015; Fransson et al., 2011; Gao et al., 2011).”
BackgroundInfluentialAge effects on the default mode and control networks in typically developing children
Sato, J. R., Salum, G. A., Gadelha, A., Picon, F. A., Pan, P. M., Vieira, G., Zugman, A., Hoexter, M. Q., Anés, M., Moura, L. M., et al. (2014) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2014.07.004 · Cited by 85 · see citing works
Whole-brain functional hypoconnectivity as an endophenotype of autism in adolescents
Moseley, R. L., Ypma, R. J. F., Holt, R., Floris, D. L., Chura, L. R., Spencer, M. D., Baron‐Cohen, S., John Suckling, A., Bullmore, E. T., & Rubinov, M. (2015) · NeuroImage Clinical · doi:10.1016/j.nicl.2015.07.015 · Cited by 82 · cited 6× · see citing works
“DSG was supported by an Autism Speaks Dennis Weatherstone Predoctoral Fellowship (#9591).”
BackgroundInfluentialHead motion and correction methods in resting-state functional MRI
GOTO, M., ABE, O., MIYATI, T., YAMASUE, H., GOMI, T., & TAKEDA, T. (2016) · Magnetic Resonance in Medical Sciences · doi:10.2463/mrms.rev.2015-0060 · Cited by 82 · see citing works
Satterthwaite, T. D., & Baker, J. T. (2014) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2014.10.005 · Cited by 76 · cited 4× · see citing works
“The first challenge is the ever-expanding evidence that Schizophrenia (Meda et al., 2014; Satterthwaite and Baker, 2015), ADHD (Costa Dias et al., 2015; Fair et al., 2012a; Gates et al., 2014; Karalunas et al., 2014), Autism (Jeste and Geschwind, 2014; Rudie et al., 2012), and potentially other DSM…”
BackgroundInfluentialAssociated Microscale Spine Density and Macroscale Connectivity Disruptions in Schizophrenia
van den Heuvel, M. P., Scholtens, L. H., de Reus, M. A., & Kahn, R. S. (2015) · Biological Psychiatry · doi:10.1016/j.biopsych.2015.10.005 · Cited by 72 · see citing works
Wisner, K. M., Atluri, G., Lim, K. O., & MacDonald, A. W. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.02.066 · Cited by 66 · cited 1× · see citing works
“Multiple studies have found evidence for limited test-retest reliability using a multitude of conventional rs-fcMRI network characteristics and analytic approaches (Braun et al., 2012; Wang et al., 2011; Wisner et al., 2013; Zuo et al., 2010; Zuo and Xing, 2014).”
BackgroundBezgin, G., Vakorin, V. A., van Opstal, A. J., McIntosh, A. R., & Bakker, R. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.04.013 · Cited by 63 · cited 2× · see citing works
“In animal studies (rodents and non-human primates), this is feasible through the use of comprehensive, histologically and functionally defined whole-brain areal parcellations (Bezgin et al., 2012; Lein et al., 2007; Paxinos et al., 2000; Saleem and Logothetis, 2007; Swanson, 2015; Van Essen et al., 2012).”
MethodDynamic network centrality summarizes learning in the human brain
Mantzaris, A. V., Bassett, D. S., Wymbs, N. F., Estrada, E., Porter, M. A., Mucha, P. J., Grafton, S. T., & Higham, D. J. (2013) · Journal of Complex Networks · doi:10.1093/comnet/cnt001 · Cited by 62 · cited 2× · see citing works
“, 2012) and node communicability (de Reus and van den Heuvel, 2014; Mantzaris et al., 2013) have seen useful application as well.”
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48 of the 259 references couldn’t be matched to a known paper.
Research works printed but not linked: 31
- Baker, 2014, Disruption of cortical association networks in schizophrenia and psychotic bipolar disorder, JAMA Psychiatry, 71, 109, 10.1001/jamapsychiatry.2013.3469 · DOI · Paper page
- Burgess, 2016, Evaluation of denoising strategies to address motion-correlated artifacts in resting-state functional magnetic resonance imaging data from the human connectome project, Brain Connect, 6, 669, 10.1089/brain.2016.0435 · DOI · Paper page
- Calabrese, 2015, A diffusion MRI tractography connectome of the mouse brain and comparison with neuronal tracer data, Cereb. Cortex, 25, 4628, 10.1093/cercor/bhv121 · DOI · Paper page
- Castellanos, 2016, Intrinsic functional connectivity in attention-deficit/hyperactivity disorder: a science in development, Biol. Psychiatry Cogn. Neurosci. Neuroimaging, 1, 253
- Chen, 2016, Distinct global brain dynamics and spatiotemporal organization of the salience network, PLoS Biol., 14, e1002469, 10.1371/journal.pbio.1002469 · DOI · Paper page
- Cohen, 2016, The segregation and integration of distinct brain networks and their relationship to cognition, J. Neurosci., 36, 12083, 10.1523/JNEUROSCI.2965-15.2016 · DOI
- Collin, 2013, Structural and functional aspects relating to cost and benefit of rich club organization in the human cerebral cortex, Cereb. Cortex
- Donahue, 2016, Using diffusion tractography to predict cortical connection strength and distance: a quantitative comparison with tracers in the monkey, J. Neurosci., 36, 6758, 10.1523/JNEUROSCI.0493-16.2016 · DOI · Paper page
- Eggebrecht, 2017, Joint attention and brain functional connectivity in infants and toddlers, Cereb. Cortex, 10.1093/cercor/bhw403 · DOI · Paper page
- Fischl, 2012, FreeSurfer, NeuroImage, 62, 774, 10.1016/j.neuroimage.2012.01.021 · DOI · Paper page
- Fuster, 2002, Frontal lobe and cognitive development, J. Neurocytol., 31, 373, 10.1023/A:1024190429920 · DOI · Paper page
- Gao, 2013, The synchronization within and interaction between the default and dorsal attention networks in early infancy, Cereb. Cortex, 23, 594, 10.1093/cercor/bhs043 · DOI · Paper page
- Gao, 2016, Functional connectivity of the infant human brain: plastic and modifiable, Neuroscientist
- Glasser, 2016, The Human Connectome Project's neuroimaging approach, Nat. Neurosci., 19, 1175, 10.1038/nn.4361 · DOI · Paper page
- Hindriks, 2016, Can sliding-window correlations reveal dynamic functional connectivity in resting-state fMRI?, NeuroImage, 127, 242, 10.1016/j.neuroimage.2015.11.055 · DOI · Paper page
- Honey, 2009, Predicting human resting-state functional connectivity from structural connectivity, Proc. Natl. Acad. Sci. USA, 106, 2035, 10.1073/pnas.0811168106 · DOI · Paper page
- Hwang, 2013, The development of hub architecture in the human functional brain network, Cereb. Cortex, 23, 2380, 10.1093/cercor/bhs227 · DOI · Paper page
- Kessler, 2016, Brain oscillations and connectivity in autism spectrum disorders (ASD): new approaches to methodology, measurement and modelling, Neurosci. Biobehav. Rev., 71, 601, 10.1016/j.neubiorev.2016.10.002 · DOI · Paper page
- Laumann, 2016, On the stability of BOLD fMRI correlations, Cereb. Cortex, 10.1093/cercor/bhw265 · DOI · Paper page
- Lohse, 2014, Resolving anatomical and functional structure in human brain organization: identifying mesoscale organization in weighted network representations, PLoS Comput. Biol., 10, e1003712, 10.1371/journal.pcbi.1003712 · DOI · Paper page
- Marquand, 2016, Beyond lumping and splitting: a review of computational approaches for stratifying psychiatric disorders, Biol. Psychiatry Cogn. Neurosci. Neuroimaging, 1, 433
- Marusak, 2016, Dynamic functional connectivity of neurocognitive networks in children, Hum. Brain Mapp.
- Patriat, 2016, An improved model of motion-related signal changes in fMRI, NeuroImage
- Power, 2016, Sources and implications of whole-brain fMRI signals in humans, NeuroImage
- Roalf, 2016, The impact of quality assurance assessment on diffusion tensor imaging outcomes in a large-scale population-based cohort, NeuroImage, 125, 903, 10.1016/j.neuroimage.2015.10.068 · DOI · Paper page
- Rubinov, 2010, Complex network measures of brain connectivity: uses and interpretations, NeuroImage, 52, 1059, 10.1016/j.neuroimage.2009.10.003 · DOI · Paper page
- Savalia, 2017, Motion-related artifacts in structural brain images revealed with independent estimates of in-scanner head motion, Hum. Brain Mapp., 38, 472, 10.1002/hbm.23397 · DOI
- Scheinost, 2016, Does prenatal stress alter the developing connectome?, Pediatr. Res.
- Siegel, 2016, Data quality influences observed links between functional connectivity and behavior, Cereb. Cortex
- Turk, 2016, Cortical chemoarchitecture shapes macroscale effective functional connectivity patterns in macaque cerebral cortex, Hum. Brain Mapp., 37, 1856, 10.1002/hbm.23141 · DOI · Paper page
- van den Heuvel, 2016, Multimodal analysis of cortical chemoarchitecture and macroscale fMRI resting-state functional connectivity, Hum. Brain Mapp., 37, 3103, 10.1002/hbm.23229 · DOI
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Sorted by citations
Marek, S., & Dosenbach, N. U. F. (2018) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2018.20.2/smarek · Cited by 836 · see citing works
Farahani, F. V., Karwowski, W., & Lighthall, N. R. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00585 · Cited by 719 · see citing works
“Modeling the lifetime trajectory of the functional connectome, multiple studies detected striking age-related alterations in highly connected hub areas mainly within the default mode, attentional, sensorimotor, and visual regions via rs-fMRI (Meunier et al., 2009; Fransson et al., 2011; Hwang et al., 2013; Wu et al.,…”
Environmental influences on the pace of brain development
Tooley, U. A., Bassett, D. S., & Mackey, A. P. (2021) · Nature reviews. Neuroscience · doi:10.1038/s41583-021-00457-5 · Cited by 488 · see citing works
The UNC/UMN Baby Connectome Project (BCP): An overview of the study design and protocol development
Howell, B., Styner, M. A., Gao, W., Yap, P., Wang, L., Baluyot, K., Yacoub, E. S., Chen, G., Potts, T., Salzwedel, A., et al. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.03.049 · Cited by 431 · see citing works
“, 1994) with aspects of the current state of knowledge summarized in several recent review papers (Cao et al., 2017; Dehaene-Lambertz and Spelke, 2015; Grayson and Fair, 2017; Gao et al., 2016; Huppi, 2011) and highlighted in the current issue.”
Segregated Systems of Human Brain Networks
Wig, G. S. (2017) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2017.09.006 · Cited by 351 · see citing works
Rudolph, M. D., Graham, A. M., Feczko, E., Miranda-Dominguez, O., Rasmussen, J. M., Nardos, R., Entringer, S., Wadhwa, P. D., Buss, C., & Fair, D. A. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0128-y · Cited by 374 · see citing works
Self-citationSpatial and Temporal Organization of the Individual Human Cerebellum
Marek, S. A., Siegel, J. S., Gordon, E. M., Raut, R. V., Gratton, C., Newbold, D. J., Ortega, M., Laumann, T. O., Adeyemo, B., Miller, D. B., et al. (2018) · Neuron · doi:10.1016/j.neuron.2018.10.010 · Cited by 291 · see citing works
“Functional networks supporting the maturation of control demonstrate a protracted development throughout adolescence and adulthood (Grayson and Fair, 2017; Luna et al., 2015; Marek et al., 2015).”
Individual Variation in Functional Topography of Association Networks in Youth
Cui, Z., Li, H., Xia, C. H., Larsen, B., Adebimpe, A., Baum, G. L., Cieslak, M., Gur, R. E., Gur, R. C., Moore, T. M., et al. (2020) · Neuron · doi:10.1016/j.neuron.2020.01.029 · Cited by 269 · see citing works
Self-citationMovies in the magnet: Naturalistic paradigms in developmental functional neuroimaging
Vanderwal, T., Eilbott, J. A., & Castellanos, F. X. (2018) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2018.10.004 · Cited by 270 · see citing works
“Appropriate approaches to reporting and balancing motion across ages and conditions are still crucial, as is the use of rigorous approaches to mitigating motion artifact (Grayson and Fair, 2017; Power et al., 2015; Yan et al., 2013).”
The development of brain network hubs
Oldham, S., & Fornito, A. (2018) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2018.12.005 · Cited by 244 · see citing works
The neurobiology of irritable bowel syndrome
Mayer, E. A., Ryu, H. J., & Bhatt, R. R. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-01972-w · Cited by 285 · see citing works
Understanding the role of puberty in structural and functional development of the adolescent brain
Goddings, A., Beltz, A., Peper, J. S., Crone, E. A., & Braams, B. R. (2019) · Journal of Research on Adolescence · doi:10.1111/jora.12408 · Cited by 219 · see citing works
Rasmussen, J. M., Graham, A. M., Entringer, S., Gilmore, J. H., Styner, M. A., Fair, D. A., Wadhwa, P. D., & Buß, C. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.04.020 · Cited by 211 · see citing works
“…developing brain to fully myelinate, based on our findings, the most likely processes to be influenced by maternal IL-6 concentration during pregnancy are pre- and postnatal neurogenesis and changes in axonal coherence (Miranda-Dominguez et al., 2014; Grayson and Fair, 2017; Stafford et al., 2014).”
Self-citationPlasticity and Spontaneous Activity Pulses in Disused Human Brain Circuits
Newbold, D. J., Laumann, T. O., Hoyt, C. R., Hampton, J. M., Montez, D. F., Raut, R. V., Ortega, M., Mitra, A., Nielsen, A. N., Miller, D. B., et al. (2020) · Neuron · doi:10.1016/j.neuron.2020.05.007 · Cited by 174 · see citing works
“Developmental FC changes (Dosenbach et al., 2010; Grayson and Fair, 2017; Nielsen et al., 2019; Smyser et al., 2010) suggest that patterns of coactivation could be accumulated over years, but little is known about the effects of behavioral changes on brain organization over shorter time frames.”
BackgroundA systematic literature review of sex differences in childhood language and brain development
Etchell, A., Adhikari, A., Weinberg, L. S., Choo, A. L., Garnett, E. O., Chow, H. M., & Chang, S.-E. (2018) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2018.04.011 · Cited by 193 · see citing works
Ostlund, B. D., Alperin, B. R., Drew, T. W., & Karalunas, S. L. (2021) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2021.100931 · Cited by 159 · see citing works
Wade, M., Prime, H., Jenkins, J. M., Yeates, K. O., Williams, T. S., & Lee, K. (2018) · Psychonomic Bulletin & Review · doi:10.3758/s13423-018-1459-0 · Cited by 180 · see citing works
“It is now widely accepted that the brain is organized into functional networks, with coordinated activity from multiple regions that support the execution of cognition that drives behavior (Grayson & Fair, 2017).”
BackgroundInterpersonal Neural Entrainment during Early Social Interaction
Wass, S. V., Whitehorn, M., Haresign, I. M., Phillips, E., & Leong, V. (2020) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2020.01.006 · Cited by 175 · see citing works
Resting-state functional MRI studies on infant brains: A decade of gap-filling efforts
Zhang, H., Shen, D. G., & Lin, W. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.07.004 · Cited by 154 · see citing works
Multiscale Structure–Function Gradients in the Neonatal Connectome
Larivière, S., de Wael, R. V., Hong, S., Paquola, C., Tavakol, S., Lowe, A. J., Schrader, D. V., & Bernhardt, B. C. (2019) · Cerebral Cortex · doi:10.1093/cercor/bhz069 · Cited by 132 · see citing works
Functional brain connectivity changes across the human life span: From fetal development to old age
Edde, M., Leroux, G., Altena, E., & Chanraud, S. (2021) · Journal of Neuroscience Research · doi:10.1002/jnr.24669 · Cited by 143 · see citing works
“Age-dependent brain reorganization has been shown through whole-brain FC analyses (Bagarinao et al., 2019; Grayson & Fair, 2017; Sala-Llonch, Bartrés-Faz, & Junqué, 2015; Zuo et al., 2017).”
BackgroundMethodMarek, S. A., Tervo‐Clemmens, B., Nielsen, A. N., Wheelock, M. D., Miller, R. L., Laumann, T. O., Earl, E., Foran, W., Cordova, M., Doyle, O. J., et al. (2019) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2019.100706 · Cited by 122 · see citing works
“Predominant neurodevelopmental models (Di Martino et al., 2014; Grayson and Fair, 2017; Luna et al., 2015) hypothesize that maturation of widely-distributed patterns of restingstate functional connectivity (RSFC) within and between functional networks underlie individual differences in cognitive development and that R…”
BackgroundSelf-citationAssociations between Neighborhood SES and Functional Brain Network Development
Tooley, U. A., Mackey, A. P., Ćirić, R., Ruparel, K., Moore, T. M., Gur, R. C., Gur, R. E., Satterthwaite, T. D., & Bassett, D. S. (2019) · Cerebral Cortex · doi:10.1093/cercor/bhz066 · Cited by 134 · see citing works
“Increased network segregation with development has been widely reported in both structural and functional brain networks [24, 25, 27] and is believed to reflect the increasing segregation and refinement of modular network architecture with age [26], a process that has been found to begin in infancy [48] and continue t…”
BackgroundWakschlag, L. S., Roberts, M. Y., Flynn, R. M., Smith, J. D., Krogh‐Jespersen, S., Kaat, A. J., Gray, L., Walkup, J. T., Marino, B. S., Norton, E. S., et al. (2019) · Journal of Clinical Child & Adolescent Psychology · doi:10.1080/15374416.2018.1561296 · Cited by 142 · see citing works
“Toward this future direction, human connectomics that focus on the maturation of segmentation and integration of brain networks across development also show promise (Grayson & Fair, 2017).”
BackgroundHierarchical functional system development supports executive function
Keller, A. S., Sydnor, V. J., Pines, A. R., Fair, D. A., Bassett, D. S., & Satterthwaite, T. D. (2022) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2022.11.005 · Cited by 123 · see citing works
Self-citationSex differences in functional connectivity during fetal brain development
Wheelock, M. D., Hect, J. L., Hernandez-Andrade, E., Hassan, S. S., Romero, R., Eggebrecht, A. T., & Thomason, M. E. (2019) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2019.100632 · Cited by 126 · see citing works
Motor control of handwriting in the developing brain: A review
Palmis, S., Danna, J., Velay, J., & Longcamp, M. (2017) · Cognitive Neuropsychology · doi:10.1080/02643294.2017.1367654 · Cited by 115 · see citing works
“It is accompanied by changes from local and diffuse connectivity to longer-range functional connectivity (Grayson & Fair, 2017; Kelly et al., 2009): brain regions relevant to the task become more specialized, and better organized in long-range networks, in the course of development (Johnson, 2011).”
BackgroundHuman lifespan changes in the brain’s functional connectome
Sun, L., Zhao, T., Liang, X., Xia, M., Li, Q., Liao, X., Gong, G., Wang, Q., Pang, C., Yu, Q., et al. (2025) · Nature Neuroscience · doi:10.1038/s41593-025-01907-4 · Cited by 127 · see citing works
Subacute effects of the psychedelic ayahuasca on the salience and default mode networks
Pasquini, L., Palhano-Fontes, F., & de Araújo, D. B. (2020) · Journal of Psychopharmacology · doi:10.1177/0269881120909409 · Cited by 115 · see citing works
“and higher cognitive and emotional functions (Fox et al., 2005; Grayson and Fair, 2017; Smith et al., 2009; van den Heuvel and Hulshoff Pol, 2010).”
Nusslock, R., Brody, G. H., Armstrong, C. C., Carroll, A., Sweet, L. H., Yu, T., Barton, A. W., Hallowell, E. S., Chen, E., Higgins, J. P., et al. (2019) · Biological Psychiatry · doi:10.1016/j.biopsych.2019.03.968 · Cited by 100 · see citing works
“Individual differences in rsFC are apparent by late childhood (28).”
BackgroundBarrett, L. F. (2022) · American Psychologist · doi:10.1037/amp0001054 · Cited by 100 · see citing works
“…is strengthened by growing evidence that humans are born with our brains under construction (e.g., Gao et al., 2017; Gilmore et al., 2018; Grayson & Fair, 2017; Zuo et al., 2017), and some of our genes allow our brain development to be biologically shaped by (and coupled to) features of…”
BackgroundKesler, S. R., Rao, A., Blayney, D. W., Oakley-Girvan, I. A., Karuturi, M. S., & Palesh, O. G. (2017) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2017.00555 · Cited by 94 · see citing works
“Modularity analysis indicated that all Model 2 regions were part of the default mode network, consistent with prior studies (Fox et al., 2005; Seeley et al., 2007; Grayson and Fair, 2017).”
ResultCui, Z., Stiso, J., Baum, G. L., Kim, J. Z., Roalf, D. R., Betzel, R. F., Gu, S., Lu, Z., Xia, C. H., He, X., et al. (2020) · eLife · doi:10.7554/elife.53060 · Cited by 87 · see citing works
Basic Units of Inter-Individual Variation in Resting State Connectomes
Sripada, C., Angstadt, M., Rutherford, S. E., Kessler, D. A., Kim, Y., Yee, M. A., & Levina, E. (2019) · Scientific Reports · doi:10.1038/s41598-018-38406-5 · Cited by 80 · see citing works
Bryce, N. V., Flournoy, J. C., Moreira, J. F. G., Rosen, M. L., Sambook, K. A., Mair, P., & McLaughlin, K. A. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118487 · Cited by 83 · see citing works
Lees, B., Squeglia, L. M., McTeague, L. M., Forbes, M. K., Krueger, R. F., Sunderland, M., Baillie, A., Koch, F. C., Teesson, M., & Mewton, L. R. (2020) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2020.09.007 · Cited by 83 · see citing works
“Gordon parcellation was chosen because it comprises major cortical functional networks, covers the entire cortical surface, has been shown to exceed many other network parcellations with respect to homogeneity of BOLD signal within each parcellation (29, 30), and has been used previously in preadolescent populations (…”
MethodFunctional network integration and attention skills in young children
Rohr, C. S., Arora, A. K., Cho, I. Y. K., Katlariwala, P., Dimond, D., Dewey, D., & Bray, S. (2018) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2018.03.007 · Cited by 80 · see citing works
“Most developmental studies have found that cognitive ICNs develop during childhood and well into adolescence (Grayson and Fair, 2017).”
InfluentialDissociable multi-scale patterns of development in personalized brain networks
Pines, A. R., Larsen, B., Cui, Z., Sydnor, V. J., Bertolero, M. A., Adebimpe, A., Alexander‐Bloch, A. F., Davatzikos, C. A., Fair, D. A., Gur, R. C., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-30244-4 · Cited by 79 · see citing works
“These results in part explain the existing heterogeneous literature, which has reported that refinement of both functional network segregation and integration is important for neurocognitive development (Baum et al., 2017; Sherman et al., 2014; Grayson and Fair, 2017; He et al., 2019).”
ResultSelf-citationNeonatal brain injury and aberrant connectivity
Smyser, C. D., Wheelock, M. D., Limbrick, D. D., & Neil, J. J. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.07.057 · Cited by 81 · see citing works
Miller, G. E., Chen, E., Armstrong, C. C., Carroll, A., Ozturk, S., Rydland, K., Brody, G. H., Parrish, T. B., & Nusslock, R. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1810067115 · Cited by 82 · see citing works
Teeuw, J., Brouwer, R. M., Guimaraes, J., Brandner, P., Koenis, M. M. G., Swagerman, S. C., Verwoert, M., Boomsma, D. I., & Pol, H. E. H. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116073 · Cited by 75 · see citing works
Brody, G. H., Yu, T., Nusslock, R., Barton, A. W., Miller, G. E., Chen, E., Holmes, C., McCormick, M., & Sweet, L. H. (2019) · Psychological Science · doi:10.1177/0956797619847989 · Cited by 82 · see citing works
“…across adolescence would interact with receipt of supportive parenting to forecast the rsFC in the CEN and ERN, large neural networks that support cognitive processes affected by poverty and critical for achievement, decision making, affective control, and mental health (Grayson & Fair, 2017).”
BackgroundNaturalistic Language Input is Associated with Resting-State Functional Connectivity in Infancy
King, L. S., Camacho, M. C., Montez, D. F., Humphreys, K. L., & Gotlib, I. H. (2020) · Journal of Neuroscience · doi:10.1523/jneurosci.0779-20.2020 · Cited by 66 · see citing works
Thomason, M. E., Hect, J. L., Waller, R. E., Manning, J. H., Stacks, A. M., Beeghly, M., Boeve, J. L., Wong, K., van den Heuvel, M. I., Hernandez‐Andrade, E. A., et al. (2018) · Development and Psychopathology · doi:10.1017/s095457941800072x · Cited by 75 · see citing works
“Among the earliest to mature are the motor and sensory systems, which support the ability of the infant to interact with and receive input from the world (Fransson, Åden, Blennow, & Lagercrantz, 2011; Gao et al., 2015; Grayson & Fair, 2017).”
BackgroundBrookes, M. J., Groom, M. J., Liuzzi, L., Hill, R. M., Smith, H. J. F., Briley, P. M., Hall, E. L., Hunt, B. A. E., Gascoyne, L. E., Taylor, M. J., et al. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.03.008 · Cited by 62 · see citing works
The Age of Reason: Functional Brain Network Development during Childhood
Tooley, U. A., Park, A. T., Leonard, J., Boroshok, A. L., McDermott, C. L., Tisdall, M. D., Bassett, D. S., & Mackey, A. P. (2022) · Journal of Neuroscience · doi:10.1523/jneurosci.0511-22.2022 · Cited by 74 · see citing works
Karahanoğlu, F. I., & Ville, D. V. D. (2017) · Current Opinion in Biomedical Engineering · doi:10.1016/j.cobme.2017.09.008 · Cited by 61 · see citing works
Age-related differences in resting-state functional connectivity from childhood to adolescence
Sanders, A. F. P., Harms, M. P., Kandala, S., Marek, S. A., Somerville, L. H., Bookheimer, S. Y., Dapretto, M., Thomas, K. M., Essen, D. C. V., Yacoub, E. S., et al. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhad011 · Cited by 67 · see citing works
Ellwood-Lowe, M. E., Whitfield, S., & Bunge, S. A. (2021) · Nature Communications · doi:10.1038/s41467-021-27336-y · Cited by 65 · see citing works
Network-specific selectivity of functional connections in the neonatal brain
Sylvester, C. M., Kaplan, S., Myers, M. J., Gordon, E. M., Schwarzlose, R. F., Alexopoulos, D. K., Nielsen, A. N., Kenley, J. K., Meyer, D., Yu, Q., et al. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac202 · Cited by 59 · see citing works
Self-citationSripada, C., Angstadt, M., Taxali, A., Clark, D. A., Greathouse, T., Rutherford, S. E., Dickens, J., Shedden, K., Gard, A. M., Hyde, L. W., et al. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01704-0 · Cited by 56 · see citing works
“During early adolescence, brain networks exhibit substantial maturation [21] and cognitive abilities rapidly improve [22].”
BackgroundTuresky, T. K., Vanderauwera, J., & Gaab, N. (2020) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2020.100893 · Cited by 62 · see citing works
Cotter, D. L., Campbell, C. E., Sukumaran, K., McConnell, R., Berhane, K. T., Schwartz, J. D., Hackman, D. A., Ahmadi, H., Chen, J., & Herting, M. M. (2023) · Environment International · doi:10.1016/j.envint.2023.108001 · Cited by 58 · see citing works
Wang, C., Hu, Y., Weng, J., Chen, F., & Liu, H. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116334 · Cited by 57 · see citing works
Steiner, L., Federspiel, A., Slavova, N., Wiest, R., Grunt, S., Steinlin, M. I., & Everts, R. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117361 · Cited by 53 · see citing works
Circuits for social learning: a unified model and application to autism spectrum disorder
DeMayo, M. M., Young, L. J., Hickie, I. B., Song, Y. J. C., & Guastella, A. J. (2019) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2019.09.034 · Cited by 52 · see citing works
“There have been many high caliber studies identifying basic mechanisms and broad clinical factors that facilitate social learning (Fitch et al., 2016; Gabard-Durnam et al., 2018; Graham et al., 2016; Grayson and Fair, 2017; Grossmann, 2015; Pitcher et al., 2017; Vasung et al., 2010).”
BackgroundInter-subject synchrony as an index of functional specialization in early childhood
Moraczewski, D., Chen, G., & Redcay, E. (2018) · Scientific Reports · doi:10.1038/s41598-018-20600-0 · Cited by 47 · see citing works
Spatial and spectral trajectories in typical neurodevelopment from childhood to middle age
Hunt, B. A. E., Wong, S. M., Vandewouw, M. M., Brookes, M. J., Dunkley, B. T., & Taylor, M. J. (2019) · Network Neuroscience · doi:10.1162/netn_a_00077 · Cited by 51 · see citing works
García, J. M. P., Suárez‐Suárez, S., Doallo, S., & Cadaveira, F. (2022) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2022.104637 · Cited by 51 · see citing works
“This task, defined as a concept categorization task, provides a measure of automatic associations used to assess unconscious bias (Greenwald et al., 1998).”
BackgroundSakurai, T., & Gamo, N. J. (2018) · Neurobiology of Disease · doi:10.1016/j.nbd.2018.11.007 · Cited by 49 · see citing works
Emerging neurodevelopmental perspectives on mathematical learning
Menon, V., & Chang, H. (2021) · Developmental Review · doi:10.1016/j.dr.2021.100964 · Cited by 58 · see citing works
Dynamic functional connectivity profile of the salience network across the life span
Snyder, W. E., Uddin, L. Q., & Nomi, J. S. (2021) · Human Brain Mapping · doi:10.1002/hbm.25581 · Cited by 49 · see citing works
“…largescale functional brain networks markedly remodel throughout all stages of life (Bagarinao et al., 2019; Faghiri, Stephen, Wang, Wilson, & Calhoun, 2019; Grayson & Fair, 2017; Gu et al., 2015; Supekar, Musen, & Menon, 2009; Váša et al., 2020; Vij, Nomi, Dajani, & Uddin, 2018; Xia et al., 2019).”
Adolescent development of cortical oscillations: Power, phase, and support of cognitive maturation
Marek, S., Tervo-Clemmens, B., Klein, N., Foran, W., Ghuman, A. S., & Luna, B. (2018) · PLOS Biology · doi:10.1371/journal.pbio.2004188 · Cited by 48 · see citing works
Imaging the neural underpinnings of freezing of gait in Parkinson’s disease
Bardakan, M. M., Fink, G. R., Zapparoli, L., Bottini, G., Paulesu, E., & Weiss, P. H. (2022) · NeuroImage: Clinical · doi:10.1016/j.nicl.2022.103123 · Cited by 51 · see citing works
“The parameters derived from rs-fMRI indicate a correlation (coupled) or an anti-correlation (anticoupled) in the activity of the examined specific functional neural networks/ICNs (Biswal et al., 1995; Grayson and Fair, 2017).”
BackgroundMorris, A. S., Squeglia, L. M., Jacobus, J., & Silk, J. S. (2018) · Journal of Research on Adolescence · doi:10.1111/jora.12379 · Cited by 48 · see citing works
“Advanced methodological and computational approaches have improved the reliability of taskbased fMRI developmental studies (Herting, Gautam, Chen, Mezher, & Vetter, 2017), and have improved data quality (Grayson & Fair, 2017).”
BackgroundUnderstanding Vulnerability and Adaptation in Early Brain Development using Network Neuroscience
Graham, A. M., Marr, M. C., Buß, C., Sullivan, E. L., & Fair, D. A. (2021) · Trends in Neurosciences · doi:10.1016/j.tins.2021.01.008 · Cited by 49 · see citing works
“How will consideration of individualized network architecture influence understanding of the effects of ELS on developing RSNs and global network topology?”
BackgroundInfluentialSelf-citationPark, A. T., Tooley, U. A., Leonard, J., Boroshok, A. L., McDermott, C. L., Tisdall, M. D., & Mackey, A. P. (2020) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2020.100909 · Cited by 46 · see citing works
“Early stress exposure is associated with heightened risk for poor mental health later in life (Green et al., 2010; McLaughlin et al., 2012).”
BackgroundVijayakumar, N., Ball, G., Seal, M. L., Mundy, L. K., Whittle, S., & Silk, T. J. (2021) · Scientific Reports · doi:10.1038/s41598-021-88918-w · Cited by 44 · see citing works
Using multiple short epochs optimises the stability of infant EEG connectivity parameters
Haartsen, R., van der Velde, B., Jones, E. J. H., Johnson, M. H., & Kemner, C. (2020) · Scientific Reports · doi:10.1038/s41598-020-68981-5 · Cited by 46 · see citing works
“In addition, developmental changes in connectivity strengths (both functional and structural) may also play a role here 70,73,74 .”
Default mode network scaffolds immature frontoparietal network in cognitive development
Chen, M., He, Y., Lei, H. C., Xu, J., Tian, T., Peng, S., Zhao, G., Lu, J., Zhao, Y., Zhao, H., et al. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac414 · Cited by 52 · see citing works
Demeter, D. V., Engelhardt, L. E., Mallett, R., Gordon, E. M., Nugiel, T., Harden, K. P., Tucker–Drob, E. M., Lewis‐Peacock, J. A., & Church, J. A. (2019) · iScience · doi:10.1016/j.isci.2019.100801 · Cited by 38 · see citing works
Camacho, M. C., Nielsen, A. N., Balser, D., Furtado, E., Steinberger, D. C., Fruchtman, L., Culver, J. P., Sylvester, C. M., & Barch, D. M. (2023) · Nature Neuroscience · doi:10.1038/s41593-023-01358-9 · Cited by 49 · see citing works
Cheng, T. W., Mills, K. L., Miranda-Domínguez, Ó., Zeithamová, D., Perrone, A. J., Sturgeon, D., Ewing, S. W. F., Fisher, P. A., Pfeifer, J. H., Fair, D. A., et al. (2020) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2020.100894 · Cited by 47 · see citing works
Self-citationDevelopment of Network Topology and Functional Connectivity of the Prefrontal Cortex.
Lopez, K. C., Kandala, S., Marek, S. A., & Barch, D. (2019) · Cerebral Cortex · doi:10.1093/cercor/bhz255 · Cited by 38 · see citing works
Neural circuits regulating visceral pain
Chang, X., Zhang, H., & Chen, S. (2024) · Communications Biology · doi:10.1038/s42003-024-06148-y · Cited by 51 · see citing works
Tooley, U. A., Bassett, D. S., & Mackey, A. P. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118843 · Cited by 38 · see citing works
Predicting Brain Age Based on Spatial and Temporal Features of Human Brain Functional Networks
Zhai, J., & Li, K. (2019) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2019.00062 · Cited by 42 · see citing works
“…functioning performance is closely related to age and much work has been done trying to disclose how aging affects integration of information within and between functional networks (Song et al., 2014; Geerligs et al., 2015a; Bassett and Sporns, 2017; Damoiseaux, 2017; Grayson and Fair, 2017).”
BackgroundComputing personalized brain functional networks from fMRI using self-supervised deep learning
Li, H., Srinivasan, D., Zhuo, C., Cui, Z., Gur, R. E., Gur, R. C., Oathes, D. J., Davatzikos, C. A., Satterthwaite, T. D., & Yong Fan, A. (2021) · Medical Image Analysis · doi:10.1016/j.media.2023.102756 · Cited by 46 · see citing works
Frew, S., Samara, A., Shearer, H., Eilbott, J. A., & Vanderwal, T. (2022) · PLoS ONE · doi:10.1371/journal.pone.0265112 · Cited by 39 · see citing works
“From late childhood to early adulthood, nodes from the somatomotor network were most predictive of age [32, 33].”
BackgroundGaffrey, M. S., Barch, D. M., Luby, J. L., & Petersen, S. E. (2020) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2020.01.024 · Cited by 39 · see citing works
“Functional connectivity measured using rs-fMRI has been suggested to reflect the stability and integrity of connections between brain regions, including changes in these features across development.(20) Because a large body of research has consistently supported the importance of the amygdala in cortico-limbic models…”
MethodKesler, S. R., Ogg, R. J., Reddick, W. E., Phillips, N. S., Scoggins, M., Glass, J. O., Cheung, Y. T., Pui, C., Robison, L. L., Hudson, M. M., et al. (2018) · Brain Connectivity · doi:10.1089/brain.2017.0574 · Cited by 47 · see citing works
“Previous studies demonstrate that the brain network is decomposable into distinct modules or subnetworks representing known functional components (Chen et al., 2013; Grayson and Fair, 2017).”
Stability and similarity of the pediatric connectome as developmental measures
Vanderwal, T., Eilbott, J. A., Kelly, C. A. M., Frew, S., Woodward, T. S., Milham, M. P., & Castellanos, F. X. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117537 · Cited by 39 · see citing works
The handwriting brain in middle childhood
Palmis, S., Velay, J., Habib, M., Anton, J., Nazarian, B., Sein, J., & Longcamp, M. (2020) · Developmental Science · doi:10.1111/desc.13046 · Cited by 42 · see citing works
“More generally, the sensorimotor networks are already mature in children aged 6-7 years (Grayson & Fair, 2017; James & Kersey, 2018; Zielinski et al., 2010), and they vary little between ages 6 and 10 (Grayson & Fair, 2017; Zielinski et al., 2010b).”
BackgroundFine-grained functional parcellation maps of the infant cerebral cortex
Wang, F., Zhang, H., Wu, Z., Hu, D., Zhou, Z., Girault, J. B., Wang, L., Lin, W., & Li, G. (2023) · eLife · doi:10.7554/elife.75401 · Cited by 40 · see citing works
Development of top-down cortical propagations in youth
Pines, A. R., Keller, A. S., Larsen, B., Bertolero, M. A., Ashourvan, A., Bassett, D. S., Cieslak, M., Covitz, S. C., Yong Fan, A., Feczko, E., et al. (2023) · Neuron · doi:10.1016/j.neuron.2023.01.014 · Cited by 38 · see citing works
Self-citationDeJoseph, M., Herzberg, M. P., Sifre, R. D., Berry, D., & Thomas, K. (2021) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2021.101043 · Cited by 44 · see citing works
“voluntary top-down attentional control as well as detecting and filtering salient stimuli (Grayson and Fair, 2017).”
Default Mode Network Maturation and Environmental Adversities During Childhood
Rebello, K., Moura, L. M., Pinaya, W. H. L., Rohde, L. A., & Sato, J. R. (2018) · Chronic Stress · doi:10.1177/2470547018808295 · Cited by 42 · see citing works
“On the other hand, evidences of environment-gene interactions have identified regularities in neurodevelopmental trajectories of individuals among diverse populations.10,60,123–125 Furthermore, most studies are based on time-stationary patterns of functional while time-varying connectivity analyses might be a valuable…”
BackgroundInfluentialNiebaum, J. C., Chevalier, N., Guild, R. M., & Munakata, Y. (2020) · Cognitive Affective & Behavioral Neuroscience · doi:10.3758/s13415-020-00832-2 · Cited by 40 · see citing works
Sleep to Internalizing Pathway in Young Adolescents (SIPYA): A proposed neurodevelopmental model
Akbar, S. A., Mattfeld, A. T., Laird, A. R., & McMakin, D. L. (2022) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2022.104780 · Cited by 38 · see citing works
Rinat, S., Izadi‐Najafabadi, S., & Zwicker, J. G. (2020) · NeuroImage Clinical · doi:10.1016/j.nicl.2020.102309 · Cited by 43 · see citing works
“Resting-state networks are highly reproducible,[53] and are found consistently across participants and groups, and in different developmental stages.[51-54] Another advantage of rsMRI is the relative simplicity of data collection due to minimal compliance demands, making it a perfect candidate for investigation of neu…”
Progressive Stabilization of Brain Network Dynamics during Childhood and Adolescence
Lei, T., Liao, X., Chen, X., Zhao, T., Xu, Y., Xia, M., Zhang, J., Xia, Y., Sun, X., Wei, Y., et al. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab263 · Cited by 36 · see citing works
Functional connectome through the human life spanPreprint
Sun, L., Zhao, T., Liang, X., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.09.12.557193 · Cited by 38 · see citing works
“Given the dramatic functional changes that occur during early development 57 , we prioritized the generation of finer age-specific atlases for these stages compared to the later life stages.”
MethodProfiling intra- and inter-individual differences in brain development across early adolescence
Bottenhorn, K. L., Cardenas‐Iniguez, C., Mills, K. L., Laird, A. R., & Herting, M. M. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120287 · Cited by 35 · see citing works
“…is foundational to studies of inter-individual variability and has implications for cognitive development (Battista et al., 2018; Blakemore and Choudhury, 2006), neurodevelopmental disorders (Grayson and Fair, 2017), and the emergence of psychopathology (Ferschmann et al., 2022; Paus et al., 2008).”
Foo, H., Mather, K. A., Jiang, J., Thalamuthu, A., Wen, W. X., & Sachdev, P. S. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.03.011 · Cited by 35 · see citing works
Sripada, C., Gard, A. M., Angstadt, M., Taxali, A., Greathouse, T., McCurry, K. L., Hyde, L. W., Weigard, A. S., Walczyk, P., & Heitzeg, M. M. (2022) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2022.101164 · Cited by 31 · see citing works
“The brain is a highly plastic organ with abundant capacities to learn/relearn, modify, and adjust, consistent with the observation that substantial neural change and reorganization extends through late adolescence up to young adulthood (59, 60).”
BackgroundEarly and late development of hub connectivity in the human brain
Oldham, S., Ball, G., & Fornito, A. (2021) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2021.10.010 · Cited by 30 · see citing works
Hutton, J. S., Dudley, J., Horowitz-Kraus, T., Dewitt, T., & Holland, S. (2019) · Brain Connectivity · doi:10.1089/brain.2019.0679 · Cited by 31 · see citing works
“…DAN and VAN is present by age 2 years and stabilized by adolescence (Grayson and Fair, 2017; Lewis et al., 2018), shaped by environmental factors (Grayson and Fair, 2017; Petersen and Posner, 2012; Rohr et al., 2018), notably cognitive stimulation in the home (Farrant and Uddin, 2015; Knudsen,…”
BackgroundMills, B. D., Grayson, D. S., Shunmugavel, A., Miranda-Domínguez, Ó., Feczko, E., Earl, E., Neve, K. A., & Fair, D. A. (2018) · Journal of Neuroscience · doi:10.1523/jneurosci.2910-17.2018 · Cited by 36 · see citing works
Self-citationControl networks of the frontal lobes
Marek, S. A., & Dosenbach, N. U. F. (2019) · Handbook of clinical neurology · doi:10.1016/b978-0-12-804281-6.00018-5 · Cited by 37 · see citing works
Anandakumar, J., Mills, K. L., Earl, E., Irwin, L., Miranda-Domínguez, Ó., Demeter, D. V., Walton-Weston, A., Karalunas, S. L., Nigg, J. T., & Fair, D. A. (2018) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2018.07.003 · Cited by 36 · see citing works
Self-citation
- Authors
- Grayson, D. S., & Fair, D. A.
- Affiliations
- Oregon Health & Science University (US)
- Corresponding author
- Fair, Damien A.
- ORCID
- Fair, Damien A.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2017-10
- Volume
- 160
- Pages
- 15-31
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC5538933
- OpenAlex
- W2585998010
- Cited by
- 411
- References
- 259
- Citations by year
- 2026: 35 · 2025: 38 · 2024: 58 · 2023: 45 · 2022: 51 · 2021: 47 · 2020: 49 · 2019: 42 · 2018: 38 · 2017: 8
- FWCI
- 4.19
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (am, 397 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- NeuroImage (acceptedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Autism Speaks Dennis Weatherstone Predoctoral Fellowship (9591)
- DeStefano Family Foundation
- Gates Foundation
- MacArthur foundation
- National Institutes of Health (UG3 OD023349, R01 MH105538, R01 MH096773, R01MH107508, P60-AA010760, R01 MH086654, R00MH091238)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- functional brain networks, developmental trajectories, resting-state functional connectivity, structural connectivity, cognitive development, network science
- MeSH terms
- Brain, Cognition, Humans, Magnetic Resonance Imaging, Neural Pathways, Neuroimaging
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