Abstract
Default mode network (DMN) plays a central role in cognition and brain disorders. It has been shown that adverse environmental conditions impact neurodevelopment, but how these conditions impact in DMN maturation is still poorly understood. This article reviews representative neuroimaging functional studies addressing the interactions between DMN development and environmental factors, focusing on early life adversities, a critical period for brain changes. Studies focused on this period of life offer a special challenge: to disentangle the neurodevelopmental connectivity changes from those related to environmental conditions. We first summarized the literature on DMN maturation, providing an overview of both typical and atypical development patterns in childhood and early adolescence. Afterward, we focused on DMN changes associated with chronic exposure to environmental adversities during childhood. This summary suggests that changes in DMN development could be a potential allostatic neural feature associated with an embodiment of environmental circumstances. Finally, we discuss about some key methodological issues that should be considered in paradigms addressing environmental adversities and open questions for future investigations.
Keywords: default mode network, connectivity, environmental exposure, typical brain development
Introduction
The investigation on how environmental conditions impact childhood development and, by extension, burden the later adult life is of fundamental importance. In fact, 13% of the world's population lives in extreme poverty, with 800 million people living under starving conditions, among other adversities, such as the lack of basic sanitation.1 Neurodevelopmental research has begun to assess differential negative aspects of environmental adversities that children live in poverty face,2,3 like social disparity,4 low socioeconomic status,5 early life stress,6 abuse, neglect,7 witnessing domestic violence or other kinds of negative parental/relative conflicts,8–10 and living in urban environments.11 These studies are related to both acute and chronic exposure on lifespan. These forms of adversity are also associated to many psychiatric disorders, as, for example, those disorders related to acute stress experiences as early life trauma due to child abuse and child neglect or maltreatment and posttraumatic stress disorders;12–16 socioeconomic issues; anxiety and depression disorders;17,18 and schizophrenia.19
It is of special interest to know when, how, and why these environmental adversities could impact neurodevelopment, especially during the different phases of childhood when brain changes are taking place.20 From this perspective, neuroimaging proved to be a useful tool for non-invasive in vivo structural and functional brain investigation. Association between environmental conditions and brain structure and function was reported in previous studies.2,16,21–26 However, only recently, few investigations have explored the influence of these conditions on brain functional connectivity and its developmental trajectory.3,27,28 The analyses of large-scale networks were demonstrated to be a useful framework to comprehend the underlying complexity of multiple brain subsystems not only in the study of cognitive functions but also in mental disorders.29–30
Considering the multiple brain subnetworks, the investigation of the default mode network (DMN)31,32 is of special interest given its pivotal role in neuroimaging studies and also in brain disorders.33,34 Atypical patterns of DMN connectivity have been associated to a wide range of psychiatric and developmental disorders such as posttraumatic stress disorder,12 autism,35 and others.34,36 Findings based on clinical samples provided insightful contributions to enhance the comprehension of DMN functioning.
Beyond its attributed role in mental disorders, alterations in DMN activity have also been associated to enduring outcomes by growing up under stressful conditions, according to retrospective reports in adult's research.3,15,37–38 However, the studies based on developmental samples (i.e., with children and adolescent samples) are still scarce. These samples should be taken in consideration given the changes occurring in this network during development.27,39–41
In this review, we aim to provide an overview and perspectives of studies on the association between environmental adversities and the DMN maturation. In order to define the scope of this study, it is important to clarify that (i) our main concern was to present representative studies in this topic (and not a systematic review); (ii) since the literature on DMN and psychiatric disorders is massive, we will not focus on specific findings for each condition. The emphasis on mental disorders may bias the interpretation of environmental exposure42 on DMN and also constrain the generalizability of the findings.
We organized this review as it follows: First, we introduce the DMN and present a brief description of its typical development from childhood to adolescence. Next, we present findings describing how early adversities may potentially impact on DMN development, structure, and functioning. Finally, we present some perspectives and discuss knowledge gaps regarding future research efforts.
Default Mode Network
The DMN is a group of functionally connected brain regions that exhibit higher levels of activity during rest than during performance of externally oriented cognitive tasks.32,33,43 Moreover, functional connectivity studies showed that the activity of these regions is negatively correlated with the activity of cognitive-control networks.44–46 Consequently, DMN has been be involved in a variety of high-level functions, such as attention and inhibitory control,40,47,48 social cognition,49 episodic memory,50 and self-related processes.51 There is still a great debate regarding the assignment of these functions53–54 although most of them could be interpreted as dimensions of internally focused thoughts.43
Altered DMN connectivity related to deficits on those assigned cognitive functions34 has been described in psychiatric and neurological disorders, such as in psychoses,55–57 mood disorders,58–60 bipolar disorder,61 attention deficit/hyperactivity disorder (ADHD),62–65 autism,35,66 schizophrenia,44,67 and bipolar disorder.68
One potential biological underpinning of DMN deregulations is identified as its orchestrated functioning with cognitive control regions.34,45,48,69 The DMN activity is typically suppressed during demanding cognitive tasks directed toward external environment and goal-directed activity45 and vice-versa. The unbalance between the activity of DMN and cognitive control network (i.e., a disruption in the functional connectivity between regions from these two networks) was related to autism disorder35,66 and to ADHD.63–64,70 Besides that, DMN hyperconnectivity was identified in mood disorders such depression58,59,71 and schizophrenia.72,57 Sato et al.73 and Castellanos et al.74 reported a decreased functional connectivity between anterior cingulate cortex and DMN regions in adults with ADHD. As mentioned in the Introduction section, the literature of DMN and psychiatric disorders is massive, and we decided to focus on other issues in this review.
Although the DMN is well-established in adults,33 the maturation trajectory from childhood to adulthood is still not fully understood. Its maturation occurs mainly in the postnatal period (as it occurs in many other large-scale networks); therefore, it could be potentially influenced by environmental factors during childhood. Actually, only 23% of the functional connectivity within DMN was found heritable.10 Many studies have suggested that environmental conditions are related to brain structure.2,16,22,23,25,75,76 However, there are few investigations exploring their associations with changes in functional connectivity.
Age-Effect in the DMN: From Childhood to Adolescence
In the adult brain, DMN nodes consist mainly of the ventral medial prefrontal cortex (vMPFC), dorsal medial prefrontal cortex (dMPFC), lateral temporal cortex (LTC), inferior parietal lobule (IPL), posterior cingulate cortex/retrosplenial (PCC/Rsp), and hippocampal formation (HF+), which are densely functionally connected to each other within the DMN.33 This network undergoes a gradual developmental change on maturation.47 Gao et al.77 and Fransson et al.78 were the first researchers to report the postnatal DMN. The authors describe that full-term babies presented a “proto-default network,” with a resting-state functional connectivity between the medial and lateral parietal cortex but no significant functional connectivity between the medial prefrontal and the temporal cortices.
Gao et al.,77 in a longitudinal study with infants from birth to the second year of life, found similar results to the ones previously described. They report that from birth to 2 weeks old, the DMN presents few connected regions, with additional regions being connected through the following 2 years toward the pattern found in adults (including MPFC, PCC/Rsp, IPL, LTC, and hippocampal regions). They highlight that until the 2 years old, the strongest connection across all brain regions was between PCC and MPFC. Both Gao et al.77 and Fransson et al.78 described a sparse and fragmented connectivity between DMN regions (i.e., weaker internal connectivity). This network immaturity persists until the 7 to 9 years old, at least.47 They speculate that these network changes may be associated to the emerging self-consciousness and self-referential activity, one of most attributed functions to DMN.
From 3 to 5 years, changes were described in relation to the hemispheric dominance in the DMN subsystems.79 A decreased right hemispheric dominance (between the medial temporal lobe and dMPFC) is observed at age 3, becoming more bilateral at age 5. The stronger interactions between dMPFC and temporal lobe in 5-year-olds support the development of social cognition, possibly as an outcome of environmental adaptation and other complex mental abilities. The network is still primitive in its functional structure when compared to adults.80
According to Fair et al.,47 DMN regions are still sparsely functionally connected until 7 to 9 years old, in which the connections between vMPFC, PCC, and parietal regions are minimal.47 This study highlights that the typical maturation of DMN may reflect a reduction in short-range connections strength and an increasing strength of long-range connectivity between its anterior and posterior regions. Besides, in the early adolescence (13–14 years old), the increasing connectivity within DMN is still an ongoing process.41,81
From 7 to 15 years old, Sato et al.41 showed the strengthening of functional connectivity between anterior–posterior regions (predominantly between the anterior and vMPFC/lateral parietal and Rsp cortices), highlighting that the anterior MPFC is especially sensitive to the maturation process. In a longitudinal study with early adolescents (10–13 aged), Sherman et al.81 found robust connections between MPFC and posterior parietal cortex, and an increased anticorrelation between DMN and central executive networks over development. Both studies described higher hierarchical DMN functional organization and integration between the posterior and anterior modules over development, toward a similar pattern of adults. These changes are accompanied by the developments in social and cognitive domains such as social learning, usually associated with increasingly sensitive to social cues and peers relationships, from family to society.82 Finally, at age 21, it is expected that DMN is fully integrated.83
In summary, these findings suggest that DMN undergoes developmental changes on maturation, reflecting a long-term trajectory from childhood to adulthood. However, the complex interplay between environmental demands and DMN maturation and how these could be related to an atypical or aberrant development pattern remains unclear.65
Environmental Adversities During Childhood and the DMN
It is established that the early onset of mental disorders can be related to atypical neurodevelopment processes,84 which in turn have been impacted by the exposure to environmental conditions.14,85,89 Many studies focused on DMN alterations in adult populations within mental disorders and also in cognitive function.34,86–90 However, few studies explored the potential enduring effects of adverse situations in childhood on the DMN.2,27,28,91
Structural findings have described the impact of early childhood negative environmental experiences on the brain, including affected areas which might be relevant for DMN functioning.2,9,24,25,76,92–94 For example, low family income is correlated with a decreased volume of the left hippocampus, bilateral IPL, insula cortex, inferior frontal gyrus, right occipital, and MPFC.25 These regions are involved in the DMN network functioning and related to various language and executive functions.76
Recently, some studies investigated the associations between adverse environmental factors, such as low socioeconomic status, poverty and other similar material deprivations, and changes in the functional connectivity involving DMN regions.3,28,95 Adults who experienced chronic poverty in childhood exhibited reduced DMN regions connectivity, as well as higher cortisol levels in anticipation of social stress.3
On the other hand, the interplay between adversities and neurodevelopment does not seem to be univocal. In other words, adversities may result in distinct direction of brain connectivity changes. Family environment adversities, such as exposure to parental aggressive behavior/conflict, were associated with hyperconnectivity between the core DMN regions (PCC/anterior MPFC) and the amygdala in children aged 6 to 12 months.28 In this context, the author interpreted DMN connectivity alterations as a mediator between higher conflict and higher negative emotionality, suggesting resilience or adequate coping with adverse experiences.38,96 In a longitudinal study following 65 children from birth to the first year of life, higher levels of income and maternal education were associated with higher within-network connectivity.27 Similarly, supportive and warmth parental practices have been suggested as a protective buffer against disturbances in the DMN development of children97 and adolescents.98 Nevertheless, it is still unknown whether the increased or decreased connectivity might be related to impairment or compensatory mechanism in the network in face of environmental demands.
Resilience
We have shown that exposure to environmental adversities is related to neurophysiological costs of adaptation to these environmental demands, specifically the potential neural embodiment in DMN. In this case, embodiment refers to the way in which an organism biologically incorporates the world around it, including societal and ecological situations.99
When children are chronically exposed to environmental adversities, their allostatic responses can be excessively required through development. This may lead to a load with potentially negative health outcomes through the physiological wear and tear, the so-called allostatic load.100–102 Allostatic process is a mechanism to establish a new (allostatic) accommodation when facing a challenge,103 which results in adaptive shifts in a broad range of physiological systems matching the internal functioning to the environmental demands.104 Specifically considering the neural systems, some of these adaptive shifts correspond to structural and functional changes in subcortical and cortical brain regions, such as connectivity changes between the amygdala, hypothalamic–pituitary–adrenal (HPA) axis, and DMN connectivity during development.3,28 Graham et al.28 reported that familiar interactions are associated to DMN functional connectivity in children (6–12 months of age). Children exposed to parental aggressive behavior/conflict showed stronger connectivity between the core DMN regions (PCC/anterior MPFC) and amygdala, which were identified as a mediator between higher conflict and higher negative emotionality. In adults, Philip et al.38 described analogous findings. Those who were exposed to a chronic stressful childhood had similar increased connectivity between MPFC and amygdala and a decreased connectivity within the DMN. These changes could represent a response to the environmental challenges, once they could preserve their mental health and cope adequately.
Eventually, this load potentially increases the risk of developing physical and mental illnesses when the threshold of an individual is exceeded, as we have briefly described in disorders in which DMN is involved. In other words, their allostatic overload could lead to cognitive dysfunctions.
However, despite facing severe adversities in life, such as deprivation or many types of threats, some individuals are still able to maintain good mental and physical health, the so-called resilients.96 According to Lupien et al.,105 the nature of the stress response elicited in this situations (negative or positive) relates more to the perception and interpretation than to the physical consequences. In this context, we conjecture that the investigation of DMN developing in individuals under these circumstances might be helpful to comprehend how overload and threshold are modulated and related to the resilience capacity.
According to Patriat et al.,106 environmental challenges are processed by DMN through its mediation of information flow between subcortical and cortical regions. The DMN might integrate salient external or internal information with the current affective individual experience and perception.107,108 Such an attribution of meaning to personal experiences has been called self-referential activity,109 an important cognitive function. This function is expected to emerge after the first 12 months of life.77 Through self-referential activity, individuals label their experiences as negative or positive (producing allostatic overload when they are excessively negative) according to their perceived social standing.37 Empirical findings suggest that parental relationships modulate these perception, as they have been related to DMN development37,97,98,114 and since the parents provide the earliest affective experiences of the children.
Perspectives
Although it is still not possible to disentangle whether abnormal DMN connectivity is the cause or the outcome of many mental disorders, the few available studies support that stress and environmental adversities are important factors to be considered in the DMN maturation. In this context, it is necessary to achieve a more in-depth understanding of how adverse environmental factors could affect DMN development. The first and most direct association is to account adversities acting as risk factors to the typical DMN connectivity and by extension, playing an important role in mental disorders; the second is to investigate the correlation between resilience and DMN. Regarding future studies, it is recommended some cautionary considerations when framing the environmental adversities.
First, there is a clear challenge in objectively defining what a stressful or an adverse environmental experience is. One possibility is to take into account the biological evidences related to physiological stress responses through HPA-axis activity114 and their possible associations with structural or functional brain alterations.3,6, Previous findings in adults have shown that the effects of chronic exposure to stress in MPFC, an important DMN node, are associated with impairments in long-range connectivity across the brain.112
Recent empirical findings investigate the possible neurochemical underpinnings of DMN activity, especially focusing on neurotransmitters such as serotonin,115 glutamate, and gamma-aminobutyric acid116–118 and exposure to stress conditions.119 The potential association between these neurotransmitters and the DMN is still an open question. One point of particular relevance is to understand the mechanisms driving DMN neurochemical modulation in typical development in children and adolescents and the effects of the exposure to adverse life experiences.
Considering the nature of child development, it is important to reinforce the crucial role of longitudinal studies, which might provide more detailed inferences on maturation. This is necessary to evaluate how exposure levels of adversity change across development. It is also important to take in account that there are some limitations of DMN studies in children. It is well-established that head motion may bias inferences on age-effect.119 Motion artifacts weaken DMN long-range connections and strength short-range connections in visual regions.120 Both situations require methodological procedures to minimize errors, such as report and account motion in the comparison between individuals or between groups,119 and volume censoring technique (scrubbing) to identify scans more affected by motion.120
It is also necessary to take into account the functional–anatomic heterogeneity,69,121,122 since the maturation of DMN is not homogeneous.41,65 Individual variability and heterogeneity of functional networks are crucial points to be considered. 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 methodological tool.125–127 Indeed, there are evidences that temporal instability exhibited by the functional connectome allows the switch between multiple configurations within a scanning session.128 Specifically, Chang et al.128 recommend the study of temporal dynamics between DMN regions, reinforcing that the majority of studies have only tested stationary relationships between resting-state networks, including the study of the variability of the strength of the anticorrelation between DMN and executive control networks. Calhoun et al.128 proposed the term “chronnectome” to describe these metrics that enable us to have a dynamic view of coupling of time-varying levels of correlated activity between spatial and temporal properties of brain regions.
Since the functional connectivity expresses complex and multivariate features, the use of machine learning methods would be a promising approach. A rising number of studies have used this approach combined with functional connectivity.129–132 For example, Dosenbach et al.130 trained a machine-learning model to make predictions about individuals' brain maturity across development, achieving an accuracy of 91%.
Second, the evaluation of environmental exposure effects on DMN maturation is important to account for possible variables as confounders or covariates in studies, such as (i) the time when environmental adversities exposure occurs and their duration; (ii) sex differences, since they might be potentially related to differences in perception of stressful events in puberty and adolescence.133 In a study with 900 children from 0 to 5 years old, Duncan, Brooks-Gunn, and Klebanov134 found that living in poverty for relatively short periods is less detrimental than longer ones through development. This finding suggests that chronicity effects may lead to different outcomes. Therefore, it is also important to consider that beyond the functional DMN analysis, greater accuracy will be provided about the environmental exposure if researchers also investigate their relationships to behavioral aspects.39
Conclusion
In summary, considering that environmental factors have been strongly associated with many psychiatric disorders, further investigation of their relationship with DMN developmental trajectories is of pivotal importance. To set up these paradigms of investigation, it is fundamental to define more accurately the environmental adversities. The better comprehension of these environmental influences on the DMN development should improve mental health knowledge, supporting more adequate decisions in interventions in the social/environmental policies and educational and parental practices.
Acknowledgments
The authors are grateful to Juliana Preto van Noort and Piter Keo for language revision. The authors are especially thankful to the three referees for their substantial contribution to improve this manuscript.
Declaration of Conflicting Interests
The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Luis A. Rohde has received grant or research support from, served as a consultant to, and served on the speakers' bureau of Eli Lilly and Co., Janssen, Medice, Novartis, and Shire. The ADHD and Juvenile Bipolar Disorder Outpatient Programs chaired by Dr Rohde have received unrestricted educational and research support from the following pharmaceutical companies: Eli Lilly and Co., Janssen, Shire, and Novartis. Dr Rohde has received authorship royalties from Oxford Press and ArtMed and travel grants from Shire to take part in the 2018 APA annual meeting and from Novartis to take part of the 2016 AACAP annual meeting. The other authors declare no conflicts of interest.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Federal University of ABC and CAPES‐Brazil.
References
- 1.United Nations. The Millennium Development Goals Report, New York, NY: United Nations, 2015. [Google Scholar]
- 2.Hair NL, Hanson JL, Wolfe BL, Pollak SD. Association of child poverty, brain development, and academic achievement. JAMA Pediatr 2015; 169(9): 822.doi:10.1001/jamapediatrics.2015.1475. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Sripada RK, Swain JE, Evans GW, Welsh RC, Liberzon I. Childhood poverty and stress reactivity are associated with aberrant functional connectivity in default mode network. Neuropsychopharmacology 2014; 39(9): 2244–2251. doi:10.1038/npp.2014.75. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Sheridan MA, Sarsour K, Jutte D, D'Esposito M, Boyce WT. The impact of social disparity on prefrontal function in childhood. PLoS One 2012; 7(4): e35744.doi:10.1371/journal.pone.0035744. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Mansur RB, Cunha GR, Asevedo E, et al. Socioeconomic disadvantage moderates the association between peripheral biomarkers and childhood psychopathology. PLoS One 2016; 11(8): e0160455.doi:10.1371/journal.pone.0160455. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Demir-Lira ÖE, Voss JL, O'Neil JT, Briggs-Gowan MJ, Wakschlag LS, Booth JR. Early-life stress exposure associated with altered prefrontal resting-state fMRI connectivity in young children. Dev Cogn Neurosci 2016; 19: 107–114. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Wang L, Dai Z, Peng H, et al. Overlapping and segregated resting-state functional connectivity in patients with major depressive disorder with and without childhood neglect. Hum Brain Mapp 2014; 35(4): 1154–1166. doi:10.1002/hbm.22241. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Singh MK, Chang KD, Kelley RG, Saggar M, Reiss AL, Gotlib IH. Early signs of anomalous neural functional connectivity in healthy offspring of parents with bipolar disorder. Bipolar Disord 2014; 16(7): 678–689. doi:10.1111/bdi.12221. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Tost H, Champagne FA, Meyer-Lindenberg A. Environmental influence in the brain, human welfare and mental health. Nat Neurosci 2015; 18(10): 1421–1431. doi:10.1038/nn.4108. [DOI] [PubMed] [Google Scholar]
- 10.Yang Z, Zuo X-N, McMahon KL, et al. Genetic and environmental contributions to functional connectivity architecture of the human brain. Cereb Cortex 2016; 26(5): 2341–2352. doi:10.1093/cercor/bhw027. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Lederbogen F, Kirsch P, Haddad L, et al. City living and urban upbringing affect neural social stress processing in humans. Nature 2011; 474(7352): 498–501. doi:10.1038/nature10190. [DOI] [PubMed] [Google Scholar]
- 12.Bluhm RL, Williamson PC, Osuch EA, et al. Alterations in default network connectivity in posttraumatic stress disorder related to early-life trauma. J Psychiatry Neurosci: JPN 2009; 34(3): 187. [PMC free article] [PubMed] [Google Scholar]
- 13.Busso DS, McLaughlin KA, Sheridan MA. Dimensions of adversity, physiological reactivity, and externalizing psychopathology in adolescence: deprivation and threat. Psychosom Med 2017; 79(2): 162–171. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Cohen P, Brown J, Smailes E. Child abuse and neglect and the development of mental disorders in the general population. Dev Psychopathol 2001; 13(04): 981–999. [PubMed] [Google Scholar]
- 15.Daniels JK, Frewen P, McKinnon MC, Lanius RA. Default mode alterations in posttraumatic stress disorder related to early-life trauma: a developmental perspective. J Psychiatry Neurosci: JPN 2011; 36(1): 56. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Korgaonkar MS, Antees C, Williams LM, et al. Early exposure to traumatic stressors impairs emotional brain circuitry. PLoS One 2013; 8(9): 1–8. doi:10.1371/journal.pone.0075524. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Najman JM, Hayatbakhsh MR, Clavarino A, Bor W, O'callaghan MJ, Williams GM. Family poverty over the early life course and recurrent adolescent and young adult anxiety and depression: a longitudinal study. Am J Public Health 2010; 100(9): 1719–1723. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Swartz JR, Hariri AR, Williamson DE. An epigenetic mechanism links socioeconomic status to changes in depression-related brain function in high-risk adolescents. Mol Psychiatry 2017; 22(2): 209. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Lee CT, Hsiao CY, Lee JF, et al. Relationship between schizophrenia and low-income based on age and sex: results from a nation-wide population-based longitudinal study. Neuropsychiatry 2018; 8(3). OMICS Publishing Group, doi:10.4172/neuropsychiatry.1000426.
- 20.Giedd JN, Rapoport JL. Structural MRI of pediatric brain development: what have we learned and where are we going? Neuron 2010; 67(5): 728–734. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Avants BB, Hackman DA, Betancourt LM, Lawson GM, Hurt H, Farah MJ. Relation of childhood home environment to cortical thickness in late adolescence: specificity of experience and timing. PloS One 2015; 10(10): e0138217. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Dannlowski U, Stuhrmann A, Beutelmann V, et al. Limbic scars: long-term consequences of childhood maltreatment revealed by functional and structural magnetic resonance imaging. Biol Psychiatry 2012; 71(4): 286–293. doi:10.1016/j.biopsych.2011.10.021. [DOI] [PubMed] [Google Scholar]
- 23.Hackman D, Farah M. Socioeconomic status and the developing brain. Trends Cogn Sci 2009; 13(2): 65–73. doi:10.1016/j.tics.2008.11.003.Socioeconomic. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Hanson JL, Adluru N, Chung MK, Alexander AL, Davidson RJ, Pollak SD. Early neglect is associated with alterations in white matter integrity and cognitive functioning. Child Dev 2013; 84(5): 1566–1578. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Noble KG, Houston SM, Brito NH, et al. Family income, parental education and brain structure in children and adolescents. Nat Neurosci 2015; 18(5): 773–778. doi:10.1038/nn.3983.Family. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Noble KG, Grieve SM, Korgaonkar MS, et al. Hippocampal volume varies with educational attainment across the life-span. Front Hum Neurosci 2012; 6: 307.doi:10.3389/fnhum.2012.00307. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Gao W, Alcauter S, Elton A, et al. Functional network development during the first year: relative sequence and socioeconomic correlations. Cereb Cortex 2015; 25(9): 2919–2928. doi:10.1093/cercor/bhu088. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Graham AM, Pfeifer JH, Fisher PA, Carpenter S, Fair DA. Early life stress is associated with default system integrity and emotionality during infancy. J Child Psychol Psychiatry 2015; 56(11): 1212–1222. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Bressler SL, Vinod M. Large-Scale Brain Networks In Cognition: Emerging Methods And Principles. Trends In Cognitive Sciences 2010; 14(6): 277–290. Elsevier BV, doi:10.1016/j.tics.2010.04.004. [DOI] [PubMed]
- 30.Fornito A, Zalesky A, Breakspear M. The connectomics of brain disorders. Nat Rev Neurosci 2015; 16(3): 159–172. doi:10.1038/nrn3901. [DOI] [PubMed] [Google Scholar]
- 31.Gusnard DA, Raichle ME. Searching for a baseline: functional imaging and the resting human brain. Nat Rev Neurosci 2001; 2(10): 685. [DOI] [PubMed] [Google Scholar]
- 32.Greicius MD, Krasnow B, Reiss AL, Menon V. Functional connectivity in the resting brain: a network analysis of the default mode hypothesis. Proc Natl Acad Sci 2003; 100(1): 253–258. doi:10.1073/pnas.0135058100. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Buckner RL, Andrews-Hanna JR, Schacter DL. The brain's default network: anatomy, function, and relevance to disease. Ann NY Acad Sci 2008; 1124(1): 1–38. doi:10.1196/annals.1440.011. [DOI] [PubMed] [Google Scholar]
- 34.Broyd SJ, Demanuele C, Debener S, Helps SK, James CJ, Sonuga-Barke EJ. Default-mode brain dysfunction in mental disorders: a systematic review. Neurosci Biobehav Rev 2009; 33(3): 279–296. doi:10.1016/j.neubiorev.2008.09.002. [DOI] [PubMed] [Google Scholar]
- 35.Assaf M, Jagannathan K, CalhounVD, et al. Abnormal functional connectivity of default mode sub-networks in autism spectrum disorder patients. Neuroimage 2010; 53(1): 247–256. doi:10.1016/j.neuroimage.2010.05.067. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Mohan A, Roberto AJ, Mohan A, et al. Focus: the aging brain: the significance of the Default Mode Network (DMN) in neurological and neuropsychiatric disorders: a review. Yale J Biol Med 2016; 89(1): 49.doi:10.1016/j.neuroimage.2009.04.069. [PMC free article] [PubMed] [Google Scholar]
- 37.Muscatell KA, Morelli SA, Falk EB, et al. Social status modulates neural activity in the mentalizing network. Neuroimage 2012; 60(3): 1771–1777. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Philip NS, Kuras YI, Valentine TR, et al. Regional homogeneity and resting state functional connectivity: associations with exposure to early life stress. Psychiatry Res Neuroimaging 2013; 214(3): 247–253. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Gao W, Lin W, Grewen K, Gilmore JH. Functional connectivity of the infant human brain: plastic and modifiable. Neuroscientist 2017; 23(2): 169–184. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Fair DA, Dosenbach NU, Church JA, et al. Development of distinct control networks through segregation and integration. Proc Natl Acad Sci 2007; 104(33): 13507–13512. doi:10.1073/pnas.0705843104. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Sato JR, Salum GA, Gadelha A, et al. Age effects on the default mode and control networks in typically developing children. J Psychiatric Res 2014; 58: 89–95. doi:10.1016/j.jpsychires.2014.07.004. [DOI] [PubMed] [Google Scholar]
- 42.Belsky J, de Haan M. Annual research review: parenting and children's brain development: the end of the beginning. J Child Psychol Psychiatry 2011; 52(4): 409–428. [DOI] [PubMed] [Google Scholar]
- 43.Immordino-Yang MH, Christodoulou JA, Singh V. Rest is not idleness: implications of the brain's default mode for human development and education. Perspect Psychol Sci 2012; 7(4): 352–364. [DOI] [PubMed] [Google Scholar]
- 44.Chai XJ, Castañón AN, Öngür D, Whitfield-Gabrieli S. Anticorrelations in resting state networks without global signal regression. Neuroimage 2012; 59(2): 1420–1428. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Fox MD, Snyder AZ, Vincent JL, Corbetta M, Van Essen DC, Raichle ME. The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci U S A 2005; 102(27): 9673–9678. doi:10.1073/pnas.0504136102. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Gao W, Gilmore JH, Shen D, Smith JK, Zhu H, Lin W. The synchronization within and interaction between the default and dorsal attention networks in early infancy. Cereb Cortex 2013; 23(3): 594–603. doi:10.1093/cercor/bhs043. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Fair DA, Cohen AL, Dosenbach NU, et al. The maturing architecture of the brain's default network. Proc Natl Acad Sci 2008; 105(10): 4028–4032. doi:10.1073/pnas.0800376105. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Whitfield-Gabrieli S, Ford JM. Default mode network activity and connectivity in psychopathology. Annu Rev Clin Psychol 2012; 8: 49–76. doi:10.1146/annurev-clinpsy-032511-143049. [DOI] [PubMed] [Google Scholar]
- 49.Iacoboni M, Lieberman MD, Knowlton BJ, et al. Watching social interactions produces dorsomedial prefrontal and medial parietal BOLD fMRI signal increases compared to a resting baseline. Neuroimage 2004; 21: 1167–1173. doi:10.1016/j.neuroimage.2003.11.013. [DOI] [PubMed] [Google Scholar]
- 50.Greicius MD, Menon V. Default-mode activity during a passive sensory task: uncoupled from deactivation but impacting activation. J Cogn Neurosci 2004; 16(9): 1484–1492. [DOI] [PubMed] [Google Scholar]
- 51.Gusnard DA, Akbudak E, Shulman GL, Raichle ME. Medial prefrontal cortex and self-referential mental activity: relation to a default mode of brain function. Proc Natl Acad Sci 2001; 98(7): 4259–4264. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Andrews-Hanna JR, Reidler JS, Sepulcre J, Poulin R, Buckner RL. Functional-anatomic fractionation of the brain's default network. Neuron 2010; 65(4): 550–562. . [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Mars RB, Neubert F-X, Noonan MP, Sallet J, Toni I, Rushworth MFS. On the relationship between the “default mode network” and the “social brain”. Front Hum Neurosci 2012; 6: 1–9. doi:10.3389/fnhum.2012.00189. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Raichle ME, Snyder AZ. A default mode of brain function: a brief history of an evolving idea. Neuroimage 2007; 37(4): 1083–1090. doi:10.1016/j.neuroimage.2007.02.041. [DOI] [PubMed] [Google Scholar]
- 55.Alexander-Bloch AF, Reiss PT, Rapoport J, et al. Abnormal cortical growth in schizophrenia targets normative modules of synchronized development. Biol Psychiatry 2014; 76(6): 438–446. doi:10.1016/j.biopsych.2014.02.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56.Satterthwaite TD, Vandekar SN, Wolf DH, et al. Connectome-wide network analysis of youth with Psychosis- Spectrum symptoms. Mol Psychiatry 2015; 20(12): 1508–1515. doi:10.1038/mp.2015.66. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57.Whitfield-Gabrieli S, Thermenos HW, Milanovic S, et al. Hyperactivity and hyperconnectivity of the default network in schizophrenia and in first-degree relatives of persons with schizophrenia. Proc Natl Acad Sci 2009; 106(4): 1279–1284. doi:10.1073/pnas.0809141106. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Greicius MD, Flores BH, Menon V, et al. Resting-state functional connectivity in major depression: abnormally increased contributions from subgenual cingulate cortex and thalamus. Biol Psychiatry 2007; 62(5): 429–437. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 59.Posner J, Cha J, Wang Z, et al. Increased default mode network connectivity in individuals at high familial risk for depression. Neuropsychopharmacology 2016; 41(7): 1759–1767. doi:10.1038/npp.2015.342. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 60.Soares JM, Marques P, Magalhães R, Santos NC, Sousa N. The association between stress and mood across the adult lifespan on default mode network. Brain Struct Funct 2017; 222(1): 101–112. doi:10.1007/s00429-016-1203-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 61.Chai XJ, Whitfield-Gabrieli S, Shinn AK, et al. Abnormal medial prefrontal cortex resting-state connectivity in bipolar disorder and schizophrenia. Neuropsychopharmacology 2011; 36(10): 2009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62.Buckholtz JW, Meyer-Lindenberg A. Psychopathology and the human connectome: toward a transdiagnostic model of risk for mental illness. Neuron 2012; 74(6): 990–1004. doi:10.1016/j.neuron.2012.06.002. [DOI] [PubMed] [Google Scholar]
- 63.Castellanos FX, Sonuga-Barke EJ, Scheres A, Di Martino A, Hyde C, Walters JR. Varieties of attention-deficit/hyperactivity disorder-related intra-individual variability. Biol Psychiatry 2005; 57(11): 1416–1423. doi:10.1016/j.biopsych.2004.12.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 64.Castellanos FX, Kelly C, Milham MP. he restless brain: attention-deficit hyperactivity disorder, resting-state functional connectivity, and intrasubject variability. Can J Psychiatry 2009; 54(10): 665–672. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 65.Fair DA, Posner J, Nagel BJ, et al. Atypical default network connectivity in youth with attention-deficit/hyperactivity disorder. Biol Psychiatry 2010; 68(12): 1084–1091. doi:10.1016/j.biopsych.2010.07.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 66.Nielsen JA, Zielinski BA, Fletcher PT, et al. Abnormal lateralization of functional connectivity between language and default mode regions in autism. Mol Autism 2014; 5(1): 1.doi:10.1186/2040-2392-5-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 67.Guo W, Yao D, Jiang J, et al. Abnormal default-mode network homogeneity in first-episode, drug-naive schizophrenia at rest. Prog Neuro-Psychopharmacol Biol Psychiatry 2014; 49: 16–20. [DOI] [PubMed] [Google Scholar]
- 68.Calhoun VD, Sui J, Kiehl K, Turner J, Allen E, Pearlson G. “Exploring the psychosis functional connectome: aberrant intrinsic networks in schizophrenia and bipolar disorder”. Frontiers In Psychiatry, vol 2, 2012. Frontiers Media SA. doi:10.3389/fpsyt.2011.00075. [DOI] [PMC free article] [PubMed]
- 69.Uddin LQ, Clare Kelly AM, Biswal BB, Xavier Castellanos F, Milham MP. Functional connectivity of default mode network components: correlation, anticorrelation, and causality. Hum Brain Mapp 2009; 30(2): 625–637. doi:10.1002/hbm.20531. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 70.Uddin LQ, Kelly AC, Biswal BB, et al. Network homogeneity reveals decreased integrity of default-mode network in ADHD. J Neurosci Methods 2008; 169(1): 249–254. [DOI] [PubMed] [Google Scholar]
- 71.Sheline YI, Barch DM, Price JL, et al. The default mode network and self-referential processes in depression. Proc Natl Acad Sci 2009; 106(6): 1942–1947. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 72.Mothersill O, Tangney N, Morris DW, et al. Further evidence of alerted default network connectivity and association with theory of mind ability in schizophrenia. Schizophr Res 2017; 184: 52–58. [DOI] [PubMed] [Google Scholar]
- 73.Sato JR, Hoexter MQ, Castellanos XF, Rohde LA. Abnormal brain connectivity patterns in adults with ADHD: a coherence study. PloS One 2012; 7(9): e45671. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 74.Castellanos FX, Margulies DS, Kelly C, et al. Cingulate-precuneus interactions: a new locus of dysfunction in adult attention-deficit/hyperactivity disorder. Biol Psychiatry 2008; 63(3): 332–337. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 75.Geng X, Li G, Lu Z, et al. Structural and maturational covariance in early childhood brain development. Cereb Cortex 2017; 27(3): 1795–1807. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 76.Noble KG, Houston SM, Kan E, Sowell ER. Neural correlates of socioeconomic status in the developing human brain. Dev Sci 2012; 15(4): 516–527. doi:10.1111/j.1467-7687.2012.01147.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 77.Gao W, Zhu H, Giovanello KS, et al. Evidence on the emergence of the brain's default network from 2-week-old to 2-year- old healthy pediatric subjects. Proc Natl Acad Sci 2009; 106(16): 6790–6795. doi:10.1073/pnas.0811221106. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 78.Fransson P, Skiöld B, Engström M, et al. Spontaneous brain activity in the newborn brain during natural sleep—an fMRI study in infants born at full term. Pediatr Res 2009; 66(3): 301–305. [DOI] [PubMed] [Google Scholar]
- 79.Xiao Y, Zhai H, Friederici AD, Jia F. The development of the intrinsic functional connectivity of default network subsystems from age 3 to 5. Brain Imaging Behav 2015; 10(1): 50–59. doi:10.1007/s11682-015-9362-z. [DOI] [PubMed] [Google Scholar]
- 80.de Bie H, Boersma M, Adriaanse S, et al. Resting-state networks in awake five-to eight-year old children. Hum Brain Mapp 2012; 33(5): 1189–1201. doi:10.1002/hbm.21280. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 81.Sherman LE, Rudie JD, Pfeifer JH, Masten CL, McNealy K, Dapretto M. Development of the default mode and central executive networks across early adolescence: a longitudinal study. Dev Cogn Neurosci 2014; 10: 148–159. doi:10.1016/j.dcn.2014.08.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 82.Nelson EE, Leibenluft E, McClure EB, Pine DS. The social re-orientation of adolescence: a neuroscience perspective on the process and its relation to psychopathology. Psychol Med 2005; 35(2): 163–174. [DOI] [PubMed] [Google Scholar]
- 83.Washington SD, VanMeter JW. Anterior-posterior connectivity within the default mode network increases during maturation. Int J Med Biol Front 2015; 21(2): 207. [PMC free article] [PubMed] [Google Scholar]
- 84.Meredith RM. Sensitive and critical periods during neurotypical and aberrant neurodevelopment: a framework for neurodevelopmental disorders. Neurosci Biobehav Rev 2015; 50: 180–188. doi:http://dx.doi.org/10.1016/j.neubiorev.2014.12.001. [DOI] [PubMed] [Google Scholar]
- 85.Kessler RC, Avenevoli S, Costello EJ, et al. Prevalence, persistence, and sociodemographic correlates of DSM-IV disorders in the National Comorbidity Survey Replication Adolescent Supplement. Arch Gen Psychiatry 2012; 69(4): 372–380. doi:10.1001/archgenpsychiatry.2011.160. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 86.Manza P, Zhang S, Hu S, Chao HH, Leung HC, Chiang-shan RL. The effects of age on resting state functional connectivity of the basal ganglia from young to middle adulthood. Neuroimage 2015; 107: 311–322. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 87.Newton AT, Morgan VL, Rogers BP, Gore JC. Modulation of steady state functional connectivity in the default mode and working memory networks by cognitive load. Hum Brain Mapp 2011; 32(10): 1649–1659. doi:10.1002/hbm.21138. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 88.Sambataro F, Murty VP, Callicott JH, et al. Age-related alterations in default mode network: impact on working memory performance. Neurobiol Aging 2010; 31(5): 839–852. doi:10.1016/j.neurobiolaging.2008.05.022. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 89.Sheng T, Gheytanchi A, Aziz-Zadeh L. Default network deactivations are correlated with psychopathic personality traits. PloS One 2010; 5(9): e12611.doi:10.1371/journal.pone.0012611. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 90.Zhou J, Yao N, Fairchild G, et al. Disrupted default mode network connectivity in male adolescents with conduct disorder. Brain Imaging Behav 2016; 10(4): 995–1003. doi:10.1007/s11682-015-9465-6. [DOI] [PubMed] [Google Scholar]
- 91.Tomalski P, Moore DG, Ribeiro H, et al. Socioeconomic status and functional brain development–associations in early infancy. Dev Sci 2013; 16(5): 676–687. doi:10.1111/desc.12079. [DOI] [PubMed] [Google Scholar]
- 92.Brito NH, Noble KG. Socioeconomic status and structural brain development. Front Neurosci 2014; 8: 276. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 93.McLaughlin KA, Sheridan MA, Lambert HK. Childhood adversity and neural development: deprivation and threat as distinct dimensions of early experience. Neurosci Biobehav Rev 2014; 47: 578–591. doi:10.1016/j.neubiorev.2014.10.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 94.Tottenham N. The importance of early experiences for neuro-affective development. The Neurobiology of Childhood, Berlin/Heidelberg, Germany: Springer, 2013, pp. 109–129. doi:10.1007/7854_2013_254. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 95.Gee DG, Gabard-Durnam LJ, Flannery J, et al. Early developmental emergence of human amygdala-prefrontal connectivity after maternal deprivation. Proc Natl Acad Sci 2013; 110(39): 15638–15643. doi:10.1073/pnas.1307893110. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 96.Chen E, Miller GE. “Shift-and-persist” strategies: why low socioeconomic status isn't always bad for health. Perspect Psychol Sci 2012; 7(2): 135–158. doi:10.1177/1745691612436694. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 97.Dégeilh F, Bernier A, Leblanc É, Daneault V, Beauchamp MH. Quality of maternal behaviour during infancy predicts functional connectivity between default mode network and salience network 9 years later. Dev Cogn Neurosci 2018; 34: 53–62. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 98.Whittle S, Vijayakumar N, Simmons JG, et al. Role of positive parenting in the association between neighborhood social disadvantage and brain development across adolescence. JAMA Psychiatry 2017; 74(8): 824–832. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 99.Krieger N. Embodiment: a conceptual glossary for epidemiology. J Epidemiol Commun Health 2005; 59(5): 350–355. doi:10.1136/jech.2004.024562. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 100.Delpierre C, Barboza-Solis C, Torrisani J, et al. Origins of health inequalities: the case for allostatic load. Longit Life Course Stud 2016; 7: 25. [Google Scholar]
- 101.Juster RP, McEwen BS, Lupien SJ. Allostatic load biomarkers of chronic stress and impact on health and cognition. Neurosci Biobehav Rev 2010; 35(1): 2–16. doi:10.1016/j.neubiorev.2009.10.002. [DOI] [PubMed] [Google Scholar]
- 102.McEwen BS, Stellar E. Stress and the individual: mechanisms leading to disease. Arch Intern Med 1993; 153(18): 2093–2101. [PubMed] [Google Scholar]
- 103.Ganzel BL, Morris PA. Allostasis and the developing human brain: explicit consideration of implicit models. Dev Psychopathol 2011; 23(04): 955–974. [DOI] [PubMed] [Google Scholar]
- 104.McEwen BS. Stress, adaptation, and disease: allostasis and allostatic load. Ann NY Acad Sci 1998; 840(1): 33–44. [DOI] [PubMed] [Google Scholar]
- 105.Lupien SJ, Ouellet-Morin I, Hupbach A, et al. Beyond the stress concept: allostatic load—a developmental biological and cognitive perspective. In: Cicchetti D, Cohen DJ. (eds). Developmental Psychopathology: Volume Two: Developmental Neuroscience, Hoboken, NJ: John Wiley & Sons Inc., 2015, pp. 578–628. [Google Scholar]
- 106.Patriat R, Birn RM, Keding TJ, Herringa RJ. Default-mode network abnormalities in pediatric posttraumatic stress disorder. J Am Acad Child Adolesc Psychiatry 2016; 55(4): 319–327. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 107.Amodio DM, Frith CD. Meeting of minds: the medial frontal cortex and social cognition. Nat Rev Neurosci 2006; 7(4): 268. [DOI] [PubMed] [Google Scholar]
- 108.Molnar-Szakacs I, Uddin LQ. Self-processing and the default mode network: interactions with the mirror neuron system. Front Hum Neurosci 2013; 7: 571. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 109.Andrews-Hanna JR, Smallwood J, Spreng RN. The default network and self-generated thought: component processes, dynamic control, and clinical relevance. Ann NY Acad Sci 2014; 1316(1): 29–52. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 110.Gianaros PJ, Jennings JR, Sheu LK, Greer PJ, Kuller LH, Matthews KA. Prospective reports of chronic life stress predict decreased grey matter volume in the hippocampus. Neuroimage 2007; 35(2): 795–803. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 111.Hackman DA, Betancourt LM, Brodsky NL, Hurt H, Farah MJ. Neighborhood disadvantage and adolescent stress reactivity. Front Hum Neurosci 2012; 6: 277. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 112.Hanson JL, Nacewicz BM, Sutterer MJ, et al. Behavioral problems after early life stress: contributions of the hippocampus and amygdala. Biol Psychiatry 2015; 77(4): 314–323. doi:10.1016/j.biopsych.2014.04.020. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 113.Marsland AL, Kuan DCH, Sheu LK, et al. Systemic inflammation and resting state connectivity of the default mode network. Brain, Behav Immun 2017; 62: 162–170. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 114.Liston C, McEwen BS, Casey BJ. Psychosocial stress reversibly disrupts prefrontal processing and attentional control. Proc Natl Acad Sci 2009; 106(3): 912–917. doi:10.1073/pnas.0807041106. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 115.Hahn A, Wadsak W, Windischberger C, et al. Differential modulation of the default mode network via serotonin-1A receptors. Proc Natl Acad Sci 2012; 109(7): 2619–2624. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 116.Duncan NW, Wiebking C, Northoff G. Associations of regional GABA and glutamate with intrinsic and extrinsic neural activity in humans—a review of multimodal imaging studies. Neurosci Biobehav Rev 2014; 47: 36–52. [DOI] [PubMed] [Google Scholar]
- 117.Kapogiannis D, Reiter DA, Willette AA, Mattson MP. Posteromedial cortex glutamate and GABA predict intrinsic functional connectivity of the default mode network. Neuroimage 2013; 64: 112–119. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 118.Zhang X, Tang Y, Maletic-Savatic M, et al. Altered neuronal spontaneous activity correlates with glutamate concentration in medial prefrontal cortex of major depressed females: an fMRI-MRS study. J Affect Disord 2016; 201: 153–161. [DOI] [PubMed] [Google Scholar]
- 119.Hermans EJ, van Marle HJ, Ossewaarde L, et al. Stress-related noradrenergic activity prompts large-scale neural network reconfiguration. Science 2011; 334(6059): 1151–1153. [DOI] [PubMed] [Google Scholar]
- 120.Power JD, Barnes KA, Snyder AZ, Schlaggar BL, Petersen SE. Steps toward optimizing motion artifact removal in functional connectivity MRI; a reply to Carp. Neuroimage 2013; 76: 439–441. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 121.Horovitz SG, Braun AR, Carr WS, et al. Decoupling of the brain's default mode network during deep sleep. Proc Natl Acad Sci U S A 2009; 106(27): 11376–11381. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 122.Leech R, Kamourieh S, Beckmann CF, Sharp DJ. Fractionating the default mode network: distinct contributions of the ventral and dorsal posterior cingulate cortex to cognitive control. J Neurosci 2011; 31(9): 3217–3224. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 123.Peeters SC, van de Ven V, Gronenschild EHM, et al. Default mode network connectivity as a function of familial and environmental risk for psychotic disorder. PloS One 2015; 10(3): e0120030.doi:10.1371/journal.pone.0120030. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 124.van den Heuvel MP, van Soelen IL, Stam CJ, Kahn RS, Boomsma DI, Pol HEH. Genetic control of functional brain network efficiency in children. Eur Neuropsychopharmacol 2013; 23(1): 19–23. doi:10.1016/j.euroneuro.2012.06.007. [DOI] [PubMed] [Google Scholar]
- 125.van der Meer D, Hartman CA, Pruim RH, et al. The interaction between 5-HTTLPR and stress exposure influences connectivity of the executive control and default mode brain networks. Brain Imaging Behav 2017; 11(5): 1486–1496. doi:10.1007/s11682-016-9633-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 126.Mueller S, Wang D, Fox MD, et al. Individual variability in functional connectivity architecture of the human brain. Neuron 2013; 77(3): 586–595. doi:10.1016/j.neuron.2012.12.028. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 127.Ryali S, Supekar K, Chen T, et al. Temporal dynamics and developmental maturation of salience, default and central-executive network interactions revealed by variational Bayes hidden Markov modeling. PLoS Comput Biol 2016; 12(12): e1005138. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 128.Grayson DS, Fair DA. Development of large-scale functional networks from birth to adulthood: a guide to the neuroimaging literature. Neuroimage 2017; 160: 15–31. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 129.Ball G, Aljabar P, Arichi T, et al. Machine-learning to characterise neonatal functional connectivity in the preterm brain. Neuroimage 2016; 124: 267–275. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 130.Dosenbach NU, Nardos B, Cohen AL, et al. Prediction of individual brain maturity using fMRI. Science 2010; 329(5997): 1358–1361. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 131.Smyser CD, Dosenbach NU, Smyser TA, et al. Prediction of brain maturity in infants using machine-learning algorithms. Neuroimage 2016; 136: 1–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 132.Evans TM, Kochalka J, Ngoon TJ, et al. Brain structural integrity and intrinsic functional connectivity forecast 6 year longitudinal growth in children's numerical abilities. J Neurosci 2015; 35(33): 11743–11750. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 133.Raffaelli B, Strache N, Parchetka C, et al. Sex-related differences in frequency and perception of stressful life events during adolescence. J Public Health 2016; 24(5): 365–374. [Google Scholar]
- 134.Duncan GJ, Brooks-Gunn J, Klebanov PK. Economic deprivation and early childhood development. Child Dev 1994; 65(2): 296–318. [PubMed] [Google Scholar]
