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Longitudinal changes in within-salience network functional connectivity mediate the relationship between childhood abuse and neglect, and mental health during adolescence

Published online by Cambridge University Press:  25 August 2021

Divyangana Rakesh Open the ORCID record for Divyangana Rakesh [Opens in a new window] ,
Nicholas B. Allen  and
Sarah Whittle
Divyangana Rakesh*
Affiliation:
Department of Psychiatry, Melbourne Neuropsychiatry Centre, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
Nicholas B. Allen
Affiliation:
Department of Psychology, The University of Oregon, Eugene, OR, USA
Sarah Whittle*
Affiliation:
Department of Psychiatry, Melbourne Neuropsychiatry Centre, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
*
Authors for correspondence: Divyangana Rakesh, E-mail: [email protected];Sarah Whittle, E-mail: [email protected]
Authors for correspondence: Divyangana Rakesh, E-mail: [email protected];Sarah Whittle, E-mail: [email protected]
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Abstract

Background

Understanding the neurobiological underpinnings of childhood maltreatment is vital given consistent links with poor mental health. Dimensional models of adversity purport that different types of adversity likely have distinct neurobiological consequences. Adolescence is a key developmental period, during which deviations from normative neurodevelopment may have particular relevance for mental health. However, longitudinal work examining links between different forms of maltreatment, neurodevelopment, and mental health is limited.

Methods

In the present study, we explored associations between abuse, neglect, and longitudinal development of within-network functional connectivity of the salience (SN), default mode (DMN), and executive control network in 142 community residing adolescents. Resting-state fMRI data were acquired at age 16 (T1; M = 16.46 years, s.d. = 0.52, 66F) and 19 (T2; mean follow-up period: 2.35 years). Mental health data were also collected at T1 and T2. Childhood maltreatment history was assessed prior to T1.

Results

Abuse and neglect were both found to be associated with increases in within-SN functional connectivity from age 16 to 19. Further, there were sex differences in the association between neglect and changes in within-DMN connectivity. Finally, increases in within-SN connectivity were found to mediate the association between abuse/neglect and lower problematic substance use and higher depressive symptoms at age 19.

Conclusions

Our findings suggest that childhood maltreatment is associated with altered neurodevelopmental trajectories, and that changes in salience processing may be linked with risk and resilience for the development of depression and substance use problems during adolescence, respectively. Further work is needed to understand the distinct neurodevelopmental and mental health outcomes of abuse and neglect.

Keywords

Abuseadolescencechildhood maltreatmentdefault mode networkdepressionfMRIlongitudinalneglectresting-state functional connectivitysalience networksubstance use
Type
Original Article
Information
Psychological Medicine , Volume 53 , Issue 4 , March 2023 , pp. 1552 - 1564
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Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

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References

Baskin-Sommers, A. R., & Foti, D. (2015). Abnormal reward functioning across substance use disorders and major depressive disorder: Considering reward as a transdiagnostic mechanism. International Journal of Psychophysiology, 98(2), 227–239. https://doi.org/10.1016/j.ijpsycho.2015.01.011.CrossRefGoogle ScholarPubMed
Bath, K. G. (2020). Synthesizing views to understand sex differences in response to early life adversity. Trends in Neurosciences, 43(5), 300–310. https://doi.org/10.1016/j.tins.2020.02.004.CrossRefGoogle ScholarPubMed
Bavelier, D., Newman, A. J., Mukherjee, M., Hauser, P., Kemeny, S., Braun, A., & Boutla, M. (2008). Encoding, rehearsal, and recall in signers and speakers: Shared network but differential engagement. Cerebral Cortex, 18(10), 2263–2274. https://doi.org/10.1093/cercor/bhm248.CrossRefGoogle ScholarPubMed
Beck, A. T., Epstein, N., Brown, G., & Steer, R. A. (1988). An inventory for measuring clinical anxiety: Psychometric properties. Journal of Consulting and Clinical Psychology, 56(6), 893–897. https://doi.org/10.1037/0022-006X.56.6.893.CrossRefGoogle ScholarPubMed
Benjamini, Y., & Hochberg, Y. (1995). Benjamini-1995.pdf. Journal of the Royal Statistical Society B, 57, 289–300. https://doi.org/10.2307/2346101.Google Scholar
Bernstein, D. P., Fink, L., Handelsman, L., Foote, J., Lovejoy, M., Wenzel, K., … Ruggiero, J. (1994). Initial reliability and validity of a new retrospective measure of child abuse and neglect. American Journal of Psychiatry, 151(8), 1132–1136. https://doi.org/10.1176/ajp.151.8.1132.Google ScholarPubMed
Burghy, C. A., Stodola, D. E., Ruttle, P. L., Molloy, E. K., Armstrong, J. M., Oler, J. A., … Birn, R. M. (2012). Developmental pathways to amygdala-prefrontal function and internalizing symptoms in adolescence. Nature Neuroscience, 15(12), 1736–1741. https://doi.org/https://dx.doi.org/10.1038/nn.3257.CrossRefGoogle ScholarPubMed
Callaghan, B. L., & Tottenham, N. (2016). The stress acceleration hypothesis: Effects of early-life adversity on emotion circuits and behavior. Current Opinion in Behavioral Sciences, 7, 76–81. https://doi.org/10.1016/j.cobeha.2015.11.018.CrossRefGoogle ScholarPubMed
Chahal, R., Vilgis, V., Grimm, K. J., Hipwell, A. E., Forbes, E. E., Keenan, K., & Guyer, A. E. (2018). Girls’ pubertal development is associated with white matter microstructure in late adolescence. NeuroImage, 181, 659–669. https://doi.org/10.1016/j.neuroimage.2018.07.050.CrossRefGoogle ScholarPubMed
Choe, A. S., Jones, C. K., Joel, S. E., Muschelli, J., Belegu, V., Caffo, B. S., … Pekar, J. J. (2015). Reproducibility and temporal structure in weekly resting-state fMRI over a period of 3.5 years. PLoS ONE, 10(10), e0140134. https://doi.org/10.1371/journal.pone.0140134.CrossRefGoogle Scholar
Cisler, J. (2017). Childhood trauma and functional connectivity between amygdala and medial prefrontal cortex: A dynamic functional connectivity and large-scale network perspective. Frontiers in Systems Neuroscience, 11, 29. https://doi.org/10.3389/fnsys.2017.00029.CrossRefGoogle ScholarPubMed
Cisler, J. M., James, G. A., Tripathi, S., Mletzko, T., Heim, C., Hu, X. P., … Kilts, C. D. (2013). Differential functional connectivity within an emotion regulation neural network among individuals resilient and susceptible to the depressogenic effects of early life stress. Psychological Medicine, 43(3), 507–518. https://doi.org/10.1017/S0033291712001390.CrossRefGoogle Scholar
Danese, A., & Widom, C. S. (2020). Objective and subjective experiences of child maltreatment and their relationships with psychopathology. Nature Human Behaviour, 4(8), 811–818.CrossRefGoogle ScholarPubMed
De Bellis, M. D., Hooper, S. R., Chen, S. D., Provenzale, J. M., Boyd, B. D., Glessner, C. E., … Woolley, D. P. (2015). Posterior structural brain volumes differ in maltreated youth with and without chronic posttraumatic stress disorder. Development and Psychopathology, 27(4 Pt 2), 1555–1576. https://doi.org/10.1017/S0954579415000942.CrossRefGoogle ScholarPubMed
De Bellis, M. D., & Keshavan, M. S. (2003). Sex differences in brain maturation in maltreatment-related pediatric posttraumatic stress disorder. Neuroscience and Biobehavioral Reviews, 27(1–2), 103–117. https://doi.org/10.1016/S0149-7634(03)00013-7.CrossRefGoogle ScholarPubMed
Dennison, M. J., Rosen, M. L., Sambrook, K. A., Jenness, J. L., Sheridan, M. A., & McLaughlin, K. A. (2019). Differential associations of distinct forms of childhood adversity with neurobehavioral measures of reward processing: A developmental pathway to depression. Child Development, 90(1), e96–e113. https://doi.org/10.1111/cdev.13011.CrossRefGoogle ScholarPubMed
DiMartino, A., Fair, D. A., Kelly, C., Satterthwaite, T. D., Castellanos, F. X., Thomason, M. E., … Milham, M. P. (2014). Unraveling the miswired connectome: A developmental perspective. Neuron, 83(6), 1335–1353. https://doi.org/10.1016/j.neuron.2014.08.050.CrossRefGoogle Scholar
Ding, H., Ming, D., Wan, B., Li, Q., Qin, W., & Yu, C. (2016). Enhanced spontaneous functional connectivity of the superior temporal gyrus in early deafness. Scientific Reports, 6(1), 1–11. https://doi.org/10.1038/srep23239.Google ScholarPubMed
Droutman, V., Read, S. J., & Bechara, A. (2015). Revisiting the role of the insula in addiction. Trends in Cognitive Sciences, 19(7), 414–420. https://doi.org/10.1016/j.tics.2015.05.005.CrossRefGoogle ScholarPubMed
Dumontheil, I. (2016). Adolescent brain development. Current Opinion in Behavioral Sciences, 10, 39–44. https://doi.org/10.1016/j.cobeha.2016.04.012.CrossRefGoogle Scholar
Edmiston, E. E., Wang, F., Mazure, C. M., Guiney, J., Sinha, R., Mayes, L. C., & Blumberg, H. P. (2011). Corticostriatal-limbic gray matter morphology in adolescents with self-reported exposure to childhood maltreatment. Archives of Pediatrics and Adolescent Medicine, 165(12), 1069–1077. https://doi.org/10.1001/archpediatrics.2011.565.CrossRefGoogle ScholarPubMed
Ernst, M., Torrisi, S., Balderston, N., Grillon, C., & Hale, E. A. (2015). fMRI functional connectivity applied to adolescent neurodevelopment. Annual Review of Clinical Psychology, 11(1), 361–377. https://doi.org/10.1146/annurev-clinpsy-032814-112753.CrossRefGoogle ScholarPubMed
Esteban, O., Markiewicz, C. J., Blair, R. W., Moodie, C. A., Isik, A. I., Erramuzpe, A., … Gorgolewski, K. J. (2019). fMRIPrep: A robust preprocessing pipeline for functional MRI. Nature Methods, 16(1), 111–116. https://doi.org/10.1038/s41592-018-0235-4.CrossRefGoogle ScholarPubMed
Fair, D. A., Nigg, J. T., Iyer, S., Bathula, D., Mills, K. L., Dosenbach, N. U. F. F., … Milham, M. P. (2013). Distinct neural signatures detected for ADHD subtypes after controlling for micro-movements in resting state functional connectivity MRI data. Frontiers in Systems Neuroscience, 6(Feb), 1–31. https://doi.org/10.3389/fnsys.2012.00080.CrossRefGoogle ScholarPubMed
Forbes, E. E., & Dahl, R. E. (2012). Research review: Altered reward function in adolescent depression: What, when and how? Journal of Child Psychology and Psychiatry, 53(1), 3–15. https://doi.org/http://dx.doi.org/10.1111/j.1469-7610.2011.02477.x.CrossRefGoogle ScholarPubMed
Fox, M. D., & Greicius, M. (2010). Clinical applications of resting state functional connectivity. Frontiers in Systems Neuroscience, 4, 19. https://doi.org/10.3389/fnsys.2010.00019.Google ScholarPubMed
Frodl, T., Reinhold, E., Koutsouleris, N., Reiser, M., & Meisenzahl, E. M. (2010). Interaction of childhood stress with hippocampus and prefrontal cortex volume reduction in major depression. Journal of Psychiatric Research, 44(13), 799–807. https://doi.org/10.1016/j.jpsychires.2010.01.006.CrossRefGoogle ScholarPubMed
Gibbons, R. D., Hedeker, D., & DuToit, S. (2010). Advances in analysis of longitudinal data. Annual Review of Clinical Psychology, 6(1), 79–107. https://doi.org/10.1146/annurev.clinpsy.032408.153550.CrossRefGoogle ScholarPubMed
Gilman, J. M., & Hommer, D. W. (2008). Modulation of brain response to emotional images by alcohol cues in alcohol-dependent patients. Addiction Biology, 13(3–4), 423–434. https://doi.org/10.1111/j.1369-1600.2008.00111.x.CrossRefGoogle ScholarPubMed
Goff, B., Gee, D. G., Telzer, E. H., Humphreys, K. L., Gabard-Durnam, L., Flannery, J., & Tottenham, N. (2013). Reduced nucleus accumbens reactivity and adolescent depression following early-life stress. Neuroscience, 249, 129–138. https://doi.org/10.1016/j.neuroscience.2012.12.010.CrossRefGoogle Scholar
Green, J. G., McLaughlin, K. A., Berglund, P. A., Gruber, M. J., Sampson, N. A., Zaslavsky, A. M., & Kessler, R. C. (2010). Childhood adversities and adult psychiatric disorders in the national comorbidity survey replication I: Associations with first onset of DSM-IV disorders. Archives of General Psychiatry, 67(2), 113–123. https://doi.org/10.1001/archgenpsychiatry.2009.186.CrossRefGoogle ScholarPubMed
Hanson, J. L., Chung, M. K., Avants, B. B., Shirtcliff, E. A., Gee, J. C., Davidson, R. J., & Pollak, S. D. (2010). Early stress is associated with alterations in the orbitofrontal cortex: A tensor-based morphometry investigation of brain structure and behavioral risk. Journal of Neuroscience, 30(22), 7466–7472. https://doi.org/10.1523/JNEUROSCI.0859-10.2010.CrossRefGoogle ScholarPubMed
Hanson, J. L., Hariri, A. R., & Williamson, D. E. (2015a). Blunted ventral striatum development in adolescence reflects emotional neglect and predicts depressive symptoms. Biological Psychiatry, 78(9), 598–605. https://doi.org/10.1016/j.biopsych.2015.05.010.CrossRefGoogle Scholar
Hanson, J. L., Nacewicz, B. M., Sutterer, M. J., Cayo, A. A., Schaefer, S. M., Rudolph, K. D., … Davidson, R. J. (2015b). Behavioral problems after early life stress: Contributions of the hippocampus and amygdala. Biological Psychiatry, 77(4), 314–323. https://doi.org/10.1016/j.biopsych.2014.04.020.CrossRefGoogle ScholarPubMed
Hart, H., Lim, L., Mehta, M. A., Simmons, A., Mirza, K. A. H., & Rubia, K. (2018). Altered fear processing in adolescents with a history of severe childhood maltreatment: An fMRI study. Psychological Medicine, 48(7), 1092–1101. https://doi.org/10.1017/S0033291716003585.CrossRefGoogle ScholarPubMed
Hayes, A. F. (2018). Introduction to mediation, moderation, and conditional process analysis: A regession approach. https://www.guilford.com/books/Introduction-to-Mediation-Moderation-and-Conditional-Process-Analysis/Andrew-Hayes/9781462534654.Google Scholar
Helpman, L., Zhu, X., Suarez-Jimenez, B., Lazarov, A., Monk, C., & Neria, Y. (2017). Sex differences in trauma-related psychopathology: A critical review of neuroimaging literature (2014–2017). Current Psychiatry Reports, 19, 1–13. https://doi.org/10.1007/s11920-017-0854-y.CrossRefGoogle ScholarPubMed
Herringa, R. J., Birn, R. M., Ruttle, P. L., Burghy, C. A., Stodola, D. E., Davidson, R. J., & Essex, M. J. (2013). Childhood maltreatment is associated with altered fear circuitry and increased internalizing symptoms by late adolescence. Proceedings of the National Academy of Sciences of the USA, 110(47), 19119–19124. https://doi.org/10.1073/pnas.1310766110.CrossRefGoogle ScholarPubMed
Herting, M. M., Gautam, P., Chen, Z., Mezher, A., & Vetter, N. C. (2018). Test-retest reliability of longitudinal task-based fMRI: Implications for developmental studies. Developmental Cognitive Neuroscience, 33, 17–26. https://doi.org/10.1016/j.dcn.2017.07.001.CrossRefGoogle ScholarPubMed
Ho, T. C., Dennis, E. L., Thompson, P. M., & Gotlib, I. H. (2018). Network-based approaches to examining stress in the adolescent brain. Neurobiology of Stress, 8, 147–157. https://doi.org/10.1016/j.ynstr.2018.05.002.CrossRefGoogle ScholarPubMed
Karl, A., Schaefer, M., Malta, L. S., Dörfel, D., Rohleder, N., & Werner, A. (2006). A meta-analysis of structural brain abnormalities in PTSD. Neuroscience and Biobehavioral Reviews, 30(7), 1004–1031. https://doi.org/10.1016/j.neubiorev.2006.03.004.CrossRefGoogle ScholarPubMed
Kelly, C., Biswal, B. B., Craddock, R. C., Castellanos, F. X., & Milham, M. P. (2012). Characterizing variation in the functional connectome: Promise and pitfalls. Trends in Cognitive Sciences, 16(3), 181–188. https://doi.org/10.1016/j.tics.2012.02.001.CrossRefGoogle ScholarPubMed
Kessler, R. C., Berglund, P., Demler, O., Jin, R., Merikangas, K. R., & Walters, E. E. (2005). Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the national comorbidity survey. Archives of General Psychiatry, 62, 593–602. https://doi.org/10.1001/archpsyc.62.6.593.CrossRefGoogle ScholarPubMed
Kessler, R. C., McLaughlin, K. A., Green, J. G., Gruber, M. J., Sampson, N. A., Zaslavsky, A. M., … Williams, D. R. (2010). Childhood adversities and adult psychopathology in the WHO world mental health surveys. British Journal of Psychiatry, 197(5), 378–385. https://doi.org/10.1192/bjp.bp.110.080499.CrossRefGoogle ScholarPubMed
Kim-Spoon, J., Deater-Deckard, K., Holmes, C., Lee, J., Chiu, P., & King-Casas, B. (2016). Behavioral and neural inhibitory control moderates the effects of reward sensitivity on adolescent substance use. Neuropsychologia, 318–326. https://doi.org/10.1016/j.neuropsychologia.2016.08.028.CrossRefGoogle ScholarPubMed
Kim, Y.-T., Song, H.-J., Seo, J.-H., Lee, J.-J., Lee, J., Kwon, D.-H., … Chang, Y. (2011). The differences in neural network activity between methamphetamine abusers and healthy subjects performing an emotion-matching task: Functional MRI study. NMR in Biomedicine, 24(10), 1392–1400. https://doi.org/10.1002/nbm.1702.CrossRefGoogle ScholarPubMed
Kumar, A., Behen, M. E., Singsoonsud, P., Veenstra, A. L., Wolfe-Christensen, C., Helder, E., & Chugani, H. T. (2014). Microstructural abnormalities in language and limbic pathways in orphanage-reared children. Journal of Child Neurology, 29(3), 318–325. https://doi.org/10.1177/0883073812474098.CrossRefGoogle ScholarPubMed
Lambert, H. K., King, K. M., Monahan, K. C., & McLaughlin, K. A. (2017). Differential associations of threat and deprivation with emotion regulation and cognitive control in adolescence. Development and Psychopathology, 29(3), 929–940. https://doi.org/10.1017/S0954579416000584.CrossRefGoogle ScholarPubMed
Lee, J., Pavuluri, M. N., Kim, J. H., Suh, S., Kim, I., & Lee, M. S. (2019). Resting-state functional connectivity in medication-naïve adolescents with major depressive disorder. Psychiatry Research – Neuroimaging, 288, 37–43. https://doi.org/10.1016/j.pscychresns.2019.04.008.CrossRefGoogle ScholarPubMed
Liu, L., Yuan, C., Ding, H., Xu, Y., Long, M., Li, Y., … Yu, C. (2017). Visual deprivation selectively reshapes the intrinsic functional architecture of the anterior insula subregions. Scientific Reports, 7(1), 1–11. https://doi.org/10.1038/srep45675.Google ScholarPubMed
Marstaller, L., Fynes-Clinton, S., Burianová, H., & Reutens, D. C. (2021). Salience and default-mode network connectivity during threat and safety processing in older adults. Human Brain Mapping, 42(1), 14–23. https://doi.org/10.1002/hbm.25199.CrossRefGoogle ScholarPubMed
Martin, S. (2015). Comment on ‘Behavioral problems after early life stress: Contributions of the hippocampus and amygdala’. Journal of the American Psychoanalytic Association, 63(6), 1244–1246. https://doi.org/http://dx.doi.org/10.1177/0003065115620405.CrossRefGoogle ScholarPubMed
Marusak, H. A., Etkin, A., & Thomason, M. E. (2015). Disrupted insula-based neural circuit organization and conflict interference in trauma-exposed youth. NeuroImage: Clinical, 8, 516–525. https://doi.org/10.1016/j.nicl.2015.04.007.CrossRefGoogle ScholarPubMed
Maxwell, S. E., & Cole, D. A. (2007). Bias in cross-sectional analyses of longitudinal mediation. Psychological Methods, 12(1), 23–44. https://doi.org/10.1037/1082-989X.12.1.23.CrossRefGoogle ScholarPubMed
Maxwell, S. E., Cole, D. A., & Mitchell, M. A. (2011). Bias in cross-sectional analyses of longitudinal mediation: Partial and complete mediation under an autoregressive model. Multivariate Behavioral Research, 46(5), 816–841. https://doi.org/10.1080/00273171.2011.606716.CrossRefGoogle ScholarPubMed
McLaughlin, K. A., & Sheridan, M. A. (2016). Beyond cumulative risk: A dimensional approach to childhood adversity. Current Directions in Psychological Science, 25(4), 239–245. https://doi.org/10.1177/0963721416655883.CrossRefGoogle Scholar
McLaughlin, K. A., Sheridan, M. A., Gold, A. L., Duys, A., Lambert, H. K., Peverill, M., … Pine, D. S. (2016). Maltreatment exposure, brain structure, and fear conditioning in children and adolescents. Neuropsychopharmacology, 41(8), 1956–1964. https://doi.org/10.1038/npp.2015.365.CrossRefGoogle ScholarPubMed
McLaughlin, K. A., Sheridan, M. A., & Lambert, H. K. (2014). Childhood adversity and neural development: Deprivation and threat as distinct dimensions of early experience. Neuroscience and Biobehavioral Reviews, 47, 578–591. https://doi.org/10.1016/j.neubiorev.2014.10.012.CrossRefGoogle Scholar
McLaughlin, K. A., Sheridan, M. A., & Nelson, C. A. (2017). Neglect as a violation of species-expectant experience: Neurodevelopmental consequences. Biological Psychiatry, 82(7), 462–471. https://doi.org/10.1016/j.biopsych.2017.02.1096.CrossRefGoogle ScholarPubMed
McLaughlin, K. A., Weissman, D., & Bitrán, D. (2019). Childhood adversity and neural development: A systematic review. Annual Review of Developmental Psychology, 1(1), 277–312. https://doi.org/10.1146/annurev-devpsych-121318-084950.CrossRefGoogle ScholarPubMed
Mehta, M. A., Gore-Langton, E., Golembo, N., Colvert, E., Williams, S. C. R., & Sonuga-Barke, E. (2010). Hyporesponsive reward anticipation in the basal ganglia following severe institutional deprivation early in life. Journal of Cognitive Neuroscience, 22(10), 2316–2325. https://doi.org/10.1162/jocn.2009.21394.CrossRefGoogle ScholarPubMed
Menon, V., & Uddin, L. Q. (2010). Saliency, switching, attention and control: A network model of insula function. Brain Structure & Function, 214(5–6), 655–667. https://doi.org/10.1007/s00429-010-0262-0.CrossRefGoogle ScholarPubMed
Plichta, M. M., Schwarz, A. J., Grimm, O., Morgen, K., Mier, D., Haddad, L., … Meyer-Lindenberg, A. (2012). Test-retest reliability of evoked BOLD signals from a cognitive-emotive fMRI test battery. NeuroImage, 60(3), 1746–1758. https://doi.org/10.1016/j.neuroimage.2012.01.129.CrossRefGoogle ScholarPubMed
Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2012). Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. NeuroImage, 59(3), 2142–2154. https://doi.org/10.1016/j.neuroimage.2011.10.018.CrossRefGoogle ScholarPubMed
Pruim, R. H. R., Mennes, M., van Rooij, D., Llera, A., Buitelaar, J. K., & Beckmann, C. F. (2015). ICA-AROMA: A robust ICA-based strategy for removing motion artifacts from fMRI data. NeuroImage, 112, 267–277. https://doi.org/10.1016/j.neuroimage.2015.02.064.CrossRefGoogle ScholarPubMed
Radloff, L. S. (1977). The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1(3), 385–401. https://doi.org/10.1177/014662167700100306.CrossRefGoogle Scholar
Rakesh, D., Allen, N. B., & Whittle, S. (2020a). Balancing act: Neural correlates of affect dysregulation in youth depression and substance use – A systematic review of functional neuroimaging studies. Developmental Cognitive Neuroscience, 42, 100775. https://doi.org/10.1016/j.dcn.2020.100775.CrossRefGoogle ScholarPubMed
Rakesh, D., Kelly, C., Vijayakumar, N., Zalesky, A., Allen, N. B., & Whittle, S. (2021). Unraveling the consequences of childhood maltreatment: Deviations from typical functional neurodevelopment mediate the relationship between maltreatment history and depressive symptoms. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 6(3), 329–342. https://doi.org/10.1016/j.bpsc.2020.09.016.Google ScholarPubMed
Rakesh, D., Lv, J., Zalesky, A., Allen, N. B., Lubman, D. I., Yücel, M., … Whittle, S. (2020b). Altered resting functional connectivity patterns associated with problematic substance use and substance use disorders during adolescence. Journal of Affective Disorders, 279, 599–608. https://doi.org/10.1016/j.jad.2020.10.051.CrossRefGoogle ScholarPubMed
Rakesh, D., Seguin, C., Zalesky, A., Cropley, V., & Whittle, S. (2021). Associations between neighborhood disadvantage, resting-state functional connectivity, and behavior in the Adolescent Brain Cognitive Development (ABCD) StudyⓇ: Moderating role of positive family and school environments. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging. https://doi.org/10.1016/j.bpsc.2021.03.008.CrossRefGoogle Scholar
Samplin, E., Ikuta, T., Malhotra, A. K., Szeszko, P. R., & DeRosse, P. (2013). Sex differences in resilience to childhood maltreatment: Effects of trauma history on hippocampal volume, general cognition and subclinical psychosis in healthy adults. Journal of Psychiatric Research, 47(9), 1174–1179. https://doi.org/10.1016/j.jpsychires.2013.05.008.CrossRefGoogle ScholarPubMed
Satterthwaite, T. D., Ciric, R., Roalf, D. R., Davatzikos, C., Bassett, D. S., & Wolf, D. H. (2019). Motion artifact in studies of functional connectivity: Characteristics and mitigation strategies. Human Brain Mapping, 40(7), 2033–2051. https://doi.org/10.1002/hbm.23665.CrossRefGoogle ScholarPubMed
Satterthwaite, T. D., Wolf, D. H., Loughead, J., Ruparel, K., Elliott, M. A., Hakonarson, H., … Gur, R. E. (2012). Impact of in-scanner head motion on multiple measures of functional connectivity: Relevance for studies of neurodevelopment in youth. NeuroImage, 60(1), 623–632. https://doi.org/10.1016/j.neuroimage.2011.12.063.CrossRefGoogle ScholarPubMed
Saxbe, D., Khoddam, H., Del Piero, L., Stoycos, S. A., Gimbel, S. I., Margolin, G., & Kaplan, J. T. (2018). Community violence exposure in early adolescence: Longitudinal associations with hippocampal and amygdala volume and resting state connectivity. Developmental Science, 21(6), 1–11. https://doi.org/http://dx.doi.org/10.1111/desc.12686.CrossRefGoogle ScholarPubMed
Scher, C. D., Stein, M. B., Asmundson, G. J. G., Mccreary, D. R., & Forde, D. R. (2001). The childhood trauma questionnaire in a community sample: Psychometric properties and normative data. Journal of Traumatic Stress, 14(4), 843–857. https://doi.org/10.1023/A:1013058625719.CrossRefGoogle Scholar
Seeley, W. W., Menon, V., Schatzberg, A. F., Keller, J., Glover, G. H., Kenna, H., … Greicius, M. D. (2007). Dissociable intrinsic connectivity networks for salience processing and executive control. Journal of Neuroscience, 27(9), 2349–2356. https://doi.org/10.1523/JNEUROSCI.5587-06.2007.CrossRefGoogle ScholarPubMed
Sheridan, M. A., & McLaughlin, K. A. (2014). Dimensions of early experience and neural development: Deprivation and threat. Trends in Cognitive Sciences, 18(11), 580–585. https://doi.org/10.1016/j.tics.2014.09.001.CrossRefGoogle ScholarPubMed
Shirer, W. R., Ryali, S., Rykhlevskaia, E., Menon, V., & Greicius, M. D. (2012). Decoding subject-driven cognitive states with whole-brain connectivity patterns. Cerebral Cortex, 22(1), 158–165. https://doi.org/10.1093/cercor/bhr099.CrossRefGoogle ScholarPubMed
Silvers, J. A., Lumian, D. S., Gabard-Durnam, L., Gee, D. G., Goff, B., Fareri, D. S., … Tottenham, N. (2016). Previous institutionalization is followed by broader amygdala–hippocampal–PFC network connectivity during aversive learning in human development. The Journal of Neuroscience, 36(24), 6420–6430. https://doi.org/10.1523/JNEUROSCI.0038-16.2016.CrossRefGoogle ScholarPubMed
Sripada, R. K., Swain, J. E., Evans, G. W., Welsh, R. C., & Liberzon, I. (2014). Childhood poverty and stress reactivity are associated with aberrant functional connectivity in default mode network. Neuropsychopharmacology, 39(9), 2244–2251. https://doi.org/10.1038/npp.2014.75.CrossRefGoogle ScholarPubMed
Stevens, M. C. (2016). The contributions of resting state and task-based functional connectivity studies to our understanding of adolescent brain network maturation. Neuroscience and Biobehavioral Reviews, 70, 13–32. https://doi.org/10.1016/j.neubiorev.2016.07.027.CrossRefGoogle ScholarPubMed
Stevens, M. C., Pearlson, G. D., & Calhoun, V. D. (2009). Changes in the interaction of resting-state neural networks from adolescence to adulthood. Human Brain Mapping, 30(8), 2356–2366. https://doi.org/10.1002/hbm.20673.CrossRefGoogle ScholarPubMed
Stewart, J. L., May, A. C., Poppa, T., Davenport, P. W., Tapert, S. F., & Paulus, M. P. (2014). You are the danger: Attenuated insula response in methamphetamine users during aversive interoceptive decision-making. Drug and Alcohol Dependence, 142, 110–119. https://doi.org/10.1016/j.drugalcdep.2014.06.003.CrossRefGoogle ScholarPubMed
Teicher, M. H., Samson, J. A., Anderson, C. M., & Ohashi, K. (2016). The effects of childhood maltreatment on brain structure, function and connectivity. Nature Reviews Neuroscience, 17(10), 652–666. https://doi.org/10.1038/nrn.2016.111.CrossRefGoogle Scholar
Thomason, M. E., Marusak, H. A., Tocco, M. A., Vila, A. M., McGarragle, O., & Rosenberg, D. R. (2014). Altered amygdala connectivity in urban youth exposed to trauma. Social Cognitive and Affective Neuroscience, 10(11), 1460–1468. https://doi.org/10.1093/scan/nsv030.CrossRefGoogle Scholar
Tottenham, N., Hare, T. A., Millner, A., Gilhooly, T., Zevin, J. D., & Casey, B. J. (2011). Elevated amygdala response to faces following early deprivation. Developmental Science, 14(2), 190–204. https://doi.org/10.1111/j.1467-7687.2010.00971.x.CrossRefGoogle ScholarPubMed
Truelove-hill, M., Erus, G., Bashyam, V., Varol, E., Sako, C., Gur, R. C., … Davatzikos, C. (2020). A multidimensional neural maturation index reveals reproducible developmental patterns in children and adolescents. Journal of Neuroscience, 40(6), 1265–1275.CrossRefGoogle Scholar
Uddin, L. Q. (2015). Salience processing and insular cortical function and dysfunction. Nature Reviews Neuroscience, 16(1), 55–61. https://doi.org/10.1038/nrn3857.CrossRefGoogle ScholarPubMed
Van der Werff, S. J. A., Pannekoek, J. N., Veer, I. M., van Tol, M. J., Aleman, A., Veltman, D. J., … van der Wee, N. J. A. (2013). Resilience to childhood maltreatment is associated with increased resting-state functional connectivity of the salience network with the lingual gyrus. Child Abuse and Neglect, 37(11), 1021–1029. https://doi.org/10.1016/j.chiabu.2013.07.008.CrossRefGoogle ScholarPubMed
Walker, E. A., Gelfand, A., Katon, W. J., Koss, M. P., Von Korff, M., Bernstein, D., & Russo, J. (1999). Adult health status of women with histories of childhood abuse and neglect. American Journal of Medicine, 107(4), 332–339. https://doi.org/10.1016/S0002-9343(99)00235-1.CrossRefGoogle ScholarPubMed
Wechler, D. (2003). Wechsler intelligence scale for children (4th ed.). San Antonio, TX: Harcourt Assessment.Google Scholar
Weissman, D. G., Conger, R. D., Robins, R. W., Hastings, P. D., & Guyer, A. E. (2018). Income change alters default mode network connectivity for adolescents in poverty. Developmental Cognitive Neuroscience, 30, 93–99. https://doi.org/10.1016/j.dcn.2018.01.008.CrossRefGoogle ScholarPubMed
Whittle, S., Vijayakumar, N., Dennison, M., Schwartz, O., Simmons, J. G., Sheeber, L., & Allen, N. B. (2016). Observed measures of negative parenting predict brain development during adolescence. PLoS ONE, 11(1), 1–15. https://doi.org/10.1371/journal.pone.0147774.CrossRefGoogle ScholarPubMed
Whittle, S., Yap, M. B. H., Yucel, M., Fornito, A., Simmons, J. G., Barrett, A., … Allen, N. B. (2008). Prefrontal and amygdala volumes are related to adolescents’ affective behaviors during parent-adolescent interactions. Proceedings of the National Academy of Sciences, 105(9), 3652–3657. https://doi.org/10.1073/pnas.0709815105.CrossRefGoogle ScholarPubMed
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