Development of subcortical volumes across adolescence in males and females: A multisample study of longitudinal changes

NeuroImage

Volumn 172, Issue , 2018, Pages 194-205

  Herting, Megan M ^a   Johnson, Cory ^a   Mills, Kathryn L ^b   Vijayakumar, Nandita ^b   Dennison, Meg ^c   Liu, Chang ^a   Goddings, Anne Lise ^d   Dahl, Ronald E ^e   Sowell, Elizabeth R ^a   Whittle, Sarah ^c   Allen, Nicholas B ^b   Tamnes, Christian K ^f  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

^b UNIVERSITY OF OREGON   (United States)

^c UNIVERSITY OF MELBOURNE   (Australia)

^d UNIVERSITY COLLEGE LONDON   (United Kingdom)

^e UNIVERSITY OF CALIFORNIA   (United States)

^f UNIVERSITY OF OSLO   (Norway)

Author keywords

Adolescence; Amygdala; Hippocampus; Longitudinal; Magnetic resonance imaging; Neurodevelopment; Replication; Sex differences; Subcortical

Indexed keywords

ADOLESCENT; ADULT; AGE; AMYGDALA; ARTICLE; BRAIN DEVELOPMENT; BRAIN REGION; BRAIN SIZE; CAUDATE NUCLEUS; CHILD; CONTROLLED STUDY; FEMALE; GLOBUS PALLIDUS; GRAY MATTER; HIPPOCAMPUS; HUMAN; HUMAN EXPERIMENT; LINEAR SYSTEM; MALE; NUCLEUS ACCUMBENS; PRIORITY JOURNAL; PUTAMEN; REPRODUCIBILITY; SEX DIFFERENCE; SUBCORTEX; THALAMUS; ADOLESCENT DEVELOPMENT; BRAIN; DIAGNOSTIC IMAGING; GROWTH, DEVELOPMENT AND AGING; IMAGE PROCESSING; INFORMATION PROCESSING; LONGITUDINAL STUDY; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; PROCEDURES; SEXUAL CHARACTERISTICS;

ADOLESCENT; ADOLESCENT DEVELOPMENT; BRAIN; DATASETS AS TOPIC; FEMALE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; LONGITUDINAL STUDIES; MAGNETIC RESONANCE IMAGING; MALE; NEUROIMAGING; SEX CHARACTERISTICS;

EID: 85043247859     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2018.01.020     Document Type: Article

References (51)

1. Alexander-Bloch, A., Clasen, L., Stockman, M., Ronan, L., Lalonde, F., Giedd, J., Raznahan, A., Subtle in-scanner motion biases automated measurement of brain anatomy from in vivo MRI. Hum. Brain Mapp. 37:7 (2016), 2385–2397.
2. Backhausen, L.L., Herting, M.M., Buse, J., Roessner, V., Smolka, M.N., Vetter, N.C., Quality control of structural MRI images applied using FreeSurfer-a hands-on workflow to rate motion artifacts. Front. Neurosci., 10, 2016, 558.
3. Chakravarty, M.M., Steadman, P., van Eede, M.C., Calcott, R.D., Gu, V., Shaw, P., Raznahan, A., Collins, D.L., Lerch, J.P., Performing label-fusion-based segmentation using multiple automatically generated templates. Hum. Brain Mapp. 34:10 (2013), 2635–2654.
4. Chepkoech, J.L., Walhovd, K.B., Grydeland, H., Fjell, A.M., I. Alzheimer's Disease Neuroimaging. Effects of change in FreeSurfer version on classification accuracy of patients with Alzheimer's disease and mild cognitive impairment. Hum. Brain Mapp. 37:5 (2016), 1831–1841.
5. Choudhury, S., Blakemore, S.J., Charman, T., Social cognitive development during adolescence. Soc. Cognit. Affect Neurosci. 1:3 (2006), 165–174.
6. Crone, E.A., Elzinga, B.M., Changing brains: how longitudinal functional magnetic resonance imaging studies can inform us about cognitive and social-affective growth trajectories. Wiley Interdiscip. Rev. Cogn. Sci. 6:1 (2015), 53–63.
7. Dennison, M., Whittle, S., Yucel, M., Vijayakumar, N., Kline, A., Simmons, J., Allen, N.B., Mapping subcortical brain maturation during adolescence: evidence of hemisphere- and sex-specific longitudinal changes. Dev. Sci. 16:5 (2013), 772–791.
8. Ducharme, S., Albaugh, M.D., Nguyen, T.V., Hudziak, J.J., Mateos-Perez, J.M., Labbe, A., Evans, A.C., Karama, S., G. Brain Development Cooperative. Trajectories of cortical thickness maturation in normal brain development–The importance of quality control procedures. Neuroimage 125 (2016), 267–279.
9. Erus, G., Battapady, H., Satterthwaite, T.D., Hakonarson, H., Gur, R.E., Davatzikos, C., Gur, R.C., Imaging patterns of brain development and their relationship to cognition. Cereb Cortex 25:6 (2015), 1676–1684.
10. Fischl, B., Salat, D.H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., van der Kouwe, A., Killiany, R., Kennedy, D., Klaveness, S., Montillo, A., Makris, N., Rosen, B., Dale, A.M., Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 33:3 (2002), 341–355.
11. Giedd, J.N., Raznahan, A., Alexander-Bloch, A., Schmitt, E., Gogtay, N., Rapoport, J.L., Child psychiatry branch of the National Institute of Mental Health longitudinal structural magnetic resonance imaging study of human brain development. Neuropsychopharmacology 40:1 (2015), 43–49.
12. Giedd, J.N., Vaituzis, A.C., Hamburger, S.D., Lange, N., Rajapakse, J.C., Kaysen, D., Vauss, Y.C., Rapoport, J.L., Quantitative MRI of the temporal lobe, amygdala, and hippocampus in normal human development: ages 4-18 years. J. Comp. Neurol. 366:2 (1996), 223–230.
13. Goddings, A.L., Mills, K.L., Clasen, L.S., Giedd, J.N., Viner, R.M., Blakemore, S.J., The influence of puberty on subcortical brain development. Neuroimage 88 (2014), 242–251.
14. Gogtay, N., Thompson, P.M., Mapping gray matter development: implications for typical development and vulnerability to psychopathology. Brain Cognit. 72:1 (2010), 6–15.
15. Gur, R.E., Gur, R.C., Sex differences in brain and behavior in adolescence: findings from the philadelphia neurodevelopmental cohort. Neurosci. Biobehav. Rev. 70 (2016), 159–170.
16. Herting, M.M., Gautam, P., Spielberg, J.M., Kan, E., Dahl, R.E., Sowell, E.R., The role of testosterone and estradiol in brain volume changes across adolescence: a longitudinal structural MRI study. Hum. Brain Mapp. 35:11 (2014), 5633–5645.
17. Jones, K., Almond, S., Moving out of the linear rut: the possibilities of generalized additive models. Trans. Inst. Br. Geogr. 17:4 (1992), 434–447.
18. Kessler, R.C., Berglund, P., Demler, O., Jin, R., Merikangas, K.R., Walters, E.E., Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the national comorbidity survey replication. Arch. Gen. Psychiatr. 62:6 (2005), 593–602.
19. Kessler, R.C., McGonagle, K.A., Swartz, M., Blazer, D.G., Nelson, C.B., Sex and depression in the national comorbidity survey. I: lifetime prevalence, chronicity and recurrence. J. Affect. Disord. 29:2–3 (1993), 85–96.
20. Koolschijn, P.C., Crone, E.A., Sex differences and structural brain maturation from childhood to early adulthood. Dev. Cogn. Neurosci. 5 (2013), 106–118.
21. Kuhn, C., Emergence of sex differences in the development of substance use and abuse during adolescence. Pharmacol. Ther. 153 (2015), 55–78.
22. Lenroot, R.K., Gogtay, N., Greenstein, D.K., Wells, E.M., Wallace, G.L., Clasen, L.S., Blumenthal, J.D., Lerch, J., Zijdenbos, A.P., Evans, A.C., Thompson, P.M., Giedd, J.N., Sexual dimorphism of brain developmental trajectories during childhood and adolescence. Neuroimage 36:4 (2007), 1065–1073.
23. LeWinn, K.Z., Sheridan, M.A., Keyes, K.M., Hamilton, A., McLaughlin, K.A., Sample composition alters associations between age and brain structure. Nat. Commun., 8(1), 2017, 874.
24. Makowski, C., Beland, S., Kostopoulos, P., Bhagwat, N., Devenyi, G.A., Malla, A.K., Joober, R., Lepage, M., Chakravarty, M.M., Evaluating accuracy of striatal, pallidal, and thalamic segmentation methods: comparing automated approaches to manual delineation. Neuroimage, 2017, 10.1016/j.neuroimage.2017.02.069.
25. Mills, K.L., Goddings, A.L., Herting, M.M., Meuwese, R., Blakemore, S.J., Crone, E.A., Dahl, R.E., Guroglu, B., Raznahan, A., Sowell, E.R., Tamnes, C.K., Structural brain development between childhood and adulthood: convergence across four longitudinal samples. Neuroimage 141 (2016), 273–281.
26. Morey, R.A., Selgrade, E.S., Wagner, H.R. 2nd, Huettel, S.A., Wang, L., McCarthy, G., Scan-rescan reliability of subcortical brain volumes derived from automated segmentation. Hum. Brain Mapp. 31:11 (2010), 1751–1762.
27. Narvacan, K., Treit, S., Camicioli, R., Martin, W., Beaulieu, C., Evolution of deep gray matter volume across the human lifespan. Hum. Brain Mapp. 38:8 (2017), 3771–3790.
28. Ostby, Y., Tamnes, C.K., Fjell, A.M., Westlye, L.T., Due-Tonnessen, P., Walhovd, K.B., Heterogeneity in subcortical brain development: a structural magnetic resonance imaging study of brain maturation from 8 to 30 years. J. Neurosci. 29:38 (2009), 11772–11782.
29. Paus, T., Keshavan, M., Giedd, J.N., Why do many psychiatric disorders emerge during adolescence?. Nat. Rev. Neurosci. 9:12 (2008), 947–957.
30. Raznahan, A., Shaw, P.W., Lerch, J.P., Clasen, L.S., Greenstein, D., Berman, R., Pipitone, J., Chakravarty, M.M., Giedd, J.N., Longitudinal four-dimensional mapping of subcortical anatomy in human development. Proc. Natl. Acad. Sci. U. S. A. 111:4 (2014), 1592–1597.
31. Reardon, P.K., Clasen, L., Giedd, J.N., Blumenthal, J., Lerch, J.P., Chakravarty, M.M., Raznahan, A., An allometric analysis of sex and sex chromosome dosage effects on subcortical anatomy in humans. J. Neurosci. 36:8 (2016), 2438–2448.
32. Reuter, M., Schmansky, N.J., Rosas, H.D., Fischl, B., Within-subject template estimation for unbiased longitudinal image analysis. Neuroimage 61:4 (2012), 1402–1418.
33. Reuter, M., Tisdall, M.D., Qureshi, A., Buckner, R.L., van der Kouwe, A.J., Fischl, B., Head motion during MRI acquisition reduces gray matter volume and thickness estimates. Neuroimage 107 (2015), 107–115.
34. Roalf, D.R., Gur, R.E., Ruparel, K., Calkins, M.E., Satterthwaite, T.D., Bilker, W.B., Hakonarson, H., Harris, L.J., Gur, R.C., Within-individual variability in neurocognitive performance: age- and sex-related differences in children and youths from ages 8 to 21. Neuropsychology 28:4 (2014), 506–518.
35. Rose, A.J., Rudolph, K.D., A review of sex differences in peer relationship processes: potential trade-offs for the emotional and behavioral development of girls and boys. Psychol. Bull. 132:1 (2006), 98–131.
36. Ruigrok, A.N., Salimi-Khorshidi, G., Lai, M.C., Baron-Cohen, S., Lombardo, M.V., Tait, R.J., Suckling, J., A meta-analysis of sex differences in human brain structure. Neurosci. Biobehav. Rev. 39 (2014), 34–50.
37. Sanfilipo, M.P., Benedict, R.H., Zivadinov, R., Bakshi, R., Correction for intracranial volume in analysis of whole brain atrophy in multiple sclerosis: the proportion vs. residual method. Neuroimage 22:4 (2004), 1732–1743.
38. Schoemaker, D., Buss, C., Head, K., Sandman, C.A., Davis, E.P., Chakravarty, M.M., Gauthier, S., Pruessner, J.C., Hippocampus and amygdala volumes from magnetic resonance images in children: assessing accuracy of FreeSurfer and FSL against manual segmentation. Neuroimage 129 (2016), 1–14.
39. Shaw, P., Gogtay, N., Rapoport, J., Childhood psychiatric disorders as anomalies in neurodevelopmental trajectories. Hum. Brain Mapp. 31:6 (2010), 917–925.
40. Sowell, E.R., Thompson, P.M., Toga, A.W., Mapping changes in the human cortex throughout the span of life. Neuroscientist 10:4 (2004), 372–392.
41. Sowell, E.R., Trauner, D.A., Gamst, A., Jernigan, T.L., Development of cortical and subcortical brain structures in childhood and adolescence: a structural MRI study. Dev. Med. Child Neurol. 44:1 (2002), 4–16.
42. Tamnes, C.K., Herting, M.M., Goddings, A.L., Meuwese, R., Blakemore, S.J., Dahl, R.E., Guroglu, B., Raznahan, A., Sowell, E.R., Crone, E.A., Mills, K.L., Development of the cerebral cortex across adolescence: a multisample study of inter-related longitudinal changes in cortical volume, surface area, and thickness. J. Neurosci. 37:12 (2017), 3402–3412.
43. Tamnes, C.K., Walhovd, K.B., Dale, A.M., Ostby, Y., Grydeland, H., Richardson, G., Westlye, L.T., Roddey, J.C., Hagler, D.J. Jr., Due-Tonnessen, P., Holland, D., Fjell, A.M., I. Alzheimer's Disease Neuroimaging. Brain development and aging: overlapping and unique patterns of change. Neuroimage 68 (2013), 63–74.
44. Tustison, N., Holbrook, A., Avants, B., Roberts, J., Cook, P., Reagh, Z., Stone, J., Gillen D., and MA Y., (Unpublished). The ANTs Longitudinal Cortical Thickness Pipeline, doi:10.1101.170209.
45. Vijayakumar, N., Mills, K.L., Alexander-Bloch, A., Tamnes, C.K., Whittle, S., Structural brain development: a review of methodological approaches and best practices. Dev. Cognit. Neurosci., 2017, 10.2016/j.dcn.2017.11.008 (Accepted).
46. Wierenga, L., Langen, M., Ambrosino, S., van Dijk, S., Oranje, B., Durston, S., Typical development of basal ganglia, hippocampus, amygdala and cerebellum from age 7 to 24. Neuroimage 96 (2014), 67–72.
47. Wierenga, L.M., Sexton, J.A., Laake, P., Giedd, J.N., Tamnes, C.K., N. the Pediatric Imaging, and Genetics Study. A key characteristic of sex differences in the developing brain: greater variability in brain structure of boys than girls. Cerebr. Cortex, 1(11), 2017.
48. Wonderlick, J.S., Ziegler, D.A., Hosseini-Varnamkhasti, P., Locascio, J.J., Bakkour, A., van der Kouwe, A., Triantafyllou, C., Corkin, S., Dickerson, B.C., Reliability of MRI-derived cortical and subcortical morphometric measures: effects of pulse sequence, voxel geometry, and parallel imaging. Neuroimage 44:4 (2009), 1324–1333.
49. Yap, M.B., Allen, N.B., O'Shea, M., di Parsia, P., Simmons, J.G., Sheeber, L., Early adolescents’ temperament, emotion regulation during mother-child interactions, and depressive symptomatology. Dev. Psychopathol. 23:1 (2011), 267–282.
50. Zhang, Y., Brady, M., Smith, S., Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Trans. Med. Imag. 20:1 (2001), 45–57.
51. Zijdenbos, A.P., Forghani, R., Evans, A.C., Automatic “pipeline” analysis of 3-D MRI data for clinical trials: application to multiple sclerosis. IEEE Trans. Med. Imag. 21:10 (2002), 1280–1291.