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Early Adolescent Cortical Thinning Is Related to Better Neuropsychological Performance

Published online by Cambridge University Press:  15 August 2013

Lindsay M. Squeglia ,
Joanna Jacobus ,
Scott F. Sorg ,
Terry L. Jernigan  and
Susan F. Tapert
Lindsay M. Squeglia
Affiliation:
Department of Psychiatry, University of California San Diego, La Jolla, California
Joanna Jacobus
Affiliation:
Department of Psychiatry, University of California San Diego, La Jolla, California VA San Diego Healthcare System, La Jolla, California
Scott F. Sorg
Affiliation:
San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, California
Terry L. Jernigan
Affiliation:
Department of Psychiatry, University of California San Diego, La Jolla, California VA San Diego Healthcare System, La Jolla, California
Susan F. Tapert*
Affiliation:
Department of Psychiatry, University of California San Diego, La Jolla, California VA San Diego Healthcare System, La Jolla, California
*
Correspondence and reprint requests to: Susan F. Tapert, VA San Diego Healthcare System, Psychology Service (116B), 3350 La Jolla Village Drive, La Jolla, CA 92161. E-mail: stapert@ucsd.edu
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Abstract

Adolescence is characterized by significant neuromaturation, including extensive cortical thinning, particularly in frontal regions. The goal of this study was to examine the behavioral correlates of neurostructural development in early adolescence. Participants were 185 healthy 12- to 14-year-olds (44% female) recruited from local schools. Participants completed a comprehensive neuropsychological test battery and magnetic resonance imaging session. Cortical surface reconstruction and thickness estimates were performed via FreeSurfer. Age and cortical thickness were negatively correlated in 10 brain regions, 7 of which were in frontal areas (β = −.15 to −.25, ps ≤ .05). Hierarchical linear regressions examined the influence of cortical thickness on working memory, attention, verbal learning and memory, visuospatial functioning, spatial planning and problem solving, and inhibition, controlling for age and intracranial volume. Thinner parietal cortices predicted better performances on tests of verbal learning and memory, visuospatial functioning, and spatial planning and problem solving (β = −.14 to −.24, ps ≤ .05). Age, spanning from 12 to 14 years, accounted for up to 6% of cortical thickness, suggesting substantial thinning during early adolescence, with males showing more accelerated thinning than females between ages 12 and 14. For both males and females, thinner parietal association cortices corresponded with better neurocognitive functioning above and beyond age alone. (JINS, 2013, 19, 1–9)

Keywords

AdolescenceCortical thicknessFreeSurferNeurocognitive testingNeuropsychologyNormal development
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 19 , Issue 9 , October 2013 , pp. 962 - 970
Copyright
Copyright © The International Neuropsychological Society 2013 

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References

American Psychological Association. (1994). Diagnostic and Statistical Manual of Mental Disorders 4th edition, (DSM-IV). Washington, DC: American Psychiatric Association.Google Scholar
Bramen, J.E., Hranilovich, J.A., Dahl, R.E., Chen, J., Rosso, C., Forbes, E.E., Sowell, E.R. (2012). Sex matters during adolescence: Testosterone-related cortical thickness maturation differs between boys and girls. PLoS One, 7, e33850.CrossRefGoogle ScholarPubMed
Brown, T.T., Jernigan, T.L. (2012). Brain development during the preschool years. Neuropsychology Review, 22, 313–333.CrossRefGoogle ScholarPubMed
Dale, A.M., Fischl, B., Sereno, M.I. (1999). Cortical surface-based analysis. I. Segmentation and surface reconstruction. Neuroimage, 9, 179–194.CrossRefGoogle ScholarPubMed
Delis, D.C., Kramer, J.H., Kaplan, E., Ober, B.A. (1994). Manual for the California Verbal Learning Test–Children's Version. San Antonio, TX: The Psychological Corporation.Google Scholar
Delis, D.C., Kaplan, E., Kramer, J.H. (2001). The Delis-Kaplan Executive Function System: Examiner's manual. San Antonio, TX: The Psychological Corporation.Google Scholar
Desikan, R.S., Segonne, F., Fischl, B., Quinn, B.T., Dickerson, B.C., Blacker, D., Killiany, R.J. (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage, 968–980.CrossRefGoogle ScholarPubMed
Fischl, B., Dale, A.M. (2000). Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proceedings of the National Academy of Sciences of the United States of America, 97, 11050–11055.CrossRefGoogle ScholarPubMed
Fischl, B., Sereno, M.I., Dale, A.M. (1999). Cortical surface-based analysis. II: Inflation, flattening, and a surface-based coordinate system. Neuroimage, 9, 195–207.CrossRefGoogle Scholar
Fischl, B., van der Kouwe, A., Destrieux, C., Halgren, E., Segonne, F., Salat, D.H., Dale, A.M. (2004). Automatically parcellating the human cerebral cortex. Cerebral Cortex, 14, 11–22.CrossRefGoogle ScholarPubMed
Ghahramani, S. (1996). Fundamentals of probability. Upper Saddle River, New Jersey: Prentice Hall.Google Scholar
Giedd, J.N., Blumenthal, J., Jeffries, N.O., Castellanos, F.X., Liu, H., Zijdenbos, A., Rapoport, J.L. (1999). Brain development during childhood and adolescence: A longitudinal MRI study. Nature Neuroscience, 2, 861–863.CrossRefGoogle ScholarPubMed
Giedd, J.N., Clasen, L.S., Lenroot, R., Greenstein, D., Wallace, G.L., Ordaz, S., Chrousos, G.P. (2006). Puberty-related influences on brain development. Molecular and Cellular Endocrinology, 254-255, 154–162.CrossRefGoogle ScholarPubMed
Giedd, J.N., Raznahan, A., Mills, K., Lenroot, R.K. (2012). Review: Magnetic resonance imaging of male/female differences in human adolescent brain anatomy. Biology of Sex Differences, 3(1), 19.CrossRefGoogle ScholarPubMed
Gogtay, N., Giedd, J.N., Lusk, L., Hayashi, K.M., Greenstein, D., Vaituzis, A.C., Thompson, P.M. (2004). Dynamic mapping of human cortical development during childhood through early adulthood. Proceedings of the National Academy of Sciences of the United States of America, 101, 8174–8179.CrossRefGoogle ScholarPubMed
Gogtay, N., Thompson, P.M. (2010). Mapping gray matter development: Implications for typical development and vulnerability to psychopathology. Brain and Cognition, 72(1), 6–15.CrossRefGoogle ScholarPubMed
Hooper, H.E. (1958). The Hooper Visual Organization Test manual. Los Angeles: Western Psychological Services.Google Scholar
Huttenlocher, P.R. (1990). Morphometric study of human cerebral cortex development. Neuropsychologia, 28, 517–527.CrossRefGoogle ScholarPubMed
Jernigan, T.L., Trauner, D.A., Hesselink, J.R., Tallal, P.A. (1991). Maturation of human cerebrum observed in vivo during adolescence. Brain, 114(Pt 5), 2037–2049.CrossRefGoogle ScholarPubMed
Karama, S., Colom, R., Johnson, W., Deary, I.J., Haier, R., Waber, D.P., Evans, A.C. (2009). Cortical thickness correlates of specific cognitive performance accounted for by the general factor of intelligence in healthy children aged 6 to 18. Neuroimage, 55(4), 1443–1453.CrossRefGoogle Scholar
Kuperberg, G.R., Broome, M.R., McGuire, P.K., David, A.S., Eddy, M., Ozawa, F., Fischl, B. (2003). Regionally localized thinning of the cerebral cortex in schizophrenia. Archives of General Psychiatry, 60(9), 878–888.CrossRefGoogle ScholarPubMed
Lebel, C., Beaulieu, C. (2011). Longitudinal development of human brain wiring continues from childhood into adulthood. [Research Support, Non-US Gov't]. Journal of Neuroscience, 31(30), 10937–10947. doi:10.1523/JNEUROSCI.5302-10.2011.CrossRefGoogle ScholarPubMed
Lenroot, R.K., Gogtay, N., Greenstein, D.K., Wells, E.M., Wallace, G.L., Clasen, L.S., Giedd, J.N. (2007). Sexual dimorphism of brain developmental trajectories during childhood and adolescence. Neuroimage, 36(4), 1065–1073.CrossRefGoogle ScholarPubMed
Lewis, R.F. (1995). Digit Vigilance Test. Odessa, FL: Psychological Assessment Resources.Google Scholar
Luders, E., Narr, K.L., Thompson, P.M., Toga, A.W. (2009). Neuroanatomical correlates of intelligence. Intelligence, 37(2), 156–163.CrossRefGoogle ScholarPubMed
Østby, Y., Tamnes, C.K., Fjell, A.M., Walhovd, K.B. (2012). Dissociating memory processes in the developing brain: The role of hippocampal volume andcortical thickness in recall after minutes versus days. Cerebral Cortex, 22(2), 381–390.CrossRefGoogle Scholar
Østby, Y., Tamnes, C.K., Fjell, A.M., Westlye, L.T., Due-Tønnessen, P., Walhovd, K.B. (2009). Heterogeneity in subcortical brain development: A structural magnetic resonance imaging study of brain maturation from 8 to 30 years. Journal of Neuroscience, 29(38), 11772–11782.CrossRefGoogle ScholarPubMed
Panizzon, M.S., Fennema-Notestine, C., Eyler, L.T., Jernigan, T.L., Prom-Wormley, E., Neale, M., Kremen, W.S. (2009). Distinct genetic influences on cortical surface area and cortical thickness. Cerebral Cortex, 19(11), 2728–2735.CrossRefGoogle ScholarPubMed
Paus, T. (2005). Mapping brain maturation and cognitive development during adolescence. Trends in Cognitive Science, 9(2), 60–68.CrossRefGoogle ScholarPubMed
Porter, J.N., Collins, P.F., Muetzel, R.L., Lim, K.O., Luciana, M. (2011). Associations between cortical thickness and verbal fluency in childhood, adolescence, and young adulthood. Neuroimage, 55(4), 1865–1877.CrossRefGoogle ScholarPubMed
Rey, A., Osterrieth, P.A. (1993). Translations of excerpts from Andre Rey's “Psychological examination of traumatic encephalopathy” and P.A. Osterrieth's “The complex figure copy test” (J. Corwin & F. W. Bylsma, Trans). The Clinical Neuropsychologist, 7, 3–21.Google Scholar
Rosas, H.D., Liu, A.K., Hersch, S., Glessner, M., Ferrante, R.J., Salat, D.H., Fischl, B. (2002). Regional and progressive thinning of the cortical ribbon in Huntington's disease. Neurology, 58, 695–701.CrossRefGoogle ScholarPubMed
Salat, D.H., Buckner, R.L., Snyder, A.Z., Greve, D.N., Desikan, R.S., Busa, E., Fischl, B. (2004). Thinning of the cerebral cortex in aging. Cerebral Cortex, 14, 721–730.CrossRefGoogle ScholarPubMed
Schilling, C., Kühn, S., Paus, T., Romanowski, A., Banaschewski, T., Barbot, A., Gallinat, J. (2013). Cortical thickness of superior frontal cortex predicts impulsiveness and perceptual reasoning in adolescence. Molecular Psychiatry, 18, 624–630.CrossRefGoogle ScholarPubMed
Shaffer, D., Fisher, P., Lucas, C.P., Dulcan, M.K., Schwab-Stone, M.E. (2000). NIMH Diagnostic Interview Schedule for Children Version IV (NIMH DISC-IV): Description, differences from previous versions, and reliability of some common diagnoses. Journal of the American Academy of Child and Adolescent Psychiatry, 39, 28–38.CrossRefGoogle ScholarPubMed
Shaw, P., Greenstein, D., Lerch, J., Clasen, L., Lenroot, R., Gogtay, N., Giedd, J. (2006). Intellectual ability and cortical development in children and adolescents. Nature, 440(7084), 676–679.CrossRefGoogle ScholarPubMed
Shaw, P., Kabani, N.J., Lerch, J.P., Eckstrand, K., Lenroot, R., Gogtay, N., Wise, S.P. (2008). Neurodevelopmental trajectories of the human cerebral cortex. Journal of Neuroscience, 28(14), 3586–3594.CrossRefGoogle ScholarPubMed
Sowell, E.R., Delis, D., Stiles, J., Jernigan, T.L. (2001). Improved memory functioning and frontal lobe maturation between childhood and adolescence: A structural MRI study. Journal of the International Neuropsychological Society, 7(3), 312–322.CrossRefGoogle ScholarPubMed
Sowell, E.R., Peterson, B.S., Thompson, P.M., Welcome, S.E., Henkenius, A.L., Toga, A.W. (2003). Mapping cortical change across the human life span. Nature Neuroscience, 6(3), 309–315.CrossRefGoogle ScholarPubMed
Sowell, E.R., Thompson, P.M., Leonard, C.M., Welcome, S.E., Kan, E., Toga, A.W. (2004). Longitudinal mapping of cortical thickness and brain growth in normal children. Journal of Neuroscience, 24(38), 8223–8231.CrossRefGoogle ScholarPubMed
Sowell, E.R., Trauner, D.A., Gamst, A., Jernigan, T.L. (2002). Development of cortical and subcortical brain structures in childhood and adolescence: A structural MRI study. Developmental Medicine and Child Neurology, 44(1), 4–16.CrossRefGoogle ScholarPubMed
Squeglia, L.M., Pulido, C., Wetherill, R.R., Jacobus, J., Brown, G.G., Tapert, S.F. (2012). Brain response to working memory over three years of adolescence: Influence of initiating heavy drinking. Journal of Studies on Alcohol and Drugs, 73(5), 749–760.CrossRefGoogle ScholarPubMed
Squeglia, L.M., Spadoni, A.D., Infante, M.A., Myers, M.G., Tapert, S.F. (2009). Initiating moderate to heavy alcohol use predicts changes in neuropsychological functioning for adolescent girls and boys. Psychology of Addictive Behaviors, 23(4), 715–722.CrossRefGoogle ScholarPubMed
Tamnes, C.K., Ostby, Y., Fjell, A.M., Westlye, L.T., Due-Tønnessen, P., Walhovd, K.B. (2010). Brain maturation in adolescence and young adulthood: Regional age-related changes in cortical thickness and white matter volume and microstructure. Cerebral Cortex, 20(3), 534–548.CrossRefGoogle Scholar
Tamnes, C.K., Østby, Y., Walhovd, K.B., Westlye, L.T., Due-Tønnessen, P., Fjell, A.M. (2010). Neuroanatomical correlates of executive functions in children and adolescents: A magnetic resonance imaging (MRI) study of cortical thickness. Neuropsychologia, 48(9), 2496–2508.CrossRefGoogle ScholarPubMed
Urošević, S., Collins, P., Muetzel, R., Lim, K., Luciana, M. (2012). Longitudinal changes in behavioral approach system sensitivity and brain structures involved in reward processing during adolescence. Developmental Psychology, 48(5), 1488–1500.CrossRefGoogle ScholarPubMed
Wechsler, D. (1991). Wechsler Intelligence Scale for Children (3rd ed.). New York: The Psychological Corporation.Google Scholar
Wechsler, D. (1997). Wechsler Adult Intelligence Scale (3rd ed.). San Antonio, TX: The Psychological Corporation.Google Scholar
Wechsler, D. (1999). Wechsler Abbreviated Scale of Intelligence. San Antonio, TX: The Psychological Corporation.Google Scholar
Wechsler, D. (2008). Wechsler Adult Intelligence Scale–Fourth Edition. San Antonio, TX: Pearson.Google Scholar
Winkler, A.M., Kochunov, P., Blangero, J., Almasy, L., Zilles, K., Fox, P.T., Glahn, D.C. (2010). Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies. Neuroimage, 53(3), 1135–1146.CrossRefGoogle ScholarPubMed
Winkler, A.M., Sabuncu, M.R., Yeo, B.T., Fischl, B., Greve, D.N., Kochunov, P., Glahn, D.C. (2012). Measuring and comparing brain cortical surface area and other areal quantities. Neuroimage, 61(4), 1428–1443.CrossRefGoogle ScholarPubMed