White matter integrity and cognitive performance in school-age children: A population-based neuroimaging study

NeuroImage

Volumn 119, Issue , 2015, Pages 119-128

  Muetzel, Ryan L ^a   Mous, Sabine E ^a   van der Ende, Jan ^a   Blanken, Laura M E ^a   van der Lugt, Aad ^b   Jaddoe, Vincent W V ^a   Verhulst, Frank C ^a   Tiemeier, Henning ^a,b   White, Tonya ^a,b  

^a SOPHIA CHILDREN S HOSPITAL   (Netherlands)

^b ERASMUS MEDICAL CENTER   (Netherlands)

Author keywords

Brain development; Diffusion tensor imaging; MRI; Neuropsychological performance; Population based imaging

Indexed keywords

ARTICLE; AXIAL DIFFUSIVITY; BRAIN DEVELOPMENT; BRAIN MICROSTRUCTURE; CHILD; CHILD BEHAVIOR CHECKLIST; COGNITION; CORRELATIONAL STUDY; DEPTH PERCEPTION; DIFFUSION TENSOR IMAGING; FEMALE; FRACTIONAL ANISOTROPY; HUMAN; INTELLIGENCE QUOTIENT; MALE; MORPHOLOGY; NEPSY II NL; NEUROIMAGING; NEUROPSYCHOLOGICAL TEST; NONVERBAL INTELLIGENCE; PHYSICAL PARAMETERS; PRIORITY JOURNAL; SCHOOL CHILD; STRUCTURAL EQUATION MODELING; STRUCTURE ACTIVITY RELATION; STRUCTURE ANALYSIS; WHITE MATTER; ANATOMY AND HISTOLOGY; BRAIN; INTELLIGENCE; NUCLEAR MAGNETIC RESONANCE IMAGING; PHYSIOLOGY; PSYCHOMOTOR PERFORMANCE;

BRAIN; CHILD; COGNITION; DIFFUSION TENSOR IMAGING; FEMALE; HUMANS; INTELLIGENCE; MAGNETIC RESONANCE IMAGING; MALE; NEUROIMAGING; NEUROPSYCHOLOGICAL TESTS; PSYCHOMOTOR PERFORMANCE; WHITE MATTER;

EID: 84935428340     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2015.06.014     Document Type: Article

References (63)

1. Achenbach T.M., Rescorla L.A. Manual for ASEBA Preschool Forms & Profiles 2000, University of Vermont, Reseach Center for Children, Youth & Families, Burlington, VT.
2. Barnea-Goraly N., Menon V., Eckert M., Tamm L., Bammer R., Karchemskiy A., Dant C.C., Reiss A.L. White matter development during childhood and adolescence: a cross-sectional diffusion tensor imaging study. Cereb. Cortex 2005, 15:1848-1854.
3. Basser P.J., Pierpaoli C. Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J. Magn. Reson. Ser. B 1996, 111:209-219.
4. Basser P.J., Mattiello J., LeBihan D. MR diffusion tensor spectroscopy and imaging. Biophys. J. 1994, 66:259-267.
5. Basten M., van der Ende J., Tiemeier H., Althoff R.R., Rijlaarsdam J., Jaddoe V.W., Hofman A., Hudziak J.J., Verhulst F.C., White T. Nonverbal intelligence in young children with dysregulation: the Generation R Study. Eur. Child Adolesc. Psychiatry 2014, 23:1061-1070.
6. Beaulieu C. The basis of anisotropic water diffusion in the nervous system - a technical review. NMR Biomed. 2002, 15:435-455.
7. Beaulieu C., Allen P.S. Determinants of anisotropic water diffusion in nerves. Magn. Reson. Med. 1994, 31:394-400.
8. Behrens T.E., Woolrich M.W., Jenkinson M., Johansen-Berg H., Nunes R.G., Clare S., Matthews P.M., Brady J.M., Smith S.M. Characterization and propagation of uncertainty in diffusion-weighted MR imaging. Magn. Reson. Med. 2003, 50:1077-1088.
9. Behrens T.E., Berg H.J., Jbabdi S., Rushworth M.F., Woolrich M.W. Probabilistic diffusion tractography with multiple fibre orientations: what can we gain?. NeuroImage 2007, 34:144-155.
10. Brooks B.L., Sherman E.M., Iverson G.L. Healthy children get low scores too: prevalence of low scores on the NEPSY-II in preschoolers, children, and adolescents. Arch. Clin. Neuropsychol. 2010, 25:182-190.
11. Chang L.C., Jones D.K., Pierpaoli C. RESTORE: robust estimation of tensors by outlier rejection. Magn. Reson. Med. 2005, 53:1088-1095.
12. Cook P.A., Bai Y., Nedjati-Gilani S., Seunarine K.K., Hall M.G., Parker G.J., Alexander D.C. Camino: Open-Source Diffusion-MRI Reconstruction and Processing. 14th Scientific Meeting of the International Society for Magnetic Resonance in Medicine, Seattle, WA, USA 2006, 2759.
13. de Groot M., Ikram M.A., Akoudad S., Krestin G.P., Hofman A., van der Lugt A., Niessen W.J., Vernooij M.W. Tract-specific white matter degeneration in aging: the Rotterdam study. Alzheimers Dement. 2015, 11:321-330.
14. 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 2015, 25:1676-1684.
15. Fryer S.L., Frank L.R., Spadoni A.D., Theilmann R.J., Nagel B.J., Schweinsburg A.D., Tapert S.F. Microstructural integrity of the corpus callosum linked with neuropsychological performance in adolescents. Brain Cogn. 2008, 67:225-233.
16. Galwey N.W. A new measure of the effective number of tests, a practical tool for comparing families of non-independent significance tests. Genet. Epidemiol. 2009, 33:559-568.
17. Ge H., Yin X., Xu J., Tang Y., Han Y., Xu W., Pang Z., Meng H., Liu S. Fiber pathways of attention subnetworks revealed with tract-based spatial statistics (TBSS) and probabilistic tractography. PLoS ONE 2013, 8:e78831.
18. Giedd J.N., Blumenthal J., Jeffries N.O., Castellanos F.X., Liu H., Zijdenbos A., Paus T., Evans A.C., Rapoport J.L. Brain development during childhood and adolescence: a longitudinal MRI study. Nat. Neurosci. 1999, 2:861-863.
19. Giorgio A., Watkins K.E., Douaud G., James A.C., James S., De Stefano N., Matthews P.M., Smith S.M., Johansen-Berg H. Changes in white matter microstructure during adolescence. NeuroImage 2008, 39:52-61.
20. Gorgolewski K., Burns C.D., Madison C., Clark D., Halchenko Y.O., Waskom M.L., Ghosh S.S. Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in python. Front. Neuroinformatics 2011, 5:13.
21. Gulani V., Webb A.G., Duncan I.D., Lauterbur P.C. Apparent diffusion tensor measurements in myelin-deficient rat spinal cords. Magn. Reson. Med. 2001, 45:191-195.
22. Hanggi J., Buchmann A., Mondadori C.R., Henke K., Jancke L., Hock C. Sexual dimorphism in the parietal substrate associated with visuospatial cognition independent of general intelligence. J. Cogn. Neurosci. 2010, 22:139-155.
23. Haselgrove J.C., Moore J.R. Correction for distortion of echo-planar images used to calculate the apparent diffusion coefficient. Magn. Reson. Med. 1996, 36:960-964.
24. Honaker J., King G., Blackwell M. Amelia II: a program for missing data. J. Stat. Softw. 2011, 45:1-47.
25. Hu L.T., Bentler P.M. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct. Equ. Model. 1999, 6:1-55.
26. Jaddoe V.W., van Duijn C.M., Franco O.H., van der Heijden A.J., van Iizendoorn M.H., de Jongste J.C., van der Lugt A., Mackenbach J.P., Moll H.A., Raat H., Rivadeneira F., Steegers E.A., Tiemeier H., Uitterlinden A.G., Verhulst F.C., Hofman A. The Generation R Study: design and cohort update 2012. Eur. J. Epidemiol. 2012, 27:739-756.
27. Jenkinson M., Smith S. A global optimisation method for robust affine registration of brain images. Med. Image Anal. 2001, 5:143-156.
28. Jenkinson M., Beckmann C.F., Behrens T.E., Woolrich M.W., Smith S.M. Fsl. Neuroimage 2012, 62:782-790.
29. Johansen-Berg H., Della-Maggiore V., Behrens T.E., Smith S.M., Paus T. Integrity of white matter in the corpus callosum correlates with bimanual co-ordination skills. NeuroImage 2007, 36(Suppl. 2):T16-T21.
30. Jones D.K., Cercignani M. Twenty-five pitfalls in the analysis of diffusion MRI data. NMR Biomed. 2010, 23:803-820.
31. Jung R.E., Haier R.J. The parieto-frontal integration theory (P-FIT) of intelligence: converging neuroimaging evidence. Behav. Brain Sci. 2007, 30. (135-+).
32. Klarborg B., Skak Madsen K., Vestergaard M., Skimminge A., Jernigan T.L., Baare W.F. Sustained attention is associated with right superior longitudinal fasciculus and superior parietal white matter microstructure in children. Hum. Brain Mapp. 2013, 34:3216-3232.
33. Lebel C., Walker L., Leemans A., Phillips L., Beaulieu C. Microstructural maturation of the human brain from childhood to adulthood. NeuroImage 2008, 40:1044-1055.
34. Leemans A., Jones D.K. The B-matrix must be rotated when correcting for subject motion in DTI data. Magn. Reson. Med. 2009, 61:1336-1349.
35. Lenroot R.K., Giedd J.N. Brain development in children and adolescents: insights from anatomical magnetic resonance imaging. Neurosci. Biobehav. Rev. 2006, 30:718-729.
36. Mabbott D.J., Rovet J., Noseworthy M.D., Smith M.L., Rockel C. The relations between white matter and declarative memory in older children and adolescents. Brain Res. 2009, 1294:80-90.
37. Maitland S.B., Intrieri R.C., Schaie W.K., Willis S.L. Gender differences and changes in cognitive abilities across the adult life span. Aging Neuropsychol. Cognit. 2000, 7:32-53.
38. McGrath J., Johnson K., O'Hanlon E., Garavan H., Gallagher L., Leemans A. White matter and visuospatial processing in autism: a constrained spherical deconvolution tractography study. Autism Res. 2013, 6:307-319.
39. Mous S.E., Schoemaker N.K., Blanken L.M.E., Thijssen S., van der Ende J., Polderman T.J.C., Jaddoe V., Hofman A., Verhulst F., Tiemeier H., White T. The association of gender, age and intelligence with neuropsychological functioning in young typically developing children - The Generation R Study. Appl. Neuropsychol.: Child 2015, (in press).
40. Muetzel R.L., Collins P.F., Mueller B.A., A, M.S., Lim K.O., Luciana M. The development of corpus callosum microstructure and associations with bimanual task performance in healthy adolescents. NeuroImage 2008, 39:1918-1925.
41. Navas-Sanchez F.J., Aleman-Gomez Y., Sanchez-Gonzalez J., Guzman-De-Villoria J.A., Franco C., Robles O., Arango C., Desco M. White matter microstructure correlates of mathematical giftedness and intelligence quotient. Hum. Brain Mapp. 2014, 35:2619-2631.
42. Paus T. Growth of white matter in the adolescent brain: myelin or axon?. Brain Cogn. 2010, 72:26-35.
43. Qiu D., Tan L.H., Zhou K., Khong P.L. Diffusion tensor imaging of normal white matter maturation from late childhood to young adulthood: voxel-wise evaluation of mean diffusivity, fractional anisotropy, radial and axial diffusivities, and correlation with reading development. NeuroImage 2008, 41:223-232.
44. R Core Team R: A Language and Environment for Statistical Computing 2014, R foundation for Statistical Computing, Vienna, Austria.
45. Rosseel Y. lavaan: an R package for structural equation modeling. J. Stat. Softw. 2012, 48:1-36.
46. Sahyoun C.P., Belliveau J.W., Mody M. White matter integrity and pictorial reasoning in high-functioning children with autism. Brain Cogn. 2010, 73:180-188.
47. Schmahmann J.D., Pandya D.N., Wang R., Dai G., D'Arceuil H.E., de Crespigny A.J., Wedeen V.J. Association fibre pathways of the brain: parallel observations from diffusion spectrum imaging and autoradiography. Brain 2007, 130:630-653.
48. Schmithorst V.J. Developmental sex differences in the relation of neuroanatomical connectivity to intelligence. Intelligence 2009, 37:164-173.
49. Schmithorst V.J., Yuan W. White matter development during adolescence as shown by diffusion MRI. Brain Cogn. 2010, 72:16-25.
50. Schmithorst V.J., Wilke M., Dardzinski B.J., Holland S.K. Correlation of white matter diffusivity and anisotropy with age during childhood and adolescence: a cross-sectional diffusion-tensor MR imaging study. Radiology 2002, 222:212-218.
51. Schmithorst V.J., Wilke M., Dardzinski B.J., Holland S.K. Cognitive functions correlate with white matter architecture in a normal pediatric population: a diffusion tensor MRI study. Hum. Brain Mapp. 2005, 26:139-147.
52. Schmithorst V.J., Holland S.K., Dardzinski B.J. Developmental differences in white matter architecture between boys and girls. Hum. Brain Mapp. 2008, 29:696-710.
53. Šidák Z. Rectangular confidence regions for the means of multivariate normal distributions. J. Am. Stat. Assoc. 1967, 62:626-633.
54. Simmonds D.J., Hallquist M.N., Asato M., Luna B. Developmental stages and sex differences of white matter and behavioral development through adolescence: a longitudinal diffusion tensor imaging (DTI) study. NeuroImage 2014, 92:356-368.
55. Smith S.M. Fast robust automated brain extraction. Hum. Brain Mapp. 2002, 17:143-155.
56. Sui J., Adali T., Yu Q., Chen J., Calhoun V.D. A review of multivariate methods for multimodal fusion of brain imaging data. J. Neurosci. Methods 2012, 204:68-81.
57. Tellegen P.J., Winkel M., Wijnberg-Williams B., Laros J.A. Snijders-Oomen Niet-Verbale Intelligentietest: SON-R 2-1/2 -to-7 2005, Boom Testuitgevers, Amsterdam.
58. Tick N.T., van der Ende J., Koot H.M., Verhulst F.C. 14-year changes in emotional and behavioral problems of very young Dutch children. J. Am. Acad. Child Adolesc. Psychiatry 2007, 46:1333-1340.
59. Tiemeier H., Velders F.P., Szekely E., Roza S.J., Dieleman G., Jaddoe V.W., Uitterlinden A.G., White T.J., Bakermans-Kranenburg M.J., Hofman A., Van Ijzendoorn M.H., Hudziak J.J., Verhulst F.C. The Generation R Study: a review of design, findings to date, and a study of the 5-HTTLPR by environmental interaction from fetal life onward. J. Am. Acad. Child Adolesc. Psychiatry 2012, 51(1119-1135):e1117.
60. Veraart J., Sijbers J., Sunaert S., Leemans A., Jeurissen B. Weighted linear least squares estimation of diffusion MRI parameters: strengths, limitations, and pitfalls. NeuroImage 2013, 81:335-346.
61. Wallace G.L., Schmitt J.E., Lenroot R., Viding E., Ordaz S., Rosenthal M.A., Molloy E.A., Clasen L.S., Kendler K.S., Neale M.C., Giedd J.N. A pediatric twin study of brain morphometry. J. Child Psychol. Psychiatry 2006, 47:987-993.
62. Wang Y., Adamson C., Yuan W., Altaye M., Rajagopal A., Byars A.W., Holland S.K. Sex differences in white matter development during adolescence: a DTI study. Brain Res. 2012, 1478:1-15.
63. White T., El Marroun H., Nijs I., Schmidt M., van der Lugt A., Wielopolki P.A., Jaddoe V.W., Hofman A., Krestin G.P., Tiemeier H., Verhulst F.C. Pediatric population-based neuroimaging and the Generation R Study: the intersection of developmental neuroscience and epidemiology. Eur. J. Epidemiol. 2013, 28:99-111.