Skip to main content

Advertisement

Springer Nature Link
Log in

The NeuroIMAGE study: a prospective phenotypic, cognitive, genetic and MRI study in children with attention-deficit/hyperactivity disorder. Design and descriptives

  • Original Contribution
  • Published:
European Child & Adolescent Psychiatry Aims and scope Submit manuscript

Abstract

Attention-deficit/hyperactivity disorder (ADHD) is a persistent neuropsychiatric disorder which is associated with impairments on a variety of cognitive measures and abnormalities in structural and functional brain measures. Genetic factors are thought to play an important role in the etiology of ADHD. The NeuroIMAGE study is a follow-up of the Dutch part of the International Multicenter ADHD Genetics (IMAGE) project. It is a multi-site prospective cohort study designed to investigate the course of ADHD, its genetic and environmental determinants, its cognitive and neurobiological underpinnings, and its consequences in adolescence and adulthood. From the original 365 ADHD families and 148 control (CON) IMAGE families, consisting of 506 participants with an ADHD diagnosis, 350 unaffected siblings, and 283 healthy controls, 79 % participated in the NeuroIMAGE follow-up study. Combined with newly recruited participants the NeuroIMAGE study comprehends an assessment of 1,069 children (751 from ADHD families; 318 from CON families) and 848 parents (582 from ADHD families; 266 from CON families). For most families, data for more than one child (82 %) and both parents (82 %) were available. Collected data include a diagnostic interview, behavioural questionnaires, cognitive measures, structural and functional neuroimaging, and genome-wide genetic information. The NeuroIMAGE dataset allows examining the course of ADHD over adolescence into young adulthood, identifying phenotypic, cognitive, and neural mechanisms associated with the persistence versus remission of ADHD, and studying their genetic and environmental underpinnings. The inclusion of siblings of ADHD probands and controls allows modelling of shared familial influences on the ADHD phenotype.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Explore related subjects

Discover the latest articles and news from researchers in related subjects, suggested using machine learning.

References

  1. Polanczyk G, de Lima MS, Horta BL et al (2007) The worldwide prevalence of ADHD: a systematic review and metaregression analysis. Am J Psychiatry 164:942–948. doi:10.1176/appi.ajp.164.6.942

    Article  PubMed  Google Scholar 

  2. Fayyad J, De Graaf R, Kessler R et al (2007) Cross-national prevalence and correlates of adult attention-deficit hyperactivity disorder. Br J Psychiatry 190:402–409. doi:10.1192/bjp.bp.106.034389

    Article  CAS  PubMed  Google Scholar 

  3. American Psychiatric Association (2000) Diagnostic and statistical manual of mental disorders, 4 edn. doi:10.1176/appi.books.9780890423349

  4. Faraone SV, Biederman J, Mick E (2006) The age-dependent decline of attention deficit hyperactivity disorder: a meta-analysis of follow-up studies. Psychol Med 36:159–165. doi:10.1017/S003329170500471X

    Article  PubMed  Google Scholar 

  5. Faraone SV, Perlis RH, Doyle AE et al (2005) Molecular genetics of attention-deficit/hyperactivity disorder. Biol Psychiatry 57:1313–1323. doi:10.1016/j.biopsych.2004.11.024

    Article  CAS  PubMed  Google Scholar 

  6. Franke B, Neale BM, Faraone SV (2009) Genome-wide association studies in ADHD. Hum Genet 126:13–50. doi:10.1007/s00439-009-0663-4

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  7. Williams NM (2012) Genome-wide analysis of copy number variants in attention deficit hyperactivity disorder: the role of rare variants and duplications at 15q13.3. Am J Psychiatry 169:195. doi:10.1176/appi.ajp.2011.11060822

    Article  PubMed Central  PubMed  Google Scholar 

  8. Lionel AC, Crosbie J, Barbosa N et al (2011) Rare copy number variation discovery and cross-disorder comparisons identify risk genes for ADHD. Sci Transl Med 3:95ra75. doi:10.1126/scitranslmed.3002464

    Article  CAS  PubMed  Google Scholar 

  9. Willcutt E, Sonuga-Barke E, Nigg J, Sergeant J (2008) Recent developments in neuropsychological models of childhood psychiatric disorders. In: Banaschewski T, Rohde LA (eds) Biological child psychiatry. Recent trends and developments, vol 24. Karger Publishers, Basel, pp 195–226. doi:10.1016/j.chc.2007.11.008

  10. Luman M, Oosterlaan J, Sergeant JA (2005) The impact of reinforcement contingencies on AD/HD: a review and theoretical appraisal. Clin Psychol Rev 25:183–213. doi:10.1016/j.cpr.2004.11.001

    Article  PubMed  Google Scholar 

  11. Toplak ME, Dockstader C, Tannock R (2006) Temporal information processing in ADHD: findings to date and new methods. J Neurosci Methods 151:15–29. doi:10.1016/j.jneumeth.2005.09.018

    Article  PubMed  Google Scholar 

  12. Valera EM, Faraone SV, Murray KE, Seidman LJ (2007) Meta-analysis of structural imaging findings in attention-deficit/hyperactivity disorder. Biol Psychiatry 61:1361–1369. doi:10.1016/j.biopsych.2006.06.011

    Article  PubMed  Google Scholar 

  13. Frodl T, Skokauskas N (2011) Meta-analysis of structural MRI studies in children and adults with attention deficit hyperactivity disorder indicates treatment effects. Acta Psychiatr Scand 125:114–126. doi:10.1111/j.1600-0447.2011.01786.x

    Article  PubMed  Google Scholar 

  14. Nakao T, Radua J, Rubia K, Mataix-Cols D (2011) Gray matter volume abnormalities in ADHD: voxel-based meta-analysis exploring the effects of age and stimulant medication. Am J Psychiatry 168:1154–1163. doi:10.1176/appi.ajp.2011.11020281

    Article  PubMed  Google Scholar 

  15. van Ewijk H, Heslenfeld DJ, Zwiers MP et al (2012) Diffusion tensor imaging in attention deficit/hyperactivity disorder: a systematic review and meta-analysis. Neurosci Biobehav Rev 36:1093–1106. doi:10.1016/j.neubiorev.2012.01.003

    Article  PubMed  Google Scholar 

  16. Cortese S, Kelly C, Chabernaud C et al (2012) Toward systems neuroscience of ADHD: a meta-analysis of 55 fMRI studies. Am J Psychiatry 169:1038–1055. doi:10.1176/appi.ajp.2012.11101521

    Article  PubMed  Google Scholar 

  17. Spencer TJ, Brown A, Seidman LJ et al (2013) Effect of psychostimulants on brain structure and function in ADHD. J Clin Psychiatry 74:902–917. doi:10.4088/JCP.12r08287

    Article  PubMed Central  PubMed  Google Scholar 

  18. Gizer IR, Ficks C, Waldman ID (2009) Candidate gene studies of ADHD: a meta-analytic review. Hum Genet 126:51–90. doi:10.1007/s00439-009-0694-x

    Article  CAS  PubMed  Google Scholar 

  19. Scheres A, Milham MP, Knutson B, Castellanos FX (2007) Ventral striatal hyporesponsiveness during reward anticipation in attention-deficit/hyperactivity disorder. Biol Psychiatry 61:720–724. doi:10.1016/j.biopsych.2006.04.042

    Article  PubMed  Google Scholar 

  20. Paloyelis Y, Mehta MA, Faraone SV et al (2012) Striatal sensitivity during reward processing in attention-deficit/hyperactivity disorder. J Am Acad Child Adolesc Psychiatry 51(722–732):e9. doi:10.1016/j.jaac.2012.05.006

    PubMed  Google Scholar 

  21. Scheres A, Oosterlaan J, Sergeant JA (2001) Response execution and inhibition in children with AD/HD and other disruptive disorders: the role of behavioural activation. J Child Psychol Psychiatry 42:347–357

    Article  CAS  PubMed  Google Scholar 

  22. Brookes K, Xu X, Chen W et al (2006) The analysis of 51 genes in DSM-IV combined type attention deficit hyperactivity disorder: association signals in DRD4, DAT1 and 16 other genes. Mol Psychiatry 11:934–953. doi:10.1038/sj.mp.4001869

    Article  CAS  PubMed  Google Scholar 

  23. Rommelse N, Altink M, Martin ME et al (2008) Neuropsychological measures probably facilitate heritability research of ADHD. Arch Clin Neuropsychol 23:579–591. doi:10.1016/j.acn.2008.06.002

    Article  PubMed Central  PubMed  Google Scholar 

  24. Asherson P, Brookes K, Franke B et al (2007) Confirmation that a specific haplotype of the dopamine transporter gene is associated with combined-type ADHD. Am J Psychiatry 164:674–677. doi:10.1176/appi.ajp.164.4.674

    Article  PubMed  Google Scholar 

  25. Asherson P, Zhou K, Anney RJL et al (2008) A high-density SNP linkage scan with 142 combined subtype ADHD sib pairs identifies linkage regions on chromosomes 9 and 16. Mol Psychiatry 13:514–521. doi:10.1038/sj.mp.4002140

    Article  CAS  PubMed  Google Scholar 

  26. Rommelse NNJ, Arias-Vásquez A, Altink ME et al (2008) Neuropsychological endophenotype approach to genome-wide linkage analysis identifies susceptibility loci for ADHD on 2q21.1 and 13q12.11. Am J Hum Genet 83:99–105. doi:10.1016/j.ajhg.2008.06.006

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  27. Zhou K, Asherson P, Sham P et al (2008) Linkage to chromosome 1p36 for attention-deficit/hyperactivity disorder traits in school and home settings. Biol Psychiatry 64:571–576. doi:10.1016/j.biopsych.2008.02.024

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  28. Lasky-Su J, Neale BM, Franke B et al (2008) Genome-wide association scan of quantitative traits for attention deficit hyperactivity disorder identifies novel associations and confirms candidate gene associations. Am J Med Genet B Neuropsychiatr Genet 147B:1345–1354. doi:10.1002/ajmg.b.30867

    Article  CAS  PubMed  Google Scholar 

  29. Lasky-Su J, Anney RJL, Neale BM et al (2008) Genome-wide association scan of the time to onset of attention deficit hyperactivity disorder. Am J Med Genet B Neuropsychiatr Genet 147B:1355–1358. doi:10.1002/ajmg.b.30869

    Article  PubMed Central  PubMed  Google Scholar 

  30. Neale BM, Lasky-Su J, Anney R et al (2008) Genome-wide association scan of attention deficit hyperactivity disorder. Am J Med Genet B Neuropsychiatr Genet 147B:1337–1344. doi:10.1002/ajmg.b.30866

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  31. Neale BM, Medland SE, Ripke S et al (2010) Meta-analysis of genome-wide association studies of attention-deficit/hyperactivity disorder. J Am Acad Child Adolesc Psychiatry 49:884–897. doi:10.1016/j.jaac.2010.06.008

    Article  PubMed Central  PubMed  Google Scholar 

  32. Zhou K, Dempfle A, Arcos-Burgos M et al (2008) Meta-analysis of genome-wide linkage scans of attention deficit hyperactivity disorder. Am J Med Genet B Neuropsychiatr Genet 147B:1392–1398. doi:10.1002/ajmg.b.30878

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  33. Andreou P, Neale BM, Chen W et al (2007) Reaction time performance in ADHD: improvement under fast-incentive condition and familial effects. Psychol Med. doi:10.1017/S0033291707000815

    PubMed Central  PubMed  Google Scholar 

  34. Rommelse NNJ, Altink ME, Oosterlaan J et al (2007) Speed, variability, and timing of motor output in ADHD: which measures are useful for endophenotypic research? Behav Genet 38:121–132. doi:10.1007/s10519-007-9186-8

    Article  PubMed Central  PubMed  Google Scholar 

  35. Rommelse NNJ, Altink ME, Oosterlaan J et al (2008) Support for an independent familial segregation of executive and intelligence endophenotypes in ADHD families. Psychol Med 38:1595. doi:10.1017/S0033291708002869

    Article  CAS  PubMed  Google Scholar 

  36. Gottesman II, Gould TD (2003) The endophenotype concept in psychiatry: etymology and strategic intentions. Am J Psychiatry 160:636–645

    Article  PubMed  Google Scholar 

  37. Rommelse NNJ, Geurts HM, Franke B et al (2011) A review on cognitive and brain endophenotypes that may be common in autism spectrum disorder and attention-deficit/hyperactivity disorder and facilitate the search for pleiotropic genes. Neurosci Biobehav Rev 35:1363–1396. doi:10.1016/j.neubiorev.2011.02.015

    Article  CAS  PubMed  Google Scholar 

  38. Groenman AP, Oosterlaan J, Rommelse N et al (2013) Substance use disorders in adolescents with attention deficit hyperactivity disorder: a 4-year follow-up study. Addiction 108:1503–1511. doi:10.1111/add.12188

    Article  PubMed  Google Scholar 

  39. Groenman AP, Oosterlaan J, Rommelse NNJ et al (2013) Stimulant treatment for attention-deficit hyperactivity disorder and risk of developing substance use disorder. Br J Psychiatry 203:112–119. doi:10.1192/bjp.bp.112.124784

    Article  PubMed  Google Scholar 

  40. Müller UC, Asherson P, Banaschewski T et al (2011) The impact of study design and diagnostic approach in a large multi-centre ADHD study. Part 1: ADHD symptom patterns. BMC Psychiatry 11:54. doi:10.1186/1471-244X-11-54

    Article  PubMed Central  PubMed  Google Scholar 

  41. Müller UC, Asherson P, Banaschewski T et al (2011) The impact of study design and diagnostic approach in a large multi-centre ADHD study: Part 2: dimensional measures of psychopathology and intelligence. BMC Psychiatry 11:55. doi:10.1186/1471-244X-11-55

    Article  PubMed Central  PubMed  Google Scholar 

  42. Nijmeijer JS, Hoekstra PJ, Minderaa RB et al (2008) PDD symptoms in ADHD, an independent familial trait? J Abnorm Child Psychol 37:443–453. doi:10.1007/s10802-008-9282-0

    Article  Google Scholar 

  43. van Lieshout M, Luman M, Twisk JWR et al. Persistence rates and symptom change in attention-deficit/hyperactivity disorder (submitted)

  44. Conners CK, Erhardt D, Sparrow E (1999) Conners’ adult ADHD rating scales: technical manual. Multi-Health Systems, New York

    Google Scholar 

  45. Conners CK, Sitarenios G, Parker JD, Epstein JN (1998) The revised Conners’ Parent Rating Scale (CPRS-R): factor structure, reliability, and criterion validity. J Abnorm Child Psychol 26:257–268

    Article  CAS  PubMed  Google Scholar 

  46. Conners CK, Wells KC, Parker JDA et al (1997) A new self-report scale for assessment of adolescent psychopathology: factor structure, reliability, validity, and diagnostic sensitivity. J Abnorm Child Psychol 25:487–497. doi:10.1023/A:1022637815797

    Article  CAS  PubMed  Google Scholar 

  47. Saunders JB, Aasland OG, Babor TF et al (1993) Development of the alcohol use disorders identification test (AUDIT): WHO collaborative project on early detection of persons with harmful alcohol consumption-II. Addiction 88:791–804. doi:10.1111/j.1360-0443.1993.tb02093.x

    Article  CAS  PubMed  Google Scholar 

  48. Gavin DR, Ross HE, Skinner HA (1989) Diagnostic validity of the drug abuse screening test in the assessment of DSM-III drug disorders. Addiction 84:301–307. doi:10.1111/j.1360-0443.1989.tb03463.x

    Article  CAS  Google Scholar 

  49. Heatherton TF, Kozlowski LT, Frecker RC, Fagerström K-O (1991) The Fagerstrom test for nicotine dependence: a revision of the Fagerstrom tolerance questionnaire. Addiction 86:1119–1127. doi:10.1111/j.1360-0443.1991.tb01879.x

    Article  CAS  Google Scholar 

  50. Sobell LC, Brown J, Leo GI, Sobell MB (1996) The reliability of the Alcohol Timeline Followback when administered by telephone and by computer. Drug Alcohol Depend 42:49–54

    Article  CAS  PubMed  Google Scholar 

  51. Selzer ML, Vinokur A, van Rooijen L (1975) A self-administered Short Michigan Alcoholism Screening Test (SMAST). J Stud Alcohol 36:117–126

    CAS  PubMed  Google Scholar 

  52. Lesieur HR, Blume SB (1987) The South Oaks Gambling Screen (SOGS): a new instrument for the identification of pathological gamblers. Am J Psychiatry 144(9):1184–1188

  53. Parker D, Reason J, Manstead A, Stradling S (1995) Driving errors, driving violations and accident involvement. TERG 38:1036–1048. doi:10.1080/00140139508925170

    Article  Google Scholar 

  54. Shaffer D, Fisher P, Lucas CP et al (2000) NIMH Diagnostic Interview Schedule for Children Version IV (NIMH DISC-IV): description, differences from previous versions, and reliability of some common diagnoses. J Am Acad Child Adolesc Psychiatry 39:28–38. doi:10.1097/00004583-200001000-00014

    Article  CAS  PubMed  Google Scholar 

  55. Johnston L, O’Malley PM, Bachman JG (1998) National survey results on drug use from the Monitoring the Future Study, 1975–1997

  56. Wilens TE, Gignac M, Swezey A et al (2006) Characteristics of adolescents and young adults with ADHD who divert or misuse their prescribed medications. J Am Acad Child Adolesc Psychiatry 45:408–414. doi:10.1097/01.chi.0000199027.68828.b3

    Article  PubMed  Google Scholar 

  57. Kaufman J, Birmaher B, Brent D et al (1997) Schedule for affective disorders and schizophrenia for school-age children-present and lifetime version (K-SADS-PL): initial reliability and validity data. J Am Acad Child Adolesc Psychiatry 36:980–988. doi:10.1097/00004583-199707000-00021

    Article  CAS  PubMed  Google Scholar 

  58. van Widenfelt BM, Goedhart AW, Treffers PDA, Goodman R (2003) Dutch version of the Strengths and Difficulties Questionnaire (SDQ). Eur Child Adolesc Psychiatry 12:281–289. doi:10.1007/s00787-003-0341-3

    Article  PubMed  Google Scholar 

  59. Donker T, Comijs H, Cuijpers P et al (2010) Psychiatry research. Psychiatry Res 176:45–50. doi:10.1016/j.psychres.2009.01.012

    Article  PubMed  Google Scholar 

  60. Kessler RC, Andrews G, Colpe LJ et al (2002) Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychol Med 32:959–976

    Article  CAS  PubMed  Google Scholar 

  61. Conners CK, Sitarenios G, Parker JD, Epstein JN (1998) Revision and restandardization of the Conners Teacher Rating Scale (CTRS-R): factor structure, reliability, and criterion validity. J Abnorm Child Psychol 26:279–291

    Article  CAS  PubMed  Google Scholar 

  62. Tremblay RE, Loeber R, Gagnon C et al (1991) Disruptive boys with stable and unstable high fighting behavior patterns during junior elementary school. J Abnorm Child Psychol 19:285–300

    Article  CAS  PubMed  Google Scholar 

  63. Bosch NM, Riese H, Reijneveld SA et al (2012) Timing matters: long term effects of adversities from prenatal period up to adolescence on adolescents’ cortisol stress response. The TRAILS study. Psychoneuroendocrinology 37:1439–1447. doi:10.1016/j.psyneuen.2012.01.013

    Article  CAS  PubMed  Google Scholar 

  64. Oldehinkel AJ, Verhulst FC, Ormel J (2008) Low heart rate: a marker of stress resilience. The TRAILS study. Biol Psychiatry 63:1141–1146. doi:10.1016/j.biopsych.2007.12.006

    Article  PubMed  Google Scholar 

  65. Walden B, McGue M, Lacono WG et al (2004) Identifying shared environmental contributions to early substance use: the respective roles of peers and parents. J Abnorm Psychol 113:440–450. doi:10.1037/0021-843X.113.3.440

    Article  PubMed  Google Scholar 

  66. Loeber R, Wung P, Keenan K, Giroux B, Stouthamer-Loeber M, Van Kammen WB, Maugham B (1993) Developmental pathways in disruptive child behavior. Dev Psychopathol 5(1–2):103–133

  67. Geluk CAML, Jansen LMC, Vermeiren R et al (2012) Autistic symptoms in childhood arrestees: longitudinal association with delinquent behavior. J Child Psychol Psychiatry 53:160–167. doi:10.1111/j.1469-7610.2011.02456.x

    Article  PubMed  Google Scholar 

  68. Kimonis ER, Frick PJ, Skeem JL et al (2008) Assessing callous–unemotional traits in adolescent offenders: validation of the Inventory of Callous–Unemotional Traits. Int J Law Psychiatry 31:241–252. doi:10.1016/j.ijlp.2008.04.002

    Article  PubMed  Google Scholar 

  69. Brooks-Gunn J, Warren MP, Rosso J, Gargiulo J (1987) Validity of self-report measures of girls’ pubertal status. Child Dev 58:829–841

    Article  CAS  PubMed  Google Scholar 

  70. Wilson BN, Kaplan BJ, Crawford SG et al (2000) Reliability and validity of a parent questionnaire on childhood motor skills. Am J Occup Ther 54:484–493

    Article  CAS  PubMed  Google Scholar 

  71. Brown GW (1966) The measurement of family activities and relationships: a methodological study. Hum Relat 19:241–263. doi:10.1177/001872676601900301

    Article  Google Scholar 

  72. Kerr M, Stattin H (2000) What parents know, how they know it, and several forms of adolescent adjustment: further support for a reinterpretation of monitoring. Dev Psychol 36:366–380. doi:10.1037//0012-1649.36.3.366

    Article  CAS  PubMed  Google Scholar 

  73. Goldberg LR (1992) The development of markers for the Big-Five factor structure. Psychol Assess 4:26

    Article  Google Scholar 

  74. Klimstra TA, Hale WW, Raaijmakers QAW et al (2009) Maturation of personality in adolescence. J Pers Soc Psychol 96:898–912. doi:10.1037/a0014746

    Article  PubMed  Google Scholar 

  75. Polanczyk G, Caspi A, Houts R et al (2010) Implications of extending the ADHD age-of-onset criterion to age 12: results from a prospectively studied birth cohort. J Am Acad Child Adolesc Psychiatry 49:210–216

    PubMed  Google Scholar 

  76. Wechsler D (2000) WAIS-III Nederlandstalige bewerking. Technische handleiding. The Psychological Corporation, London

    Google Scholar 

  77. Wechsler D (2002) WISC-III Handleiding. The Psychological Corporation, London

    Google Scholar 

  78. Logan GD, Cowan WB, Davis KA (1984) On the ability to inhibit simple and choice reaction time responses: a model and a method. J Exp Psychol Hum Percept Perform 10:276–291

    Article  CAS  PubMed  Google Scholar 

  79. Klingberg T, Forssberg H, Westerberg H (2002) Training of working memory in children with ADHD. J Clin Exp Neuropsychol (Neuropsychol Dev Cognit Sect A) 24:781–791. doi:10.1076/jcen.24.6.781.8395

    Article  Google Scholar 

  80. McNab F, Leroux G, Strand F et al (2008) Common and unique components of inhibition and working memory: an fMRI, within-subjects investigation. Neuropsychologia 46:2668–2682. doi:10.1016/j.neuropsychologia.2008.04.023

    Article  PubMed  Google Scholar 

  81. De Sonneville L (1999) Amsterdam neuropsychological tasks: a computer-aided assessment program. Computers in psychology

  82. Rommelse NNJ, Altink ME, de Sonneville LMJ et al (2007) Are motor inhibition and cognitive flexibility dead ends in ADHD? J Abnorm Child Psychol 35:957–967. doi:10.1007/s10802-007-9146-z

    Article  PubMed  Google Scholar 

  83. Rommelse NNJ, Oosterlaan J, Buitelaar J et al (2007) Time reproduction in children with ADHD and their nonaffected siblings. J Am Acad Child Adolesc Psychiatry 46:582–590. doi:10.1097/CHI.0b013e3180335af7

    Article  PubMed  Google Scholar 

  84. Brus BT, Voeten M (1973) Een-Minuut-Test. Vorm A en B. Harcourt Test. Lisse, The Netherlands

    Google Scholar 

  85. Itami S, Uno H (2002) Orbitofrontal cortex dysfunction in attention-deficit hyperactivity disorder revealed by reversal and extinction tasks. NeuroReport 13:2453–2457. doi:10.1097/01.wnr.0000047687.08940.42

    Article  PubMed  Google Scholar 

  86. Scheres A, Dijkstra M, Ainslie E et al (2006) Temporal and probabilistic discounting of rewards in children and adolescents: effects of age and ADHD symptoms. Neuropsychologia 44:2092–2103. doi:10.1016/j.neuropsychologia.2005.10.012

    Article  PubMed  Google Scholar 

  87. Knutson B, Fong GW, Adams CM et al (2001) Dissociation of reward anticipation and outcome with event-related fMRI. NeuroReport 12:3683–3687

    Article  CAS  PubMed  Google Scholar 

  88. Power JD, Barnes KA, Snyder AZ et al (2012) Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage 59:2142–2154. doi:10.1016/j.neuroimage.2011.10.018

    Article  PubMed Central  PubMed  Google Scholar 

  89. Satterthwaite TD, Wolf DH, Loughead J et al (2012) Impact of in-scanner head motion on multiple measures of functional connectivity: relevance for studies of neurodevelopment in youth. Neuroimage 60:623–632. doi:10.1016/j.neuroimage.2011.12.063

    Article  PubMed Central  PubMed  Google Scholar 

  90. Van Dijk KRA, Sabuncu MR, Buckner RL (2012) The influence of head motion on intrinsic functional connectivity MRI. Neuroimage 59:431–438. doi:10.1016/j.neuroimage.2011.07.044

    Article  PubMed Central  PubMed  Google Scholar 

  91. Henkelman RM (1985) Measurement of signal intensities in the presence of noise in MR images. Med Phys 12:232–233

    Article  CAS  PubMed  Google Scholar 

  92. Filippini N, MacIntosh BJ, Hough MG et al (2009) Distinct patterns of brain activity in young carriers of the APOE-ε4 allele. Proc Natl Acad Sci USA 106:7209–7214

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  93. Bureau A, Croteau J, Tayeb A et al (2011) Latent class model with familial dependence to address heterogeneity in complex diseases: adapting the approach to family-based association studies. Genet Epidemiol 35:182–189. doi:10.1002/gepi.20566

    Article  PubMed Central  PubMed  Google Scholar 

  94. Fair DA, Bathula D, Nikolas MA, Nigg JT (2012) Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD. Proc Natl Acad Sci 109:6769–6774. doi:10.1073/pnas.1115365109

    Article  PubMed Central  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

The NeuroIMAGE project was supported by NIH Grant R01MH62873 (to Stephen V. Faraone), NWO Large Investment Grant 1750102007010 and ZonMW Grant 60-60600-97-193 (to Jan Buitelaar), and grants from Radboud University Nijmegen Medical Center, University Medical Center Groningen and Accare, and VU University Amsterdam. We acknowledge the department of Pediatrics of the VU University Medical Center for giving us the opportunity to use their mock scanner for preparation of our participants. We thank Paul Gaalman and IT staff of the VU University Amsterdam for technical MRI assistance, all PhD students for their contribution to the data acquisition and are grateful to all participating families.

Conflict of interest

Jan Buitelaar has been in the past 3 years a consultant to/member of advisory board of/speaker for Janssen Cilag BV, Eli Lilly, Bristol-Myer Squibb, Shering Plough, UCB, Shire, Novartis and Servier. He is not an employee of any of these companies, and not a stock shareholder of any of these companies. He has no other financial or material support, including expert testimony, patents and royalties. Jaap Oosterlaan has been on the advisory board of Shire and UCB Pharmaceuticals. He has received an unrestricted grant from Shire. Pieter Hoekstra has received honoraria for advice from Eli Lilly and Shire. In the past year, Stephen V. Faraone received consulting income and/or research support from Shire, Otsuka and Alcobra and research support from the National Institutes of Health (NIH). In previous years, he received consulting fees or was on Advisory Boards or participated in continuing medical education programs sponsored by: Shire, McNeil, Janssen, Novartis, Pfizer and Eli Lilly. SVF receives royalties from books published by Guilford Press: Straight Talk about Your Child’s Mental Health and Oxford University Press: Schizophrenia: The Facts. The other authors have no potentially competing interests.

Author information

Authors and Affiliations

  1. Centre for Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands

    Daniel von Rhein, Maarten Mennes, Annabeth P. Groenman, Marcel P. Zwiers & Jan Buitelaar

  2. Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands

    Daniel von Rhein, Maarten Mennes & Marcel P. Zwiers

  3. Department of Clinical Neuropsychology, VU University, Amsterdam, The Netherlands

    Hanneke van Ewijk, Annabeth P. Groenman, Jaap Oosterlaan & Dirk Heslenfeld

  4. Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands

    Barbara Franke

  5. Department of Psychiatry, University Medical Center, Groningen, The Netherlands

    Pieter J. Hoekstra & Catharina Hartman

  6. Department of Psychiatry, Radboud University Medical Centre, Nijmegen, The Netherlands

    Barbara Franke & Jan Buitelaar

  7. Departments of Psychiatry and of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, USA

    Stephen V. Faraone

  8. Department of Cognitive Neuroscience (204), P.O. Box 9101, 6500 HG, Nijmegen, The Netherlands

    Jan Buitelaar

Authors
  1. Daniel von Rhein
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Maarten Mennes
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Hanneke van Ewijk
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Annabeth P. Groenman
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Marcel P. Zwiers
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Jaap Oosterlaan
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Dirk Heslenfeld
    View author publications

    You can also search for this author inPubMed Google Scholar

  8. Barbara Franke
    View author publications

    You can also search for this author inPubMed Google Scholar

  9. Pieter J. Hoekstra
    View author publications

    You can also search for this author inPubMed Google Scholar

  10. Stephen V. Faraone
    View author publications

    You can also search for this author inPubMed Google Scholar

  11. Catharina Hartman
    View author publications

    You can also search for this author inPubMed Google Scholar

  12. Jan Buitelaar
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Jan Buitelaar.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (XLS 33 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

von Rhein, D., Mennes, M., van Ewijk, H. et al. The NeuroIMAGE study: a prospective phenotypic, cognitive, genetic and MRI study in children with attention-deficit/hyperactivity disorder. Design and descriptives. Eur Child Adolesc Psychiatry 24, 265–281 (2015). https://doi.org/10.1007/s00787-014-0573-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00787-014-0573-4

Keywords