Classifying adolescent attention-deficit/hyperactivity disorder (ADHD) based on functional and structural imaging
- 1.2k Downloads
Attention-deficit/hyperactivity disorder (ADHD) is a common disabling psychiatric disorder associated with consistent deficits in error processing, inhibition and regionally decreased grey matter volumes. The diagnosis is based on clinical presentation, interviews and questionnaires, which are to some degree subjective and would benefit from verification through biomarkers. Here, pattern recognition of multiple discriminative functional and structural brain patterns was applied to classify adolescents with ADHD and controls. Functional activation features in a Flanker/NoGo task probing error processing and inhibition along with structural magnetic resonance imaging data served to predict group membership using support vector machines (SVMs). The SVM pattern recognition algorithm correctly classified 77.78 % of the subjects with a sensitivity and specificity of 77.78 % based on error processing. Predictive regions for controls were mainly detected in core areas for error processing and attention such as the medial and dorsolateral frontal areas reflecting deficient processing in ADHD (Hart et al., in Hum Brain Mapp 35:3083–3094, 2014), and overlapped with decreased activations in patients in conventional group comparisons. Regions more predictive for ADHD patients were identified in the posterior cingulate, temporal and occipital cortex. Interestingly despite pronounced univariate group differences in inhibition-related activation and grey matter volumes the corresponding classifiers failed or only yielded a poor discrimination. The present study corroborates the potential of task-related brain activation for classification shown in previous studies. It remains to be clarified whether error processing, which performed best here, also contributes to the discrimination of useful dimensions and subtypes, different psychiatric disorders, and prediction of treatment success across studies and sites.
KeywordsADHD fMRI Classification Attention Adolescence
This study was supported by Swiss National Science Foundation grant (No. 320030_130237) and the Hartmann Mueller Foundation (No. 1,460). We thank Julia Frey and Maya Schneebeli for assistance with MR-measurements, recruitment and administrative work, Carolin Knie for help with clinical interviews, and Philipp Staempfli and Marco Piccirelli for their helpful inputs on our MR-sequence. We thank the anonymous reviewers for their helpful suggestions to improve this article.
Conflict of interest
S. Walitza received speakers’ honoraria from Eli Lilly, Opo-Pharma, Janssen-Cilag and AstraZeneca in the last 5 years.
- 1.Albrecht B, Brandeis D, Uebel H, Heinrich H, Mueller UC, Hasselhorn M, Steinhausen HC, Rothenberger A, Banaschewski T (2008) Action monitoring in boys with attention-deficit/hyperactivity disorder, their nonaffected siblings, and normal control subjects: evidence for an endophenotype. Biol Psychiatry 64:615–625PubMedCentralCrossRefPubMedGoogle Scholar
- 3.APA (2000) DSM IV: Diagnositic and statistical manual of mental disorders. American Psychiatric Press, Washington DCGoogle Scholar
- 11.Castellanos FX, Lee PP, Sharp W, Jeffries NO, Greenstein DK, Clasen LS, Blumenthal JD, James RS, Ebens CL, Walter JM, Zijdenbos A, Evans AC, Giedd JN, Rapoport JL (2002) Developmental trajectories of brain volume abnormalities in children and adolescents with attention-deficit/hyperactivity disorder. JAMA 288:1740–1748CrossRefPubMedGoogle Scholar
- 13.Cubillo A, Halari R, Smith A, Taylor E, Rubia K (2012) A review of fronto-striatal and fronto-cortical brain abnormalities in children and adults with Attention Deficit Hyperactivity Disorder (ADHD) and new evidence for dysfunction in adults with ADHD during motivation and attention. Cortex 48:194–215CrossRefPubMedGoogle Scholar
- 16.Ecker C, Marquand A, Mourão-Miranda J, Johnston P, Daly EM, Brammer MJ, Maltezos S, Murphy CM, Robertson D, Williams SC, Murphy DGM (2010) Describing the brain in autism in five dimensions—magnetic resonance imaging-assisted diagnosis of autism spectrum disorder using a multiparameter classification approach. J Neurosci 30:10612–10623CrossRefPubMedGoogle Scholar
- 28.Hart H, Marquand AF, Smith A, Cubillo A, Simmons A, Brammer M, Rubia K (2014) Predictive neurofunctional markers of attention-deficit/hyperactivity disorder based on pattern classification of temporal processing. J Am Acad Child Adolesc Psychiatry 53(569–578):e561Google Scholar
- 29.Hastie T, Tibshirani R, Friedman JH (2003) The elements of statistical learning. Springer, New YorkGoogle Scholar
- 34.Kaufman J, Birmaher B, Brent D, Rao U, Flynn C, Moreci P, Williamson D, Ryan N (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 36:980–988CrossRefPubMedGoogle Scholar
- 37.Lim L, Marquand A, Cubillo AA, Smith AB, Chantiluke K, Simmons A, Mehta M, Rubia K (2013) Disorder-specific predictive classification of adolescents with attention deficit hyperactivity disorder (ADHD) relative to autism using structural magnetic resonance imaging. PLoS ONE 8:e63660PubMedCentralCrossRefPubMedGoogle Scholar
- 40.Marquand A, Rondina J, Mourao-Miranda J, Rocha-Rego V, Giampietro V Manual: Pattern Recognition of Brain Image Data—PROBID. Version 1.03Google Scholar
- 45.Mørch N, Hansen L, Strother S, Svarer C, Rottenberg D, Lautrup B, Savoy R, Paulson O (1997) Nonlinear versus linear models in functional neuroimaging: learning curves and generalization crossover. In: Duncan J, Gindi G (eds) Information Processing in Medical Imaging. Springer, Berlin Heidelberg, pp 259–270CrossRefGoogle Scholar
- 48.Mourao-Miranda J, Reinders AATS, Rocha-Rego V, Lappin J, Rondina J, Morgan C, Morgan KD, Fearon P, Jones PB, Doody GA, Murray RM, Kapur S, Dazzan P (2012) Individualized prediction of illness course at the first psychotic episode: a support vector machine MRI study. Psychol Med 42:1037–1047PubMedCentralCrossRefPubMedGoogle Scholar
- 59.Rubia K, Cubillo A, Smith AB, Woolley J, Heyman I, Brammer MJ (2010) Disorder-specific dysfunction in right inferior prefrontal cortex during two inhibition tasks in boys with attention-deficit hyperactivity disorder compared to boys with obsessive–compulsive disorder. Hum Brain Mapp 31:287–299CrossRefPubMedGoogle Scholar
- 60.Rubia K, Halari R, Cubillo A, Mohammad AM, Brammer M, Taylor E (2009) Methylphenidate normalises activation and functional connectivity deficits in attention and motivation networks in medication-naive children with ADHD during a rewarded continuous performance task. Neuropharmacology 57:640–652CrossRefPubMedGoogle Scholar
- 74.WHO (2010) International Classification of Diseases (ICD-10)Google Scholar