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Pattern classification of response inhibition in ADHD: Toward the development of neurobiological markers for ADHD

Hart, Heledd ; Chantiluke, Kaylita ; Cubillo, Ana I. ; Smith, Anna B. ; Simmons, Andrew ; Brammer, Michael J. ; Marquand, Andre F. ; Rubia, Katya

Human brain mapping, 2014-07, Vol.35 (7), p.3083-3094 [Periódico revisado por pares]

New York, NY: Blackwell Publishing Ltd

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Título:
Pattern classification of response inhibition in ADHD: Toward the development of neurobiological markers for ADHD
Autor: Hart, Heledd ; Chantiluke, Kaylita ; Cubillo, Ana I. ; Smith, Anna B. ; Simmons, Andrew ; Brammer, Michael J. ; Marquand, Andre F. ; Rubia, Katya
Assuntos: ADHD ; Adolescent ; Analysis of Variance ; Attention Deficit Disorder with Hyperactivity - complications ; Attention Deficit Disorder with Hyperactivity - psychology ; Biological and medical sciences ; biomarker ; Brain - blood supply ; Brain - physiopathology ; Child ; diagnosis ; Electrodiagnosis. Electric activity recording ; functional magnetic resonance imaging ; Gaussian process classifier ; Humans ; Image Processing, Computer-Assisted ; inhibition ; Inhibition (Psychology) ; Investigative techniques, diagnostic techniques (general aspects) ; Magnetic Resonance Imaging ; Male ; Medical sciences ; Miscellaneous. Technology ; Nervous system ; Nervous System Diseases - etiology ; Neuropsychological Tests ; Normal Distribution ; Oxygen - blood ; Radiodiagnosis. Nmr imagery. Nmr spectrometry ; Reaction Time
É parte de: Human brain mapping, 2014-07, Vol.35 (7), p.3083-3094
Notas: NIHR Biomedical Research Centre (BRC) for Mental Health at South London and Maudsley NHS Foundation Trust and Institute of Psychiatry, Kings College London and Lilly Pharmaceuticals, Kids Company, NIHR BRC, King's College London Centre of Excellence in Medical Engineering
Well-come Trust and EPSRC - No. Nr WT088641/Z/09/Z
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Descrição: The diagnosis of Attention Deficit Hyperactivity Disorder (ADHD) is based on subjective measures despite evidence for multisystemic structural and functional deficits. ADHD patients have consistent neurofunctional deficits in motor response inhibition. The aim of this study was to apply pattern classification to task‐based functional magnetic resonance imaging (fMRI) of inhibition, to accurately predict the diagnostic status of ADHD. Thirty adolescent ADHD and thirty age‐matched healthy boys underwent fMRI while performing a Stop task. fMRI data were analyzed with Gaussian process classifiers (GPC), a machine learning approach, to predict individual ADHD diagnosis based on task‐based activation patterns. Traditional univariate case‐control analyses were also performed to replicate previous findings in a relatively large dataset. The pattern of brain activation correctly classified up to 90% of patients and 63% of controls, achieving an overall classification accuracy of 77%. The regions of the discriminative network most predictive of controls included later developing lateral prefrontal, striatal, and temporo‐parietal areas that mediate inhibition, while regions most predictive of ADHD were in earlier developing ventromedial fronto‐limbic regions, which furthermore correlated with symptom severity. Univariate analysis showed reduced activation in ADHD in bilateral ventrolateral prefrontal, striatal, and temporo‐parietal regions that overlapped with areas predictive of controls, suggesting the latter are dysfunctional areas in ADHD. We show that significant individual classification of ADHD patients of 77% can be achieved using whole brain pattern analysis of task‐based fMRI inhibition data, suggesting that multivariate pattern recognition analyses of inhibition networks can provide objective diagnostic neuroimaging biomarkers of ADHD. Hum Brain Mapp 35:3083–3094, 2014. © 2013 Wiley Periodicals, Inc.
Editor: New York, NY: Blackwell Publishing Ltd
Idioma: Inglês

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Pattern classification of response inhibition in ADHD: Toward the development of neurobiological markers for ADHD

Hart, Heledd ; Chantiluke, Kaylita ; Cubillo, Ana I. ; Smith, Anna B. ; Simmons, Andrew ; Brammer, Michael J. ; Marquand, Andre F. ; Rubia, Katya

New York, NY: Blackwell Publishing Ltd

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