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

Abstract

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.

Brain abnormalities in adults with Attention Deficit Hyperactivity Disorder revealed by voxel-based morphometry

“…This is the first volumetric study in ADHD adult population that has shown smaller GM in the SMA. Functional neuroimaging studies suggest that a network of fronto-parietal brain regions -including the inferior prefrontal, medial prefrontal (the SMA and pre-SMA) and inferior parietal areas, are implicated in motor response inhibition (Hart et al, 2013), with SMA as one of the key motor inhibition areas (Hart et al, 2014). This may be significant, since some psychological theories have proposed that ADHD symptoms result from a primary deficit in inhibitory control (Barkley, 1997).…”

Structural and functional neuroimaging in attention‐deficit/hyperactivity disorder

“…Increased activity has been observed in regions constituting the default mode network (DMN), whose activation is normally reduced during tasks and increased during resting‐state in typically developing participants . Multivariate pattern recognition analysis of inhibition networks based on task‐based functional MRI was proposed as a potential complementary diagnostic tool for ADHD . Nevertheless, meta‐analyses and individual studies have also reported increased inhibition‐related activity in regions typically showing a reduced activation in ADHD during inhibition tasks, such as the inferior frontal gyrus, suggesting that response‐inhibition related activity in children with ADHD cannot at this time be considered as a systematic biomarker for ADHD.…”

Multivariate classification of autism spectrum disorder using frequency-specific resting-state functional connectivity—A multi-center study

“…Recently, an increasing number of studies have focused on applying MVPA to discriminate brain disease at the individual level. Some success has been achieved in the study of major depressive disorder (Liu et al, 2012), Alzheimer's Disease (Liu et al, 2014) and attention-deficit hyperactivity disorder (Hart et al, 2014).…”