|Shared and Drug-Specific Effects of Atomoxetine and Methylphenidate on Inhibitory Brain Dysfunction in Medication-Naive ADHD Boys.|
|Jump to Full Text|
|PMID: 23048018 Owner: NLM Status: Publisher|
|The stimulant methylphenidate (MPX) and the nonstimulant atomoxetine (ATX) are the most commonly prescribed medications for attention deficit hyperactivity disorder (ADHD). However, no functional magnetic resonance imaging (fMRI) study has as yet investigated the effects of ATX on inhibitory or any other brain function in ADHD patients or compared its effects with those of MPX. A randomized, double-blind, placebo-controlled, crossover pharmacological design was used to compare the neurofunctional effects of single doses of MPX, ATX, and placebo during a stop task, combined with fMRI within 19 medication-naive ADHD boys, and their potential normalization effects relative to 29 age-matched healthy boys. Compared with controls, ADHD boys under placebo showed bilateral ventrolateral prefrontal, middle temporal, and cerebellar underactivation. Within patients, MPX relative to ATX and placebo significantly upregulated right ventrolateral prefrontal activation, which correlated with enhanced inhibitory capacity. Relative to controls, both drugs significantly normalized the left ventrolateral prefrontal underactivation observed under placebo, while MPX had a drug-specific effect of normalizing right ventrolateral prefrontal and cerebellar underactivation observed under both placebo and ATX. The findings show shared and drug-specific effects of MPX and ATX on performance and brain activation during inhibitory control in ADHD patients with superior upregulation and normalization effects of MPX.|
|Ana Cubillo; Anna B Smith; Nadia Barrett; Vincent Giampietro; Michael J Brammer; Andrew Simmons; Katya Rubia|
Related Documents :
|7713458 - Drug accumulation and elimination in calliphora vicina larvae.
24421838 - Successful management of nosocomial ventriculitis and meningitis caused by extensively ...
21284528 - Oxidative stress and endothelial dysfunction: therapeutic implications.
9476508 - Fluconazole: comparison of pharmacokinetics, therapy and in vitro susceptibility.
3092648 - Sorption of four drugs to polyvinyl chloride and polybutadiene intravenous administrati...
9426808 - The neurological basis of attention deficit hyperactivity disorder.
|Type: JOURNAL ARTICLE Date: 2012-10-9|
|Title: Cerebral cortex (New York, N.Y. : 1991) Volume: - ISSN: 1460-2199 ISO Abbreviation: Cereb. Cortex Publication Date: 2012 Oct|
|Created Date: 2012-10-10 Completed Date: - Revised Date: -|
Medline Journal Info:
|Nlm Unique ID: 9110718 Medline TA: Cereb Cortex Country: -|
|Languages: ENG Pagination: - Citation Subset: -|
|Department of Child Psychiatry.|
|APA/MLA Format Download EndNote Download BibTex|
Journal ID (nlm-ta): Cereb Cortex
Journal ID (iso-abbrev): Cereb. Cortex
Journal ID (publisher-id): cercor
Journal ID (hwp): cercor
Publisher: Oxford University Press
© The Author 2012. Published by Oxford University Press.
Print publication date: Month: 1 Year: 2014
Electronic publication date: Day: 9 Month: 10 Year: 2012
pmc-release publication date: Day: 9 Month: 10 Year: 2012
Volume: 24 Issue: 1
First Page: 174 Last Page: 185
PubMed Id: 23048018
Publisher Id: bhs296
|Shared and Drug-Specific Effects of Atomoxetine and Methylphenidate on Inhibitory Brain Dysfunction in Medication-Naive ADHD Boys|
|Anna B. Smith1|
|Michael J. Brammer2|
1Department of Child Psychiatry,
2Department of Neuroimaging,
3Center for Neurodegeneration Research,
4NIHR Biomedical Research Centre for Mental Health at South London and Maudsley NHS Trust, Institute of Psychiatry, King's College London, London, UK
|A.C. and A.B.S. have equally contributed to first authorship.
Correspondence: Address correspondence to Katya Rubia, Department of Child Psychiatry/SGDP, P046, Institute of Psychiatry, 16 De Crespigny Park, London SE5 8AF, UK. Email: email@example.com
Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by age-inappropriate levels of impulsivity, inattention, and hyperactivity (American Psychiatric Association 2000). One of the most consistent findings are deficits in motor response inhibition, in particular during a stop task (Alderson et al. 2007), underpinned by functional magnetic resonance imaging (fMRI) findings of reduced activation in key areas of motor response inhibition such as ventrolateral prefrontal cortex (VLPFC), supplementary motor area (SMA), and caudate (Rubia 2011; Cubillo et al. 2012).
The stimulant methylphenidate (MPX) and the nonstimulant atomoxetine (ATX) are the most frequently prescribed drugs for the treatment of ADHD. Recent meta-analyses show that both drugs have comparable efficacy rates in reducing ADHD symptoms (Hazell et al. 2010; van Wyk et al. 2012), with 1 meta-analysis showing the superior efficacy of the long-acting but not short-acting MPX preparation (Hanwella et al. 2011). However, their mechanisms of action in ADHD are relatively unknown. In humans, at therapeutic doses, MPX blocks 60–70% of the dopamine transporter in the striatum (Volkow et al. 1998). However, MPX has also shown to block 70–80% of the norepinephrine transporter in noradrenaline transporter-rich brain regions, including the prefrontal cortex (Hannestad et al. 2010). In rodent studies, MPX has shown to enhance the extracellular levels of both noradrenaline and dopamine (Bymaster et al. 2002). ATX is a selective presynaptic noradrenaline transporter blocker, which at therapeutic doses has shown to occupy noradrenaline transporters almost completely in the anterior cingulate (ACC), thalamus, brain stem, midbrain, locus ceruleus, and cerebellum in nonhuman primates (Gallezot et al. 2011).
In healthy adults, a single dose of MPX has been shown to downregulate right VLPFC activation during successful inhibitory trials in the stop task (Pauls et al. forthcoming 2012) and to upregulate activation in the putamen during errors in a go/no-go task, without significant effects during successful inhibition on brain activation or performance (Costa et al. forthcoming 2012). In ADHD patients, however, the effects of a single-dose MPX challenge on brain networks of motor inhibition have been more pronounced. Thus, in previously medicated children with ADHD, MPX has been shown to upregulate activation in the frontal, ACC, striatal, and parietal areas during go/no-go tasks (Vaidya et al. 1998; Epstein et al. 2007) and to normalize all brain activation deficits in the VLPFC, SMA, parieto-temporal, and cerebellar regions in medication-naive children with ADHD during the stop task (Rubia, Halari, Mohammad et al. 2011). Furthermore, during other cognitive control, attention, and timing functions, single-dose MPX challenges in ADHD children have shown to upregulate or normalize most prominently fronto-striatal, but also temporo-parietal, cingulate, and cerebellar activations (Shafritz et al. 2004; Rubia, Halari, Christakou et al. 2009; Rubia, Halari, Cubillo et al. 2009; 2011).
However, no fMRI study has as yet investigated the effects of ATX in ADHD patients, or compared its effects with those of MPX during any cognitive function. In healthy adults, a single-dose challenge of ATX upregulated VLPFC, superior temporal gyrus (STG), and SMA activation during motor inhibition tasks (Chamberlain et al. 2009; Graf et al. 2011).
The aim of this study was therefore to compare the effects of a single dose of MPX and ATX in medication-naive ADHD boys during a challenging stop task using a randomized, double-blind, placebo-controlled, crossover design. To identify potential normalization effects, the brain activation in the ADHD group under each drug condition was compared with that of a group of age-matched healthy boys. Based on previous studies on the stop task in children with ADHD, we hypothesized that medication-naive ADHD boys under placebo compared with healthy control boys would show reduced activation in the VLPFC, SMA/ACC, and caudate during successful inhibition (Rubia et al. 1999, 2005, 2008, 2010; Pliszka et al. 2006). Furthermore, we hypothesized that, based on previous upregulation and normalization findings in ADHD during fMRI inhibition tasks, MPX would enhance frontal, striatal, SMA/ACC, and parietal activation (Vaidya et al. 1998; Epstein et al. 2007; Rubia, Halari, Cubillo et al. 2011; Rubia, Halari, Mohammad et al. 2011). With regard to ATX, there are no data on ADHD patients to base our hypotheses on, but we expected that ATX would also enhance the activation of VLPFC and STG in ADHD patients to the same extent or in a more pronounced manner than in healthy controls (Chamberlain et al. 2009; Graf et al. 2011), parallel to the more pronounced effects of MPX in ADHD relative to healthy controls, due to lower baseline catecholamine levels in ADHD patients (Del Campo et al. 2011; Fusar-Poli et al. 2012).
Forty-eight right-handed boys in the age range between 10 and 17 years participated. Nineteen (mean age [years, months] [SD] = 13 years, 1 month [2 years, 6 months]) medication-naive right-handed boys, who had a clinical diagnosis of ADHD, inattentive/hyperactive-impulsive combined subtype, as assessed by an experienced child psychiatrist using the standardized Maudsley diagnostic interview that assesses ADHD according to diagnostic and statistical manual of mental disorders, 4th edition, text revision criteria (Goldberg and Murray 2002), were recruited from clinics. The diagnosis of ADHD was determined by a multidisciplinary clinical team. The assessment process included information from semi-structured clinical assessment interviews with parents/carers, questionnaires from parents and teachers, school reports, developmental history, cognitive assessments, and behavioral observation of the child. The presence of learning disability was excluded based on information provided by parents and schools during the clinical and cognitive assessments, or by the presence of significant discrepancies between verbal and performance intelligence quotient (IQ) subscores, which is considered an indicator of potential learning difficulties.
ADHD boys scored above the clinical threshold for hyperactive-impulsive/inattentive symptoms on the strengths and difficulties questionnaire for parents (SDQ; Goodman and Scott 1999) and the Conners' Parent Rating Scale (CPRS-R; Conners et al. 1998), and below a clinical threshold on the social communication questionnaire (SCQ; Rutter et al. 2003; Table 1). Patients were scanned in a double-blind, placebo-controlled, crossover design. On each scanning session, they received a single dose of either placebo (Vitamin C, 50 mg), MPX (Equasym, 0.3 mg/kg, range 5–20 mg), or ATX (Strattera, 1 mg/kg, range 16–66 mg), in a pseudo-randomized order, and remained medication-free between scans. National Institute for Clinical Excellence (NICE) guidelines of clinical efficacious dosages with minimal side effects at the time of the study were followed (http://www.nice.org.uk/CG72). All 3 drug conditions were over-encapsulated using the same opaque capsules by the pharmacist. Based on pharmacokinetic evidence, both medications were administered 1.5 h before the scan to allow for maximum absorption (Chan et al. 1983; Witcher et al. 2003). The same or similar dosages and time lapses between drug administration and the scan have been shown to be sufficient to observe changes in brain activation and performance in ADHD patients (MPX; Rubia, Halari, Cubillo et al. 2011; Rubia, Halari, Mohammad et al. 2011) and healthy controls (ATX; Chamberlain et al. 2007, 2009).
Twenty-nine healthy control boys (mean age [years, months] [SD] = 13 years, 9 months [1 years, 7 months]) were recruited through advertisement in the same geographical area and scanned once, unmedicated. They scored below the clinical threshold on the SDQ, SCQ, and CPRS-R (Table 1).
Exclusion criteria for all participants were IQ <70 on the Wechsler Abbreviated Scale of Intelligence (Wechsler 1999), history of substance abuse or neurological deficits, presence of other psychiatric disorder (except for conduct disorder/oppositional defiant disorder in the ADHD group, N = 2), learning disability, reading, speech, or language disorder.
One-way analyses of variance (ANOVAs) showed no between-group differences for age (F1,46 = 1.16; P = 0.28), but for IQ (F1,46 = 28.07; P < 0.001) (Table 1). Low IQ is associated with ADHD (Bridgett and Walker 2006). Although ANCOVA is commonly conducted in case–control studies, this is statistically illegitimate when the covariate is an attribute of the disorder and when, as in this study, groups were not randomly selected. It then becomes meaningless to “adjust” the group effects for differences in the covariate, and ANCOVA cannot be used to control group assignment independent of the covariate as it would alter the group effect in potentially problematic ways, leading to spurious results (Miller and Chapman 2001; Dennis et al. 2009). Therefore, all analyses were conducted without IQ as a covariate.
Participants received £50 per scanning session. Parental and child informed consent/assent and approval from the local ethical committee were obtained.
Participants practiced once the 9-min mixed-trials, event-related fMRI stop task, which measures the ability to suppress an already triggered motor response (Rubia et al. 2003, 2005, 2008, 2010; Rubia, Smith, Taylor et al. 2007). The basic go task is a choice reaction time task with a mean intertrial interval of 1.8 s, where participants have to respond to go arrows of 500 ms duration (80% of trials, 236 trials) pointing either right or left with a right or left button response with the right/left thumb, followed by a blank of 1300 ms. In 20% of trials (60 trials), the go-signals are followed and sometimes interrupted (about 250 ms later) by stop-signals, and participants have to inhibit their motor responses (Fig. 1). A tracking algorithm changes the time interval between go-signal and stop-signal onsets according to each subject's performance on previous trials based on the average percentage of inhibition over previous stop trials, recalculated after each stop trial, resulting in 50% successful and 50% unsuccessful inhibition trials.
Gradient echo-planar MRI data were acquired on a GE Signa 3T Horizon HDx system (General Electric, Milwaukee, WI, United States of America) at the Centre for Neuroimaging Sciences, Institute of Psychiatry, King's College London, United Kingdom. A semi-automated quality control procedure ensured consistent image quality (Simmons et al. 1999). A quadrature birdcage headcoil was used for radiofrequency transmission and reception. In each of 28 noncontiguous planes parallel to the anterior–posterior commissure, 296 T2*-weighted MRimages depicting blood oxygen level-dependent (BOLD) contrast covering the whole brain were acquired with echo delay time (TE) = 30 ms, repetition time (TR) = 1.8 s, flip angle = 75°, in-plane resolution = 3 mm, and slice thickness =5.5 mm (including slice skip = 0.5 mm). In addition, a high-resolution gradient echo-planar image was also acquired in the intercommissural plane, with TE = 30 ms, TR = 1.8 s, flip angle = 90°, 43 slices, slice thickness = 3.0 mm, slice skip = 0.3 mm, and in-plane voxel size of 1.875 mm (matrix size 128 × 128), providing complete brain coverage.
For fMRI analysis, the software package of XBAM was used (http://www.brainmap.co.uk; Brammer et al. 1997), which makes no normality assumptions (violated in fMRI data), but instead uses median statistics to control outlier effects and permutation rather than normal theory-based inference. Furthermore, the most common test statistic is computed by standardizing for individual differences in residual noise before embarking on second-level, multi-subject testing using robust permutation-based methods. This allows a mixed-effects approach to analysis, recommended for fMRI (Thirion et al. 2007).
fMRI data were first processed to minimize the motion-related artifacts (Bullmore, Brammer et al. 1999). A 3-dimensional (3D) volume consisting of the average intensity at each voxel over the whole experiment was calculated and used as a template. The 3D image volume at each time point was then realigned to this template by computing the combination of rotations (around the x, y, and z axes) and translations (in x, y, and z) that maximized the correlation between the image intensities of the volume in question and the template (rigid-body registration). Following realignment, data were then smoothed using a Gaussian filter (full width at half maximum, 7.2 mm) to improve the signal-to-noise characteristics of the images.
After motion correction, global detrending, and spin-excitation history correction, we first convolved the main experimental condition (successful inhibitory trials, contrasted with the go trials that formed the implicit baseline; Rubia et al. 2003, 2005, 2008; Rubia, Smith, Taylor et al. 2007) with two Poisson model functions (peaking at 4 and 8 s). We then calculated the weighted sum of these two convolutions that gave the best fit (least squares) to the time series at each voxel. A goodness-of-fit statistic [an sum of squares quotient (SSQ) ratio] was then computed at each voxel consisting of the ratio of the sum of squares of deviations from the mean intensity value due to the model (fitted time series) divided by the sum of squares due to the residuals (original time series minus model time series). The appropriate null distribution for assessing the significance of any given SSQ ratio was established using a wavelet-based data resampling method for the functional MRI data (Bullmore, Brammer et al. 1999; Bullmore et al. 2001) and applying the model-fitting process to the resampled data. This process was repeated 20 times at each voxel and the data combined over all voxels, resulting in 20 null parametric maps of an SSQ ratio for each subject, which were combined to give the overall null distribution of SSQ ratio. The same permutation strategy was applied at each voxel to preserve spatial correlation structure in the data.
At the individual-subject level, a standard general linear modeling approach was used to obtain estimates of the response size (beta) to the successful stop trials against an implicit baseline (go trials). After first-level analysis, the individual statistical maps were normalized into Talairach standard space (Bullmore et al. 2001).
A group activation map was then produced for the experimental condition (successful inhibition—go) by calculating the median SSQ ratio over all subjects at each voxel in standard space and testing them against the null distribution of median SSQ ratios computed from the identically transformed wavelet resampled data (Brammer et al. 1997). ANOVAs were conducted using randomization-based tests for voxel- or cluster-wise differences (Bullmore, Suckling et al. 1999). The voxel-level threshold was first set to P < 0.05 to give maximum sensitivity and to avoid Type II errors. Next, a cluster-level threshold was computed for the resulting 3D voxel clusters such that the final expected number of Type I error clusters was <1 per whole brain. Thus, an expected cluster-level Type I error rate of <1 per brain was achieved by first applying a voxel-level threshold of P < 0.05, followed by thresholding the 3D clusters formed from the voxels that survived this initial step at a cluster-level threshold of P < 0.01. The cluster-level threshold of P < 0.01 was therefore not applied to the whole brain (which would be lenient), but rather to the data previously thresholded at a voxel-wise level of P < 0.05. The necessary combination of voxel- and cluster-level thresholds is not assumed from theory but rather determined by direct permutation for each data set. In large connected clusters, we identified local maxima that were farther apart than the upper bound of the likely Talairach mapping error (3 voxel radius: 10 mm; Thirion et al. 2007). Voxels were then assigned to the nearest local maximum with a statistical value that exceeded that of the voxels. A cluster mass rather than a cluster extent threshold was used, to minimize discrimination against possible small, strongly responding foci of activation (Bullmore, Suckling et al. 1999). These combined voxel/cluster tests coupled with permutation testing allow for Type I error control at the cluster level (Bullmore, Brammer et al. 1999; Bullmore, Suckling et al. 1999). Thus, for each analysis, <1 false-positive 3D cluster per map was expected at a P-value of <0.05 at the voxel level and <0.005 at the cluster level.
For between-group comparisons, 3 ANOVAs were conducted comparing controls with patients under 1) placebo; 2) MPX; and 3) ATX. We were particularly interested in whether each drug would upregulate brain regions that were abnormally functioning in ADHD patients. For this purpose, to assess potential upregulation effects of either drug on brain regions that were impaired in ADHD patients, we created a mask of those activation clusters that differed between patients under placebo and controls and then conducted a within-patients repeated-measures ANOVA (drug condition: Placebo, MPX, ATX). Then statistical measures of the BOLD response were extracted for each participant in each of the clusters of within-group drug effects, and post hoc analyses were conducted to clarify the direction of these effects. To rule out the potential effects of training in the task on brain activation, repeated-measures ANOVAs on the extracted BOLD response measures were conducted within patients to test for potential scan-order effects. To assess whether brain regions, other than those that were abnormally functioning in ADHD patients relative to controls, were modulated by each drug, we also performed a whole-brain within-patients repeated-measures ANOVA (drug condition: Placebo, MPX, and ATX) at a stringent P < 0.001, allowing <1 error clusters.
Multiple univariate ANOVAs were conducted between controls and patients under each drug condition (separately) in the main performance variables: The stop-signal reaction time (SSRT), calculated by subtracting the mean stop-signal delay (SSD: Average time between the go- and stop-signal, at which the subject inhibited 50% of stop trials) from the mean reaction time (MRT) to go trials, that is, MRT − SSD (Rubia et al. 2003, 2005, 2008; Rubia, Smith, Taylor et al. 2007). Measures of the go process of the task are the MRT to go trials and intra-subject standard deviation (SD) of the MRT (SD of MRT). Repeated-measures ANOVAs were conducted within patients to test for drug-condition effects (placebo, MPX, and ATX) and for potential scan-order effects.
There were no between-groups differences in the probability of inhibition (F3,82 = 1.25, P < 0.3), demonstrating that the tracking algorithm was successful (Table 2). There were no significant performance differences between controls and patients under placebo. Patients under MPX showed a significantly shorter SSRT than controls (F1,46 = 5.32, P < 0.026). Under ATX, patients relative to controls showed a reduced MRT to go trials (F1,46 = 5.04, P < 0.03; Table 2).
Within-patients repeated-measures ANOVA showed a significant drug-condition effect on MRT to go trials (F2,36 = 3.28, P < 0.049), which was significantly reduced when patients were under ATX compared with placebo (P < 0.009; Table 2). No significant differences in SSRTs were observed within patients under the different drug conditions. There were no scan order effects within patients.
A multivariate ANOVA showed no significant differences between controls and patients under each drug condition in the extent of maximum rotation and translation movement parameters in the 3D Euclidean space (F6,164 = 1.56, P = 0.16).
Brain activation within each group for the contrast of successful stop relative to successful go trials is shown in Figure 2 and Supplementary Table 1.
Healthy boys showed activation in the bilateral VLPFC and premotor cortex, ACC extending to the SMA, left and right medial frontal cortex, putamen, thalamus and subthalamic nuclei, inferior and superior temporal and parietal cortices, and in the posterior cingulate, occipital cortex, and cerebellum.
Boys with ADHD under placebo showed activation in similar but less extensive bilateral VLPFC and premotor regions, insula, ACC/SMA, superior temporal, inferior and superior parietal regions, right putamen, right inferior and medial temporal regions, occipital and parahippocampal cortices, and in the cerebellum.
The group of ADHD boys under MPX showed activation in bilateral VLPFC, premotor regions, ACC, putamen, thalamus, posterior cingulate gyrus, medial and superior temporal cortices, inferior and superior parietal lobes, occipital cortices (including parahippocampal gyrus), and cerebellum.
When under ATX, boys with ADHD showed activation in the right medial and superior frontal areas, bilateral VLPFC, premotor regions, ACC/SMA, putamen, thalamus and subthalamic nuclei, posterior cingulate, medial and superior temporal regions, inferior and superior parietal cortices, occipital gyri, and cerebellum.
Compared with healthy controls, ADHD boys showed underactivation in the left and right VLPFC, left middle temporal gyri (MTG)/inferior temporal gyri, and reaching into the inferior parietal lobe (IPL) and right anterior cerebellum/fusiform gyrus (Table 3, Fig. 3).
Patients showed enhanced activation compared with controls in a cluster comprising left posterior cerebellum/posterior cingulate gyrus (PCC), in the right STG, and reaching into the posterior insula and putamen (Table 3; Fig. 3). Given prior evidence for enhanced posterior cerebellum/PCC activation in ADHD patients to compensate for reduced VLPFC activation (Rubia, Smith et al. 2009; Cubillo et al. 2012), we used 1-tailed Pearson correlations within patients on the BOLD response in these two enhanced activation clusters to test whether they were negatively correlated with the reduced VLPFC clusters. Only activation in the right STG–putamen, but not the cerebellum, was negatively correlated with that of the left VLPFC (r = −0.39, P < 0.05).
To test whether areas of group differences were associated with inhibitory function, 1-tailed Pearson correlations were performed between BOLD responses in these regions and SSRTs within each group. Within healthy boys, the enhanced activation in the right cerebellum correlated with a shorter SSRT (r = −0.45, P < 0.007). Within patients, the (enhanced) activation in the right STG–putamen was negatively correlated with the SSRT (r = −0.41, P < 0.04).
ADHD boys under methylphenidate compared with controls showed reduced activation in the same left MTG cluster (Table 3; Fig. 3). All other previously reduced activation clusters were no longer observed.
Patients under MPX showed enhanced activation compared with healthy boys in 3 clusters: 1) bilateral occipital cortex, PCC, and precuneus, 2) left occipital cortex and cerebellum, and 3) left occipital and MTG/IPL (Table 3; Fig. 3).
Within patients, enhanced activation in the left cerebellum was negatively correlated with the SSRT (r = −0.44, P < 0.03). Within controls, there were no significant associations between brain activation and the SSRT.
After a single dose of ATX, patients relative to controls showed reduced activation in the same left MTG cluster and, as with MPX, all other previously reduced activation clusters were no longer observed (Table 3; Fig. 3). There were no areas of enhanced activation in patients and no significant associations between brain activation and SSRT within patients or controls.
Although covariation for IQ in nonrandomly selected groups violates the ANCOVA assumption (Miller and Chapman 2001; Dennis et al. 2009), and hence we do present noncovaried findings, we nevertheless wanted to assess the potential impact of IQ on group differences in brain activation. For this purpose, all case–control ANOVAs were repeated with IQ as a covariate. All findings remained significant at a more lenient P-value (P < 0.03).
To establish whether the group differences between controls and patients under each drug condition were significantly different, we directly compared the effect sizes of the group differences from the 3 case–control comparisons (Matthews and Altman 1996). We used a rigorous effect size comparison test of normalization, which is necessary to avoid spurious results. For example, it could be that differences between cases and controls are no longer observed, simply because the underactivation is below the statistical threshold, spurious, or underpowered. This effect size comparison procedure was also used to test for the significance of the upregulation effects of MPX on the two brain activation clusters that were significantly enhanced under MPX relative to controls. When comparing two effect sizes, the z-test can evaluate the likelihood of whether they are significantly heterogeneous. The difference between the two effect sizes can be considered a normalized variable, where the standard error of the difference is a combination of the standard errors of the two comparisons. Based upon this, the probability of a Type I error can be calculated using the formula
The z-test showed that the effect sizes differed significantly between all case–control contrasts in the left VLPFC, so that the “normalization effect” of this underactivation under placebo was significant for both drug conditions (P < 0.03). In the right VLPFC, the normalization effect was significant for the comparison between the case–control comparison effect size under MPX relative to the case–control comparison effect size under placebo (P < 0.02) and relative to the effect size of the case–control comparison under ATX (P < 0.05), while the case–control comparison under ATX did not differ in effect size from that under placebo, suggesting that only MPX had a significant and drug-specific normalization effect on this region. For the right cerebellum, only the case–control contrast under MPX showed a significant difference in effect size relative to the case–control comparison under placebo (P < 0.04), while the ATX case–control comparison relative to the placebo case–control comparison only showed a trend for differing in effect sizes (P < 0.1; Table 4).
Within-group effects of each drug were tested in region of interests (ROIs) that differed between ADHD patients under placebo and controls to assess whether each drug would upregulate the areas that are abnormally functioning in ADHD patients. There was a main effect of drug condition within patients in a cluster in the right VLPFC, reaching into STG (11 voxels, peak Talairach coordinates [x, y, z]: 29, 7, −26; Brodman area [BA] 47/38; P < 0.037), which was significantly enhanced in patients under MPX compared with ATX (P < 0.008) and placebo (P < 0.002), the latter of which did not differ between each other (P < 0.73; Fig. 4).
Furthermore, activation in this cluster was negatively correlated with the SSRT only when patients were under MPX (r = −0.37, P < 0.05). There were no scan-order effects on brain activation. To assess whether other areas that were not dysfunctional in ADHD were also upregulated with either drug, we also conducted a whole-brain within-patients ANOVA. The whole-brain analysis showed a cluster in the right inferior parietal/superior temporal lobe (Talairach coordinates [x, y, z]: 46, −37, 9; P < 0.001) which was due to the fact that it was enhanced under ATX relative to placebo (P < 0.05), but not relative to MPH (Supplementary Fig. 1).
No differences were observed between controls and patients under placebo or under ATX for the inverse contrast of go–successful stop trials. However, patients under MPX showed enhanced activation in the left insula/VLPFC and premotor cortex, reaching into caudate, putamen, and globus pallidus (187 voxels, peak Talairach coordinates [x, y, z]: −25, 19, 13; BA 45/6; P < 0.006), and also in ACC/SMA (162 voxels, peak Talairach coordinates (x, y, z): 4, 11, 43; BA 6/24/32; P < 0.003; Fig. 5).
There were no scan-order effects on brain activation or correlations with performance. There were significant differences in effect sizes for both clusters for the MPX case–control contrast relative to the placebo case–control comparison (P < 0.01) and relative to the ATX case–control comparison (P < 0.01).
The study shows both shared and drug-specific normalization and upregulation effects on inhibitory brain regions in ADHD patients. ADHD relative to control boys showed no performance deficits but significantly improved in their inhibitory capacity relative to controls under MPX. Under placebo, patients had reduced activation in left and right VLPFC, left MTG, and right cerebellum. Within patients, MPX relative to ATX and placebo significantly upregulated right VLPFC/STG activation which was furthermore associated with improved inhibitory performance, which exceeded that of controls under this drug condition. Rigorous testing for shared or drug-specific differences in normalization effects using effect size comparisons of case–control differences under each drug showed that relative to controls, both drugs significantly normalized the left VLPFC underactivation that was observed under placebo. However, MPX showed a drug-specific normalization effect relative to ATX of significantly normalizing the right VLPFC and right cerebellar underactivations that were present under placebo.
The underactivation in ADHD patients in key areas of motor response inhibition in the right and left VLPFC and in parieto-temporal regions is in line with previous findings (Rubia et al. 1999, 2005, 2008, 2010; Epstein et al. 2007; Rubia 2011; Cubillo et al. 2012). The right VLPFC, together with the pre-SMA, is a key area of motor response inhibition in adolescents and adults, as has consistently been shown in lesion, fMRI and transcranial magnetic stimulation studies (Aron et al. 2003, 2004, 2007; Rubia et al. 2003; Aron and Poldrack 2006; Chambers et al. 2006, 2009; Chevrier et al. 2007; Rubia, Smith, Taylor et al. 2007; Goghari and MacDonald 2009), although recent fMRI evidence has argued for a more prominent role of the right VLPFC for attentional capture rather than inhibition itself (Sharp et al. 2010; Pauls et al. forthcoming 2012). The left VLPFC forms also part of the inhibition network (Nee et al. 2007; Swick et al. 2008), but has been suggested to mediate performance monitoring, necessary for correct inhibitory task performance (Derrfuss et al. 2005; Stevens et al. 2009). Although less commonly reported, the cerebellum is also typically activated in the stop task in healthy adolescents and adults and correlated with the SSRT (Rubia, Smith, Taylor et al. 2007), which was also observed in this study. The finding of cerebellar underactivation replicates a previous finding of cerebellar underactivation during the stop task in ADHD children (Rubia, Halari, Mohammad et al. 2011). The enhanced activation in patients under placebo relative to controls in the right STG–putamen and the left cerebellum/occipital cortex was likely compensatory, as suggested by the negative association of STG–putamen activation with inhibitory capacity and with the (reduced) left VLPFC activation. This compensatory enhanced activation in STG that is considered a part of the inferior frontal–superior temporal junction that mediates inhibition (Rubia et al. 2003; Rubia, Smith, Taylor et al. 2007; Chambers et al. 2009) may have prevented patients from inhibitory impairment in the task.
Only MPX significantly normalized the right VLPFC and cerebellar underactivations in ADHD boys relative to controls that were observed under both placebo and ATX. The normalization effect was, furthermore, drug-specific relative to the effects of ATX. The findings suggest a drug-specific effect of MPX on normalizing abnormal activation in ADHD patients in key inhibition areas of the inferior frontal cortex and cerebellum. This was further confirmed by the within-subject effect, which showed that MPX upregulated right VLPFC activation relative to ATX and placebo. The upregulated right VLPFC activation cluster was, furthermore, associated with better inhibitory capacity in patients, which even exceeded that of controls under MPX. The underactivated cerebellar cluster that was normalized with MPX was also associated with inhibitory performance, albeit in controls. Together, the findings suggest that MPX had a drug-specific effect relative to ATX on key inhibitory performance-correlated regions within an established right VLPFC–striato-cerebellar network for motor response inhibition (Rubia, Smith, Taylor et al. 2007). Thus, the findings extend previous normalization and upregulation findings with MPX in these fronto-striato-cerebellar areas during inhibition tasks in children with ADHD (Vaidya et al. 1998; Epstein et al. 2007; Rubia, Halari, Cubillo et al. 2011; Rubia, Halari, Mohammad et al. 2011) by showing for the first time that these effects are drug-specific relative to ATX.
The shared normalization findings of ATX and MPX in left VLPFC underactivation are interesting and extend, for the first time, previous findings of the upregulation of right (Chamberlain et al. 2009) and bilateral VLPFC (Graf et al. 2011) with ATX in healthy adults during motor inhibition tasks to adolescents with ADHD. Left lateralized effects may suggest stronger effects of ATX on performance monitoring (Derrfuss et al. 2005; Stevens et al. 2009) rather than inhibition per se. Alternatively, considering that ATX typically takes longer to show behavioral effects than MPX (Montoya et al. 2009), longer-term administration may have resulted in significant effect size differences relative to placebo for the below-threshold normalized right VLPFC and cerebellar underactivations, which in the cerebellum reached a trend level of significance. Future studies will have to compare long-term administration of both drugs to elucidate this question. ATX, however, in the whole-brain analysis of within-patient drug effects, enhanced activation in a cluster in the right superior temporal/inferior parietal junction, although this effect was not drug-specific, but only survived significance compared with placebo. The upregulation findings in the temporo-parietal junction with ATX in ADHD extend findings of the increase in right superior temporal lobe activation with ATX in healthy adults (Chamberlain et al. 2009). The right parieto-temporal junction is a key region for visual-spatial attention (Corbetta and Shulman 2002; Downar et al. 2002; Behrmann et al. 2004; Weissman and Woldorff 2005) and its activation may reflect task-related cognitive attention processes necessary for the detection of the relevant/salient stimuli, in this case the stop stimuli (Berridge and Waterhouse 2003; Aston-Jones and Cohen 2005). The temporo-parietal junction is commonly reported to be abnormal in ADHD children and adults during attention and inhibition tasks (Smith et al. 2006; Tamm et al. 2006; Epstein et al. 2007; Rubia, Smith, Brammer et al. 2007; Stevens et al. 2007; Rubia, Halari, Cubillo et al. 2009; Rubia et al. 2010; Rubia, Halari, Mohammad et al. 2011; Cubillo et al. 2012). Our finding of an upregulation effect of ATX in this region may thus suggest a stronger effect of ATX on attention rather than inhibition networks, which could be a reflection of an impact of ATX on right-lateralized noradrenergically mediated attention networks (Tucker and Williamson 1984).
Interestingly, MPX, in addition, showed a drug-specific upregulation effect during the executive go process of the task in key regions for response selection and motor execution in ACC/SMA, left premotor cortex, and basal ganglia (Haber 2003). Together, the findings thus suggest that MPX upregulates and normalizes right-lateralized VLPFC–cerebellar motor inhibition networks as well as medial fronto-striatal circuits of motor response execution.
While there were no performance differences between patients under placebo and healthy controls, boys with ADHD were significantly better in their inhibitory capacity relative to controls when under MPX. Although acute MPH administration reduced the SSRT slightly within patients, this did not reach significance. The finding of no significant effects of MPH on the SSRT is in line with previous fMRI studies using the stop task in ADHD patients (Rubia, Halari, Mohammad et al. 2011) and healthy adults (Pauls et al. forthcoming 2012), or in healthy adults during the go/no-go task (Costa et al. forthcoming 2012). fMRI stop task designs, however, lose behavioral sensitivity over neuropsychological task versions. This is due to the fact that stop stimuli are more predictable, given that they need to be separated by at least 3 trials, and cannot be consecutive, to allow for the separation of hemodynamic response curves. Furthermore, while fMRI studies in 20 subjects for each group are sufficiently powered for fMRI analysis (Thirion et al. 2007), they are underpowered for behavioral analyses. In fact in larger numbered neuropsychological studies, single doses of MPX have shown to improve inhibitory performance in children with ADHD (Tannock et al. 1989; Bedard et al. 2003; Scheres et al. 2003; Konrad et al. 2004; Lijffijt et al. 2006; DeVito et al. 2009) and in healthy adults (Nandam et al. 2011). Although restrictions in fMRI task design may have contributed to the lack of significant effects of the drugs on performance within patients, MPX nevertheless significantly improved inhibitory performance in children with ADHD relative to that of the healthy control group, suggesting it did have a positive impact on the SSRT. The stronger effects of MPH on inhibitory brain function than inhibitory performance is in line with prior evidence, showing that brain activation is more sensitive to the effects of stimulant medication than behavior during inhibitory and related cognitive tasks (Shafritz et al. 2004; Konrad et al. 2007; Peterson et al. 2009; Rubia, Halari, Christakou et al. 2009; Rubia, Halari, Cubillo et al. 2009; Rubia, Halari, Cubillo et al. 2011; Rubia, Halari, Mohammad et al. 2011). Thus, the normalization effects on key inhibitory activation areas after a single dose of MPX may have accounted for their relative improvement on inhibitory performance compared with healthy controls. This is further reinforced by the finding that activation in the right VLPFC was negatively correlated with the SSRT only when patients were under MPX.
A strength of this study is the double-blind, placebo-controlled crossover design in exclusively medication-naive boys with combined-type ADHD, thus testing a homogeneous sample and avoiding the potential confound of previous stimulant medication history, known to confound brain structure and function deficits (Konrad et al. 2007; Nakao et al. 2011; Frodl and Skokauskas 2012). A limitation is that ADHD boys performed the task 3 times, while, for financial and ethical reasons, controls were scanned only once. However, the lack of practice effects within patients suggests that these unlikely confounded the between-groups analyses. Another limitation is the single-dose administration. While MPX has immediate effects on behavior (Greenhill et al. 2001), ATX reaches its maximum behavioral efficacy at about 12 weeks (Montoya et al. 2009). Consequently, a single-dose comparison may have favored MPX. The investigation of acute mechanisms of action, however, is a first step toward improving our understanding of drug-specific effects on brain activation and cognition, and has the advantage of avoiding potential confounds of long-term treatment such as symptomatic improvement, side effects, or chronic effects on brain activation. Nevertheless, future studies should compare long-term effects of both drugs on brain activation after reaching maximum clinical efficacy. Lastly, the findings are only generalizable to right-handed male adolescents with combined-type ADHD and may not apply to other ADHD subtypes, female or left-handed patients.
To summarize, the findings show shared effects of both drugs in normalizing left VLPFC activation deficits in ADHD patients, presumably mediating performance monitoring. MPX, however, had drug-specific upregulation and normalization effects in the right VLPFC, which, furthermore, was associated with improved inhibitory performance in ADHD patients relative to controls, as well as of normalizing cerebellum dysfunction. In addition, MPX not only upregulated fronto-cerebellar areas of inhibitory control, but also fronto-striatal regions mediating the executive go process of the task. While the findings need to be replicated in longer-term administration of both drugs, they point toward potentially superior effects of MPX on alleviating abnormalities in inhibitory neural networks in ADHD.
Supplementary material can be found at: http://www.cercor.oxfordjournals.org/.
This work was supported by the Department of Health via the National Institute for Health Research(NIHR) Biomedical Research Centre (BRC) for Mental Health at South London and Maudsley NHS Foundation Trust and Institute of Psychiatry, King's College London and Lilly Pharmaceuticals. The NIHR also supported A.C. and A.B.S. via a PhD studentship and postdoctoral fellowship, respectively. Lilly had no input into the design and conduct of the study, data collection, management, analysis, or interpretation of the data. Funding to pay the Open Access publication charges for this article was provided by Lilly pharmaceuticals.
Click here for additional data file (supp_bhs296_bhs296supp.doc)
Conflict of Interest: K.R. has received speaker's honoraria from Shire, Novartis, and Medice and Lilly.
|Alderson RM,Rapport MD,Kofler MJ. Attention-deficit/hyperactivity disorder and behavioral inhibition: a meta-analytic review of the stop-signal paradigmJ Abnorm Child PsycholYear: 200735745758 doi:10.1007/s10802-007-9131-6. 17668315|
|American Psychiatric AssociationDiagnostic and Statistical Manual of Mental DisordersYear: 20004th ed.Washington, DCAmerican Psychiatric Association Text Revision.|
|Aron AR,Durston S,Eagle DM,Logan GD,Stinear CM,Stuphorn V. Converging evidence for a fronto-basal-ganglia network for inhibitory control of action and cognitionJ NeurosciYear: 2007271186011864 doi:10.1523/JNEUROSCI.3644-07.2007. 17978025|
|Aron AR,Fletcher PC,Bullmore ET,Sahakian BJ,Robbins TW. Stop-signal inhibition disrupted by damage to right inferior frontal gyrus in humansNat NeurosciYear: 2003611511612536210|
|Aron AR,Poldrack RA. Cortical and subcortical contributions to stop signal response inhibition: role of the subthalamic nucleusJ NeurosciYear: 20062624242433 doi:10.1523/JNEUROSCI.4682-05.2006. 16510720|
|Aron AR,Robbins TW,Poldrack RA. Inhibition and the right inferior frontal cortexTrends Cogn SciYear: 20048170177 doi:10.1016/j.tics.2004.02.010. 15050513|
|Aston-Jones G,Cohen JD. An integrative theory of locus coeruleus-norepinephrine function: adaptive gain and optimal performanceAnnu Rev NeurosciYear: 200528403450 doi:10.1146/annurev.neuro.28.061604.135709. 16022602|
|Bedard AC,Ickowicz A,Logan GD,Hogg-Johnson S,Schachar R,Tannock R. Selective inhibition in children with attention-deficit hyperactivity disorder off and on stimulant medicationJ Abnorm Child PsycholYear: 200331315327 doi:10.1023/A:1023285614844. 12774864|
|Behrmann M,Geng JJ,Shomstein S. Parietal cortex and attentionCurr Opin NeurobiolYear: 200414212217 doi:10.1016/j.conb.2004.03.012. 15082327|
|Berridge CW,Waterhouse BD. The locus coeruleus-noradrenergic system: modulation of behavioral state and state-dependent cognitive processesBrain Res Brain Res RevYear: 2003423384 doi:10.1016/S0165-0173(03)00143-7. 12668290|
|Brammer MJ,Bullmore ET,Simmons A,Williams SC,Grasby PM,Howard RJ,Woodruff PW,Rabe-Hesketh S. Generic brain activation mapping in functional magnetic resonance imaging: a nonparametric approachMagn Res ImagingYear: 199715763770 doi:10.1016/S0730-725X(97)00135-5.|
|Bridgett DJ,Walker ME. Intellectual functioning in adults with ADHD: a meta-analytic examination of full scale IQ differences between adults with and without ADHDPsychol AssessYear: 200618114 doi:10.1037/1040-35220.127.116.11. 16594807|
|Bullmore E,Long C,Suckling J,Fadili J,Calvert G,Zelaya F,Carpenter TA,Brammer M. Colored noise and computational inference in neurophysiological (fMRI) time series analysis: resampling methods in time and wavelet domainsHum Brain MappYear: 2001126178 doi:10.1002/1097-0193(200102)12:2<61::AID-HBM1004>3.0.CO;2-W. 11169871|
|Bullmore ET,Brammer MJ,Rabe-Hesketh S,Curtis VA,Morris RG,Williams SC,Sharma T,McGuire PK. Methods for diagnosis and treatment of stimulus-correlated motion in generic brain activation studies using fMRIHum Brain MappYear: 199973848 doi:10.1002/(SICI)1097-0193(1999)7:1<38::AID-HBM4>3.0.CO;2-Q. 9882089|
|Bullmore ET,Suckling J,Overmeyer S,Rabe-Hesketh S,Taylor E,Brammer MJ. Global, voxel, and cluster tests, by theory and permutation, for a difference between two groups of structural MR images of the brainIEEE Trans Med ImagingYear: 1999183242 doi:10.1109/42.750253. 10193695|
|Bymaster FP,Katner JS,Nelson DL,Hemrick-Luecke SK,Threlkeld PG,Heiligenstein JH,Morin SM,Gehlert DR,Perry KW. Atomoxetine increases extracellular levels of norepinephrine and dopamine in prefrontal cortex of rat: a potential mechanism for efficacy in attention deficit/hyperactivity disorderNeuropsychopharmacologyYear: 200227699711 doi:10.1016/S0893-133X(02)00346-9. 12431845|
|Chamberlain SR,Del Campo N,Dowson J,Muller U,Clark L,Robbins TW,Sahakian BJ. Atomoxetine improved response inhibition in adults with attention deficit/hyperactivity disorderBiol PsychiatryYear: 200762977984 doi:10.1016/j.biopsych.2007.03.003. 17644072|
|Chamberlain SR,Hampshire A,Muller U,Rubia K,Del Campo N,Craig K,Regenthal R,Suckling J,Roiser JP,Grant JE,et al. Atomoxetine modulates right inferior frontal activation during inhibitory control: a pharmacological functional magnetic resonance imaging studyBiol PsychiatryYear: 200965550555 doi:10.1016/j.biopsych.2008.10.014. 19026407|
|Chambers CD,Bellgrove MA,Stokes MG,Henderson TR,Garavan H,Robertson IH,Morris AP,Mattingley JB. Executive “brake failure” following deactivation of human frontal lobeJ Cogn NeurosciYear: 20061844445516513008|
|Chambers CD,Garavan H,Bellgrove MA. Insights into the neural basis of response inhibition from cognitive and clinical neuroscienceNeurosci Biobehav RevYear: 200933631646 doi:10.1016/j.neubiorev.2008.08.016. 18835296|
|Chan YP,Swanson JM,Soldin SS,Thiessen JJ,Macleod SM,Logan W. Methylphenidate hydrochloride given with or before breakfast: II. Effects on plasma concentration of methylphenidate and ritalinic acidPediatricsYear: 19837256596866592|
|Chevrier AD,Noseworthy MD,Schachar R. Dissociation of response inhibition and performance monitoring in the stop signal task using event-related fMRIHum Brain MappYear: 20072813471358 doi:10.1002/hbm.20355. 17274022|
|Conners CK,Sitarenios G,Parker JDA,Epstein JN. Revision and restandardization of the Conners Teacher Rating Scale (CTRS-R): factor structure, reliability, and criterion validityJ Abnorm Child PsycholYear: 199826279291 doi:10.1023/A:1022606501530. 9700520|
|Corbetta M,Shulman GL. Control of goal-directed and stimulus-driven attention in the brainNat Rev NeurosciYear: 2002320121511994752|
|Costa A,Riedel M,Pogarell O,Menzel-Zelnitschek F,Schwarz M,Reiser M,Moller HJ,Rubia K,Meindl T,Ettinger U. Methylphenidate effects on neural activity during response inhibition in healthy humansCereb CortexYear: Forthcoming 2013231179118922581848|
|Cubillo A,Halari R,Smith A,Taylor E,Rubia K. A review of fronto-striatal and frontocortical brain abnormalities in children and adults with Attention Deficit Hyperactivity Disorder (ADHD) and new evidence for dysfunction in adults with ADHD during motivation and attentionCortexYear: 201248194215 doi:10.1016/j.cortex.2011.04.007. 21575934|
|Del Campo N,Chamberlain SR,Sahakian BJ,Robbins TW. The roles of dopamine and noradrenaline in the pathophysiology and treatment of attention-deficit/hyperactivity disorderBiol PsychiatryYear: 201169e145e157 doi:10.1016/j.biopsych.2011.02.036. 21550021|
|Dennis M,Francis DJ,Cirino PT,Schachar R,Barnes MA,Fletcher JM. Why IQ is not a covariate in cognitive studies of neurodevelopmental disordersJ Int Neuropsychol SocYear: 200915331343 doi:10.1017/S1355617709090481. 19402919|
|Derrfuss J,Brass M,Neumann J,von Cramon DY. Involvement of the inferior frontal junction in cognitive control: meta-analyses of switching and Stroop studiesHum Brain MappYear: 2005252234 doi:10.1002/hbm.20127. 15846824|
|DeVito EE,Blackwell AD,Clark L,Kent L,Dezsery AM,Turner DC,Aitken MR,Sahakian BJ. Methylphenidate improves response inhibition but not reflection-impulsivity in children with attention deficit hyperactivity disorder (ADHD)Psychopharmacology (Berl)Year: 2009202531539 doi:10.1007/s00213-008-1337-y. 18818905|
|Downar J,Crawley AP,Mikulis DJ,Davis KD. A cortical network sensitive to stimulus salience in a neutral behavioral context across multiple sensory modalitiesJ Clin NeurophysiolYear: 200287615620|
|Epstein JN,Casey BJ,Tonev ST,Davidson MC,Reiss AL,Garrett A,Hinshaw SP,Greenhill LL,Glover G,Shafritz KM,et al. ADHD- and medication-related brain activation effects in concordantly affected parent-child dyads with ADHDJ Child Psychol PsychiatryYear: 200748899913 doi:10.1111/j.1469-7610.2007.01761.x. 17714375|
|Frodl T,Skokauskas N. Meta-analysis of structural MRI studies in children and adults with attention deficit hyperactivity disorder indicates treatment effectsActa Psychiatr ScandYear: 2012125114126 doi:10.1111/j.1600-0447.2011.01786.x. 22118249|
|Fusar-Poli P,Rubia K,Rossi G,Sartori G,Balottin U. Striatal dopamine transporter alterations in ADHD: pathophysiology or adaptation to psychostimulants? A meta-analysisAm J PsychiatryYear: 2012169264272 doi:10.1176/appi.ajp.2011.11060940. 22294258|
|Gallezot JD,Weinzimmer D,Nabulsi N,Lin SF,Fowles K,Sandiego C,McCarthy TJ,Maguire RP,Carson RE,Ding YS. Evaluation of [(11)C]MRB for assessment of occupancy of norepinephrine transporters: studies with atomoxetine in non-human primatesNeuroimageYear: 201156268279 doi:10.1016/j.neuroimage.2010.09.040. 20869448|
|Goghari VM,MacDonald AW 3rd. The neural basis of cognitive control: response selection and inhibitionBrain CognYear: 2009717283 doi:10.1016/j.bandc.2009.04.004. 19427089|
|Goldberg D,Murray R. Maudsley handbook of practical psychiatryYear: 2002OxfordOxford University Press|
|Goodman R,Scott S. Comparing the strengths and difficulties questionnaire and the child behavior checklist: is small beautiful?J Abnorm Child PsycholYear: 1999271724 doi:10.1023/A:1022658222914. 10197403|
|Graf H,Abler B,Freudenmann R,Beschoner P,Schaeffeler E,Spitzer M,Schwab M,Gron G. Neural correlates of error monitoring modulated by atomoxetine in healthy volunteersBiol PsychiatryYear: 201169890897 doi:10.1016/j.biopsych.2010.10.018. 21168122|
|Greenhill LL,Swanson JM,Vitiello B,Davies M,Clevenger W,Wu M,Arnold LE,Abikoff HB,Bukstein OG,Conners CK,et al. Impairment and deportment responses to different methylphenidate doses in children with ADHD: the MTA titration trialJ Am Acad Child Adolesc PsychiatryYear: 200140180187 doi:10.1097/00004583-200102000-00012. 11211366|
|Haber SN. The primate basal ganglia: parallel and integrative networksJ Chem NeuroanatYear: 200326317330 doi:10.1016/j.jchemneu.2003.10.003. 14729134|
|Hannestad J,Gallezot JD,Planeta-Wilson B,Lin SF,Williams WA,van Dyck CH,Malison RT,Carson RE,Ding YS. Clinically relevant doses of methylphenidate significantly occupy norepinephrine transporters in humans in vivoBiol PsychiatryYear: 201068854860 doi:10.1016/j.biopsych.2010.06.017. 20691429|
|Hanwella R,Senanayake M,de Silva V. Comparative efficacy and acceptability of methylphenidate and atomoxetine in treatment of attention deficit hyperactivity disorder in children and adolescents: a meta-analysisBMC PsychiatryYear: 201111176184 doi:10.1186/1471-244X-11-176. 22074258|
|Hazell PL,Kohn MR,Dickson R,Walton RJ,Granger RE,van Wyk GW. Core ADHD symptom improvement with atomoxetine versus methylphenidate: a direct comparison meta-analysisJ Atten DisordYear: 201015674683 doi:10.1177/1087054710379737. 20837981|
|Konrad K,Gunther T,Hanisch C,Herpertz-Dahlmann B. Differential effects of methylphenidate on attentional functions in children with attention-deficit/hyperactivity disorderJ Am Acad Child Adolesc PsychiatryYear: 200443191198 doi:10.1097/00004583-200402000-00015. 14726726|
|Konrad K,Neufang S,Fink GR,Herpertz-Dahlmann B. Long-term effects of methylphenidate on neural networks associated with executive attention in children with ADHD: results from a longitudinal functional MRI studyJ Am Acad Child Adolesc PsychiatryYear: 20074616331641 doi:10.1097/chi.0b013e318157cb3b. 18030085|
|Lijffijt M,Kenemans JL,ter Wal A,Quik EH,Kemner C,Westenberg H,Verbaten MN,van Engeland H. Dose-related effect of methylphenidate on stopping and changing in children with attention-deficit/hyperactivity disorderEur PsychiatryYear: 200621544547 doi:10.1016/j.eurpsy.2005.04.003. 15994064|
|Matthews JN,Altman DG. Statistics notes. Interaction 2: compare effect sizes not P valuesBMJYear: 19963138088842080|
|Miller G,Chapman J. Misunderstanding analysis of covarianceJ Abnorm PsycholYear: 20011104048 doi:10.1037/0021-843X.110.1.40. 11261398|
|Montoya A,Hervas A,Cardo E,Artigas J,Mardomingo MJ,Alda JA,Gastaminza X,Garcia-Polavieja MJ,Gilaberte I,Escobar R. Evaluation of atomoxetine for first-line treatment of newly diagnosed, treatment-naive children and adolescents with attention deficit/hyperactivity disorderCurr Med Res OpinYear: 2009252745275419785510|
|Nakao T,Radua J,Rubia K,Mataix-Cols D. Gray matter volume abnormalities in ADHD and the effects of stimulant medication: voxel-based meta-analysisAm J PsychiatryYear: 20111681154116321865529|
|Nandam LS,Hester R,Wagner J,Cummins TD,Garner K,Dean AJ,Kim BN,Nathan PJ,Mattingley JB,Bellgrove MA. Methylphenidate but not atomoxetine or citalopram modulates inhibitory control and response time variabilityBiol PsychiatryYear: 201169902904 doi:10.1016/j.biopsych.2010.11.014. 21193172|
|Nee DE,Wager TD,Jonides J. Interference resolution: insights from a meta-analysis of neuroimaging tasksCogn Affect Behav NeurosciYear: 20077117 doi:10.3758/CABN.7.1.1. 17598730|
|Pauls AM,O'Daly OG,Rubia K,Riedel WJ,Williams SC,Mehta MA. Methylphenidate effects on prefrontal functioning during attentional-capture and response inhibitionBiol PsychiatryYear: Forthcoming 20127214214922552046|
|Peterson BS,Potenza MN,Wang Z,Zhu H,Martin A,Marsh R,Plessen KJ,Yu S. An FMRI study of the effects of psychostimulants on default-mode processing during Stroop task performance in youths with ADHDAm J PsychiatryYear: 200916612861294 doi:10.1176/appi.ajp.2009.08050724. 19755575|
|Pliszka SR,Glahn DC,Semrud-Clikeman M,Franklin C,Perez R,Xiong JJ. Neuroimaging of inhibitory control areas in children with attention deficit hyperactivity disorder who were treatment naive or in long-term treatmentAm J PsychiatryYear: 200616310521060 doi:10.1176/appi.ajp.163.6.1052. 16741206|
|Rubia K. Cool” inferior fronto-striatal dysfunction in attention-deficit hyperactivity disorder (ADHD) versus “hot” ventromedial orbitofronto-limbic dysfunction in conduct disorder: a reviewBiol PsychiatryYear: 201169e69e87 doi:10.1016/j.biopsych.2010.09.023. 21094938|
|Rubia K,Cubillo A,Smith AB,Woolley J,Heyman I,Brammer MJ. 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 disorderHum Brain MappYear: 20103128729919777552|
|Rubia K,Halari R,Christakou A,Taylor E. Impulsiveness as a timing disturbance: neurocognitive abnormalities in attention-deficit hyperactivity disorder during temporal processes and normalization with methylphenidatePhilos Trans R Soc Lond B Biol SciYear: 200936419191931 doi:10.1098/rstb.2009.0014. 19487194|
|Rubia K,Halari R,Cubillo A,Mohammad AM,Brammer M,Taylor E. Methylphenidate normalises fronto-striatal underactivation during interference inhibition in medication-naive children with attention-deficit hyperactivity disorderNeuropsychopharmacologyYear: 20113615751586 doi:10.1038/npp.2011.30. 21451498|
|Rubia K,Halari R,Cubillo A,Mohammad M,Taylor E. Methylphenidate normalises activation and functional connectivity deficits in attention and motivation networks in medication-naïve children with ADHD during a rewarded continuous performance taskNeuropharmacologyYear: 200957640652 doi:10.1016/j.neuropharm.2009.08.013. 19715709|
|Rubia K,Halari R,Mohammad AM,Taylor E,Brammer M. Methylphenidate normalises fronto-cingulate underactivation during error processing in attention-deficit hyperactivity disorderBiol PsychiatryYear: 201170255262 doi:10.1016/j.biopsych.2011.04.018. 21664605|
|Rubia K,Halari R,Smith AB,Mohammed M,Scott S,Giampietro V,Taylor E,Brammer MJ. Dissociated functional brain abnormalities of inhibition in boys with pure conduct disorder and in boys with pure attention deficit hyperactivity disorderAm J PsychiatryYear: 2008165889897 doi:10.1176/appi.ajp.2008.07071084. 18413706|
|Rubia K,Overmeyer S,Taylor E,Brammer M,Williams SC,Simmons A,Bullmore ET. Hypofrontality in attention deficit hyperactivity disorder during higher-order motor control: a study with functional MRIAm J PsychiatryYear: 199915689189610360128|
|Rubia K,Smith AB,Brammer MJ,Toone B,Taylor E. Abnormal brain activation during inhibition and error detection in medication-naive adolescents with ADHDAm J PsychiatryYear: 200516210671075 doi:10.1176/appi.ajp.162.6.1067. 15930054|
|Rubia K,Smith AB,Brammer MJ,Taylor E. Right inferior prefrontal cortex mediates response inhibition while mesial prefrontal cortex is responsible for error detectionNeuroimageYear: 200320351358 doi:10.1016/S1053-8119(03)00275-1. 14527595|
|Rubia K,Smith AB,Brammer MJ,Taylor E. Temporal lobe dysfunction in medication-naive boys with attention-deficit/hyperactivity disorder during attention allocation and its relation to response variabilityBiol PsychiatryYear: 2007629991006 doi:10.1016/j.biopsych.2007.02.024. 17585887|
|Rubia K,Smith A,Halari R,Matukura F,Mohammad M,Taylor E,Brammer M. Disorder-specific dissociation of orbitofrontal dysfunction in boys with pure Conduct disorder during reward and ventrolateral prefrontal dysfunction in boys with pure attention-deficit/hyperactivity disorder during sustained attentionAm J PsychiatryYear: 20091668394 doi:10.1176/appi.ajp.2008.08020212. 18829871|
|Rubia K,Smith AB,Taylor E,Brammer M. Linear age-correlated functional development of right inferior fronto-striato-cerebellar networks during response inhibition and anterior cingulate during error-related processesHum Brain MappYear: 20072811631177 doi:10.1002/hbm.20347. 17538951|
|Rutter M,Bailey A,Berument S,LeCouteur A,Lord C,Pickles A. Social Communication Questionnaire (SCQ)Year: 2003Los Angeles,CAWestern Psychological Services|
|Scheres A,Oosterlaan J,Swanson J,Morein-Zamir S,Meiran N,Schut H,Vlasveld L,Sergeant JA. The effect of methylphenidate on three forms of response inhibition in boys with AD/HDJ Abnorm Child PsycholYear: 200331105120 doi:10.1023/A:1021729501230. 12597703|
|Shafritz KM,Marchione KE,Gore JC,Shaywitz SE,Shaywitz BA. The effects of methylphenidate on neural systems of attention in attention deficit hyperactivity disorderAm J PsychiatryYear: 200416119901997 doi:10.1176/appi.ajp.161.11.1990. 15514398|
|Sharp DJ,Bonnelle V,De Boissezon X,Beckmann CF,James SG,Patel MC,Mehta MA. Distinct frontal systems for response inhibition, attentional capture, and error processingProc Natl Acad Sci USAYear: 201010761066111 doi:10.1073/pnas.1000175107. 20220100|
|Simmons A,Moore E,Williams SC. Quality control for functional magnetic resonance imaging using automated data analysis and Shewhart chartingMagn Reson MedYear: 19994112741278 doi:10.1002/(SICI)1522-2594(199906)41:6<1274::AID-MRM27>3.0.CO;2-1. 10371463|
|Smith A,Taylor E,Brammer M,Toone B,Rubia K. Task-specific hypoactivation in prefrontal and temporoparietal brain regions during motor inhibition and task switching in medication-naive children and adolescents with attention deficit hyperactivity disorderAm J PsychiatryYear: 200616310441051 doi:10.1176/appi.ajp.163.6.1044. 16741205|
|Stevens MC,Kiehl KA,Pearlson GD,Calhoun VD. Brain network dynamics during error commissionHum Brain MappYear: 2009302437 doi:10.1002/hbm.20478. 17979124|
|Stevens MC,Pearlson GD,Kiehl KA. An fMRI auditory oddball study of combined-subtype attention deficit hyperactivity disorderAm J PsychiatryYear: 200716417371749 doi:10.1176/appi.ajp.2007.06050876. 17974940|
|Swick D,Ashley V,Turken AU. Left inferior frontal gyrus is critical for response inhibitionBMC NeurosciYear: 20089102113 doi:10.1186/1471-2202-9-102. 18939997|
|Tamm L,Menon V,Reiss AL. Parietal attentional system aberrations during target detection in adolescents with attention deficit hyperactivity disorder: event-related fMRI evidenceAm J PsychiatryYear: 200616310331043 doi:10.1176/appi.ajp.163.6.1033. 16741204|
|Tannock R,Schachar RJ,Carr RP,Chajczyk D,Logan GD. Effects of methylphenidate on inhibitory control in hyperactive childrenJ Abnorm Child PsycholYear: 198917473491 doi:10.1007/BF00916508. 2681316|
|Thirion B,Pinel P,Meriaux S,Roche A,Dehaene S,Poline JB. Analysis of a large fMRI cohort: statistical and methodological issues for group analysesNeuroimageYear: 200735105120 doi:10.1016/j.neuroimage.2006.11.054. 17239619|
|Tucker DM,Williamson PA. Asymmetric neural control systems in human self-regulationPsychol RevYear: 198491185215 doi:10.1037/0033-295X.91.2.185. 6152836|
|Vaidya CJ,Austin G,Kirkorian G,Ridlehuber HW,Desmond JE,Glover GH,Gabrieli JDE. Selective effects of methylphenidate in attention deficit hyperactivity disorder: a functional magnetic resonance studyProc Natl Acad Sci USAYear: 1998951449414499 doi:10.1073/pnas.95.24.14494. 9826728|
|van Wyk GW,Hazell PL,Kohn MR,Granger RR,Walton RJ. How oppositionality, inattention, and hyperactivity affect response to atomoxetine versus methylphenidate: a meta-analysisJ Atten DisordYear: 201216314324 doi:10.1177/1087054710389989. 21289234|
|Volkow ND,Wang GJ,Fowler JS,Gatley SJ,Logan J,Ding YS,Hitzemann R,Pappas N. Dopamine transporter occupancies in the human brain induced by therapeutic doses of oral methylphenidateAm J PsychiatryYear: 1998155132513319766762|
|Wechsler D. Wechsler Abbreviated Scale of IntelligenceYear: 1999San Antonio, TexasThe Psychological Corporation|
|Weissman DH,Woldorff MG. Hemispheric asymmetries for different components of global/local attention occur in distinct temporo-parietal lociCereb CortexYear: 200515870876 doi:10.1093/cercor/bhh187. 15459080|
|Witcher JW,Long A,Smith B,Sauer JM,Heilgenstein J,Wilens T,Spencer T,Biederman J. Atomoxetine pharmacokinetics in children and adolescents with attention deficit hyperactivity disorderJ Child Adolesc PsychopharmacolYear: 2003135363 doi:10.1089/104454603321666199. 12804126|
Sample characteristics for healthy control boys and patients with ADHD
|Controls (29)||ADHD (19)|
|Age (years, months)||13 years, 9 months (2 years, 6 months)||13 years, 1 month (1 years, 7 months)|
|IQ||110 (12)||92 (11)|
|SDQ hyperactive-impulsive/inattentive subscale||1.45 (1.63)||7.86 (2.53)|
|SDQ total||3.72 (3.95)||22.46 (6.90)|
|SCQ total||1.18 (1.40)||9.53 (4.54)|
|CPRS-R total t score||44.09 (4.74)||79 (11.37)|
Note: SDQ = strengths and difficulties questionnaire; SCQ = social communication questionnaire; CPRS-R = Conners' Parent Rating Scale; SD = standard deviation.
Performance data for 29 healthy control boys and 19 boys with ADHD under each medication condition
|Performance variable||Controls mean (SD)||ADHD placebo mean (SD)||ADHD MPX mean (SD)||ADHD ATX mean (SD)|
|Pi (%)||51 (3)||51 (4)||53 (4)||53 (10)|
|MRT go trials (ms)||615 (117)||592 (77)||576 (79)||548 (71)|
|SD go trials (ms)||163 (56)||166 (50)||152 (42)||155 (65)|
|SSRT (ms)||165 (103)||126 (82)||93 (110)||133 (121)|
Note: Pi = probability of inhibition; MRT = mean reaction time. SD = intrasubject standard deviation; SSRT = stop-signal reaction time.
ANOVAs comparing controls and ADHD patients under each drug condition during successful motor response inhibition in the stop task
|Subject contrast||Brain regions of activation||Brodman area (BA)||Peak Talairach coordinates (x, y, z)||N. of voxels||Cluster P-value||Cohen's d|
|C > ADHD placebo||R ventrolateral prefrontal cortex||47/11||32, 30, −10||156||0.009||0.67|
|L ventrolateral prefrontal cortex||45/47||−22, 33, −13||110||0.01||1.16|
|L middle/inferior/temporal/parietal gyri||21/37/22/40||−43, −52, 0||287||0.002||1.22|
|R cerebellum/fusiform gyrus||36/37||36, −59, −10||97||0.01||1.06|
|ADHD placebo > C||L cerebellum/R + L posterior cingulate/occipital gyri||29/30/31/18/19||−25, −70, −16||637||<0.001||1.00|
|R superior temporal/postcentral gyri/posterior insula/putamen||42/22/21/4||47, −15, 7||190||0.008||1.03|
|C > ADHD MPX||L middle temporal gyrus||21/37||−40, −59, −3||108||0.005||0.91|
|ADHD MPX > C||L cerebellum/parahippocampus/occipital gyri||36/37||−29, −37, −26||201||0.005||1.18|
|L occipital/middle temporal/precuneus||39/22/40/7/19||−32, −70, 27||243||0.003||0.50|
|L + R occipital gyri/posterior cingulate/precuneus||23/29/30/31/7/18/19||−11, −52, −3||624||<0.001||1.19|
|C > ADHD ATX||L middle temporal gyrus||21/37||−40, −56, −7||156||0.003||1.23|
|ADHD ATX > C||Nil|
Note: N voxels = number of voxels. L = left; R = right; the maps are thresholded to give less than 1 Type I error 3D cluster per map. Talairach coordinates, number of voxels, and areas are included underneath the corresponding cluster. Although both drugs normalized underactivation in the left and right VLPFC and cerebellum, rigorous effect size comparisons testing for normalization effects showed that the normalization was significant for both drugs in the left VLPFC but only significant for MPX and not ATX in the right VLPFC and cerebellum.
Comparison between effect sizes of the different case–control comparisons (ADHD placebo vs. controls; ADHD MPX vs. controls; ADHD ATX vs. controls; and ADHD ATX vs. ADHD MPX)
|R VLPFC||Controls: 0.0100||C-placebo
|ADHD placebo: −0.0072||C-placebo
|ADHD MPX: 0.0129||C-MPX
|ADHD ATX: 0.00007|
|L VLPFC||Controls: 0.0052||C-placebo
|ADHD placebo: −0.0227||C-placebo
|ADHD MPX: 0.0008||C-MPX
|ADHD ATX: −0.0048|
|R CB-OCC||Controls: 0.0330||C-placebo
|ADHD placebo: −0.0007||C-Placebo
|ADHD MPX: 0.0244||C-MPX
|ADHD ATX: 0.0174|
|L premotor/basal ganglia||Controls: 0.0018||C-placebo
|ADHD placebo: −0.0013||C-placebo
|ADHD MPX: −0.03101||C-MPX
|ADHD ATX: 0.0017|
|ADHD placebo: 0.0359||C-placebo
|ADHD MPX: −0.0232||C-MPX
|ADHD ATX: 0.02464|
Note: C = healthy control boys; placebo = ADHD boys under placebo; MPX = ADHD boys under MPX; ATX = ADHD boys under ATX; R = right; L = left; VLPFC = ventrolateral prefrontal cortex; OCC-CB = occipito-cerebellum; SMA = supplementary motor area; ACC = anterior cingulate gyrus; BOLD = blood oxygen level-dependent.
Keywords: atomoxetine, attention deficit hyperactivity disorder, functional magnetic resonance imaging, methylphenidate, motor response inhibition, stop task.
Previous Document: Shoot phototropism in higher plants: New light through old concepts.
Next Document: Spectral Organization of the Human Lateral Superior Temporal Gyrus Revealed by Intracranial Recordin...