Structural and functional brain imaging in adult attention-deficit/hyperactivity disorder

603

Review

www.expert-reviews.com ISSN 1473-7175© 2010 Expert Reviews Ltd10.1586/ERN.10.4

Attention-deficit/hyperactivity disorder (ADHD) is a developmental disorder, defined as age-inap-propriate levels of hyperactivity, impulsivity and inattention (Diagnostic and Statistical Manual of Mental Disorders [DSM] IV) [1].

Traditionally conceptualized as a childhood disorder, the majority of research has focused on children with ADHD. However, recent studies have shown the persistence of behavioral symp-toms in up to 65% of cases [2,3], with a prevalence of 3–4% of the adult population [4,5].

Children with ADHD have deficits in execu-tive functions, in particular in tasks of motor and cognitive inhibition, sustained attention and tem-poral processes [6–9], with some evidence for moti-vational deficits [10]. Neuropsychological deficits have shown persistence into adulthood [11], with the most consistent findings showing abnormali-ties in motor response and interference inhibi-tion [12–20], working memory [18–22], and sus-tained, selective and flexible attention [18,19,23–26], with some evidence for deficits in motivation processes [26].

The majority of functional imaging studies in both children and adults with ADHD have focused predominantly on these cognitive func-tions that are impaired in the disorder. There has been a difference in focus, however, with

functional studies in children with ADHD focus-ing more on motor response inhibition and atten-tion tasks, while studies in adult ADHD have focused more on tasks of interference inhibition, working memory and motivation control.

The aim of this review is to summarize the main findings of modern structural and func-tional imaging studies in adults with ADHD, with particular emphasis on the most recent studies.

Structural imagingIn children with ADHD, structural deficits have been observed in the frontal lobes, basal gan-glia, cerebellum and parietotemporal regions [27], with longitudinal studies showing evidence for a maturational delay in brain structure of a mean of 3 years [28].

Relatively few structural imaging studies have been published regarding adult ADHD. Nevertheless, deficits appear to be similar both in structure and function. An early study observed decreased volume in left orbitofrontal cortex in eight medication-naive adult males with ADHD who had no comorbid conditions (age range of 19–40 years) compared with healthy controls in an a priori selected region of interest (ROI) [29]. A sample of 24 adult males and females with ADHD (age range of 19–58 years) compared

Ana Cubillo and Katya Rubia†

†Author for correspondenceDepartment of Child Psychiatry/SGDP, P046, Institute of Psychiatry, 16 De Crespigny Park, London, SE5 8AF, UK Tel.: +44 207 848 0463 Fax: +44 207 208 5800 [email protected]

Attention-deficit/hyperactivity disorder (ADHD) is a childhood disorder that persists into adulthood. Nevertheless, there are far fewer imaging studies in adult compared with childhood ADHD. Here we review the imaging literature on brain structure, function and structural and functional connectivity in adult ADHD, as well as the effects of psychostimulants on brain dysfunctions. Importantly, we discuss similarities and differences between these deficit findings and those in childhood ADHD to address the key question of continuity of brain abnormalities into adulthood. Findings show strikingly similar but more inconsistent abnormalities in adult ADHD in key childhood ADHD deficit areas of frontostriatal, temporoparietal and cerebellar regions, presumably due to highly prevalent confounding factors in adult ADHD of elevated rates of comorbidity and medication history.

Keywords: adult attention-deficit/hyperactivity disorder • attention • basal ganglia • cerebellum • frontal lobe • functional connectivity • functional MRI • inhibition • magnetic resonance imaging • methylphenidate • MRI • near-infrared spectroscopy • parietal lobes • positron emission tomography

Structural and functional brain imaging in adult attention-deficit/hyperactivity disorderExpert Rev. Neurother. 10(4), 603–620 (2010)

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Expert Rev. Neurother. 10(4), (2010)604

Review

with controls had a decreased volume in overall cortical gray matter, right anterior cingulate and left superior/dorsolateral prefrontal cortex, but also an increased volume of the nucleus accumbens [30]. Furthermore, the same ADHD sample showed decreased cortical thickness in bilateral dorsolateral and orbi-tofrontal cortices, anterior and posterior cingulate and in the temporo–occipito–parietal junction. [31].

Only one study has used diffusion-tensor imaging to test for deficits in white matter tracts. A group of 12 male and female adults (age range of 37–46 years) with persistent symptoms of ADHD selected from a longitudinal study showed reduced size of right-hemispheric fiber tracts in the cingulum bundle connecting the anterior cingulate with the dorsolateral prefrontal cortex, and in the superior longitudinal fascicle that connects prefrontal and parietal regions, which are crucial for executive functions and attention, respectively [32].

In conclusion, the few published structural studies in adult ADHD seem to show similar deficits to those observed in chil-dren with ADHD [27] in the structure as well as the structural interconnectivity in prefrontal, cingulate and temporoparietal brain regions.

Functional imagingThere is a vast amount of published literature on the functional imaging deficits in children with ADHD. Most consistently, studies have found reduced activation in children with ADHD compared with healthy controls predominantly in inferior fron-tostriatal as well as temporoparietal and cerebellar brain regions during tasks of inhibitory control and attention [33–41] (for meta-ana lysis and review see [42,43]), as well as timing processes [9,36,44]

(for review see [9]). Reduced activation of the inferior prefrontal cortex in particular is one of the most consistently observed find-ings in childhood ADHD and has even been shown to be dis-order-specific compared with other childhood disorders, such as conduct disorder [45–48] and obsessive–compulsive disorder [49,50].

Despite evidence showing the persistence of neuropsycho-logical deficits in adults with ADHD [11], relatively few func-tional imaging studies have assessed brain dysfunctions asso-ciated with the observed impairments. However, functional imaging research in adults with ADHD has increased expo-nentially in recent years and most of the studies are very recent, that is less than 5 years old. The following is a review of the functional imaging studies conducted in adult ADHD. The main findings of these functional MRI (fMRI) studies are summarized in Table 1.

Motor response inhibition Compared with the vast functional imaging literature in childhood ADHD using tasks of response inhibition, there are only three published fMRI studies in adult ADHD on this key neurocognitive deficit function in ADHD.

Motor response inhibition is typically measured in Go/No-go or Stop tasks, where subjects have to inhibit a prepotent motor response to a frequent Go stimulus after the presentation of infrequent No-go or Stop signals. fMRI studies of Go/No-go

and Stop tasks have shown activation during inhibition tri-als in predominantly right dorsolateral and inferior prefrontal cortex, supplementary motor area, anterior cingulate, caudate and thalamus as well as inferior parietal brain regions [51–54].

Two of the fMRI studies in adults with ADHD used a Go/No-go task. A study by Epstein et al. found that nine male and female parents of ADHD children who had a clinical diagno-sis of ADHD themselves, including one subject with a medication history, showed underactivation when compared with healthy controls in bilateral inferior frontal cortex and left caudate, which were furthermore correlated with attention performance mea-sures in the task (which did not differ between patients and con-trols) [55]. They also showed increased activation in left inferior parietal lobe and anterior cingulate, which was interpreted by the authors as a potential alternative, compensatory recruitment for the fronto striatal dysfunction. A later study of Dibbets et al. found no significant underactivation in 15 previously medicated adults with ADHD compared with controls during the inhibi-tory trials of the task [56] (in which they did not differ in perfor-mance), but found increased activation during the executive Go trials (in which they differed in performance) in right medial frontal cortex, a region that is important for response selection and execution [54].

A study from our laboratory used a tracking Stop task in a group of medication-naive adults followed up from childhood ADHD within an epidemiological study and who had persistent inat-tentive and hyperactive symptoms [57]. The adults with ADHD, despite no performance deficits, showed underactivation in bilat-eral inferior frontal and premotor cortices, anterior cingulate, striatum and right thalamus during successful inhibition, and in right inferior frontal cortex, striatum and bilateral thalamus during inhibition failures.

In conclusion (see Table 1), the findings of reduced fronto-striatal activation in adults with ADHD in two of the studies during inhibitory processes is parallel to the findings of fronto-striatal dysfunction in children with ADHD during the same and similar Go/No-go and Stop tasks [33–38,46,58]. The enhanced activation in the medial frontal and parietal regions in two of the studies [55,56] contrasts with the underactivation finding of the same regions in the only study that exclusively included medication-naive adults with ADHD with a confirmed child-hood diagnosis [57]. Compensatory activation in adult ADHD may possibly be related to long-term medication effects. The studies that found overactivation also included a relative age range of up to 20 years and included female participants, which may have increased the heterogeneity, given evidence for the effects of age and gender on brain activation [51,52,59], as well as on the behavioral, cognitive and functional imaging phenotype of ADHD [60–63].

Interference inhibitionInterference inhibition measures the cognitive inhibition of interfering information or distraction. It is typically measured in Color–Word Stroop, Simon or Eriksen Flanker tasks, where automatic and prepotent response tendencies to interfering

Cubillo & Rubia

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Structural & functional brain imaging in adult ADHD


ReviewTa

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Cubillo & Rubia


Review

information have to be inhibited. fMRI stud-ies using interference inhibition tasks have consistently found activation in predomi-nantly left hemispheric inferior and dorso-lateral prefrontal cortices, the basal ganglia, anterior cingulate and inferior parietal brain regions [51,59,64–67].

The first fMRI study to test interference inhibition in adult ADHD used a counting Stroop task and found reduced activation in eight adult males and females with ADHD with a previous history of medication in an a priori-defined ROI in the cognitive division of the dorsal anterior cingulate [68]. Two later studies replicated and extended these find-ings. We replicated the finding of reduced activation in anterior cingulate in medication-naive adults with ADHD with a confirmed childhood diagnosis in a Simon interference inhibition task using whole-brain fMRI ana-lysis [69]. In addition, we also observed reduced activation in left ventromedial orbitofrontal and dorsolateral prefrontal cortices and the caudate [69].

A recent study by Banich et al. used a hybrid block/event-related fMRI design of a Stroop Color–Word task in high-functioning female and male adults with ADHD with a previous history of stimulant medication who showed better task performance than the control group [70]. The high-functioning patients showed reduced activation in right inferior prefrontal cortex for the specific contrast of incongruent versus congruent trials, while for the blocked ana lysis, presumably reflecting sustained interference inhibition, they showed enhanced medial frontal activation. They also showed reduced activation in dorsolateral prefrontal cortex across all blocks, includ-ing neutral and congruent ones, which was interpreted by the authors as reduced atten-tion control, independent of the difficulty of the condition. The findings remained when performance was covaried.

Functional neuroimaging findings are, thus, consistent with respect to the underac-tivation of key regions for attention control of anterior cingulate and inferior prefrontal cortex [71,72] in adult ADHD during tasks of interference inhibition (see Table 1) [68–70], although differences were observed in the laterality of the inferior prefrontal dysfunc-tion findings [69,70], which could be due to differences in task design or the inclusion of females and chronically medicated patients in Ta

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mem

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tas

k.



Review

the study of Banich et al. [70]. The findings of reduced activation in anterior cingulate and fronto striatal brain regions are in line with dysfunction findings in children with ADHD during similar interference inhibition tasks [47,73,74].

Selective, sustained & flexible attention Compared with childhood ADHD, adult ADHD is typified by a decrease in the number and severity of symptoms of hyper activity and impulsiveness, while the decline of attention symptoms is much more moderate [75]. It is therefore surprising that, given the persistence of attention problems into adulthood, few studies have tested for brain dysfunctions during attention tasks.

Attention allocation is typically measured in oddball tasks, which have been shown to activate a distributed neural net-work that includes dorsolateral and inferior prefrontal, inferior parietal and temporo–occipital areas, as well as insula, ante-rior and posterior cingulate [39,76–79]. During the performance of a simple oddball task, which measurde perceptive attention allocation, a group of 11 medication-naive males with ADHD, selected from an epidemiological study with a confirmed child-hood ADHD diagnosis, showed underactivation in fMRI in left inferior and dorsolateral pre frontal cortex compared with a healthy control group [69]. This parallels the prefrontal deficit findings from fMRI studies in children with ADHD during oddball tasks [40,47].

The same group of patients was also scanned during sus-tained-attention [80] and cognitive-switch tasks [57]. In healthy adults, sustained attention predominantly activates right hemi-spheric dorsolateral and inferior prefrontal, striatal, thalamic and inferior parietal brain regions [67,81,82], while cognitive switching has been shown to activate dorsolateral prefrontal cortex, anterior cingulate and bilateral inferior frontal and parietal lobes [51,64,83,84]. During the sustained-attention task, underactivation compared with healthy controls was observed in left inferior frontal cortex, bilateral striatum and thalamus, and temporoparietal cortices. However, increased activation was also observed in right inferior/dorsolateral prefrontal cor-tex, and bilateral cerebellum and occipital regions, which we interpreted as a compensation for the reduced left-hemispheric frontostriatal activation. During the switch task, measuring cognitive flexibility, underactivation was observed in typical brain regions of cognitive switching in bilateral inferior frontal cortices, reaching into the insula, striatum, and left premotor and inferior parietal cortices [57].

Thus, it seems that across studies, despite no performance deficits in any of them, left inferior and dorsolateral prefron-tal cortices appear to be consistently underfunctioning during sustained-, selective- and flexible-attention processes in adult ADHD, with additional evidence for dysfunctions in striatal and posterior temporoparietal attention regions (see Table 1). These deficits in inferior frontostriatal and parietotemporal regions during attention tasks are parallel to findings in children with ADHD [38–41,45,47,48,50] with the difference that the prefrontal deficit findings appear more left-lateralized in adults and more bilateral in children with ADHD.

Working memoryThe majority of modern functional imaging studies in adult ADHD have focused on verbal working memory functions, presumably due to the abnormality findings in this function in neuropsychological studies in adult ADHD [18–22].

In healthy adults, verbal working memory has been shown to activate lateral prefrontal brain regions, in particular left infe-rior and dorsolateral prefrontal cortex, but also temporoparietal regions and the cerebellum [67]. Two early studies used PET with the paced auditory serial addition working memory task in a small group of six adult males with ADHD, two of whom had a previous history of stimulant medication, and subsequently in ten male and female adults with ADHD. The patients made more errors on the task than controls in both studies. No direct group comparison was conducted in the first study [85], but the second study showed reduced medial frontal and reduced inferior frontal and superior temporal activation [86], but also enhanced activation in midbrain, right caudate, cerbellar vermis and left middle frontal cortex [86]. A study using functional near-infrared spectroscopy during an N-back working memory task [87] found reduced activation in 13 males and females with ADHD in bilateral ventrolateral pre-frontal cortex, in particular during the more difficult condition, despite no performance deficits. A limitation of near-infrared spectroscopy is the poor depth penetration that can only test cortical activation. Furthermore, this study only selected lateral prefrontal brain regions as ROIs and did not test for differences in other cortical regions that are known to be important for working memory processing, such as temporal and parietal areas. Wolf et al. used fMRI combined with a delay working memory task in 13 adults with ADHD with a medication history and found that despite no performance differences, the adult ADHD patients had extensive underactivation compared with controls in left ven-trolateral/inferior and right medial prefrontal cortices, but also in posterior regions of cerebellum, insula and occipital areas [88].

A study by Hale et al. compared ten adults with ADHD, includ-ing patients with a medication history, with healthy controls that were almost 8 years younger during a digit span working memory task [89]. The patients showed significant reduced activation in left and right superior and inferior parietal and left temporo–occipital regions, but also demonstrated enhanced activation in left midcin-gulate and superior temporal and parieto–occipital regions. Unfortunately, this study is difficult to interpret given the large age difference between groups. Frontostriatal and frontoparietal neural networks that mediate executive functions increase linearly with age in their activation between 10 and 43 years [51,52,59,90]. Therefore, an age superiority of 8 years is a major confound that could well explain the enhanced activation in patients in cingu-late and temporoparietal brain areas that are known to increase progressively with age in their activation during young adulthood.

Two fMRI studies from the same research group have used relatively large numbers of participants. A study by Valera et al. tested 20 mixed-gender adults with ADHD of whom 50% had a previous stimulant medication history during a difficult N-back working memory task [91]. Despite no performance deficits, they found reduced activation in the patient group in the left lateral

Cubillo & Rubia


Review

cerebellum. However, a later published study in a larger sample of 44 adults with ADHD showed underactivation in patients in left and right middle frontal cortex, including the anterior cingulate [63]. Apart from the large subject numbers, a strength of both studies is the relative low rate of comorbid conditions in their sample and the fact that existing comorbid conditions, such as learning disability, anxiety and depression, as well as medica-tion history, were controlled for in the analyses. Furthermore, the second study analyzed sex by group effects and found that males showed significantly larger deficits than females in large clusters of right orbitofrontal cortex, extending into temporal regions, striatum and hypothalamus and in right middle fron-tal and left occipito–temporal regions. Females had no signifi-cantly enhanced deficits compared with males and did not dif-fer from the control female group. These findings show, for the first time, that the underlying neurobiology of female and male adult ADHD is fundamentally different, with brain dysfunctions being much more extensive in males and females being similar to control females. The findings add neurofunctional underpin-nings to the notion that male and female ADHD differ in their behavioral and cognitive phenotype [60–62]. The findings of a lack of dysfunction in females with ADHD are in line with the only other two studies that have compared females with ADHD alone with healthy controls in adolescents and found no significant differences [92,93].

To summarize, studies using working memory paradigms in adults with ADHD found decreased activation in inferior/ventro lateral prefrontal, parietal, temporo–occipital and cer-ebellar regions (see Table 1) [63,87–89,91]. An important message from the study of Valera et al. is that the inclusion of females, which is more typical of adult than childhood ADHD imaging studies, increases the heterogeneity of the sample substantially and may overshadow deficit findings that are more prominent and may only be observed in males [62]. Future imaging studies of adult ADHD should, therefore, separately study men and women with ADHD. In the studies reviewed in this section, the presence of psychiatric comorbidities [89], the inclusion of sub-jects with a previous history of stimulant medication [63,87–89,91] and the wide age range used [63,87,89,91] are additional factors that may have increased the heterogeneity of the samples and confounded findings. No study in childhood ADHD has used a working memory task and, hence, comparison with childhood fMRI deficits is not possible.

Reward-related motivation functionsRelatively few imaging studies have studied reward-related func-tions in childhood ADHD, finding reduced activation in ventral striatum during reward anticipation [94], in posterior cingulate during reward outcome [45] and in fronto–striato–cerebellar net-works during reward delay [9]. A few recent functional imaging studies have also focused on reward-related motivation processes in adult ADHD.

Gambling tasks measure reward-related decision making and temporal foresight and have been shown to activate orbito-frontal, limbic and ventral striatum regions in healthy adults

during impulsive choices and ventromedial and dorsolateral prefrontal cortices during foresighted decision making [59,95]. A study using PET during a gambling task in ten adults of both genders with ADHD with a previous medication history, found reduced activation in left insula and parahippocampal gyrus, and hyperactivation in the caudal part of the right anterior cingulate [96].

A fMRI study used a monetary-incentive delay task that mea-sures the neural substrates of reward outcome and reward anticipa-tion related to a reaction time task in ten male adults with ADHD. The task typically activates the ventral striatum in relation to reward anticipation, while reward outcome has been associated with mesial and orbital prefrontal and striatal activation [97–99]. Despite no performance deficits there was a neural dissociation during the reward processes involved in the task. Patients had reduced activation compared with healthy controls during the anticipation of gain in the limbic left ventral striatum, while dur-ing the outcome phase, they showed increased activation in typical areas of reward processing, such as right orbitofrontal and bilateral lateral frontal regions, right caudate and putamen [100].

Similar findings of dissociated neural networks with respect to the more cognitive and more motivational aspects of the task were observed in another fMRI study by Plichta et al. [101] during temporal discounting in 14 male adults with ADHD. Subjects had to choose between a smaller immediate reward, or a larger delayed reward. Typical areas of activation in tem-poral discounting tasks are limbic regions for immediate delay choices including the ventral striatum and amygdala [102,103], with lateral orbitofrontal, insular and striatal network activa-tion for delayed reward choices [9,104,105]. In the ADHD adults, the delay-dependent valence decay was significantly higher than in controls. The fMRI comparison unfortunately only tested for group differences in a small group of a priori-defined ROIs of nucleus accumbens, caudate and amygdala. Ventral striatum and bilateral amygdala were reduced in the ADHD group during immediate choices, while during delayed choices they showed increased activation in the dorsal striatum and bilateral amygdala. Given that delay discounting tasks measure not only limbic responsiveness during immediate or delayed rewards but are also an important measure of fronto parietal net-works of temporal foresight, it is unfortunate that the authors did not conduct or present a whole-brain ana lysis or test for ROIs within frontal or parietal regions. This makes it diffi-cult to compare the activation patterns with those observed in children with ADHD, who in a whole-brain ana lysis showed reduced activation for delayed versus immediate delay choices in a predominantly left hemispheric orbital and inferior fronto–striato–parieto–cerebellar network [9].

Two studies have investigated the effect of motivation within cognitive tasks. A study from our group measured the effect of reward within a sustained-attention network in a continuous-performance task in medication-naive ADHD males with a confirmed childhood ADHD diagnosis [80]. The patient group showed underactivation in right ventromedial orbitofrontal cortex [80].



Review

Positive and negative feedback has been incorporated into a Go/No-go task to test for motivation effects within inhibitory networks [56]. In line with the study of Cubillo et al. [80], dur-ing positive feedback, adult patients showed underactivation in reward-processing brain regions of bilateral inferior/orbito-frontal and medial cortices, and during negative feedback in hippocampus/nucleus accumbens.

In conclusion, there is relatively consistent evidence from these studies that areas of the limbic and paralimbic systems in ventral striatum, amygdala and ventromedial orbitofrontal cortex, which are known to be involved in motivation/reward processes [99,102,103,106], are dysfunctional in adults with ADHD in the context of motiva-tion (Table 1). However, the direction of some of the dysfunctions seems inconsistent, in particular with respect to orbitofrontal under-activation [56,80] or overactivation [100] during reward or positive- feedback processing. The findings of abnormalities in ventral stri-atum, orbitofrontal and cingulate cortices during reward-related processes are strikingly similar to the imaging findings in studies during childhood ADHD during similar tasks [9,45,94].

Association between behavioral symptoms & imaging data An interesting question in fMRI studies is whether ADHD symp-toms correlate with brain activation networks that are activated dur-ing a particular task. This is best addressed in whole-brain regression analyses between symptoms and brain activation. Relatively few studies have conducted such analyses; however, these have, by and large, been able to confirm and reinforce the association between fronto–striato–parietal dysfunction and ADHD symptoms.

During a decision-making task, Ernst et al. observed negative correlations between ADHD symptoms, as assessed using the Conners teacher’s rating scale, and brain activation in ventro-medial and dorsolateral prefrontal cortices, anterior and poste-rior cingulate, and temporal and parietal cortices [96]. However, they also observed a positive correlation between symptoms and a different region of right dorsolateral prefrontal cortex, which was interpreted as a possibly compensatory recruitment for the symptom-associated underactivation in other regions.

Using the subscale of inattentiveness/restless behavior in the Adults Hyperactivity Interview, adapted from the Adult Personality Functioning Assessment [107], we observed a negative correlation between the severity of the attention/hyperactivity symptoms and brain activation during tasks of motor inhibition and cognitive switching in an extensive network of superior and inferior frontal lobes, caudate, putamen, thalamus, temporal and parietal regions and cerebellum, which overlapped with the dys-function areas when compared with controls [57]. Furthermore, we also observed a negative correlation between severity of ADHD symptoms and deficit areas of left inferior and medial prefrontal cortex, anterior and posterior cingulate, caudate, temporoparietal areas and cerebellum during an interference inhibition task [69].

The largest study published to date included 44 adults with ADHD and correlated symptoms separately for male and female ADHD with brain activation during a working memory task [63]. The whole-brain regression ana lysis showed a negative correlation

between the number of hyperactive, but not inattentive, symp-toms and activation in occipitocerebellar regions in men with ADHD, whereas in female patients a negative correlation was observed between the number of inattentive, but not hyperac-tive, symptoms and activation in a widespread network, includ-ing left orbitofrontal and inferior parietal cortex, bilateral insula, cingulate, striatum, hippocampus, temporo–occipito–cerebellar regions, amygdala and right basal ganglia [63].

Testing for behavior–brain correlations in ROIs that differ between groups is not advisable as it is based on circularity, given that the groups were selected based on behavioral symptoms [108]. However, several imaging studies have conducted such analyses, which, given that they are highly questionable, will only be briefly described. Plichta et al. observed a positive correlation in the ADHD group between the scores in the hyperactive/impul-sive items of the ADHD symptoms scale and activation in the caudate and amygdala during delayed rewards [101]. Wolf et al. observed a negative correlation between total ADHD symp-tom scores and activation in right cerebellum during working memory [88], and Stroehle et al. observed a negative correlation between the total of DSM-IV ADHD symptoms and hyperac-tivity scores and brain activation in left ventral striatum during gain anticipation [100].

In conclusion, the findings from whole-brain regression analy-ses between behavioral symptoms and activation seem to strongly confirm and reinforce the association between dysfunction in prefrontal, striatal, temporoparietal, cerebellar and even limbic brain regions and symptoms of the disorder. Interestingly, while in males it is hyperactive symptoms that more strongly correlate with brain activation in deficit areas, it is inattentive symptoms that correlate with brain activation in female patients, in line with the notion that inattentive symptoms are more prevalent in females [60] and, hence, may be the ones that are associated with brain underfunctioning.

Studies of functional connectivityIt has been argued that ADHD is not only characterized by deficits in the structure and function of isolated frontal, parietal and cerebellar brain regions, but also in the functional inter-regional connectivity between these regions that form neural networks. Consequently, in recent years, several imaging studies have tested for deficits in the functional inter-regional connec-tivity between these key deficit regions during rest and in the context of cognitive tasks.

Functional connectivity during restIn children with ADHD, there is evidence for reduced func-tional connectivity in frontostriatal, frontoparietal and fronto-cerebellar networks during the resting state [109,110], although increased inter-regional connectivity between anterior cin-gulate, striatum and temporocerebellar regions has also been reported [110,111].

The only study of functional connectivity in adult ADHD during rest by Castellanos et al. observed decreased functional connectivity in a group of 20 previously medicated adult males

Cubillo & Rubia


Review

and females with ADHD compared with controls between the anterior and posterior components of the default resting network, namely between ventromedial prefrontal cortex including the anterior cingulate and the precuneus and posterior cingulate [112].

Task-related functional connectivityWe are only aware of one published paper on childhood ADHD that tested for task-related functional connectivity abnormalities and found a reduced degree of functional connectivity in children with ADHD between inferior prefrontal cortex and the basal gan-glia, parietal lobes and cerebellum as well as between cerebellum and parietal and striatal brain regions during a sustained-attention task [113].

In adult ADHD, to our knowledge, there are only two pub-lished studies on functional connectivity during cognitive tasks. During the performance of a working memory task, Wolf et al. used brain regions that differed between groups as ROIs in order to identify abnormalities in functional connectivity [88]. ADHD adults showed reduced functional connectivity in bilat-eral inferior prefrontal cortex, left anterior cingulate, superior medial frontal cortex, bilateral superior parietal regions and the cerebellum. However, increased functional connectivity was also observed in a different region of the left dorsal anterior cingulate, right superior frontal gyrus and left occipital lobe. This was interpreted as compensatory by the authors, due to the observed positive correlation between measures of task accuracy and indices of functional connectivity strength in right inferior frontal gyrus.

In order to aviod biasing connectiv-ity deficit findings towards brain regions that differ between groups in activation, we tested for differences between medica-tion-naive adults with ADHD and con-trols in connectivity in brain areas that were activated in all subjects, patients and controls, during a Stop task, rather than choosing areas from a difference compari-son [57]. Nevertheless, we observed signifi-cantly reduced functional inter-regional connectivity in patients between the key inhibitory deficit area, the right inferior prefrontal cortex and other brain regions, including left inferior prefrontal cortex, caudate/thalamus, anterior and posterior cingulate and bilateral temporoparietal regions, as well as between thalamus and posterior cingulate (Figure 1).

Thus, the findings of functional connec-tivity analyses suggest that the dysfunc-tions observed in ADHD patients not only affect isolated brain regions but also the functional inter-regional interconnectiv-ity between these affected brain regions. The two studies that tested for task-related functional connectivity deficits in ADHD,

despite using different methods for the connectivity analyses, found surprisingly similar deficits, in particular between key areas of dysfunction in ADHD adults and children, between inferior prefrontal cortex, cingulate, striatal, parietal and cer-ebellar regions. These studies elevate the findings of isolated brain dysfunctions in ADHD to the level of a disturbance in fronto–striato–parieto–cerebellar neural networks during executive functions.

Effects of methylphenidate on brain functionPsychostimulants are the most effective first-choice treatment for ADHD. Methylphenidate (MPH) ameliorates the behavioral symptoms in 70% of children with ADHD [114,115]. fMRI stud-ies on the effects of an acute clinical dose on brain activation in children with ADHD during cognitive tasks have most consis-tently shown activation enhancement in the caudate, but also in prefrontal, cingulate and temporoparietal areas and cerebel-lum [9,113,116,117], with some studies finding complete normaliza-tion of activation deficits in fronto–striato–cerebellar activation and connected networks [9,113,117]. However, chronic treatment with MPH has shown either no effect on brain activation [118], or only a reduction of the possibly compensatory abnormal baseline hyperactivation in insula and striatum [119].

Relatively few imaging studies have tested for MPH effects on brain activation in adult ADHD. Schweitzer et al., using PET, observed that prolonged (3 weeks) MPH treatment in a group of ten adult males with ADHD improved performance in

Left inferior frontal Right inferior frontal

Right medial frontal/anterior cingulate

Right anterior/posterior cingulate/SMA

Right thalamus/striatum

Bilateral parieto–temporo–occipital

Controls = 0.811Patients = 0.566






Figure 1. Differences in functional connectivity between regions that were activated in both groups during the Stop task. Pearson correlations are shown for the two groups for inter-regional correlations that differed between the two groups. Significant group differences were at p < 0.0023 at a family-wise error rate of 0.05, corrected for multiple comparisons using the Dunn–Sidak method. SMA: Supplementary motor area. Data from [54].



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a working memory task, and reduced regional cerebral blood flow in prefrontal cortex and increased blood flow in right thalamus and precentral gyrus [86]. MPH, however, did not improve the deficits in patients compared with controls of reduced inferior frontal, superior temporal and anterior cingulate activation or of enhanced activation in the basal ganglia, sensory and motor regions and cerebellum.

Bush et al. studied the effects of 6 weeks of treatment with sustained-release MPH during an interference-inhibition task in a group of 21 unmedicated adult males and females with ADHD in a ROI of dorsal midanterior cingulate, as well as using whole-brain analyses [120]. In the absence of differences in performance, MPH increased activation during the interference condition in the patient group in dorsal anterior midcingulate, but also in dorsolateral prefrontal, premotor and parietal cortices, caudate, thalamus and cerebellum. Furthermore, they observed that those subjects who responded to chronic MPH treatment were more likely to show an increment in the activation in dorsal anterior midcingulate cortex.

Only one study tested the effects of acute MPH on brain acti-vation. Epstein et al. recruited parent–child dyads, where both had a diagnosis of ADHD [55]. Using a Go/No-go task, the group of parents with ADHD showed an improved performance in the task under an acute clinical dose of MPH, with decreased reaction time variability and improved stimulus discrimination. MPH increased activation in left caudate and hippocampus, and decreased activation in right inferior parietal lobe in the patient group.

In conclusion, the available evidence suggests a modulatory effect of MPH in areas that are affected in adults with ADHD in frontal, striatal, thalamus, cingulate and parietocerebellar areas. However, the studies have been inconsistent with respect to whether MPH enhances or reduces activation in these key, disorder-relevant brain regions, particularly with respect to increased [120] or decreased frontal activation [86]. This is prob-ably due to the relatively small sample sizes used in these studies, and potential heterogeneity with respect to inclusion of comorbid cases [55] and females [55,120]. Consequently, the findings need to be considered as preliminary and replicated in larger subject numbers. Furthermore, while MPH has been shown to modulate disorder-relevant brain regions, there is no evidence for substan-tial amelioration or normalization of the deficits compared with controls [86], as has been shown in children with ADHD [9,117], suggesting relatively limited effects on brain dysfunctions in adult ADHD.

Similarities between findings in adults & children with ADHDA crucial question is whether brain dysfunctions in adults are similar to those observed in childhood. Unfortunately, few fMRI studies have used the same fMRI paradigms in children and adults, which makes a comparison difficult. Some of the fMRI studies that have used the same fMRI tasks, however, show strik-ingly similar dysfunctions in children and adults with ADHD, as illustrated in Figure 2.

Using the same Go/No-go task in dyads of parents and chil-dren with ADHD, similar underactivation was observed com-pared with the respective age-matched controls in both popu-lations in right inferior prefrontal cortex and the caudate [55]. The inferior frontocaudate dysfunction findings in adults are also strikingly similar to deficit findings in different popula-tions of ADHD children by Booth et al. [34] and Durston et al. (Figure 2a) [33,35].

Similarly, in the Stop task, the underactivation in inferior pre-frontal cortex in medication-naive adults with ADHD who were followed up from a childhood ADHD diagnosis [57] was in a similar location to that observed in children with ADHD in the same [37,46] and similar Stop tasks [6,36]. The caudate was reduced in the right hemisphere in adults [57] but in the left hemisphere in children with ADHD (Figure 2b) [36].

During the same visual–spatial switch task, medication-naive adults and children with ADHD both showed reduced activa-tion in bilateral inferior prefrontal cortex and caudate compared with their respective controls [38,57]. Parietal dysfunction was also observed in both groups, although with differences in lateral-ity, with right parietal dysfunction in children and left parietal dysfunction in adults with ADHD (Figure 2C).

Strikingly similar hypofunction was observed in left dorso-lateral prefrontal activation in children and adults with ADHD compared with their respective age-matched controls during the same oddball task, measuring attention allocation (Figure 2D) [47,69].

Finally, two fMRI studies that used the same fMRI version of the monetary-incentive delay task found reduced nucleus accum-bens activation in children and adults with ADHD compared with their age-matched controls in almost the identical location (Figure 2e) [94,100].

In conclusion, the existing evidence suggests that when the same cognitive paradigms are used, children and adults with ADHD appear to show strikingly similar activation deficits compared with their age-matched peers, in particular in those studies where both groups are medication-naive. The findings suggest that there appears to be continuity of brain dysfunctions in adults with ADHD who persist in their symptoms. However, longitudinal fMRI studies that follow the same patients into young adulthood are urgently needed to corroborate these findings, which are based only on cross-sectional descriptive comparisons.

So far, longitudinal imaging studies in ADHD have only been conducted using structural measures. These studies found nonprogressive gray and white matter volume reductions in all cortical brain regions in 152 children with ADHD who were scanned repeatedly up to the age of 20 years. The only brain region that normalized by the age of 20 years was the gray matter volume of the caudate [121]. Within the cerebellum, a similar nonprogressive loss of volume was observed in the supe-rior cerebellar vermis in 36 children with ADHD who were scanned several times between the ages of 8 and 19 years [122]. However, Differences in the left anterior cerebellar hemisphere normalized with age, which was significant in those who had a better clinical outcome. An interesting longitudinal fMRI study by Shaw et al. combining gene-imaging interaction data

Cubillo & Rubia


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in 105 ADHD children and a similar number of controls found that reduced cortical thickness in children with ADHD in right inferior frontal and inferior parietotemporal cortices normalized in young adulthood at the age of 18 years [123]. Furthermore, the DRD4 genotype had an age-specific effect, as it was associated with more pronounced thickness differ-ences in childhood at the age of 7 years, but with a stronger normalization in the parietal lobes in adulthood [123].

Thus, it appears that some structural deficits in parietal, infe-rior frontal, striatal and cerebellar brain regions can normalize in young adults with ADHD, in particular in those that improve clinically. fMRI studies, however, seem to suggest the persis-tence of at least some functional deficits in these brain regions. However, this needs to be further elucidated in longitudinal fMRI studies.

Expert commentaryThe majority of modern imaging studies in adult ADHD seem to be in line with findings in childhood ADHD of deficits in structure and function of inferior and dorsolateral prefrontal lobe, anterior cingulate, parietotemporal and cerebellar areas, as well as limbic areas of reward processing of ventral striatum and amygdala. Nevertheless, the adult ADHD literature is far less consistent than the childhood ADHD literature and there have also been several studies that have found increased activation in the same brain regions in adult ADHD (Table 1).

There are several possible explanations for the larger hetero-geneity in findings in the adult functional imaging literature compared with that in childhood. Some typical confounding factors in ADHD imaging research are much more pronounced in adult compared with childhood ADHD imaging studies, such as the small sample sizes, the elevated rate of comorbid conditions, long-term medication history and the need for retrospective diagnosis.

A limitation to most of the reviewed studies is small sample sizes. Most studies have been conducted in less than 15 sub-jects. The only larger sample studies are one by Banich et al., which included 23 subjects [70], and two by Valera et al., which included 20 and 44 participants [63,91]. Valera et al. found reduced fronto–striato–parietal and cerebellar dysfunction in ADHD patients [63,91], although the study by Banich et al. also found increased activation in right dorsolateral prefrontal cortex [70].

Adult diagnosis of ADHD is usually made in a retrospective fashion. DSM-IV diagnostic criteria for ADHD were devel-oped for the diagnosis of the childhood disorder, and are not adequate for an adult ADHD diagnosis, which remains a cli-nician’s decision. The clinician must establish the presence of inattention/hyperactive/impulsivity symptoms, their pervasive character and impairment caused across situations and make a clear differential diagnosis with other possible comorbid disor-ders. Furthermore, the diagnosis of adult ADHD requires the presence of these symptoms before the age of 7 years, despite recent considerations about this criteria being too stringent for adults when making retrospective diagnoses of ADHD [124,125]. To do so, external informants, school records or any source of

information from that period is necessary, subject to the pos-sibility of recall bias [126]. Only four of the reviewed studies, three functional and one structural imaging study, have included ADHD patients that were followed up from childhood to adult-hood, and thus had a confirmed childhood ADHD diagnosis. These studies showed reduced activation in frontostriatal, pari-etal and cerebellar brain regions as well as reduced structural connectivity between frontocingulate and parietotemporal regions [32,57,69,80].

Adult ADHD is characterized by an elevated rate and severity of comorbid psychiatric conditions with approximately 85% having some Axis I disorders, especially mood, anxiety, substance abuse or impulsive disorders [5,127], and Axis II disorders [128], which complicates the diagnosis and presents a confounder in imaging studies. On the other hand, given the elevated rate of comorbid-ity present in typical adult ADHD, the selection of a sample of adults with pure ADHD without any comorbid disorders may be affected by selection bias, as the patients may have a milder form of the disorder or be higher functioning subjects, and hence not representative of the typical adult ADHD population. A few of the reviewed studies carefully selected only noncomorbid cases or controlled for comorbidities (Table 1) [63,68,70,88,91,100,101].

The severity of the disorder may also be different depending on the origin of the population, that is, whether patients were clini-cally referred or from an epidemiological sample. Adults attend-ing clinical settings are usually self-referred and may therefore experience a more disabling form of the condition than those in epidemiological settings [129].

Another confound in adult ADHD imaging studies is the inclu-sion of both sexes in one study. Males and females with ADHD dif-fer in their cognitive and behavioral phenotype [60–62]. However, the majority of functional imaging studies have included mixed-sex samples (Table 1) [55,63,68,87,89,91]. The recent, largest-sampled fMRI study to date by Valera et al., demonstrated that male and female ADHD also differ substantially in their brain activation patterns during a working memory task with males being sub-stantially more abnormal than females (who were not abnormal) in all key areas associated with ADHD [63]. Therefore, it seems that the inclusion of females and males with ADHD within the same study will overshadow the identification of abnormalities present in gender- or male-homogeneous samples.

However, the most important confounder, is likely to be the existence of a previous medication history. Ideally, this should be avoided, given the evidence for long-term effects of stimulant med-ication on brain structure [130] and brain function [119]. Given the difficulty to recruit medication-naive adults with ADHD, most of the reviewed studies included at least some patients with a stimu-lant medication history (Table 1) [55,56,63,68,70,88,89,91,101]. The only studies that only included medication-naive adults with ADHD found reduced activation in fronto–striato–parietal and cerebellar regions during tasks of executive function and reward [57,69,80].

Finally, an additional confounder may be the inclusion of young and older adults within a wide age range [56,89,100] – some studies having an age range of more than 30 years (Table 1) [68,91] – which significantly increases the heterogeneity of the samples.

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Key issues

• Attention-deficit/hyperactivity disorder (ADHD) is a childhood disorder that persists into adulthood in behavioral and cognitive phenotype.

• Adults with ADHD show strikingly similar deficits to those observed in children with ADHD in the structure and function, as well as structural and functional connectivity, of frontal, striatal, cingulate and parietotemporal brain regions and networks.

• Methylphenidate modulates abnormal activation in these brain areas.

• However, there are more inconsistencies in functional deficit findings in adult ADHD, with some studies finding under- and others finding overactivation of the same brain regions.

• Inconsistencies are likely to be due to confounders in adult ADHD studies, such as small sample sizes, elevated inclusion, rate and severity of comorbid conditions, the inclusion of adults with a previous long-term medication history, and of both male and female subjects that are known to differ in their cognitive and behavioral phenotype as well as their functional brain activation.

• Future imaging studies of adult ADHD should avoid these confounding factors.

• The mechanisms of action of the standard treatments of methylphenidate and atomoxetine need to be further investigated in adult ADHD.

• Longitudinal functional and structural imaging studies from childhood into mid-adulthood are needed to corroborate the notion, based on cross-sectional studies, that structural and functional deficits in childhood ADHD persist into adulthood.

• Gene-imaging and brain–behavior associations should reveal to what extent genotype and clinical course of the disorder are associated with the life course of brain abnormalities.

Very few studies have tested for the effects of acute and chronic MPH on brain activation in adult ADHD. The published stud-ies, although showing a modulating effect on key dysfunction areas in ADHD, have been controversial with respect to up- or downregulation of chronic MPH treatment on frontal brain regions [120,131] and have been shown to be relatively moder-ate with respect to normalization or amelioration of existing brain dysfunctions [131]. Although it may be too early to draw conclusions from these few published studies, it is possible that MPH may be more potent in normalizing brain abnormalities in childhood than in adult ADHD.

Five-year viewFuture studies should be conducted in larger sample sizes of at least 20 patients. Furthermore, given the evidence for the long-term effects of stimulant medication on brain function and brain structure [119,130], studies should focus on patients who have never been medicated before. The findings of sex differ-ences of Valera et al. suggest that males and females with adult ADHD need to be studied separately in imaging studies so that the presence of females does not overshadow deficit findings in males [63]. Longitudinal imaging studies are needed to elucidate to what extent brain structure and function deficits in childhood ADHD persist into young- and mid-adult ADHD. The compari-son between brain abnormalities between those who persist with and those who grow out of their symptoms will shed light on the underlying brain mechanism that may be associated with normal-ization in adulthood, such as normalization of the maturational delay or compensatory brain mechanisms. Gene-imaging studies have shown associations with the dopamine DAT1 and DRD4 genotypes and caudate and inferior frontal volumes and activa-tion, respectively [123,132,133]. An important question for future research is whether these gene-imaging associations persist in adulthood and how they differ from the associations observed in childhood ADHD. Gene-imaging associations have been shown to differ depending on the age of the disorder with evidence for an impairing effect of DRD4 genotypes on brain structure in children but an association with brain structure normalization

in adults [123]. Genes may thus have different effects in ADHD depending on the developmental stage. It will also be important to study to what extent dopamine or noradrenaline genotypes could predict treatment response to MPH or the newly licensed selective noradrenaline transporter-blocking drug, atomoxetine. Larger sample studies that investigate the neurofunctional mech-anisms of action of these two drugs on brain activation in adult ADHD, and in particular on functional connectivity deficits are needed, given the evidence in children with ADHD for larger normalization effects of MPH on functional connectivity than activation deficits [113]. New MRI ana lysis methods, such as machine-learning-based multivariate pattern recognition ana-lysis classification systems, have been able to differentiate related patient groups (such as autism and depression) from controls on the basis of quantitatively distributed neural networks rather than isolated brain regions with high specificity and sensitivity of up to 80% in both structure and function [134,135]. Recently developed Gaussian-based multivariate regression algorithms for the quantitative prediction of MRI data [136] would be able to address the heterogeneity within adult ADHD by predict-ing brain structure and activation patterns associated with the comorbid as well as the core conditions. These recently developed machine learning-based methods using quantitatively distributed neural networks have been shown to be very effective diagnostic classifiers [134,135,137], and to be able to predict treatment response based on brain activation patterns, which makes them potentially very useful for clinical use in diagnosis or treatment prediction.

Financial & competing interests disclosureAna Cubillo was funded by the Alicia Koplowitz Foundation and by a PhD studentship grant by the Department of Health via the National Institute for Health Research (NIHR) Specialist Biomedical Research Centre (BRC) for Mental Health award to South London and Maudsley NHS Foundation Trust (SLaM) and the IOP at KCL, London. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

No writing assistance was utilized in the production of this manuscript.



Review

ReferencesPapers of special note have been highlighted as:• of interest•• of considerable interest

1 American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. American Psychiatric Association, DC, USA (1994).

2 Barkley RA, Fischer M, Smallish L, Fletcher K. The persistence of attention-deficit/hyperactivity disorder into young adulthood as a function of reporting source and definition of disorder. J. Abnorm. Psychol. 111(2), 279–289 (2002).

3 Biederman J, Monuteaux MC, Mick E et al. Young adult outcome of attention deficit hyperactivity disorder: a controlled 10-year follow-up study. Psychol. Med. 36(2), 167–179 (2006).

4 Faraone SV, Biederman J. What is the prevalence of adult ADHD? Results of a population screen of 966 adults. J. Atten. Disord. 9(2), 384–391 (2005).

5 Kessler RC, Adler L, Barkley R et al. The prevalence and correlates of adult ADHD in the United States: results from the National Comorbidity Survey Replication. Am. J. Psychiatry 163(4), 716–723 (2006).

6 Rubia K, Taylor E, Smith AB, Oksanen H, Overmeyer S, Newman S. Neuropsychological analyses of impulsiveness in childhood hyperactivity. Br. J. Psychiatry 179, 138–143 (2001).

7 Willcutt EG, Doyle AE, Nigg JT, Faraone SV, Pennington BF. Validity of the executive function theory of attention-deficit/hyperactivity disorder: a meta-analytic review. Biol. Psychiatry 57(11), 1336–1346 (2005).

8 Rubia K, Smith A, Taylor E. Performance of children with attention deficit hyperactivity disorder (ADHD) on a test battery for impulsiveness. Child Neuropsychology 30(2), 659–695 (2007).

9 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 methylphenidate. Philos. Trans. R. Soc. Lond. B Biol. Sci. 364(1525), 1919–1931 (2009).

10 Luman M, Oosterlaan J, Sergeant JA. The impact of reinforcement contingencies on AD/HD: a review and theoretical appraisal. Clin. Psychol. Rev. 25(2), 183–213 (2005).

11 Biederman J, Petty CR, Fried R et al. Stability of executive function deficits into young adult years: a prospective

longitudinal follow-up study of grown up males with ADHD. Acta Psychiatr. Scand. 116(2), 129–136 (2007).

12 Bekker EM, Overtoom CC, Kooij JJ, Buitelaar JK, Verbaten MN, Kenemans JL. Disentangling deficits in adults with attention-deficit/hyperactivity disorder. Arch. Gen. Psychiatry 62(10), 1129–1136 (2005).

13 Bekker EM, Overtoom CC, Kenemans JL et al. Stopping and changing in adults with ADHD. Psychol. Med. 35(6), 807–816 (2005).

14 King JA, Colla M, Brass M, Heuser I, von Cramon D. Inefficient cognitive control in adult ADHD: evidence from trial-by-trial Stroop test and cued task switching performance. Behav. Brain Funct. 3, 42–61 (2007).

15 Rapport LJ, Van Voorhis A, Tzelepis A, Friedman SR. Executive functioning in adult attention-deficit hyperactivity disorder. Clin. Neuropsychol. 15(4), 479–491 (2001).

16 Epstein JN, Johnson DE, Varia IM, Conners CK. Neuropsychological assessment of response inhibition in adults with ADHD. J. Clin. Exp. Neuropsychol. 23(3), 362–371 (2001).

17 Murphy P. Inhibitory control in adults with attention-deficit/hyperactivity disorder. J. Atten. Disord. 6(1), 1–4 (2002).

18 Boonstra A, Oosterlaan J, Sergeant J, Buitelaar J. Executive functioning in adult ADHD: a meta-analytic review. Psychol. Med. 35(8), 1097–1108 (2005).

19 McLean A, Dowson J, Toone B et al. Characteristic neurocognitive profile associated with adult attention-deficit/hyperactivity disorder. Psychol. Med. 34(4), 681–692 (2004).

20 Hervey AS, Epstein JN, Curry JF. Neuropsychology of adults with attention-deficit/hyperactivity disorder: a meta-analytic review. Neuropsychology 18(3), 485–503 (2004).

21 Dige N, Wik G. Adult attention deficit hyperactivity disorder identified by neuropsychological testing. Int. J. Neurosci. 115(2), 169–183 (2005).

22 Dige N, Maahr E, Backenroth-Ohsako G. Reduced capacity in a dichotic memory test for adult patients with ADHD. J. Atten. Disord. DOI: 10.1177/1087054709347245 (2009) (Epub ahead of print).

23 Epstein JN, Conners CK, Sitarenios G, Erhardt D. Continuous performance test results of adults with attention deficit hyperactivity disorder. Clin. Neuropsychol. 12(2), 155–168 (1998).

24 Corbett B, Stanczak DE. Neuropsychological performance of adults evidencing attention-deficit hyperactivity disorder. Arch. Clin. Neuropsychol. 14(4), 373–387 (1999).

25 Walker AJ, Shores EA, Trollor JN, Lee T, Sachdev PS. Neuropsychological functioning of adults with attention deficit hyperactivity disorder. J. Clin. Exp. Neuropsychol. 22(1), 115–124 (2000).

26 Malloy-Diniz L, Fuentes D, Leite WB, Correa H, Bechara A. Impulsive behavior in adults with attention deficit/hyperactivity disorder: characterization of attentional, motor and cognitive impulsiveness. J. Int. Neuropsychol. Soc. 13(4), 693–698 (2007).

27 Krain AL, Castellanos FX. Brain development and ADHD. Clin. Psychol. Rev. 26(4), 433–444 (2006).

28 Shaw P, Eckstrand K, Sharp W et al. Attention-deficit/hyperactivity disorder is characterized by a delay in cortical maturation. Proc. Natl Acad. Sci. USA 104(49), 19649–19654 (2007).

•• Large-scalelongitudinalstructuralimagingstudyprovidingthefirstevidenceforadelay(ofanaverageof3years)inthepeakofmaturationofcorticalthicknessinattention-deficit/hyperactivitydisorder(ADHD)patientsinfronto–temporo–parietalregions.

29 Hesslinger B, Tebartz van Elst L, Thiel T, Haegele K, Hennig J, Ebert D. Frontoorbital volume reductions in adult patients with attention deficit hyperactivity disorder. Neurosci. Lett. 328(3), 319–321 (2002).

30 Seidman LJ, Valera EM, Makris N et al. Dorsolateral prefrontal and anterior cingulate cortex volumetric abnormalities in adults with attention-deficit/hyperactivity disorder identified by magnetic resonance imaging. Biol. Psychiatry 60(10), 1071–1080 (2006).

31 Makris N, Biederman J, Valera EM et al. Cortical thinning of the attention and executive function networks in adults with attention-deficit/hyperactivity disorder. Cereb. Cortex 17(6), 1364–1375 (2007).

32 Makris N, Buka SL, Biederman J et al. Attention and executive systems abnormalities in adults with childhood ADHD: a DT-MRI study of connections. Cereb. Cortex 18(5), 1210–1220 (2008).

• Firstdiffusion-tensorimagingstudyinadultswithaconfirmedchildhoodADHDdiagnosisfollowedupfromchildhoodthatfoundreducedsizeofwhitemattertractsinthecingulumbundleandthesuperiorlongitudinalfasciculus.

Cubillo & Rubia


Review

33 Durston S, Tottenham NT, Thomas KM et al. Differential patterns of striatal activation in young children with and without ADHD. Biol. Psychiatry 53(10), 871–878 (2003).

34 Booth JR, Burman DD, Meyer JR et al. Larger deficits in brain networks for response inhibition than for visual selective attention in attention deficit hyperactivity disorder (ADHD). J. Child. Psychol. Pschiatry 46(1), 94–111 (2005).

35 Durston S, Mulder M, Casey BJ, Ziermans T, van Engeland H. Activation in ventral prefrontal cortex is sensitive to genetic vulnerability for attention-deficit hyperactivity disorder. Biol. Psychiatry 60(10), 1062–1070 (2006).

36 Rubia K, Overmeyer S, Taylor E et al. Hypofrontality in attention deficit hyperactivity disorder during higher-order motor control: a study with functional MRI. Am. J. Psychiatry 156(6), 891–896 (1999).

37 Rubia K, Smith AB, Brammer MJ, Toone B, Taylor E. Abnormal brain activation during inhibition and error detection in medication-naive adolescents with ADHD. Am. J. Psychiatry 162(6), 1067–1075 (2005).

38 Smith AB, 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 disorder. Am. J. Psychiatry 163(6), 1044–1051 (2006).

39 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 variability. Biol. Psychiatry 62(9), 999–1006 (2007).

40 Stevens MC, Pearlson GD, Kiehl KA. An fMRI auditory oddball study of combined-subtype attention deficit hyperactivity disorder. Am. J. Psychiatry 164(11), 1737–1749 (2007).

41 Tamm L, Menon V, Reiss AL. Parietal attentional system aberrations during target detection in adolescents with attention deficit hyperactivity disorder: event-related fMRI evidence. Am. J. Psychiatry 163(6), 1033–1043 (2006).

42 Dickstein SG, Bannon K, Castellanos FX, Milham MP. The neural correlates of attention deficit hyperactivity disorder: an ALE meta-analysis. J. Child. Psychol. Pschiatry 47(10), 1051–1062 (2006).

43 Paloyelis Y, Mehta MA, Kuntsi J, Asherson P. Functional MRI in ADHD: a systematic literature review. Expert Rev. Neurother. 7(10), 1337–1356 (2007).

44 Smith AB, Taylor E, Brammer M, Halari R, Rubia K. Reduced activation in right lateral prefrontal cortex and anterior cingulate gyrus in medication-naive adolescents with attention deficit hyperactivity disorder during time discrimination. J. Child. Psychol. Pschiatry 49(9), 977–985 (2008).

45 Rubia K, Smith A, Halari R et al. 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 attention. Am. J. Psychiatry 166, 83–94 (2009).

46 Rubia K, Halari R, Smith AB et al. Dissociated functional brain abnormalities of inhibition in boys with pure conduct disorder and in boys with pure attention deficit hyperactivity disorder. Am. J. Psychiatry 165(7), 889–897 (2008).

47 Rubia K, Halari R, Smith AB, Mohammad M, Scott S, Brammer MJ. Shared and disorder-specific prefrontal abnormalities in boys with pure attention-deficit/hyperactivity disorder compared to boys with pure CD during interference inhibition and attention allocation. J. Child. Psychol. Psychiatry 50(6), 669–678 (2009).

48 Rubia K, Halari R, Cubillo A, Mohammad A, Scott S, Brammer M. Disorder-specific inferior frontal dysfunction in boys with pure attention-deficit/hyperactivity disorder compared to boys with pure CD during cognitive flexibility. Hum. Brain Mapp. DOI: 10.1002/hbm.20975 (2010) (In press).

49 Rubia K, Cubillo A, Woolley J, Halari R, Smith A, Brammer M. Disorder-specific dysfunctions in boys with attention-deficit/hyperactivity disorder compared to boys with obsessive-compulsive disorder during interference inhibition and attention allocation. Hum. Brain Mapp. DOI: 10.1002/hbm.21048 (2010) (In press).

50 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 disorder. Hum. Brain Mapp. 31(2), 287–299(2010).

51 Rubia K, Smith AB, Woolley J et al. Progressive increase of frontostriatal brain activation from childhood to adulthood during event-related tasks of cognitive control. Hum. Brain Mapp. 27(12), 973–993 (2006).

52 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 processes. Hum. Brain Mapp. 28(11), 1163–1177 (2007).

53 Rubia K, Smith AB, Brammer MJ, Taylor E. Right inferior prefrontal cortex mediates response inhibition while mesial prefrontal cortex is responsible for error detection. Neuroimage 20(1), 351–358 (2003).

54 Rubia K, Russell T, Overmeyer S et al. Mapping motor inhibition: conjunctive brain activations across different versions of go/no-go and stop tasks. Neuroimage 13(2), 250–261 (2001).

55 Epstein JN, Casey BJ, Tonev ST et al. ADHD- and medication-related brain activation effects in concordantly affected parent-child dyads with ADHD. J. Child Psychol. Psychiatry 48(9), 899–913 (2007).

• InterestingfunctionalMRI(fMRI)studythatfoundreducedfronto–striatalactivationinbothparentsandchildrenwithADHDduringresponseinhibitionandfoundmethylphenidatetoupregulatethecaudate.

56 Dibbets P, Evers L, Hurks P, Marchetta N, Jolles J. Differences in feedback- and inhibition-related neural activity in adult ADHD. Brain Cogn. 70(1), 73–83 (2009).

57 Cubillo A, Halari R, Ecker C, Giampietro V, Taylor E, Rubia K. Reduced activation and inter-regional functional connectivity of fronto–striatal networks in adults with childhood attention deficit hyperactivity disorder (ADHD) and persisting symptoms during tasks of motor inhibition and cognitive switching. J. Psychiatr. Res. DOI: 10.1016/j.psychires.2009.11.016 (2010) (Epub ahead of print).

•• ThefirstfMRIstudyinadultADHDthatincludedonlymedication-naivepatientswhowerefollowedupfromaconfirmedchildhoodADHDdiagnosis.Thepatientsshowedreducedactivationandfunctionalconnectivityinfronto–striato–parietalnetworksduringtasksofinhibitorycontrol.



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58 Pliszka SR, Glahn DC, Semrud-Clikeman M et al. Neuroimaging of inhibitory control areas in children with attention deficit hyperactivity disorder who were treatment naive or in long-term treatment. Am. J. Psychiatry 163(6), 1052–1060 (2006).

59 Christakou A, Halari R, Smith AB, Ifkovits E, Brammer M, Rubia K. Sex-dependent age modulation of frontostriatal and temporo–parietal activation during cognitive control. Neuroimage 48(1), 223–236 (2009).

60 Biederman J, Mick E, Faraone SV et al. Influence of gender on attention deficit hyperactivity disorder in children referred to a psychiatric clinic. Am. J. Psychiatry 159(1), 36–42 (2002).

61 Gershon J. A meta-analytic review of gender differences in ADHD. J. Atten. Disord. 5(3), 143–154 (2002).

62 Mahone EM, Wodka EL. The neurobiological profile of girls with ADHD. Dev. Disabil. Res. Rev. 14(4), 276–284 (2008).

63 Valera EM, Brown A, Biederman J et al. Sex differences in the functional neuroanatomy of working memory in adults with ADHD. Am. J. Psychiatry 167(1), 86–94 (2009).

•• LargestfMRIstudyinadultADHDpublishedtodateandthefirsttoshowgender-specificbraindysfunctioninADHD,withintactbrainactivationinfemalesandsignificantlylargerreducedactivationinmalesthanfemaleswithADHDcomparedwithcontrolsandeachotherinfronto–temporal,temporal,striatalandoccipito–temporalregionsduringworkingmemory.

64 Derrfuss J, Brass M, Neumann J, von Cramon DY. Involvement of the inferior frontal junction in cognitive control: meta-analyses of switching and Stroop studies. Hum. Brain Mapp. 25, 22–34 (2005).

65 Laird AR, McMillan KM, Lancaster JL et al. A comparison of label-based review and ALE meta-analysis in the Stroop task. Hum. Brain Mapp. 25(1), 6–21 (2005).

66 Liu X, Banich MT, Jacobson BL, Tanabe JL. Common and distinct neural substrates of attentional control in an integrated Simon and spatial Stroop task as assessed by event-related fMRI. Neuroimage 22(3), 1097–1106 (2004).

67 Cabeza R, Nyberg L. Imaging cognition II: an empirical review of 275 PET and fMRI studies. J. Cogn. Neurosci. 12(1), 1–47 (2000).

68 Bush G, Frazier JA, Rauch SL et al. Anterior cingulate cortex dysfunction in attention-deficit/hyperactivity disorder revealed by fMRI and the Counting Stroop. Biol. Psychiatry 45(12), 1542–1552 (1999).

69 Cubillo A, Halari R, Giampietro V, Taylor E, Rubia K. Fronto–striatal hypo-activation during interference inhibition and attention allocation in a group of grown up children with ADHD with persistent hyperactive/inattentive behaviours in adulthood. J. Am. Acad. Child Adolsc. Psychiatry (2010) (In press).

70 Banich MT, Burgess GC, Depue BE et al. The neural basis of sustained and transient attentional control in young adults with ADHD. Neuropsychologia 47(14), 3095–3104 (2009).

71 Carter C, Braver TS, Barch DM, Botvinick MM, Noll D, Cohen JD. Anterior cingulate cortex, error detection and the on-line monitoring of performance. Science 280, 747–749 (1998).

72 Ridderinkhof KR, van den Wildenberg WPM, Segalowitz SJ, Carter CS. Neurocognitive mechanisms of cognitive control: the role of prefrontal cortex in action selection, response inhibition, performance monitoring, and reward-based learning. Brain Cogn. 56, 129–140 (2004).

73 Konrad K, Neufang S, Hanisch C, Fink GR, Herpertz-Dahlmann B. Dysfunctional attentional networks in children with attention deficit/hyperactivity disorder: evidence from an event-related functional magnetic resonance imaging study. Biol. Psychiatry 59(7), 643–651 (2006).

74 Vaidya CJ, Bunge SA, Dudukovic NM, Zalecki CA. Altered neural substrates of cognitive control in childhood ADHD: evidence from functional magnetic resonance imaging. Am. J. Psychiatry 162(9), 1605–1613 (2005).

75 Biederman J, Mick E, Faraone SV. Age-dependent decline of symptoms of attention deficit hyperactivity disorder: impact of remission definition and symptom type. Am. J. Psychiatry 157(5), 816–818 (2000).

76 Clark VP, Fannon S, Lai S, Benson R, Bauer L. Responses to rare visual target and distracter stimuli using event-related fMRI. J. Neurophysiol. 83(5), 3133–3139 (2000).

77 Downar J, Crawley AP, Mikulis DJ, Davis KD. A multimodal cortical network for the detection of changes in the sensory environment. Nat. Neurosci. 3(3), 277–283 (2000).

78 Ardekani BA, Choi SJ, Hossein-Zadeh GA et al. Functional magnetic resonance imaging of brain activity in the visual oddball task. Brain Res. Cogn. Brain Res. 14(3), 347–356 (2002).

79 Rubia K, Hyde Z, Halari R, Giampietro V. Effects of age and sex on developmental neural networks of visual-spatial attention allocation. Neuroimage DOI: 10.1016/j.neuroimage.2010.02.058 (2010) (In press).

80 Cubillo A, Halari R, Smith A, Taylor E, Rubia K. Fronto–cerebellar brain dysfunction in adults with childhood ADHD during sustained attention and reward Eur. Neuropsychopharmacol. 19(Suppl. 3), S303 (2009).

81 Voisin J, Bidet-Caulet A, Bertrand O, Fonlupt P. Listening in silence activates auditory areas: a functional magnetic resonance imaging study. J. Neurosci. 26(1), 273–278 (2006).

82 Lawrence NS, Ross TJ, Hoffmann R, Garavan H, Stein EA. Multiple neuronal networks mediate sustained attention. J. Cogn. Neurosci. 15(7) 1028–1038 (2003).

83 Smith AB, Taylor E, Brammer M, Rubia K. Neural correlates of switching set as measured in fast, event-related functional magnetic resonance imaging. Hum. Brain Mapp. 21(4), 247–256 (2004).

84 Buchsbaum BR, Greer S, Chang WL, Berman KF. Meta-analysis of neuroimaging studies of the Wisconsin card-sorting task and component processes. Hum. Brain Mapp. 25(1), 35–45 (2005).

85 Schweitzer J, Faber T, Grafton S, Tune L, Hoffman J, Kilts C. Alterations in the functional anatomy of working memory in adult attention deficit hyperactivity disorder. Am. J. Psychiatry 157(2), 278–280 (2000).

86 Schweitzer JB, Lee DO, Hanford RB et al. Effect of methylphenidate on executive functioning in adults with attention-deficit/hyperactivity disorder: normalization of behavior but not related brain activity. Biol. Psychiatry 56(8), 597–606 (2004).

87 Ehlis AC, Bahne CG, Jacob CP, Herrmann MJ, Fallgatter AJ. Reduced lateral prefrontal activation in adult patients with attention-deficit/hyperactivity disorder (ADHD) during a working memory task: a functional near-infrared spectroscopy (fNIRS) study. J. Psychiatr. Res. 42(13), 1060–1067 (2008).

88 Wolf RC, Plichta MM, Sambataro F et al. Regional brain activation changes and abnormal functional connectivity of the ventrolateral prefrontal cortex during

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working memory processing in adults with attention-deficit/hyperactivity disorder. Hum. Brain Mapp. 30(7), 2252–2266 (2009).

• FirstfMRIstudytestingfunctionalconnectivityinadultADHDfindingreducedinferiorfronto–parieto–cerebellarnetworks.

89 Hale TS, Bookheimer S, McGough JJ, Phillips JM, McCracken JT. Atypical brain activation during simple and complex levels of processing in adult ADHD: an fMRI study. J. Atten. Disord. 11(2), 125–139 (2007).

90 Marsh R, Gerber AJ, Peterson BS. Neuroimaging studies of normal brain development and their relevance for understanding childhood neuropsychiatric disorders. J. Am. Acad. Child Adolesc. Psychiatry 47(11), 1233–1251 (2008).

91 Valera EM, Faraone SV, Biederman J, Poldrack RA, Seidman LJ. Functional neuroanatomy of working memory in adults with attention-deficit/hyperactivity disorder. Biol. Psychiatry 57(5), 439–447 (2005).

92 Ernst M, Cohen RM, Liebenauer LL, Jons PH, Zametkin AJ. Cerebral glucose metabolism in adolescent girls with attention-deficit/hyperactivity disorder. J. Am. Acad. Child Adolesc. Psychiatry 36(10), 1399–1406 (1997).

93 Sheridan MA, Hinshaw S, D’Esposito M. Efficiency of the prefrontal cortex during working memory in attention-deficit/hyperactivity disorder. J. Am. Acad. Child Adolesc. Psychiatry 46(10), 1357–1366 (2007).

94 Scheres A, Milham MP, Knutson B, Castellanos FX. Ventral striatal hyporesponsiveness during reward anticipation in attention-deficit/hyperactivity disorder. Biol. Psychiatry 61(5), 720–724 (2007).

95 Lawrence NS, Jollant F, O’Daly O, Zelaya F, Phillips ML. Distinct roles of prefrontal cortical subregions in the Iowa Gambling Task. Cereb. Cortex 19(5), 1134–1143 (2009).

96 Ernst M, Kimes AS, London ED et al. Neural substrates of decision making in adults with attention deficit hyperactivity disorder. Am. J. Psychiatry 160(6), 1061–1070 (2003).

97 Knutson B, Fong GW, Adams CM, Varner JL, Hommer D. Dissociation of reward anticipation and outcome with event-related fMRI. Neuroreport 12(17), 3683–3687 (2001).

98 Knutson B, Cooper JC. Functional magnetic resonance imaging of reward prediction. Curr. Opin. Neurol. 18(4), 411–417 (2005).

99 Smith A, Halari R, Giampietro V, Brammer M, Rubia K. Developmental effects of reward on sustained attention networks. Hum. Brain Mapp. (2010) (In press).

100 Ströhle A, Stoy M, Wrase J et al. Reward anticipation and outcomes in adult males with attention-deficit/hyperactivity disorder. Neuroimage 39(3), 966–972 (2008).

• ExcludedcomorbiditywithotherdisordersandfoundreducedactivationinthenucleusaccumbensinadultADHDduringrewardanticipation.

101 Plichta MM, Vasic N, Wolf RC et al. Neural hyporesponsiveness and hyperresponsiveness during immediate and delayed reward processing in adult attention-deficit/hyperactivity disorder. Biol. Psychiatry 65(1), 7–14 (2009).

102 Ballard K, Knutson B. Dissociable neural representations of future reward magnitude and delay during temporal discounting. Neuroimage 45(1), 143–150 (2009).

103 Hariri AR, Brown SM, Williamson DE, Flory JD, de Wit H, Manuck SB. Preference for immediate over delayed rewards is associated with magnitude of ventral striatal activity. J. Neurosci. 26(51), 13213–13217 (2006).

104 Xu L, Liang ZY, Wang K, Li S, Jiang T. Neural mechanism of intertemporal choice: from discounting future gains to future losses. Brain Res. 1261, 65–74 (2009).

105 Wittmann M, Leland DS, Paulus MP. Time and decision making: differential contribution of the posterior insular cortex and the striatum during a delay discounting task. Exp. Brain Res. 179(4), 643–653 (2007).

106 Blair RJ. The roles of orbital frontal cortex in the modulation of antisocial behavior. Brain Cogn. 55(1), 198–208 (2004).

107 Hill J, Harrington R, Fudge H, Rutter M, Pickles A. Adult personality functioning assessment (APFA). An investigator-based standardised interview. Br. J. Psychiatry 155, 24–35 (1989).

108 Kriegeskorte N, Simmons WK, Bellgowan PS, Baker CI. Circular analysis in systems neuroscience: the dangers of double dipping. Nat. Neurosci. 12(5), 535–540 (2009).

109 Cao QJ, Zang YF, Sun L et al. Abnormal neural activity in children with attention deficit hyperactivity disorder: a resting-state functional magnetic resonance imaging study. Neuroreport 17(10), 1033–1036 (2006).

110 Zang YF, He Y, Zhu CZ et al. Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI. Brain Dev. 29(2), 83–91 (2007).

111 Tian L, Jiang T, Wang Y et al. Altered resting-state functional connectivity patterns of anterior cingulate cortex in adolescents with attention deficit hyperactivity disorder. Neurosci. Lett. 400(1–2), 39–43 (2006).

112 Castellanos FX, Margulies DS, Kelly C et al. Cingulate-precuneus interactions: a new locus of dysfunction in adult attention-deficit/hyperactivity disorder. Biol. Psychiatry 63(3), 332–337 (2008).

• FirststudytestingforfunctionalconnectivitydeficitsinADHDadultsduringtherestingstate,findingreducedinter-regionalconnectivitybetweentheanteriorandposteriorcingulate.

113 Rubia K, Halari R, Cubillo A, Mohammad M, Taylor E. 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(7–8), 640–652 (2009).

114 Arnsten AFT. Stimulants: therapeutic actions in ADHD. Neuropsychopharmacology 31(11), 2376–2383 (2006).

115 Wilens TE. Effects of methylphenidate on the catecholaminergic system in attention-deficit/hyperactivity disorder. J. Clin. Psychopharmacol. 28(3 Suppl. 2), S46–S53 (2008).

116 Vaidya CJ, Austin G, Kirkorian G et al. Selective effects of methylphenidate in attention deficit hyperactivity disorder: a functional magnetic resonance study. Proc. Natl Acad. Sci. USA 95(24), 14494–14499 (1998).

117 Shafritz KM, Marchione KE, Gore JC, Shaywitz SE, Shaywitz BA. The effects of methylphenidate on neural systems of attention in attention deficit hyperactivity disorder. Am. J. Psychiatry 161(11), 1990–1997 (2004).

118 Kobel M, Bechtel N, Weber P et al. Effects of methylphenidate on working memory functioning in children with attention deficit/hyperactivity disorder. Eur. J. Paediatr. Neurol. 13(6), 516–523 (2008).

119 Konrad K, Neufang S, Fink GR, Herpertz-Dahlmann B. Long-term effects of methylphenidate on neural networks associated with executive attention in



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children with ADHD: results from a longitudinal functional MRI study. J. Am. Acad. Child Adolesc. Psychiatry 46, 1633–1641 (2007).

120 Bush G, Spencer TJ, Holmes J et al. Functional magnetic resonance imaging of methylphenidate and placebo in attention-deficit/hyperactivity disorder during the multi-source interference task. Arch. Gen. Psychiatry 65(1), 102–114 (2008).

•• FirstfMRIstudytestingforeffectsofchronicmedicationinadultADHDinalargesampleandcontrollingforcomorbidities.Thestudyfoundupregulationwithmethylphenidateindisorder-typicaldysfunctionregionsoffrontal,cingulate,striatalandparieto–cerebellarcortices.

121 Castellanos FX, Lee PP, Sharp W et al. Developmental trajectories of brain volume abnormalities in children and adolescents with attention-deficit/hyperactivity disorder. JAMA 288(14), 1740–1748 (2002).

122 Mackie S, Shaw P, Lenroot R et al. Cerebellar development and clinical outcome in attention deficit hyperactivity disorder. Am. J. Psychiatry 164(4), 647–655 (2007).

123 Shaw P, Gornick M, Lerch J et al. Polymorphisms of the dopamine D-4 receptor, clinical outcome, and cortical structure in attention-deficit/hyperactivity disorder. Arch. Gen. Psychiatry 64(8), 921–931 (2007).

124 Todd RD, Huang H, Henderson CA. Poor utility of the age of onset criterion for DSM-IV attention deficit/hyperactivity disorder: recommendations for DSM-V and ICD-11. J. Child Psychol. Psychiatry 49(9), 942–949 (2008).

125 Faraone SV, Biederman J, Spencer T et al. Diagnosing adult attention deficit hyperactivity disorder: are late onset and subthreshold diagnoses valid? Am. J. Psychiatry 163(10), 1720–1729; quiz 1859 (2006).

126 Mannuzza S, Klein RG, Klein DF, Bessler A, Shrout P. Accuracy of adult recall of childhood attention deficit hyperactivity disorder. Am. J. Psychiatry 159(11), 1882–1888 (2002).

127 McGough JJ, Smalley SL, McCracken JT et al. Psychiatric comorbidity in adult attention deficit hyperactivity disorder: findings from multiplex families. Am. J. Psychiatry 162(9), 1621–1627 (2005).

128 Miller TW, Nigg JT, Faraone SV. Axis I and II comorbidity in adults with ADHD. J. Abnorm. Psychol. 116(3), 519–528 (2007).

129 Jensen PS, Martin D, Cantwell DP. Comorbidity in ADHD: implications for research, practice, and DSM-V. J. Am. Acad. Child Adolesc. Psychiatry 36(8), 1065–1079 (1997).

130 Shaw P, Sharp WS, Morrison M et al. Psychostimulant treatment and the developing cortex in attention deficit hyperactivity disorder. Am. J. Psychiatry 166(1), 58–63 (2009).

131 Schweitzer JB, Lee DO, Hanford RB et al. A positron emission tomography study of methylphenidate in adults with ADHD: alterations in resting blood flow and predicting treatment response. Neuropsychopharmacology 28(5), 967–973 (2003).

132 Durston S, Fossella JA, Casey BJ et al. Differential effects of DRD4 and DAT1 genotype on fronto–striatal gray matter volumes in a sample of subjects with attention deficit hyperactivity disorder, their unaffected siblings, and controls. Mol. Psychiatry 10(7), 678–685 (2005).

133 Durston S, Fossella JA, Mulder MJ et al. Dopamine transporter genotype conveys familial risk of attention-deficit/hyperactivity disorder through striatal activation. J. Am. Acad. Child Adolesc. Psychiatry 47(1), 61–67 (2008).

134 Ecker C, Rocha-Rego V, Johnston P et al. Investigating the predictive value of whole-brain structural MR scans in autism: a pattern classification approach. Neuroimage 49(1), 44–56 (2010).

135 Fu CH, Mourao-Miranda J, Costafreda SG et al. Pattern classification of sad facial processing: toward the development of neurobiological markers in depression. Biol. Psychiatry 63(7), 656–662 (2008).

136 Marquand A, Howard M, Brammer M, Chu C, Coen S, Mourao-Miranda J. Quantitative prediction of subjective pain intensity from whole-brain fMRI data using Gaussian processes. Neuroimage 49(3), 2178–2189 (2010).

137 Davatzikos C, Shen D, Gur RC et al. Whole-brain morphometric study of schizophrenia revealing a spatially complex set of focal abnormalities. Arch. Gen. Psychiatry 62(11), 1218–1227 (2005).

Affiliations• Ana Cubillo

Department of Child Psychiatry/SGDP, P046, Institute of Psychiatry, 16 De Crespigny Park, London, SE5 8AF, UK Tel.: +44 207 848 0873 Fax: +44 207 208 5800 [email protected]

• Katya Rubia Department of Child Psychiatry/SGDP, P046, Institute of Psychiatry, 16 De Crespigny Park, London, SE5 8AF, UK Tel.: +44 207 848 0463 Fax: +44 207 208 5800 [email protected]

Cubillo & Rubia

Structural and functional brain imaging in adult attention-deficit/hyperactivity disorder

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