The current study examined a well-characterized sample of adults with ADHD from an ongoing longitudinal study that did not include individuals with comorbid conditions. As such, the observed differences in brain activation between individuals with ADHD and controls are unlikely to be due to factors that may be related to inaccurate retrospective assessment of ADHD symptoms or due to disorders that are often comorbid with ADHD. Consistent with the hypothesis that dysfunction of the frontal lobes is present in individuals with ADHD and consistent with functional neuroimaging studies that have investigated the neural correlates of response inhibition in ADHD children (Dickstein et al., 2006
; Rubia et al., 2008
; Suskauer et al., 2008
; Passarotti et al., 2010
), our study suggests that ADHD adults display less activation than controls during inhibition of a prepotent motor response.
Participants in our two experimental group were observed to activate a predominantly right-lateralized frontoparietal network of brain regions during the correct performance of “No-Go” trials. Regions identified through contrast of “No-Go” trials with implicit task baseline included areas that have been previously associated with inhibitory control such as the right IFG and medial prefrontal cortex (pre-SMA) as well as other areas that have frequently been observed to be co-activated during the correct performance of “No-Go” trials including premotor cortex (FEF), right anterior insula, and the bilateral inferior parietal lobes (Garavan et al., 2006
; Simmonds et al., 2008
). Although inferior occipital and left precuneus regions were also identified as being activated at our originally selected thresholds, post hoc Monte Carlo permutation procedures suggested that we could not reject the possibility that these clusters could have been identified as being active by chance ().
In a meta-analysis of event-related functional neuroimaging studies that compared the neural correlates of “simple” and “complex” versions of the Go/No-Go task, Simmonds and colleagues (2008)
proposed that contrast of “No-Go” trials against implicit task baseline and use of a “complex” version of the Go/No-Go task identical to the one used in the present study likely elicits brain activation associated with response inhibition amongst other cognitive abilities including selective attention, stimulus recognition, working memory (i.e.
, updating of stimulus-response associations), and response selection, including selecting not to respond. Consistent with their hypothesis, their results showed that in addition to brain regions thought to be critically involved in response inhibition, such as the pre-SMA, “complex” versions of the Go/No-Go task that involved additional cognitive task demands such as selective attention and updating of working memory were observed to elicit additional activation in a predominantly right-lateralized network including regions in the right middle/inferior frontal gyrus and bilateral inferior parietal regions. The authors interpreted this evidence to suggest that the neural basis of response inhibition may vary depending on task demands. This interpretation is consistent with the results of a prior study suggesting that the pre-SMA is recruited during the performance of “No-Go” trials regardless of whether a “simple” or “complex” versions of the Go/No-Go task are administered, but an additional frontoparietal network is recruited as working memory demands associated with the Go/No-Go task are added (Mostofsky et al., 2003
). This evidence suggests that the neural basis of response inhibition may be made up of a network of brain regions some of which play a critical role in supporting response inhibition and others that may be recruited to play a more auxiliary role depending on task demands. However, it is also possible that use of a “complex” version of the Go/No-Go task and contrast of “No-Go” related activity against implicit task baseline may reveal activation patterns that are associated with cognitive operations co-occuring with the performance of response inhibition tasks rather than with the cognitive operation of canceling a response itself.
Contrast of “Go” trials and “No-Go” trials may be one way to address this issue as it is conceivable that “Go”-related activation may be subtracted from “No-Go”-related activation in order to identify activation uniquely and therefore specifically associated with response inhibition. However, as was discussed in the introduction, contrast of “Go” trials and “No-Go” trials may also fail to identify areas that make critical contributions to the performance of both trial types. The results of our own analysis suggested that direct contrast of activation associated with “Go” and “No-Go” trials produced null findings (), suggesting that several areas that contributed to “No-Go” trials also contributed to “Go” trials, a hypothesis that our follow-up MS/CN conjunction analyses supported (). Furthermore, areas of the pre-SMA and the right IFG were also identified among the set of regions that were commonly recruited during “Go” and “No-Go” trials, consistent with the idea that areas that may be critically involved in response inhibition may be recruited during the performance of both trial types. Although the results of our conjunction analysis could also be interpreted to suggest that areas recruited during both trial types are not uniquely related response inhibition and are therefore not specifically related to response inhibition, we find this interpretation to be less likely for two reasons: 1) as mentioned above, recent work has identified a critical role for the pre-SMA and the right IFG in response inhibition; and 2) the results of our follow-up fROI analyses suggested that areas of the pre-SMA that were commonly recruited during both trial types were differentially activated by our ADHD and control groups depending on whether they were performing “Go” or “No-Go” trials. More specifically, our control group demonstrated greater mean activation of this region than our ADHD group only while correctly performing “No-Go” trials () suggesting that this region is specifically involved in response inhibition despite its recruitment during “Go” and “No-Go” trials.
Although we cannot rule out the possibility that activation described by the contrast of “No-Go” related activation and implicit task baseline may be associated with co-occuring cognitive processes including but not limited to selective attention, updating of working memory, task switching, response selection (including selecting not to respond), and performance monitoring, several studies have suggested that brain regions associated with these cognitive operations may make significant contributions to the performance of response inhibition tasks (for reviews see Garavan et al., 2006
; Chambers et al., 2009
). If this were confirmed, brain regions identified by the contrast of “No-Go” related activation with implicit task baseline may in fact describe a network of brain regions associated with response inhibition. Within the context of this literature, our results are most consistent with the view that contrast of “No-Go” related activation with implicit task baseline using a “complex” version of the “No-Go” task reveals a network of brain regions some of which are critically involved in response inhibition and others which may play a more auxiliary role depending on additional task demands.
There were no areas within the network of brain regions defined by this contrast in which our group of adults with ADHD exhibited greater activation than controls or demonstrated activation outside of this network. As we predicted, areas in which a significant reduction in activation was observed included the pre-SMA, a functionally-defined sub-region of medial prefrontal cortex that is considered to be a critical node within the network of brain regions associated with inhibitory control (Floden and Stuss, 2006
; Picton et al., 2007
; Chen et al., 2009
). Additional reductions in activation were also observed in a premotor area (right FEF), the left precentral gyrus (motor cortex), and in the inferior parietal lobes bilaterally.
Our findings are supported by the results of the study by Cubillo and colleagues (2010)
another study that examined the neural correlates of response inhibition in a prospectively defined sample of adults with verifiable symptoms of ADHD in childhood and adulthood. Examining a sample of 11 ADHD adults and 14 age-matched controls, the authors reported that their group of adults with ADHD exhibited less activation than controls during the performance of “Stop” trials of a Stop Signal task. Significant reductions in activation were observed in the right caudate, thalamus, and putamen as well as bilateral premotor, bilateral inferior frontal/anterior insula, and medial prefrontal brain regions including the anterior cingulate and the SMA. Our study also found evidence that adults with ADHD exhibited less activation than controls in premotor and medial prefrontal cortex during inhibition of a prepotent motor response. Furthermore, similar findings were observed between the two studies despite differences in sample exclusion criteria as the previous study did not exclude participants with conditions that were commonly comorbid with ADHD. Nevertheless, there were some inconsistencies between the two studies as our study did not confirm that adults with ADHD exhibit less activation than controls in the inferior frontal gyrus and subcortical brain regions, and the previous study did not report that adults with ADHD display less activation than controls in the pre-SMA, the left precentral gyrus, the left precuneus, and the inferior parietal lobe bilaterally.
There are several possible explanations that may account for the inconsistent findings. For one, Cubillo and colleagues contrasted successful “Stop” trials against successful “Go” trials rather than contrasting “Stop” trials against implicit task baseline. As was reviewed earlier, contrast of “Stop” and “Go” trials may succeed in revealing brain regions that are uniquely related to inhibitory control, but may also fail to reveal any brain region that makes equivalent contributions to the performance of both trial types including regions that may make critical contributions to inhibitory control such as the pre-SMA. For example, because the pre-SMA has been implicated in processes related to both response selection and response inhibition (for review see Mostofsky and Simmonds, 2008
), it is possible that these investigators did not find activation differences that were located in the pre-SMA due to the similar recruitment of this brain region during both trial types.
Another possibility that may account for the inconsistent findings between the present study and that of Cubillo and colleagues (2010)
may be related to the possibility that the Stop Signal and the Go/No-Go tasks may measure different aspects of response inhibition. Some authors have proposed that this explanation can potentially account for differences in the neural correlates of these two tasks (Rubia et al., 2001
; Aron and Poldrack, 2006
; Zheng et al., 2008
). The Go/No-Go task has been described as a measure of response inhibition (Chambers et al., 2009
), but unlike the Stop Signal task, the cognitive abilities involved in successful performance of this task may not be limited to cancellation of an already initiated motor response (Aron and Poldrack, 2006
). Whereas the Stop Signal task may measure processes related to the “cancellation” of an already initiated motor response, the Go/No-Go task may place a greater demand on “restraint” during stimulus presentation (Schachar et al., 2007
). Thus, ADHD-associated dysfunction of brain regions during inhibition of a motor response may vary depending on the point in time when the motor plan is countermanded. Thus, the results of our study may describe ADHD-associated dysfunction in a fronto-parietal network of brain regions that may be present during inhibition of a prepotent cognitive bias while Cubillo and colleagues' study may describe ADHD-related dysfunction in a fronto-striatal network of brain regions evident during cancellation of an already initiated motor response. Future studies may consider evaluating differences in the time course of neural processes related to response inhibition in samples of adults with ADHD more explicitly.
Cubillo and colleagues (2010)
also found evidence of differences in activation between adult ADHD and control participants that were located in the right IFG. We also expected to find activation differences located in this brain region. Although our group of healthy control participants exhibited activation in pars opercularis
of the right IFG, a region of the brain thought to be critically related to inhibitory control (Aron et al., 2003
), we observed no statistical difference between ADHD and controls in this brain region. Another previous study also administered a Go/No-Go task to a group of adults with ADHD (ADHD, n
= 9; Controls, n
= 9) also found evidence of reduced activation in the IFG during the performance of “No-Go” trials (Epstein et al., 2007
). However, that study also did not exclude individuals with common comorbidities, calling into question whether their findings were specifically associated with ADHD. It is possible that reduced activation of the right IFG may not account for deficits in inhibition in adults with ADHD. This possibility would also be consistent with recent fMRI studies that have challenged the notion that the right IFG directly controls response inhibition and favor attributing this role to the pre-SMA (Duann et al., 2009
; Sharp et al., 2010
Consistent with our hypotheses and with the results of fMRI studies of ADHD children (Tamm et al., 2004
; Rubia et al., 2008
; Suskauer et al., 2008
), our group of adults with ADHD was observed to display reduced activation during the correct performance of “No-Go” trials in a medial prefrontal region located rostral to the SMA known as the pre-SMA (Picard and Strick, 2001
). Several authors have suggested that the pre-SMA may play a critical role during successful response inhibition by maintaining stimulus-response associations used to select a response (or the inhibition of a response) (Floden and Stuss, 2006
; Picton et al., 2007
; Mostofsky and Simmonds, 2008
; Simmonds et al., 2008
; Chambers et al., 2009
; Chen et al., 2009
). This interpretation would be consistent with the results of a study that used a variation of the Go/No-Go task used in the present study to investigate whether activation patterns associated with response conflict could be dissociated from activation patterns associated with error processing (Garavan et al., 2003
). The study attempted to vary the level of response conflict present during inhibition of a prepotent response through administration of different stimulus presentation rates that elicited “fast” and “slow” responding while activation patterns associated with both of these conditions were examined separately in association with correct and incorrect trials. The results of that study suggested that an area of the anterior cingulate cortex (ACC) showed significant responses to errors of commission, but was not sensitive to the task's changing conflict demands whereas an area of the pre-SMA was sensitive to response conflict but not to errors of commission. Taken together, this evidence suggests that the pre-SMA is sensitive to manipulations that may disrupt the maintenance of stimulus-response associations within the context of performing a task requiring response selection or inhibition. By contrast, the ACC may be more important for monitoring of performance. It is unlikely that our observed results within the pre-SMA may be ascribed to differences in the neural correlates of error monitoring as we examined activation associated with correct trials only. This may explain why contrast of activation associated with correct “No-Go” trials with implicit task baseline did not reveal activation in the ACC. As we were unable to examine error-related activation within the context of this study due to an insufficient number of trials, it remains possible that adult ADHD and control participants demonstrate differential activation in the ACC during error processing, a hypothesis that should be explored in future studies.
A recent paired-pulse transcutaneous stimulation study demonstrated that the pre-SMA modulates activity in motor cortex in the presence of cognitive conflict but this is not observed when the same actions are performed in the absence of conflict (Mars et al., 2009
). This raises the possibility that our group of adults with ADHD displayed less activation than controls in left precentral gyrus (motor cortex) during inhibition trials due to underactivation of the pre-SMA. Future studies might test this hypothesis using effective connectivity methods.
Our ADHD group also displayed reduced activation in the parietal lobes and the right FEF bilaterally consistent with structural neuroimaging evidence indicating that the inferior parietal lobe may be underdeveloped in adults with ADHD (Makris et al., 2007
) and with functional neuroimaging evidence suggesting that adults with ADHD demonstrate reduced activation in premotor cortex during the performance of inhibitory control tasks (Cubillo et al., 2010
). Activation of the parietal lobes has been reliably observed during the performance of response inhibition tasks, but magnetic stimulation of this region does not result in worse performance on the Stop-Signal task (Chambers et al., 2006
). This suggests that the right inferior parietal lobe may not be critically related to successful response inhibition or that this brain region may not be related to the act of inhibiting an already initiated motor response. It is possible that recruitment of right inferior parietal lobe during inhibition trials may reflect a phasic increase in a more general attentional process (Garavan et al., 1999
) that may co-occur with inhibition of a prepotent cognitive bias such as during sustained attention (Fassbender et al., 2004
) or triggering shifts of attention (Corbetta and Shulman, 2002
). Alternatively, the bilateral inferior parietal lobes may be necessary for maintenance of items in working memory during the performance of response inhibition tasks (Hester et al., 2004a
). The FEF is important for volitional eye saccade movements (Pierrot-Deseilligny et al., 2004
). As such, this brain region may play an important role in support of stimulus recognition during the performance of a manual version of the Go/No-Go task not involving inhibition of eye movements. By contrast, left parietal cortex has been implicated in response selection (Bunge et al., 2002
), an important component process that may contribute to more deliberative aspects of response inhibition (Garavan et al., 2002
). Within the context of this literature our results suggest that adults with ADHD may demonstrate reduced activation in brain regions that support higher order attentional, working memory, and response selection processes that contribute to inhibition of a prepotent cognitive bias.
Our behavioral finding that adults with ADHD did not perform significantly worse than controls on “No-Go” trials (10% worse) was unexpected. Post-hoc analyses suggested that the association between ADHD and response inhibition was moderate (d
= -0.53), consistent with results of a meta-analysis including 17 studies and nearly 1200 children (d
= 0.58) (Lijffijt et al., 2005
). This power analysis suggested that in order to detect a group difference in behavioral performance for response inhibition with 0.80 power (α=0.05), 57 participants per group would be necessary. Since significant differences in brain activation were nonetheless observed in six brain regions, these results are consistent with the view that functional neuroimaging methods may be more sensitive than behavioral measures in the detection of brain disorders. However, an undetected difference in accuracy of “Go” trial performance was not likely since ADHD and control participants performed very similarly on these trials (94% ±3% vs. 94% ±3%). This suggests that potential differences between the ADHD and control groups with regard to performance of “No-Go” trials were not likely to be due to primary ADHD deficits in working memory or attention.
Limitations to our study deserve consideration. As was mentioned earlier, it is possible that our choice to contrast activation associated with “No-Go” trials against an implicit task baseline may have revealed areas of activation that were not specifically related to response inhibition. As such, these brain regions may have been associated with cognitive operations co-occuring with the performance of response inhibition tasks rather than with response inhibition itself (Type I error). Although we acknowledge this possibility, we chose to perform this contrast in order to avoid exclusion of brain regions that may make significant contributions to both “Go” and “No-Go” trials (Type II error). Furthermore, the results of our conjunction and follow-up fROI analyses suggested that some of the brain regions that were recruited during both trial types may be specifically and critically implicated in inhibitory control. Finally, we cannot reject the possibility that brain regions that are associated with cognitive processes co-occuring with response inhibition are not part of the network associated with inhibitory control although they may not be critical nodes within this network.
Our exclusion criteria to eliminate common comorbidities likely limited our sample. As such, our low sample size may have limited our power to detect behavioral differences under the “No-Go” condition. However, if this were the case, then it is likely that the five previous fMRI studies that attempted to examine the neural correlates of response inhibition in adults with ADHD may have been similarly underpowered as the sample sizes in these studies ranged between 9 and 17 participants per group. In fact, not one of the five studies reported that they observed a significant difference between ADHD and control participants with regard to accuracy of performance during inhibition trials while studies with higher sample sizes reportedly found significant differences (Bekker et al., 2005
; O'Connell et al., 2009
). In the event that our study was underpowered to detect behavioral differences in performance of this task, the differences in activation that were observed between ADHD and control participants could be attributable to differential task difficulty rather than to dysfunction of brain regions (Price and Friston, 1999
). We attempted to address this problem by modeling activation of correct trials only. Future studies should attempt to replicate our findings using higher sample sizes.
All of our ADHD participants were clinically referred during childhood and had a previous history of stimulant medication. A recent study suggested that chronic exposure to stimulant medication may have an effect on brain function in individuals with ADHD (Konrad et al., 2007
). Our study could not rule out the possibility that history of stimulant medication impacted upon on our findings, but it should be noted that history of treatment with stimulant medication may also be correlated with greater severity of ADHD symptoms (Barkley et al., 2003
). Future studies should attempt to repeat our procedures with a medication naive group.
In sum, our results suggest that adults with ADHD demonstrate less activation than matched controls within a fronto-parietal network of brain regions that has been previously associated with inhibition of a prepotent cognitive bias. Areas in which reduced activation was observed include premotor, medial prefrontal, and inferior parietal brain regions. As each of these brain regions may play a different role within the execution of response inhibition, it is possible that adults with ADHD have more difficulty with the component abilities that contribute to successful response inhibition, namely working memory, goal-oriented attention, and selection of a motor response. Considering that individuals with common comorbid conditions were excluded, the profile of reduced activation demonstrated may be specifically associated with persistent symptoms of adult ADHD. Future studies should determine whether this pattern of reduced activation varies with task demands or if it can be used for the purpose of diagnosis.