One source of morbidity in ADHD has been attributed to deficits in the capacity to accurately and consistently process and act on temporal information, namely deficits in timing abilities. Such a capacity is critical to personal safety and to successful management of everyday activities such as social interactions, driving and performing cognitive tasks. It has also been argued that abnormalities in timing functions are fundamental to impulsiveness (3), a core feature of ADHD.

Observational and experimental data on ADHD support the hypothesis that individuals with ADHD have widespread timing deficits. For example, some impulsive behavior in ADHD individuals could indicate an inability to adjust to environmental timing demands. Also, difficulties arriving at appointments on time, poor planning and tendencies to forgo delayed larger rewards for smaller immediate rewards (4) could suggest an altered sense of time. Experimental data of ADHD youth have shown either less accurate or more variable performance than matched controls on a number of timing tasks including paced finger tapping (5), duration reproduction (6-8), duration discrimination (9), verbal time estimation (10), and temporal anticipation (5, for review see 11). In fact, one of the most consistent findings in ADHD youth is increased within-subject variability on a range of tasks (as reviewed in 12-13), indicating an inability to register responses at evenly-timed intervals. This variability has been shown to be related to attentional ratings and to decrease in response to methylphenidate (5,14). Thus, an increased understanding of this variability, as well as timing more generally, has potential implications for treatment of and understanding core features of ADHD.

Although most support for timing deficits have been shown in ADHD youth, abnormalities in time estimation, discrimination and reproduction have been shown in ADHD adults (7, 15). However, these data are limited, and restricted to the supra-second level.

In healthy adults, brain regions most commonly associated with timing processes are the frontal cortex, basal ganglia (BG), and cerebellum (16-18), with support for differential functional localization of timing involving short versus long time intervals. Timing of supra-second intervals, as used in the previous adult ADHD studies, is thought to occur in BG and frontal cortex regions with task-related neural activity often being attributed to attention and working memory demands (11,19-21). Timing of sub-second intervals is associated with the cerebellum which has been described as a millisecond-range timekeeper or the “internal clock” (19, 20). Despite these general distinctions, there is also evidence of BG and frontal involvement in sub-second timing as well as cerebellar involvement in supra-second timing (for reviews see 20,22-23).

Interestingly, although numerous brain regions have shown structural or functional neuroimaging abnormalities in ADHD, some of the most consistent findings have been in areas associated with timing including frontal, BG and cerebellar regions (24-30). There have been no studies using fMRI to examine timing functions in ADHD adults. However, Rubia and colleagues (31-32) showed that ADHD adolescents had less activation than controls in cingulate regions during 5s-interval synchronized tapping, although no differences were observed with a 600ms interval. Smith et al. (33) found less activation in several frontal regions for ADHD adolescents relative to controls during performance on a duration discrimination task. Also, ADHD youth showed less cerebellar activation than controls while performing a temporal expectancy task (34).

The neural signature of ADHD has been conceptualized in terms of abnormalities in networks of response inhibition (35), attention (36) and reward (37), among others. However, despite demonstrating behavioral impairments across a range of timing-related functions, the idea that the neural underpinnings of ADHD result from abnormalities in timing networks is not a common model. The goal of this study was to elucidate the neural substrates of sensorimotor timing in ADHD using a simple timing task to test the hypothesis that abnormalities in timing networks contribute to the pathophysiology of ADHD.

The behavioral findings are notable in several ways. First, these data show that motor timing abnormalities (e.g., increased within-subject variability), previously observed in ADHD youth (57) can also be observed in ADHD adults. There have been no previous studies examining either tapping or sub-second time intervals in ADHD adults. Thus, this study extends what we know about timing irregularities in this population. Future studies designed to examine whether ADHD adults with high vs. low within-subject variability systematically differ in neural activity would be informative.

Second, the behavioral data show that, on average, ADHD adults have greater tapping variability than controls. Most interestingly, using a temporal variance decomposition method (41) we show for the first time that this variability is related to variability of the central clock rather than motor implementation. Given the ubiquitous nature of the higher performance variability for ADHD individuals, knowing more about the mechanism of this atypical variability is an important issue. Our data provide support for abnormalities in timing mechanisms rather than abnormalities in movement execution.

This result is consistent with conclusions drawn by Rommelse and colleagues (58) who had ADHD and control children conduct tapping tasks with and without a pacing stimulus. They found that ADHD children showed abnormal speed and variability for paced tapping, but typical performance while tapping as quickly as they could at their own rate. Rommelse et al. (58) interpreted this result as reflecting timing rather than motor function differences.

Neuroimaging results show that ADHD adults have abnormal patterns of activation while performing the tapping task. As predicted, ADHD adults showed relatively less activity than controls in frontal, cerebellar and BG regions. More specifically, regions of relative hypoactivity were observed in primary motor and premotor (IFG and MFG) frontal areas, and the cerebellum (culmen and declive lobules IV-VI and dentate nuclei), as well as the caudate and putamen.

Failure of the ADHD adults to activate frontal and cerebellar regions to the same degree as controls could indicate difficulties in engaging fronto-cerebellar circuits critical for optimal task performance. For example, lobules IV-VI in the right cerebellar hemisphere and the left primary motor cortex (BA 4) comprise nodes of a network associated with motor timing (16,59-60). Strick and colleagues (for review see 61) have shown that there are multiple cortico-cerebellar loops, one of which includes reciprocal projections between the motor cortex and cerebellar hemispheres IV-VI. These data suggest a fronto-cerebellar substrate for timing processes engaged for movement control (16, 60-62). It is possible that difficulties in optimally engaging this network could contribute to the relatively greater within-subject variability of the ADHD adults over controls while performing this task.

The BG and IFG have been noted to be key timing areas (63-64), shown to be active in tapping tasks similar to those used here (55) and also in paradigms for which motor confounds have been controlled (22, 65). The BG, in particular the putamen, have been shown to be preferentially involved in internally generated movements (66). The IFG may involve the internal timing of movements perhaps via subvocalization of the tones (55). Failure to activate the BG and IFG as strongly as controls may make it more difficult for the ADHD adults to internally generate movements at the appropriate rate.

Our neuroimaging findings contrast with the results of Rubia and colleagues (5,31) who reported no differences between ADHD and control youth for sub-second timing synchronization and differences in cingulate regions for a supra-second timing. However, these experiments differ from ours in that they were conducted with adolescents, relied on smaller samples (7 ADHD, 9 controls), and used a visual pacing stimulus. That we did not find between-group differences in cingulate regions could also result from our use of a sub-, rather than supra-, second timing pacing task. There is an abundance of evidence for differential functional neuroanatomy for sub- vs. supra-second timing. Our results show more consistency with the findings of Durston et al. (34) and Smith et al. (33) who found less activation in ADHD youth relative to controls in cerebellar and frontal regions (including the IFG) during time expectancy violations and duration discrimination tasks respectively. Notably, these studies were conducted with youth in contrast to our study using adults. Additional research is needed for all age groups to gain converging evidence on the neural substrates of timing in ADHD.

Functional abnormalities for non-timing-related tasks in the IFG and BG in ADHD samples have been well established (26,28). Also, our finding of decreased activation in the motor cortex is consistent with data of Mostofsky and colleagues (67) who found a smaller extent of activation in the motor cortex for ADHD children relative to controls during performance of a self-paced sequential finger tapping task.

In addition to predicted regions of abnormality during tapping task performance, ADHD adults showed less activation compared to controls in several other regions commonly associated with sensorimotor timing. The insula has been shown to be involved in sensorimotor synchronization (56,68). In conjunction with the IFG, the insula has been proposed to facilitate timing via subvocal rehearsal of the target interval and through multi-modal integration (69). Less activation for the ADHD adults relative to the controls in the IFG and insula could reflect more difficulty for the ADHD adults in integrating their internal rehearsal of the tones with the motor response.

The inferior parietal lobe's (IPL) involvement in time perception is well established (22,70-71). One hypothesized role for the IPL involves its making covert shifts of attention to temporal stimuli (72). Thus, abnormalities in this region could contribute to more difficulties shifting and maintaining attention to the tones.

The role of the STG in timing appears to vary depending on the location within the STG. Coull and colleagues (63) proposed an anterior-posterior timing gradient in the STG such that areas at ~y = −20 are linked with automatic motor timing, such as paced tapping to an auditory tone (55,73), and posterior regions are implicated in cognitive perceptual timing (74-75) showing activation in the absence of auditory cues (22). In our data, the location where the ADHD adults showed less activation than controls, ~y = −50, is consistent with the area that has been shown to be active during perceptual duration discrimination tasks. Thus, the failure of the ADHD adults to engage this region could contribute to difficulties perceiving the precise timing of the tones and subsequently maintaining the proper timing of the taps.

While performing the tapping task, ADHD adults consistently demonstrated less activation than the controls suggesting that the ADHD adults are not sufficiently recruiting regions associated with sensorimotor timing. Notably, the lack of activation differences between the ADHD adults and controls on the listen task and lack of differences in areas of the auditory cortex associated with hearing tones (~y = −20 in the STG) for the paced task, indicates that the hypoactivity relative to the controls was not a nonspecific global reduction, but rather more specific to the demands of the temporally demanding tapping task.

In all, abnormal neural activity was demonstrated in our predicted brain regions commonly associated with both ADHD and timing (frontal cortex, BG, cerebellum), as well as other regions often involved in timing (e.g., insula, IPL, STG). These data support our hypothesis that abnormalities in timing networks contribute to the pathophysiology of ADHD and may represent a core dysfunction of the disorder. The kinds of temporal processing deficits observed here are in keeping with the consistently reported increased within-subject response time variability in ADHD (12-13). We hypothesize that suboptimal engagement of this timing network (which overlaps with a cerebellar-prefrontal-striatal network long hypothesized to be abnormal in ADHD; 76) represents a core neurofunctional abnormality and contributes to basic timing impairments as well as possibly other behavioral features of ADHD (e.g., delay aversion, inability to wait one's turn). As such, testing hypotheses that these and other relevant behavioral manifestations of ADHD reflect abnormalities in timing-related neural networks should further our understanding of the disorder.

Finally, there were no relationships between ADHD symptoms and behavioral or imaging data for the unpaced tapping task. This suggests that this timing abnormality is not associated with number of ADHD symptoms and supports a hypothesis that timing abnormalities are core features of ADHD independently of inattentive and hyperactive symptoms. However, it could also be that other symptom measures which we did not use or perhaps a more precise measure of symptom severity (rather than symptom number) would have shown a relationship. Future studies designed to address such questions using dimensional ADHD rating scales could be revealing.

Our study and its conclusions need to be considered in light of methodological limitations. First, ADHD individuals have been shown to have abnormalities in both fine and gross motor abilities (77). The atypical activity associated with our tapping task could be associated with either timing or movement implementation problems rather than timing per se, or could be a result of the combination of the two. Our paradigm does not allow us to definitively resolve this question. However, analyses with the Wing and Kristofferson model (41), which show differences in clock, but not motor, variance, suggest a timing explanation for our results. Also, the lack of any between-group differences for the paced vs. listen group by task interaction (see the Supplement) suggests that ADHD and control adults do not differ in movement-related activation. Additionally, many of the regions showing atypical activation in the ADHD adults are consistent with results of a recent meta-analysis of timing which included a range of timing tasks that accounted for motor processes (18). Still, future studies which employ other timing paradigms without movement would be helpful in addressing this question. Second, some of our ADHD participants did not meet the symptom threshold at the time of scan. However, it is common for adults to fall below symptom threshold (54). If anything we would expect this to diminish the strength of ADHD vs. control effects rather than create spurious effects. Third, although matched, the mean IQ of our groups was higher than “average” and it is unclear how well these results would generalize to ADHD adults with average mean IQs. Additionally, although group-matched on sex, both males and females were included in our sample and it is possible that between-group differences may not be the same for males and females. Future studies should employ larger groups balanced by sex to address potential sex differences. ADHD subjects who were taking psychostimulants underwent a 24-hour wash-out period. However, it is still possible that long- or short-term effects of psychostimulants could have affected our results. If this were the case, we would expect potential effects of psychostimulants to diminish our between-group effects (78). Finally, employing a parametric characterization of the tapping task or supra-second timing would be useful in evaluating the effects of timing load and/or time scale on neural abnormalities in ADHD adults and should be used in future studies.