Attention Deficit Hyperactivity Disorder

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that is typically first diagnosed in childhood, but symptoms often persist into adolescence (DSM-IV-TR; APA, 2000). Current working models of ADHD suggest that it is best characterized as a disorder of executive function (Barkley, 1997a,b; 1998). Certainly, individuals with ADHD have demonstrated poorer performance on tasks involving inhibitory control (Schachar, Mota, Logan, Tannock, & Klim, 2000) and working memory, set shifting, and planning (Pennington & Ozonoff, 1996) relative to normal controls (e.g., reviewed by Barkley, 1997a, b; Pennington & Ozonoff, 1996; Tannock, 2003). However, these differences are not always observed consistently and are not unique to ADHD, as such deficits are often observed in other clinical samples (Pennington & Ozonoff, 1996; Sergeant, Geurts, & Oosterlaan, 2002).

Cognitive studies of ADHD have implicated time perception, which refers to the perceived length of a time interval, as a potentially important cognitive deficit in ADHD (Barkley, 1997b, 1998; Barkley, Edwards, Laneri, Fletcher, & Metevia, 2001a; Barkley, Koplowitz, Anderson, & McMurray, 1997; Barkley, Murphy, & Bush, 2001b; Kerns, McInerney, & Wilde, 2001; Rubia et al., 1999a, 2001; Rubia, Noorloos, Smith, Gunning, & Sergeant, 2003; Rubia, Taylor, Taylor & Sergeant, 1999b; Smith, Taylor, Warner Rogers, Newman, & Rubia, 2002; Sonuga-Barke, Saxton, & Hall, 1998; Toplak, Rucklidge, Hetherington, John, & Tannock, 2003; West et al., 2000). The contention that time perception (also described as time estimation in this literature) is impaired in individuals with ADHD has emerged from the idea that time perception is an executive function (Barkley, 1997b). However, cognitive models of time perception implicate mechanisms other than frontal executive functions, such as cerebellar timing mechanisms (Ivry & Fiez, 2000). The conceptualization and measurement of time perception becomes crucial, as there are very different implications of understanding time perception as another measure of executive function versus understanding time perception as an index of an internal timing mechanism driven by cerebellar processes. From the latter perspective, evidence of time perception impairments in ADHD would indicate the need to broaden the current conceptualization of ADHD as a disorder of executive function to include possible cerebellar or perceptual deficits.

Recent advances in the neuroscience of ADHD highlight the plausibility of time perception deficits in ADHD. This is because of findings that children and adolescents with ADHD have smaller cerebellar volumes than comparison controls (Castellanos et al., 2001). Converging evidence from the neuroscience literature indicates that the cerebellum may be involved in time perception (Ivry & Fiez, 2000; Ivry & Spencer, 2004). Both of these literatures are in their infancy, as it is still not clear what types of time perception are reliably impaired in ADHD, and what the role of the cerebellum has in timing functions (Ivry & Fiez, 2000). Clinically, there is also good reason to examine the construct of time perception further, as individuals with ADHD have been reported to have a poor sense of time. Parents will often report that their adolescents blurt out answers before it is their turn to respond, and they cannot seem to wait for their turn, suggesting that even brief spans of time "are like forever" to these adolescents. The purpose of the present research was to further examine time perception systematically in a sample of adolescents with and without ADHD.

Time Perception in ADHD

The focus of the present study was on the perception of time intervals rather than on production or reproduction. One important reason for selecting perception is because time perception tasks minimize the motor demands of timing performance, unlike interval production and reproduction tasks. The impact of motor demands is a critical variable in the study of ADHD, as motor difficulties also characterize individuals with ADHD (Carte, Nigg, & Hinshaw, 1996; Denckla & Rudel, 1978; Riordan et al., 1999). Moreover, duration discrimination is reportedly impaired in patients with cerebellar lesions relative to normal controls (Ivry & Keele, 1989). Also, neuroimaging studies of healthy controls have implicated cerebellar involvement in duration discrimination (Smith, Taylor, Lidzba, & Rubia, 2003).

Duration discrimination is the typical method used to measure time perception, and involves the comparison of two brief intervals similar in duration (such as, 500 ms vs, 600 ms) to determine which is the longest or shortest. This task has been administered in two ways in the ADHD literature, using either discrete trials (Smith et al., 2002) or psychophysical methods (Toplak et al., 2003). Accuracy is the typical dependent measure when discrete trials are used, while duration threshold is the dependent measure when psychophysical methods are used. In psychophysical methods, an adaptive procedure is used to determine a participants' duration threshold. The duration threshold represents the duration of the comparison interval (i.e., the duration threshold) at which the participant can reliably distinguish the comparison from the target interval with 80% accuracy. Psychophysical methods of time perception afford more precise measurement than discrete trials.

Collectively, studies thus far that have examined duration discrimination in ADHD have used very different methodologies and tasks, so that is it not possible to integrate findings across studies. Specifically, studies have used discrete trials or psychophysical methods, tasks presented in different modalities (auditory, visual, or both), across different duration intervals, (from 400 ms to 60 s), and across different levels of development (child, adolescent, and adult samples).

Across these different task versions, however, group differences on the time perception measures have been observed in the ADHD literature. Of the studies conducted thus far, three of the four studies have reported significant differences on duration discrimination (Rubia et al., 1999b, 2003; Smith et al., 2002; Toplak et al., 2003); specifically individuals with ADHD were less accurate in discriminating durations or had higher duration thresholds, meaning that participants needed a greater difference between comparison and target intervals to discriminate the item reliably. In this study, we used psychophysical methods to assess duration discrimination and we also developed parallel methods that varied in stimulus modality (auditory and visual) and duration of intervals (200 ms and 1000 ms) to determine whether modality and length of modality had differential effects on performance.

Modality

The effect of the modality of the stimulus is an important variable to examine more closely, both from the perspective of the time perception literature and the ADHD literature. In the time perception literature, it has been reported that auditorily defined intervals are experienced as longer than visually defined intervals (Sebel & Wilsoncroft, 1983) in a sample of adult males. Consistent with the cognitive literature, it has been argued that visual sensory memory is available for considerably less time than auditory sensory information (Ashcraft, 2002); specifically, visual sensory information is reportedly available for up to 0.5 s, while auditory sensory information is available for up to 4 s. This has been called the modality effect, referring to superior recall of the end of a list when an auditory mode of presentation is used as opposed to a visual mode (Ashcraft, 2002). It has also been reported that within-task variability tends to be larger in visual than in the auditory versions of a cued tapping task in a normative sample (Chen, Repp, & Patel, 2002).

Modality is also an important variable to consider based on the clinical literature. There has been some suggestion that ADHD is characterized by visual-spatial memory deficits (Barnett et al., 2001; Kempton et al., 1999; Martinussen, Hayden, Hogg-Johnson, & Tannock, 2005; Nigg, Blaskey, Huang-Pollock, & Rappley, 2002), while verbal auditory memory deficits characterize other disorders, such as reading disorder (Heim, Freeman, Eulitz, & Elbert, 2001). Therefore from a cognitive perspective, there may be important differences in the way that time intervals are perceived depending on the modality in which they are presented, and from a clinical perspective, modality may dissociate cognitive deficits in ADHD from other disorders, such as reading disorders.

Length of Interval/Duration

In the time perception literature using ADHD samples, a broad range of duration intervals have been used, ranging from 400 ms to 60 s. There is some question, however, whether the same or different processes are involved in perceiving this wide range of durations. Ivry (1996) has suggested that processing short intervals (less than 1 s) may be more related to an internal timing mechanism or cerebellar processes (Mangels, Ivry, & Shimizu, 1998), while longer intervals (1 s or greater) may be more related to working memory processes. The attentional-gate model is one model of time perception which predicts that when intervals exceed the range relevant for typical sensory events, then greater demands are placed on other cognitive functions, such as sustained attention and working memory (Mangels & Ivry, 2001). Others have also suggested that processing in the range of seconds is a function of working memory processes (Fortin & Couture, 2002; Lalonde & Hannequin, 1999; Rammsayer, Hennig, Haag, & Lange, 2001). Therefore, length of duration was examined systematically by using 200 and 1000 ms intervals to represent short and long durations.

We also included standardized measures of auditory-verbal and visual-spatial span and working memory to examine associations between time perception performance and working memory. Based on the attentional-gate model, we would expect to find associations between working memory and duration discrimination of intervals around 1000 ms. In a previous study, auditory-verbal memory span was found to be a significant predictor of duration discrimination threshold at the 400 ms target interval in the clinical sample (ADHD and ADHD with comorbid reading difficulties), but not in the control sample (Toplak et al., 2003). This result was interpreted as indicative of the need to draw on additional cognitive processes by individuals with ADHD. As this particular finding did not follow the predictions of the attentional-gate model, we were interested in exploring this notion further.

The Presence of Comorbid Reading Disorders (RD)

At least one study on time perception in ADHD has included participants with comorbid reading difficulties (Toplak et al., 2003), and most of the deficits observed were in the comorbid ADHD+RD group. The presence of reading disabilities may present a unique problem in attempts to understand time perception in ADHD. To date, there is an extensive literature on timing deficits in reading disabilities (Wolf, 1999; 2001), including duration discrimination deficits (Nicolson, Fawcett, & Dean, 1995). The hypothesized link between timing deficits and reading disorder has been termed the "cerebellar deficit hypothesis" (Nicolson, Fawcett, & Dean, 2001), as some research has suggested that reading disorder is associated with abnormal cerebellar activation and functioning (Nicolson, Daum, Schugens, Fawcett, & Schulz, 2002). Certainly one implication is the importance of testing or controlling for reading difficulties in studies of ADHD. For these reasons, we took into account the presence of reading disorders in this study.

We examined time perception performance on a set of duration discrimination tasks in adolescents with and without ADHD using psychophysical methods. We developed both visual and auditory analogs of this task so that we could systematically test the effect of modality. We examined two duration lengths to determine whether any group differences may be attributable to only shorter (200 ms), only longer (1000 ms) durations, or both short and long durations. The dependent measure on the duration discrimination task was duration threshold. We included two measures of memory span and working memory, one auditory-verbal and one visual-spatial, in order to investigate associations between duration discrimination and memory. In addition, we included a set of other standardized measures, including estimated full-scale IQ, reading and oral language ability, and behaviour ratings of ADHD symptomatology.

METHOD

Participants

Two groups of adolescents participated: 46 adolescents (87% male) with a confirmed clinical diagnosis of ADHD based on DSM-IV criteria and 44 comparison adolescents (45.5% male). All adolescents were between the ages of 13 years and 18 years (mean 15.5 years; SD = 1.4). Nineteen (39.6%) of the adolescents with ADHD were recruited from patients who were previously assessed in childhood and were re-diagnosed with ADHD. The remaining clinical participants were recruited through advertisements at pediatric offices as well as from new referrals to the Hospital for Sick Children. Adolescents in the control comparison group were recruited through hospital staff and community resources. All adolescents participating in the study were native English speakers.

ADHD Sample

All adolescents had a DSM-IV diagnosis of ADHD confirmed at the time of this study by a systematic and comprehensive clinical diagnostic assessment. The assessment comprised a semi-structured clinical diagnostic interview [Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version; K-SADS-PL] conducted separately with parents and adolescents by a PhD level clinical psychologist (MT) or a supervised Ph.D. Candidate in clinical psychology. Note that the information from the adolescent K-SADS-PL was used to obtain information about internalizing symptoms. The same interview was utilized consistently across interviewers. The K-SADS-PL has been used extensively to make diagnostic decisions based on DSM criteria and has been validated with children aged 6-17 (Kaufman, Birmaher, Brent, Rao, & Ryan, 1997). Also, parents, teachers, and adolescents completed the Conners' Rating Scales-Revised (Conners, 1997) to obtain standardized ratings of behaviour. Diagnosis of ADHD in adolescents was based on the following algorithm: (1) met DSM-IV criteria for ADHD according to the clinician summary based on the K-SADS-PL parent and adolescent interviews; (2) met the clinical cut-offs for the externalizing symptoms of ADHD on the Conners teacher questionnaires in order to ensure pervasiveness of symptoms across settings; (3) evidence of ADHD symptoms prior to the age of seven established either through a past diagnosis of ADHD or in new cases, according to parental report and school report cards; and (4) symptoms of ADHD accompanied by evidence of impairment. Adolescents were excluded if they had psychosis, pervasive developmental disorder, a serious medical condition, or an estimated IQ below 80 or a lack of evidence of childhood onset of ADHD. A proportion of the adolescents had comorbid disorders in addition to ADHD: 11 (24%) of the participants had a reading disorder, 5 (11%) had a math disorder, 13 (28%) had oppositional defiant disorder, 2 (4%) had conduct disorder, 3 (6%) had depression, and 4 (9%) had generalized anxiety disorder.

Fourteen of our participants used stimulant medication (30%), eight had previously used stimulant medication (17%), five used a non-stimulant medication (11%), and 20 had never used psychoactive medication (43%). All adolescents were asked to stop taking any medication 24 hr prior to the assessment, except for two participants who used antidepressants, but participants were otherwise medication free during testing.

Comparison Sample

Parents and adolescents confirmed on the Conners' questionnaire that the adolescent did not have any Axis I diagnosis other than a specific phobia, or any history or current complaints of problems in attention, behavior, mood disturbances, or learning. Adolescents in the comparison sample were also excluded if they had psychosis, pervasive developmental disorder, a serious medical condition or an estimated IQ below 80. Initially, the KSADS-PL was given to all participants in the comparison sample, but was discontinued after the first 21 participants as the instrument did not serve a diagnostic purpose. However, if any concerns were raised on the Conners' questionnaires, a complete K-SADS-PL interview was done to rule out any of these difficulties. A total of four K-SADS-PL were conducted to follow up on issues raised on the Conners' questionnaires in the comparison control group.

Standardized Measures

Additional components of the adolescent assessment included measures of intellectual ability, accuracy and efficiency of single-word reading and reading-related skills, math computational ability, and oral language ability. The Wechsler Abbreviated Scale of Intelligence (WASI; Wechsler, 1999), which comprised four subtests (Vocabulary, Block Design, Similarities, and Matrices), was used to provide an estimate of intellectual ability. The reading measures included the Reading subtest from the Wide Range Achievement Test-3 (WRAT-3; Wilkinson, 1993), the Elision and Blending subtests from the Comprehensive Test of Phonological Processing (CTOPP; Wagner, Torgesen, & Rashotte, 1999), and the Test of Word Reading Efficiency (TOWRE; Torgesen, Wagner, & Rashotte, 1999). Math ability was assessed with the Arithmetic subtest from the WRAT-3. Oral language ability was assessed with the Recalling Sentences subtest from the Clinical Evaluation of Language Fundamentals--3rd Edition (CELF-3; Semel, Wiig, & Secord, 1995), and the Nonword Repetition subtest from the CTOPP, as nonword repetition is believed to be a marker of generic forms of language impairment (Briscoe, Bishop, & Norbury, 2001).

Group Differences on Standardized Measures

Table I displays the diagnostic characteristics of the ADHD and comparison groups of adolescents. Overall, as might be expected, the individuals with ADHD exhibited lower scores compared to controls on virtually all of the standardized measures, including intellectual ability, memory span and working memory, reading, language, math, and higher scores on the behavioral features of ADHD. Notably, all the scores were within the average range.

Presence of Reading Disorders

Approximately 24% (n = 11) of the adolescents with ADHD had a comorbid reading disorder. A definition of low achievement in both single-word reading and reading efficiency were used to classify reading disabilities, as both accuracy and fluency of single word decoding are important markers of reading problems in adolescents (Lovett & Barron, 2003; Pennington, Cardosa-Martins, Green, & Lefly, 2001). Reading disorders were identified by a standard score below the 25th percentile (SS 90) on the reading subtest of the WRAT-3 and on the Test of Word Reading Efficiency (TOWRE).

Experimental Tasks

Duration Discrimination Tasks

Based on the methodology of the auditory duration discrimination task used by Hetherington, Dennis, and Spiegler (2000) and by Toplak et al. (2003), four novel versions of this task were developed; these included visual and auditory tasks that both used two interval lengths (200 and 1000 ms). The 200 ms interval was chosen to represent those processes that are believed to be linked to an internal timing mechanism, and the 1000 ms interval was chosen to represent processes that may be associated with memory functions (Ivry, 1996).

Two control tasks (size and frequency discrimination) were included to test for more general deficits in perceptual processing that could confound the interpretation of performance on the duration discrimination tasks. For the visual control task, size of stimuli was used as the perceptual feature, and for the auditory control task, frequency of tone was used. In the visual control task, participants were presented with two squares (target square was 100 X 100 pixels, and the comparison square was smaller or larger) on the computer screen, and they were asked to determine which of the two squares was larger. In the auditory control task, participants were presented with two tones (target tone was 3000 Hz, and comparison tone was always higher) generated by the computer, and they were asked to determine which of the two tones sounded higher. Unfilled intervals were used to minimize any confound from the ongoing processing of stimuli that may occur when filled intervals are used (Ivry, 1996). Thus, in the auditory version of the duration discrimination task, participants were presented with two intervals defined by 50 ms, 1000 Hz boundary tones at the beginning and end of each interval, and separated by an inter-stimulus interval (ISI) of 500 ms. In the visual version of the duration discrimination task, participants were presented with two intervals defined by 50 ms, visual image of a 100 X 100 pixel square at the beginning and end of each interval, also separated by an ISI of 500 ms. The target interval refers to the consistently presented stimulus (either 200 or 1000 ms), while the comparison interval refers to the interval that was adapted to participants performance. The target interval (200 or 1000 ms) was randomly presented as the first or second duration. For the 200 ms target version, increments of the target duration changed by 5 ms (the first comparison duration was 230 ms), and for the 1000 ms target version, increments changed by 25 ms (the first comparison duration was 1200 ms). The comparison intervals and increment parameters were interpolated from those used by Hetherington et al. (2000). The inter-trial interval was 1000 ms.

An up-down-transformed-response (UDTR) adaptive procedure (Wetherill & Levitt, 1965) was used to estimate the threshold at which the participant could accurately discriminate the target duration from the comparison duration with 80% accuracy. The procedure stopped after six reversals of direction (see Wetherill & Levitt, 1965). The last five reversal values were averaged to produce the estimate of threshold duration discrimination. The primary dependent measure for the discrimination tasks was the participant's duration threshold minus the target interval. The threshold was defined as the difference between the target duration and the shortest comparison which participants could reliably discriminate with 80% accuracy.

These tasks were all programmed using Presentation software for a Pentium PC computer. All tasks were presented in similar 2-alternative forced choice trials using the mouse for response input. There were four practice trials for each task to help participants understand the task demands. The practice trials utilized 1000 ms as the target duration and 500 ms as the comparison duration. Longer comparison durations during the practice trials were used in order to help ease the participant into the task. Participants were told that they would hear two sets of beeps (or see two pairs of squares for the visual tasks), and that each set would be separated by a short space or gap, and that one gap would be longer than the other. Furthermore, they were told that their task was to decide which of the two gaps was the longest and to press the corresponding button on the mouse (that is, left button if it was the first set or right button if it was the second set). On-screen cues in the form of numbered boxes mapping the tones in each trial on to the left-right mouse buttons were always available to provide a guide for participant responses. Response buttons and on-screen cues would flash the color orange to register the participants' responses. No feedback about errors was provided during the task.

The order of presentation of these six tasks was counterbalanced across participants to control for order effects. Participants used their dominant hand for responding. After each task, participants were asked if they used any strategies to do the task. We coded for any reported use of counting strategies on the four duration discrimination tasks; the dependent measure was coded as strategy use or no strategy use.

Memory Span and Working Memory Tasks

We used two different tasks to measure memory performance, one auditory-verbal and one visual-spatial. Our measure of auditory-working memory was the Digit Span subtest from the Wechsler Intelligence Scale for Children--Third Edition (WISC-III; Wechsler, 1991) and the Wechsler Adult Intelligence Scale--Third Edition (WAIS-III; Wechsler, 1997). Our measure of visual-spatial memory was the Spatial Span subtest from the WISC-III Processing Instrument (WISC-III-PI, Kaplan, Fein, Kramer, Delis, & Morris, 1999). Each task included one measure of memory span (the ability to maintain information) and one measure of working memory (ability to maintain and manipulate the information at the same time). The measure of auditory-verbal span was the Digit Forwards subtest and the measure of auditory-verbal working memory was the Digits Backwards subtest, both of which comprise the Digit Span subtest. The measure of visual-spatial span was the Spatial Span Forwards subtest and the measure of visual-spatial working memory was the Spatial Span Backwards subtest, both of which comprise the Spatial Span subtest. We also constructed two composite scores (auditory-verbal and visual-spatial) by combining the scaled scores for the span and working memory scores. Standard scores for the span and working memory components of each measure were derived from the WISC-III-PI norms, as these norms are not provided for auditory-verbal span and working memory tests in the WISC-III or WAIS-III.

Statistical Analysis

Outliers

Some individuals displayed extreme performance on individual tasks but were within a normal range on others. Based on Tabachnick and Fidell (1989), each deviant score was changed to equal the next highest score in the distribution, plus one unit. This procedure was applied to the duration discrimination tasks, but there were no outliers on the memory tasks. Six scores for the control participants had to be adjusted, and seven scores for the ADHD participants had to be adjusted.

Gender

As the gender ratio in the ADHD and control groups was unequal, we conducted t-tests on all of the standardized and experimental time perception measures to determine whether the male and female ADHD and control adolescents differed in any important ways from each other. Consistent with previous research, there were no significant differences on duration discrimination or the standardized measures between males and females in either group (Rucklidge & Tannock, 2001). Thus results are presented collapsed across gender groups.

Data Analysis and Statistical Methods

We created composite measures for reading and oral language ability. Performance on the four reading measures was significantly intercorrelated within both the ADHD and control samples, with correlations ranging from .45 to .80. Correlations between the two language measures were .30 (ADHD sample) and .53 (control sample). Our composites were created by standardizing (z-score) the raw score of each subtest, and averaging the respective reading (Elision and Blending, CTOPP; TOWRE; Reading subtest, WRAT-3) and language measures (Recalling Sentences, CELF-3; Nonword Repetition, CTOPP), creating separate composites for reading and oral language.

In order to examine all of our variables of interest on the duration discrimination task, including group, duration, and modality, we conducted a repeated measures Multivariate Analysis of Variance (MANOVA), with group as a between-subjects factor and duration and modality as within-subjects factors. Effect sizes, using Cohen's d (Cohen, 1992), were also calculated for the duration discrimination tasks. Following the MANOVA, correlational analyses were conducted to examine whether any of the standardized measures (including memory span and working memory) and the behaviour ratings were significantly correlated with the duration discrimination thresholds. Then, we conducted regression analyses to determine whether span or working memory, reading or oral language ability, or severity of behaviour symptoms of ADHD predicted duration discrimination threshold.

RESULTS

Duration Discrimination: Effects of Group, Duration, and Modality

Table II displays the mean threshold (that is, participants' mean threshold minus target duration) and standard deviation in the two groups. There was a significant group effect, indicating that the adolescents with ADHD displayed significantly higher thresholds than controls on all of the duration discrimination tasks, F(1, 85) = 16.72, p = .0001. As shown in Table II, the effect sizes were moderate to large.

Participants were also asked about strategy use, and only the reported use of counting strategies was included in this analysis. Data on strategy use were only available for 72 of the 90 participants, and chi-square analyses were used to compare reported strategy use in the two groups. There were no group differences that reached significance in the counting strategies reported.

We obtained a significant effect of duration, F(1, 85) = 242.15, p = .001, indicating that duration thresholds were higher at the longer duration than at the shorter duration across both modalities. The significant duration effect across both modalities indicates that larger intervals were required to successfully discriminate longer durations, indicating that our manipulation of duration worked properly. There was no significant effect of modality.

There was a significant duration by group interaction, F(1, 85) = 11.41, p = .001, and a significant modality by group interaction, F(1, 85) = 5.47, p = .022, indicating that the effects of group and modality differentially varied by group status. There was also a significant three-way interaction, F(1, 85) = 4.08, p = .046, indicating that both the modality and duration experimental manipulations differentially affected group performance. In order to facilitate interpretation of the three-way interaction, Fig. 1 displays the means and standard errors in a visual format.

We proceeded to analyze the three-way interaction instead of the two two-way interactions to understand the combined effects of modality and duration on group status. Within-subjects post hoc contrasts indicated that the significant differences emerged with the 1000 ms interval, F(1, 85) = 5.17, p = 0.025, and in the visual modality, F(1, 85) = 11.44, p = 0.001. This pattern in the visual 1000 ms duration discrimination task can be observed in Fig. 1, and is consistent with the effect size calculations.

Controlling for Estimated Full-Scale IQ

We performed the same analysis, examining estimated full-scale IQ as a covariate of performance. All of the significant effects were maintained, and estimated full-scale IQ did not enter as a significant covariate. Effect sizes were re-calculated with the adjusted means after IQ was entered into the analysis, and these effect sizes are displayed in Table II. Overall, the effect sizes were slightly lower, but the small to moderate effect sizes were maintained on the duration discrimination tasks, particularly on the visual tasks.

Control Tasks

To examine group differences on the visual and auditory threshold measures of the control tasks, two separate one-way ANOVAs were conducted. These means and standard deviations are also presented in Table II. No significant group differences were observed on discrimination thresholds for the visual or auditory control tasks. Effect sizes were small to moderate on the control tasks. The lack of group differences obtained on the control tasks suggest that group differences on the duration discrimination tasks are not attributable to general perceptual skills (e.g., size or tone discrimination), or problems with the response demands (forced choice), but to time perception difficulties. In addition, we re-examined duration discrimination performance by entering the visual and auditory control tasks as covariates of performance. Both the visual, F(1, 83) = 18.19, p = .0001, and the auditory, F(1, 83) = 19.71, p = .0001, control tasks entered as significant covariates. All of the significant effects were maintained, except the three-way interaction, which became marginally significant, F(1, 83) = 3.0, p = .087.

[FIGURE 1 OMITTED]

We also examined whether estimated full-scale IQ was a significant covariate of performance on the control tasks. Estimated full-scale IQ did not enter as a significant covariate on the visual control task, but did on the auditory control task, F(1, 87) = 13.81, p = .0001. The lack of group differences were maintained even after IQ was entered as a covariate. Effect sizes were re-calculated with the adjusted means, and a small effect size was maintained on the visual control task (shown in Table II).

Reading Ability

Recognizing the potentially important contribution of reading ability in our experimental measures, we conducted a preliminary comparison of performance between our adolescents who only met criteria for ADHD and adolescents who met criteria for ADHD and a reading disorder. These two groups did not differ on any of the experimental time perception measures. There were, as would be expected, differences on auditory span memory, reading ability, and language ability.

ADHD Subtype

As 46% of our ADHD sample met criteria for the Inattentive subtype, and 54% met criteria for the Combined subtype, we compared duration discrimination performance in these groups. Overall, no differences between subtype were obtained on the duration discrimination and control tasks. This was not unexpected given that both of these groups had clinically significant inattention symptoms, which previous research has shown to be associated with cognitive difficulties (Chhabildas, Pennington, & Willcutt, 2001).

Correlational Analyses

Correlations Between Duration Discrimination and Standardized Measures

We performed correlational analyses in order to specifically investigate relationships between the duration discrimination threshold and memory (memory span and working memory). However, we also conducted analyses between duration threshold and other clinical measures, including, reading and language ability, and severity of behaviour symptoms. These correlations were performed separately in the ADHD and control samples, as our previous work has indicated that cognitive and behavioural variables may be associated differently in clinical and control samples (see Toplak et al., 2003). These correlations are displayed in Table III.

Few associations were obtained with age, estimated full-scale IQ, reading and language ability, and the behaviour ratings, which was unexpected. Two of the three associations obtained with the behaviour ratings were obtained in the control sample, perhaps because there was a wider range of scores from parent and teacher reports in the control sample, whereas ratings tended to be clinically elevated and therefore reflecting ceiling scores in the ADHD sample. The most striking pattern was the relationships between measures of memory and duration threshold. Notably, duration threshold for the visual tasks was related to auditory-verbal and visual-spatial memory in the ADHD group but not in the control group. In order to understand this pattern of associations further, we performed regression analyses with the duration discrimination tasks.

We also conducted these same correlations with the entire sample for comparison. The main differences from the separate group correlations were that estimated full-scale IQ was significantly negatively correlated with the visual 1000 ms and auditory 200 ms thresholds. Also, there were more significant associations obtained between duration discrimination performance and parent and teacher behaviour ratings, likely due to the wider range of the scales in the behaviour ratings within the full sample.

Correlations Between the Duration Discrimination Tasks

We also examined correlations among the duration discrimination and control tasks separately in the ADHD and control samples. There was no interpretable pattern among the duration discrimination and control tasks, however there was an obvious difference in the number of significant associations in the ADHD and control samples. Of the 15 possible associations, five significant positive associations were obtained within the control sample, and 11 significant positive associations were obtained within the ADHD sample. Importantly, these tasks were completely analogous in task design, and in response demands.

Regression Analyses

Based on the correlational analyses, simultaneous multiple regression analyses were performed separately with the ADHD and control samples to determine which of the variables correlated with duration threshold actually enter as significant predictors of performance. Regression analyses were conducted separately for each group because of the differential pattern of correlations reported in Table III. Our strategy was to enter those variables as predictors which correlated significantly with duration threshold. The results of these regression analyses are displayed in Table IV.

With the visual 200 ms duration threshold as the criterion variable, only age entered as a significant predictor of duration threshold in the ADHD sample, and in fact, age explained 10% of the unique variance. We performed the same regression analysis in the control sample, but the analysis did not reach significance.

Then visual 1000 ms duration threshold was examined as the criterion variable. As both span and working memory were both correlated with threshold for both the visual and auditory memory tasks in the ADHD group, we entered the composite auditory and visual-spatial memory measures into the regression. Only the visual-spatial memory composite entered as a significant predictor, explaining 14% of the unique variance. When the analysis was re-done in the ADHD sample entering visual-spatial span and working memory separately, only visual-spatial span entered as a significant predictor, explaining a larger component of the unique variance (8%) than visual-spatial working memory (2%). When the same analysis was performed in the control sample, the regression analysis did not reach significance.

None of the variables that were entered in the correlational analysis were significantly associated with the auditory 200 ms duration discrimination threshold in the ADHD sample. Only auditory working memory was a significant predictor of threshold in the control sample, predicting 9% of the unique variance.

The significant predictors of auditory duration threshold at the 1000 ms interval were examined in both the ADHD and control samples. In the ADHD sample, only the visual-spatial memory composite entered as a significant predictor in the regression analysis, explaining 20% of the unique variance. A second regression was performed to examine whether visual-spatial span or working memory were separable predictors in the ADHD sample, but both entered as significant predictors. In the control sample, both auditory working memory and parent reported inattention entered as significant predictors, explaining 22% and 16% of the unique variance.

DISCUSSION

In the present study, we examined the performance of adolescents with ADHD and comparison controls on a set of time perception tasks, specifically duration discrimination tasks. We systematically examined modality and length of duration. On the duration discrimination tasks, there was a significant effect of duration, indicating that both groups of adolescents exhibited larger thresholds in the longer, 1000 ms interval, than in the shorter, 200 ms interval. In contrast to previous research, there was no significant effect of modality. No significant group differences were observed on the control tasks, but significant group differences were observed on all of the duration discrimination tasks. The largest effect size (0.85) was found on the visual duration discrimination task at the 1000 ms interval. When estimated full-scale IQ was co-varied in these analyses, effect sizes were slightly reduced. We conducted correlational analyses to examine associations between duration discrimination, reading and oral language ability, and the behaviour ratings within each of our ADHD and control groups. We found a different pattern of associations between the duration discrimination tasks and the memory measures in the ADHD and control samples. Specifically, visual-spatial memory was significantly associated with visual and auditory duration threshold at the 1000 ms interval in the ADHD sample, and auditory memory was significantly associated with auditory duration threshold at the longer 1000 ms interval in the control sample. Neither reading nor language was associated with duration threshold.

ADHD and Time Perception

Based on previous findings, we had expected to find group differences on the duration discrimination tasks. Previous work has demonstrated that children and adolescents with ADHD display deficits in duration discrimination (Rubia et al., 2003; Smith et al., 2002; Toplak et al., 2003). Our main interest was to determine whether we would observe differences in duration discrimination performance across different modalities and across different durations. The literature has been mixed, and our within-subject design permitted us to put this question to a more rigorous test. Indeed, we observed group differences across short and long durations, and across visual and auditory modalities. That we obtained group differences in duration discrimination is consistent with previously reported time perception deficits in visual (Rubia et al., 2003; Smith et al., 2002) and auditory (Toplak et al., 2003) modalities. However, what is most notable is that we observed group differences in both the short (200 ms) and long (1000 ms) durations. Most of the literature in ADHD has focused on durations greater than 1 s. That individuals with ADHD displayed deficits on the short durations challenges current conceptualizations of ADHD; in particular, these group differences at short durations suggest the presence of deficits in basic internal timing mechanisms (Ivry, 1996).

The largest group difference was in the visual modality at the longer duration of 1000 ms. This difference is consistent with other work that has suggested visual-spatial based deficits in ADHD, such as working memory (Barnett et al., 2001; Kempton et al., 1999; Martinussen et al., 2005; Nigg et al., 2002). Importantly, there were no significant group differences on the control perceptual tasks, which indicates that group differences on the time perception tasks do not simply reflect general perceptual problems nor are they attributable to problems with the response demands of the tasks. Although the group effect on the visual control task did not reach significance, the moderate effect size alerts one to the possibility of considering visual processing deficits in ADHD. Controlling for estimated full-scale IQ did not alter the overall pattern of findings. It was not unexpected that general intelligence would alter the results somewhat, as the co-occurrence of ADHD and lower IQ has genetic origins (Kuntsi et al., 2004). Given the fairly substantive literature on timing deficits in reading disorder, the lack of associations with reading and language ability suggest that the group differences obtained in the present investigation are not attributable to reading or language ability.

Time Perception and Memory

One of our questions of interest was whether time perception performance would be associated with other cognitive functions, such as memory span and working memory. In particular, it has been reported that processing durations longer than 1 s may invoke more complex cognitive mechanisms, such as working memory. Toplak et al. (2003) reported that auditory span or maintenance memory (Digits Forwards) was a significant predictor of auditory duration discrimination at the 400 ms target in their clinical (ADHD, ADHD+RD) sample, but no such association was obtained in the control sample. It seems paradoxical that memory would have been associated with duration discrimination performance at 400 ms, as with such a short duration it would seem unlikely to invoke memory resources. However, it was suggested that the requirement to make a comparison and judgment may have invoked memory resources in the clinical groups, but not in the control group. In the current study, a wider range of durations were examined in duration discrimination across modalities to examine whether there would be any dissociations based on length of duration and modality.

In the current study, some interesting associations between duration discrimination and memory emerged. Specifically, in the correlational analyses, there were fewer significant associations between the 200 ms, short-interval duration discrimination tasks and the memory measures than between the 1000 ms, longer interval duration discrimination tasks and the memory measures, occurring most consistently in the ADHD sample. In the regression analyses, visual-spatial memory (particularly span) was a significant predictor of visual duration discrimination at the 1000 ms interval in the ADHD sample, and visual-spatial memory was also a significant predictor of performance in the auditory 1000 ms duration discrimination task in the ADHD sample. By contrast, auditory-verbal working memory was a significant predictor of auditory duration discrimination for both short and long intervals in the control sample. The regression analyses are fairly consistent with the attentional-gate model, that longer durations invoke other cognitive processes, such as working memory (Fortin & Couture, 2002; Lalonde & Hannequin, 1999; Mangels & Ivry, 2001; Rammsayer et al., 2001).

What is also novel in this study is the pattern of associations obtained in the ADHD and control samples. That visual-spatial span was a significant predictor of visual duration discrimination performance at the 1000 ms interval in the ADHD, but not in the control group, suggests that participants with ADHD activate different processes because they may need to recruit additional resources on some cognitive tasks that are not necessary for control participants. Then, our dissociation in predictors of auditory duration discrimination at the 1000 ms interval (visual-spatial memory in the ADHD group and auditory-verbal working memory in the control group), adds an additional conceptualization of understanding cognitive performance in participants with ADHD. Specifically, not only is it likely that individuals with ADHD need to recruit additional cognitive resources, but they may also recruit different resources than controls on the same task. These results therefore suggest that inefficiencies in basic processing, like duration discrimination, may have cascading effects on other cognitive mechanisms, resulting in a general inefficiency in the system and giving rise to the deficits we observe in ADHD. If this is the case, then these findings are consistent with some recent functional magnetic resonance imaging research that has reported that children with ADHD do not activate frontostriatal regions in the same manner as normally developing children, but rather rely on a more diffuse network of regions (Durston et al., 2003). This pattern has also been reported in samples of adults with ADHD (Schweitzer et al., 2003). One of the key questions is whether the pattern of associations and dissociations we observed are specific to the mechanisms of timing and memory that were examined in the present study, or whether these patterns reflect only a sample of the types of inefficiency that occur in the cognitive processes in individuals with ADHD. This line of work needs further examination.

Implications for Neuroimaging Research

Based on the current findings, one important question that emerges is whether time perception, as measured in this study, is related specifically to basic timing or to other functions, such as working memory. Although adolescents with ADHD were consistently worse in duration discrimination, the largest difference seemed to occur in the visual modality at the longer 1000 ms interval. Some research has reported cerebellar activation with visual tasks (Penhune, Zatorre, & Evans, 1998; Schubotz, Friederici, & von Cramon, 2000), and duration discrimination tasks have been found to be sensitive to cerebellar dysfunction (Hetherington et al., 2000; Ivry, 1997; Ivry & Keele, 1989). While the cerebellum has traditionally been viewed as the key part of the motor system, recent investigations have implicated the cerebellum in the internal control of timing (Casini & Ivry, 1999; Ivry, 1996; Ivry & Fiez, 2000; Mangels, Ivry, & Shimizu, 1998). We also know that, based on the largest prospective, longitudinal neuroimaging study to date of children and adolescents with ADHD, Castellanos et al. (2001) reported that participants with ADHD had significantly smaller cerebral volumes and smaller cerebellar volumes than controls. While group differences were observed on all of the duration discrimination tasks, the largest effect size was at 1000 ms in the visual modality, and not the 200 ms duration. This raises questions about the extent of cerebellar involvement, as sensory events greater than 1 s have been hypothesized to place greater demands on frontal functions, such as working memory (Mangels & Ivry, 2001). In addition, the pattern of correlations between the discrimination tasks and the visual working memory tasks in the adolescents with ADHD suggest an important role for working memory in timing functions.

There have been speculations on the link between cerebellar and frontal processes. It has been hypothesized that the cerebellum has prerequisite connections for processes that occur in the prefrontal cortex (Ivry & Fiez, 2000). Three possible accounts of how frontal and neocerebellar regions interact have been described by Mangels, Ivry, and Shimizu (1998). One possibility is that the frontal and neocerebellar regions both assume timing functions, with the neocerebellar regions processing short durations and the frontal regions processing longer durations. A second possibility is that the prefrontal cortex may not be integrally involved in timing, but may support the maintenance, monitoring, and organization of temporal information. Recent evidence, however, has implicated the frontal lobe in timing functions (Smith et al., 2003). But this does not rule out the possibility that the primary role of the frontal regions may be to provide collective resources to support timing functions. Finally, an alternative possibility is that timing deficits may arise because of broader executive control deficits. Mangels et al. (1998) and Casini and Ivry (1999) concluded that the second possibility, that the prefrontal cortex manages resources for acquiring and maintaining temporal information, is most viable based on their study of frontal and cerebellar patients. Therefore, our interpretation of the pattern of associations and dissociations remain consistent with neuroscientific explanations that individuals with ADHD may need to recruit different and/or additional cognitive resources from the prefrontal cortex in order to maintain temporal representations.

Recent models of ADHD have argued that multiple neuropsychological pathways give rise to the heterogeneous presentation of ADHD (Castellanos & Tannock, 2002; Nigg, 2001; Sonuga-Barke, 2002). For example, Sonuga-Barke (2002) highlights the executive function and delay aversion contributions to ADHD, which is consistent with Nigg's (2001) distinction between executive inhibition and motivational inhibitory processes. At this time, it is unclear whether time perception interacts with both of these pathways, or whether time perception is specifically linked to executive processes, such as working memory. The results of the present study suggest a link between time perception and working memory executive processes. Castellanos and Tannock (2002) have suggested that temporal processing and working memory may be separable endophenotypes, however the results from the present study, in particular, the different pattern of associations among duration discrimination and memory in the ADHD and control samples, provide support for an integral relationship between these two endophenotypes in individuals with ADHD.

What is novel here is the behavioural data to suggest that there may be an important association between time perception and memory, consistent with a cerebellothalamo-prefrontal circuit dysfunction in ADHD (Berquin et al., 1998; Castellanos et al., 2001). There has been recent evidence to suggest that there are closed circuit connections between the cerebellum and frontal lobes in monkeys (Kelly & Strick, 2003). Disentangling the contributing roles of frontal and cerebellar processes will be difficult, and the current research implicates the important roles of each. We know that both reach maturity late, and both are activated in similar cognitive tasks, and this has been evidenced by close co-activation of the neocerebellum and dorsolateral prefrontal cortex in functional neuroimaging (Diamond, 2000). It will be difficult to disentangle the relative cerebellar and frontal contributions to performance in individuals with ADHD.

ADHD and Behaviour Ratings

At some point, these cognitive studies must be linked with the clinical phenomenon of ADHD. We observed some correlations between the Conners' behaviour rating scales and duration discrimination performance. In the regression analyses, only parent reported inattention was a significant predictor of auditory 1000 ms duration discrimination performance in the control sample. One difficulty in examining associations between behaviour ratings and cognitive performance separately in individuals with ADHD and controls is that the range in behaviour ratings in individuals with ADHD is a highly restricted range. Other studies have reported significant associations between behaviour and motor timing and tapping performance, likely when the entire sample was included in the same correlational analysis (Rubia et al., 1999b). When we examined correlations between the parent and teacher Conners scales and duration discrimination in the entire sample, 10 of the 16 correlations reached significance. Six of these correlations were associations with inattentive symptoms, and four were associations with hyperactive/impulsive symptoms. Therefore, when we examined these associations in the entire sample, our results indicate that higher thresholds in duration discrimination are associated with more severe symptoms of ADHD.

In conclusion, the current work supports the idea of time perception deficits in ADHD that is separable from reading and language ability. What is novel is the investigation of modality and length of duration in time perception and the differential pattern of associations with memory. This work remains consistent with the idea of executive function deficits in ADHD, and in addition, this work also implicates deficits in more basic, internal timing mechanisms and cerebellar processes. From this line of work, it is becoming more and more apparent that the phenotype we observe as ADHD is likely due to a distributed set of mechanisms, some frontal and some perhaps cerebellar, that interact in suboptimal ways. If this is the case, this possibility offers new ways to conceptualize treatment for ADHD: specifically, we may need to target a combination of areas to optimize cognitive performance in ADHD.

ACKNOWLEDGMENTS

This research was supported in part by research grants from the National Institute of Mental Health (Grant R21-MH066393), HSC Psychiatry Endowment Fund, and a Canadian Institutes of Health Research (CIHR) Fellowship granted to M. Toplak. We thank Rebecca Stewart for assistance with data collection and scoring, and Bilal Ahmed for programming the computer tasks. We also thank Dr. Umesh Jain and Ruth Barton at the Centre for Addiction and Mental Health (CAMH) for clinical support, Karen Ghelani for assistance with interviewing, and Colleen Dockstader for suggestions on the manuscript.

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Maggie E. Toplak (1) and Rosemary Tannock (1,2)

Received February 19, 2004; revision received June 4, 2004; accepted July 4, 2004

(1) Brain and Behaviour Research Program, Research Institute of The Hospital for Sick Children, Ontario, Canada.

(2) Address all correspondence to Dr. Rosemary Tannock, Brain & Behaviour Research Program, The Hospital for Sick Children, 555 University Avenue, Toronto, Ontario, Canada M5G 1X8; e-mail: rosemary.tannock@sickkids.on.ca.

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