Temporal processing impairment in children with attention-deficit-hyperactivity disorder

Research in Developmental Disabilities 33 (2012) 538–548

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Research in Developmental Disabilities

Temporal processing impairment in children with attention-deficit-hyperactivity disorder

Jia Huang a,1, Bin-rang Yang b,1, Xiao-bing Zou c, Jin Jing d, Gang Pen e,Grainne M. McAlonan f, Raymond C.K. Chan a,*a Neuropsychology and Applied Cognitive Neuroscience Laboratory, Key Laboratory of Mental Health, Institute of Psychology,

Chinese Academy of Sciences, Beijing, Chinab Shenzhen Children’s Hospital, Shenzhen, Chinac Child Developmental Behavior Center, the Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Chinad School of Public Health, Sun Yat-Sen University, Guangzhou, Chinae Maternal and Child Health Hospital, Zhuhai, Chinaf Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, King’s College London,UK

A R T I C L E I N F O

Article history:

Received 19 September 2011

Received in revised form 25 October 2011

Accepted 26 October 2011

Available online 24 November 2011

Keywords:

ADHD

Temporal processing

Genetic factor

A B S T R A C T

The current study aimed to investigate temporal processing in Chinese children with

Attention-Deficit-Hyperactivity Disorder(ADHD) using time production, time reproduc-

tion paradigm and duration discrimination tasks. A battery of tests specifically designed to

measure temporal processing was administered to 94 children with ADHD and 100

demographically matched healthy children. A multivariate analysis of variance (MANOVA)

and a repeated measure MANOVA indicated that children with ADHD were impaired in

time processing functions. The results of pairwise comparisons showed that the probands

with a family history of ADHD performed significantly worse than those without family

history in the time production tasks and the time reproduction task. Logistic regression

analysis showed duration discrimination had a significant role in predicting whether the

children were suffering from ADHD or not, while temporal processing had a significant

role in predicting whether the ADHD children had a family history or not. This study

provides further support for the existence of a generic temporal processing impairment in

ADHD children and suggests that abnormalities in time processing and ADHD share some

common genetic factors.

� 2011 Elsevier Ltd. All rights reserved.

1. Introduction

Temporal information processing refers to the analysis of stimulus time patterns. Central systems that decode temporalinformation and record time series (Mauk & Buonomano, 2004) allow perception and organization of sequences of eventsand actions and facilitate anticipation or prediction of when future events will occur (Toplak, Dockstader, & Tannock, 2006).A number of theoretical models of how the brain organizes and stores events for the future use have been suggested, and the‘internal clock’ model has been widely accepted (Matell & Meck, 2000, 2004). Within this model, Zakay has emphasized therole of attention in temporal processing and proposed an ‘‘Attentional-Gate Model’’ (Zakay, 2000).

* Corresponding author at: Neuropsychology and Applied Cognitive Neuroscience Laboratory, Institute of Psychology, Chinese Academy of Sciences, 4A

Datun Road, Beijing 100101, China.

E-mail address: [email protected] (Raymond C.K. Chan).1 These authors contributed equally.

0891-4222/$ – see front matter � 2011 Elsevier Ltd. All rights reserved.

doi:10.1016/j.ridd.2011.10.021

http://dx.doi.org/10.1016/j.ridd.2011.10.021

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http://dx.doi.org/10.1016/j.ridd.2011.10.021

J. Huang et al. / Research in Developmental Disabilities 33 (2012) 538–548 539

Attention deficit hyperactivity disorder (ADHD) is a cognitive developmental disorder characterized by levels ofinattention, hyperactivity, and impulsivity that are age-inappropriate. Growing evidence links ADHD to problems in severalaspects of temporal information processing, including duration discrimination, duration reproduction, and finger tappingand it has been suggested that deficits in temporal information processing contribute to poor cognitive and behavioraloutcomes (Toplak et al., 2006). However, temporal information processing is a multidimensional construct that has spurredthe development of a wide variety of methods designed to quantify its component abilities. Consequently it is difficult tointegrate findings across studies of temporal information processing in the field of ADHD.

Two models offer an explanation of how temporal processing might be impaired in ADHD. The most common, behavioralinhibition, argues that poor inhibitory control and interference affect working memory, which subsequently affects temporalprocessing (Barkley, 1997). In contrast, the delay aversion concept, considers the primary deficit in ADHD is a preference forimmediate reward or an aversion to delay (Sonuga-Barke, 2003) rather than a deficit in their working memory. Inter-connected circuitry through frontal, striatal, parietal, temporal and cerebellar regions that are involved in time perception,inhibitory control and reward-related behavior have consistently been implicated in the pathophysiology of ADHD(Carmona et al., 2011; Cubillo, Halari, Giampietro, Taylor, & Rubia, 2011a; Cubillo, Halari, Smith, Taylor, & Rubia, 2011b;Posner et al., 2011; Scheres, Tontsch, Thoeny, & Kaczkurkin, 2010; Sonuga-Barke, Bitsakou, & Thompson, 2010), andempirical evidence has shown that children with ADHD have deficits in time production (van Meel, Oosterlaan, Heslenfeld, &Sergeant, 2005), time reproduction (Bauermeister et al., 2005; Carelli, Forman, & Mantyla, 2008; Gonzalez-Garrido et al.,2008; Kerns, McInerney, & Wilde, 2001; Meaux & Chelonis, 2003; Rommelse, Oosterlaan, Buitelaar, Faraone, & Sergeant,2007; Smith, Taylor, Rogers, Newman, & Rubia, 2002; Sonuga-Barke, Saxton, & Hall, 1998; Toplak, Rucklidge, Hetherington,John, & Tannock, 2003), and motor timing tasks (Rubia, Noorloos, Smith, Gunning, & Sergeant, 2003; Rubia, Taylor, Taylor, &Sergeant, 1999). However, there is no consensus on the performance of time discrimination tasks in ADHD (Radonovich &Mostofsky, 2004; Toplak, Jain, & Tannock, 2005; Yang et al., 2007) and many previous studies of temporal processing inADHD have been limited by small sample sizes and did not include subtypes of ADHD, e.g., ADHD with inattention, andADHD with combined hyperactivity and inattention (Richard, Balentine, & Lynam, 2001).

Time discrimination in ADHD might depend upon the length of time interval examined. Some have suggested that theprocessing of short intervals (less than 1 s) may rely on an internal timing mechanism or cerebellar process, whereas longerintervals (1 s or greater) may access working memory processes (Ivry, 1996; Mangels, Ivry, & Shimizu, 1998). Theattentional-gate model predicts that when intervals exceed the range that is relevant for typical sensory events, greaterdemands is placed on other cognitive functions such as sustained attention and working memory (Mangels, Ivry, & Rapp,2001). In a previous study (Yang et al., 2007), children with ADHD were asked to discriminate between 2 sets of time interval:one was less than 1 s, the other longer than 1 s. We found that children with ADHD had significantly higher discriminationthresholds than healthy controls, and there was an interaction effect between group and duration. Children with ADHD werealso less accurate in discriminating the duration of stimuli. Working memory was associated with the discriminationthreshold at a duration of 800 ms after controlling for FIQ in ADHD children.

Discrimination of brief intervals has been represented as a candidate endophenotype for ADHD (Himpel et al., 2009).Since twin and family studies indicate that attention problems have a major genetic component explaining up to 80% of thetotal variance (van’t Ent et al., 2009), confirming a temporal processing endophenotype for ADHD could offer a usefultranslational tool for further investigation of genetic factors. Therefore we planned a study to replicate and extend ourprevious findings and investigate whether subtype of ADHD and family history differentially impacts upon temporalprocessing in ADHD.

We also wished to examine multiple aspects of temporal processing capacity in children with ADHD. For example, thedifficulty children with ADHD have in time reproduction task might be explained by an inhibition difficulty rather than a‘pure’ temporal processing anomaly (Sonuga-Barke, Saxton, & Hall, 1998). Therefore, in the present study, we employed twotime reproduction tasks to rule out the impact of inhibition deficit. One had two conditions: the signaled condition (SC) tocontrol for response inhibition and the unsignaled condition (USC) to reproduce time. Sonuga-Barke et al. have argued that ifthe subject can respond correctly in the SC while performing poorly in the USC, any deficit could not be explained byinhibition impairment and was due to a temporal processing impairment (Sonuga-Barke et al., 1998). However the latterresult has been questioned because the visual structure of the signals used in SC and USC were different (Smith et al., 2002;Sonuga-Barke et al., 1998). In the current study we adapted this paradigm to minimize any visual structural difference in thetask conditions.

Another possible confound in the study of time perception in ADHD is the impact of motor demands. The organization ofmotor output is heavily dependent on the representation of time in the brain, and motor difficulties also characterizeindividuals with ADHD (Carte, Nigg, & Hinshaw, 1996; Riordan et al., 1999). Moreover, time perception and motorcoordination share the same underlying neural system, which is predominantly a right hemispheric fronto-striato-cerebellarnetwork (Smith et al., 2003). Unlike time production and reproduction tasks, the duration discrimination tasks minimize themotor demands of timing performance (Carte et al., 1996; Riordan et al., 1999) and have no speed requirement, thereforetime discrimination was also examined in the present study.

Based on previous findings, we hypothesized that children with ADHD would have significant differences in multipletasks of temporal processing compared to typically developing control children. We also predicted that children with ADHD(probands), with a family history of ADHD, would perform more poorly in temporal processing tasks than those without afamily history.

J. Huang et al. / Research in Developmental Disabilities 33 (2012) 538–548540

2. Method

2.1. Participants

The selection and assessment of the participants has been described in detail elsewhere (Yang et al., 2007). In brief, thechildren with ADHD were recruited from consecutive referrals to three child behavioral clinics that serve large urbanpopulations in Guangdong Province, China. Handedness was assessed by means of the Annett Hand PreferenceQuestionnaire (Annett, 1976). Inclusion in the study required an ICD-10 diagnosis of ADHD based on clinical semi-structured parent and child interviews with an expert consultant pediatrician. Comorbidities such as oppositional defiantdisorder, conduct disorder or other learning disorders were assessed using ICD-10 criteria. All participants had to meet thefollowing criteria: (1) age from 6 to 12 years; (2) full scale IQ (FIQ) on Wechsler Intelligence (C-WISC) sores > 80; (3) normalauditory and bilateral corrected visual acuity, no major nervous system disease or impairment or other medical problemwhich could impact upon mental function; (4) no obvious language developmental delay; and (5) psychotropic medicationnaive.

The final sample consisted of children with ADHD (n = 94) and a matched healthy control group (n = 100). Table 1illustrates their demographic information such age, gender and handedness. Seventy participants with ADHD (66 boys) had adiagnosis of ADHD combined type (ADHD-CT), and 24 were of the ADHD inattentive type (ADHD-PI) (19 boys). In ADHD-CTgroup, 20 suffered from comorbid oppositional defiant or conduct disorders, 8 had learning disability, 1 had Tic disorder.Only 5 in the ADHD-PI group had any of these comorbidities. In ADHD-CT group, 31 children had a family history of ADHD[ADHD (H+)] and 39 children were without family history [ADHD (H�)]. In the ADHD-PI group, 11 children had a familyhistory of ADHD [ADHD (H+)] and 13 children were without a family history [ADHD (H�)]. Hyperactivity was scored usingthe Conners Parent Rating Scale[CPRS-48, (Conners, 1989)], the Conners Teacher Rating Scale[(CTRS-28, (Conners, 1989))]and the Child Behavioral Checklist [CBCL, (Achenback & Edelbrock, 1978)]. Table 1 also illustrates hyperactivity scores forADHD (H+) and ADHD (H�).

One hundred typically developing children (89 boys and 11 girls) matched for age, sex, and handedness were recruitedfrom a primary school in Guangdong Province as healthy controls. The mean age and estimated full scale IQ (FIQ) was 8.49years (SD = 1.58) and 106.82 (SD = 11.12), respectively. The healthy children had no identified behavioral problems asdefined by the CRS-R scales. Their school records were checked before they were admitted into the study. None had anyindication of difficulties on their school reports.

2.2. Measures

2.2.1. Temporal processing

2.2.1.1. Temporal production task (TPT). The temporal production task (TPT) has been described in our previous study (Yanget al., 2007). In brief, it was modified from the paradigm used by van Meel et al. (2005). Subjects were required to indicate theend of 1, 3, 6, 12, and 24-s intervals (each produced 8 times) by pressing a button with their right index finger. The start ofeach interval was announced by a short tone presented via computer speakers (duration: 50 ms, 800 Hz). Fig. 1 illustrates theprocedure.

To prevent the participants timing using oral or mental counting strategies, the children were told to read aloud a numberfrom 1 to 9 presented randomly while estimating the time interval. The numbers were presented over 200–800 ms with a200 ms inter-trial interval. The high frequency of the numbers presented increased the difficulty of timing, thereforeparticipants had 3 practices to ensure they understood the task demands. The five target time intervals were randomlyshown on screen and the mean estimate for each target interval recorded.

Table 1

Summary of demographic and clinic characteristics among ADHD groups and control group.

Items ADHD

(H+)(N = 42)

ADHD(H�)(N = 52) HC(N = 100) F/x2 Scheffe pairwise comparison

Mean SD Mean SD Mean SD

Age 8.3 1.5 8.45 1.53 8.49 1.58 0.21 NS

Grade 2.43 1.43 2.44 1.42 2.45 1.47 0.003 NS

CPRS hyperactivity index 1.49 0.11 1.42 0.074 0.35 0.31 82.11 A_P***,A_N***> HC

CTRS hyperactivity index 1.62 0.68 1.49 0.67 0.31 0.32 74.03 A_P***,A_N***> HC

CBCL raw score 62.71 29.53 56.79 19.49 13.39 11.78 84.02 A_P***,A_N***> HC

Gender (male N) 37 48 89 0.58 NS

Handedness (right N/both N) 28 14 32 19 57 43 3.945 NS

FIQ 97.81 10.94 100.67 10.4 106.82 11.12 12.065 A_P***,A_N***< HC

CPRS: Conners Parent Rating Scale; CTRS: Conners Teacher Rating Scale; CBCL: child behavioral checklist; FIQ: full scale IQ; A_P: ADHD(H+); A_N:

ADHD(H�) HC: healthy control.*** p < 0.001.

Fig. 1. Trial procedure in the temporal processing task.


2.2.1.2. The time reproduction task (TRT). There were two kinds of time reproduction task in the present study. Task 1 (TRT1)was used to measure the participants’ subjective time sense in a similar method to that used in the study by McInerney andKerns (2003). A 500 ms ‘‘+’’ directed gaze to the center of the screen. This was followed by a red circle of 3 cm diameter, whichremained for the target duration which the subject would be asked to reproduce. The subject was asked to remember theduration as well as possible. A prompt ‘‘please click the left mouse button’’ would occur on the computer screen after the redcircle vanished. A 3 cm green circle would follow the click and the subject was required to click the left mouse button againwhen he or she believed that the green circle had lasted as long the red one. If the time reproduced by the subject was veryclose to the goal time, a correct feed back would be presented for 1 s, otherwise, the next trial carried on without feedback.Five practices were done to ensure the subject understood. Seven goal durations (3, 5, 6, 12, 17, 30, and 45 s) to be reproducedwere set randomly and each was repeated 5 times. The researcher recorded whether the subject estimated the time bycounting aloud and the mean estimates of each duration were recorded for analysis.

The time reproduction task 2 (TRT2) consisted of two conditions: the signaled condition (SC), to control the responseinhibition, and the unsignaled condition (USC), to reproduce time. In TRT2, we used three simple cartoon pictures to minimizethe problem of differences in visual simulation which may have confounded previous research. The simple cartoon pictureswere used as the ‘press’ signal in the present study; one was a smiling face, another was an unhappy face, and the third was a facewith a neural emotion. There were two target durations: 5 s and 15 s, and each with 10 trials, for the SC and the USC. In the SCperiod, a 500 ms ‘‘+’’ would gaze to the screen, followed by a smiling face, then an unhappy face 5 or 15 s later. The subject wasasked to remember the duration of the smiling face in order to reproduce it in the USC period. The unhappy face would bepresented for 2 s, and the subject had to press the key in this period, followed by ‘‘correct’’ feedback on the screen. Responsesbefore unhappy face appeared were considered to be ‘‘Early Errors’’, whereas response made after 2 s were ‘‘Late Errors’’, andthere was no feedback in these two situations. In the following USC period, after the subject pressed the key, a neutral face wouldbe presented on the screen, without response signal. In this period, the subject had to respond according to the duration of thesmiling face estimated in the SC. If the time reproduced by the subject was very close to the goal time, correct feedback would bepresented for 1 s; otherwise, the next trial would proceed without feedback. The subject could respond only once in the SC andUSC, and the mouse could not be activated until the next trial. Each subject had to complete 20 pairs with 5 and 15 s durationspresented stochastically. Practice would be carried out before the test to ensure that the subject had understood. The actual timeproduced or reproduced by the subjects was recorded to calculate two indices for analysis, the average absolute differentialvalue and the average accurate coefficient of the target time (TPT and TRT).

2.2.1.3. Time discrimination task (TDT). This was based on forced-choice judgments and was used to determine individualthresholds at which intervals differing by several milliseconds (ms) can be perceived as different (for details, see (Yang et al.,2007).

2.2.2. Other cognitive functions testing

IQ was assessed by the short form of the Chinese version of the Wechsler Intelligence Scale for Children-Revised [C-WISC,(Gong & Cai, 1993)]. Items included block design, picture completion, information, and vocabulary. These four subtests werecombined because previous studies have demonstrated that they strongly correlate (0.95) with a child’s Full scale IQ (FIQ)(Goh, 1980).


2.3. Procedure

The study protocol was approved by the local clinical research ethics committee. Written consent was provided by theguardians of both the children with ADHD and the healthy controls. Each child received the battery of temporal processingand IQ tests, in a standardized order. Each child with ADHD was seated comfortably in front of a laptop computer in a quietroom on site, and the control children were tested at their school in a quiet room.

2.4. Data analysis

The results were analyzed using SPSS version 12. Between group differences in demographic characteristics, clinicalfeatures and full scale IQ (FIQ) were tested across the three groups – ADHD (H+), ADHD (H�), and healthy controls, usingANOVA. To examine all of our variables of interest on the temporal processing tasks (TPT, TRT1, TRT2, and DDT), weconducted a repeated measures MANOVA, with group as a between-subject factor and the duration as a within-subjectfactor, and conducted a further post-hoc ANOVA for each task when the MANOVA was statistically significant.

Scheffe post hoc tests were used for pairwise comparison. Chi-square tests were used to analyze count data (such asdifferences by gender or handedness). Logistic regression analysis was used to explore whether the duration discriminationscore, the absolute discrepancy score and accuracy coefficient in temporal processing tasks could predict those children withADHD and their family history.

3. Results

3.1. Temporal processing functions

Repeated measures MANOVA was used to analyze performances in the time production task, time reproduction task andthe time discrimination task, with the target duration as a repeated measurement factor, group as inter-subject factor, andFIQ as covariate (see Table 2). The Huynh–Feldt (HF-F) values in F-test were used to indicate statistical significance becausethe results of Mauchly Sphericity test were significant.

3.1.1. Time production task

There was a significant main effect of time interval on the absolute value of the difference (absolute discrepancy) betweentarget duration and actual time produced by the subject [HF-F (1.54, 292.317) = 15.968, p < 0.001], such that the absolutedifference increased as the target duration increased. The main effect of group [F (2,189) = 29.872, p < 0.001] was statisticallysignificant; the absolute discrepancies of the ADHD(H+) group were significantly larger than the ADHD (H�), group, and thelatter was significantly larger than controls (see Table 2).

An interaction between groups and time intervals [F (3.093, 292.317) = 21.372, p < 0.001] suggested that the main effectsshould be interpreted cautiously. Scheffe multiple comparisons for each target interval showed that the absolutediscrepancy in the ADHD (H+) was significantly larger than that of the ADHD (H�) (p < 0.01), and the latter was significantlylarger than that of the controls (p < 0.001), in both 6 and 24 s duration conditions. However, in the condition of 12 s duration,the absolute difference of the ADHD (H+) was significantly larger than that of the ADHD (H�) and the controls (p < 0.001),with no significant difference between the latter two groups. There was no significant difference among the three groups inthe conditions with shorter durations (1 s and 3 s) (see Table 2), indicating that the children with ADHD, especially the ADHD(H+) group, made more mistakes as the target duration increased.

There was a main effect of duration [HF-F (2.697, 509.673) = 5.746, p < 0.001], group [F (2,189) = 17.815, p < 0.001] andinteraction [HF-F (5.393, 509.673) = 4.21, p < 0.001] in accuracy of time produce (see Table 2). The main effect of the durationshowed that the children in three groups estimated shorter times as the target duration increased; the main effect of groupshowed a significant difference in the accuracy among the three groups as the children with ADHD underestimated time.Scheffe multiple comparison showed that in the 6 and 12 s durations, the children with ADHD (H+) were liable tounderestimate the time compared to the children with ADHD (H�) and the controls (p < 0.001), with no significantdifference between the latter two groups; in the 24 s duration condition, the time estimated by the ADHD (H+) wassignificantly shorter than that estimated by the ADHD (H�) group (p < 0.001), and the latter was shorter than that estimatedby the controls (p < 0.001) (see Table 2). Thus, children with ADHD were liable to underestimate the time compared to thecontrols, especially when the children had a family history of ADHD.

3.1.2. Time reproduction task 1 (TRT 1)

Repeated measures MANOVA showed a main effect of duration on absolute difference [HF-F (1.923, 344.606) = 24.365,p < 0.001], such that the absolute difference in three groups increased as the target duration increased. A main effect of group[F (2,183) = 25.575, p < 0.001] indicated significant differences among three groups since the absolute difference in patientgroups was larger than the normal control group, with no significant differences between the two patient groups (see Table2). There was interaction effect between group and duration [HF-F (3.846, 353.779) = 16.236, p < 0.001], and Scheffemultiple comparison test showed that the children in either ADHD groups made many more mistakes in the 12, 17, 30 and45 s durations (p < 0.001); in the 5 s duration condition, the absolute difference in the ADHD (H+) group was obviously larger

Table 2

Comparison of absolute discrepancy, accuracy coefficient and effect size controlling FIQ.

Items ADHD(H+) ADHD (H�) Controls F group F duration F group� duration

Mean SD Mean SD Mean SD

TPT absolute discrepancy (1 s) 309.85 392.85 254.53 238.09 213.18 194.86 29.872*** 15.968*** 21.372***

TPT absolute discrepancy (3 s) 895.94 694.06 781.33 598.78 811.27 1315.3




TPT accuracy coefficient (1 s) 1.06 0.50 1.07 0.34 0.99 0.29 17.815*** 5.746*** 4.210***

TPT accuracy coefficient (3 s) 0.82 0.33 0.84 0.29 0.99 0.52




TRT1 absolute discrepancy (3 s) 1285.99 1259.04 1356.63 1169.65 1056.65 1558.52 25.58*** 24.37*** 16.326***

TRT1 absolute discrepancy (5 s) 2164.39 1846.16 1978.01 1885.97 1153.42 1583.42



TRT1 absolute discrepancy (17 s) 7052.64 4644.71 8375.84 4657.31 3921 4035.33



TRT1 accuracy coefficient (3 s) 1.13 0.59 1.16 0.58 1.17 0.61 9.223*** 11.743*** 2.638**

TRT1 accuracy coefficient (5 s) 1.00 0.57 1.06 0.55 1.06 0.39






TRT2 absolute discrepancy (5 s) 1903.28 1359.55 1368.65 1167.98 979.55 977.22 22.72*** 18.23*** 23.76***


TRT2 accuracy coefficient (5 s) 0.84 0.44 0.74 0.25 0.95 0.27 16.62*** 13.38*** 5.15***


DDT threshold (300 ms) 59.58 23.31 59.63 19.31 45.05 19.23 25.286*** 2.78 3.68*

DDT threshold (800 ms) 143.37 40.20 127.47 41.54 105.94 35.61

DDT threshold (1200 ms) 197.79 49.09 197.00 51.60 132.7 50.17

FIQ: full scale IQ; TPT: time production task; TRT: time reproduction task; DDT: duration discrimination task.* p< 0.05.** p< 0.01.*** p< 0.001.

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than that in the normal control group (p < 0.01); without significant difference among three groups in the shorter durations(3 and 6 s) (see Table 2).

The patterns of results for accuracy coefficient were similar to those of the absolute difference. The children in each groupwere liable to underestimate durations as the target durations increased; the children with ADHD estimated that durationswere significantly shorter than the normal controls (see Table 2). Scheffe multiple comparison showed that the children inADHD (H+) group clearly underestimated time compared to those in ADHD (H�) group in 6 s duration condition (p < 0.05);for 12 s durations, the ADHD (H+) was more liable to underestimate the duration than the ADHD (H�) (p < 0.05) and thecontrols (p < 0.001), without significant differences between the two latter groups; for long durations (17, 30 and 45 s),patients were significantly more likely to underestimate the durations than the controls (p < 0.001), without significantdifference between the two patient groups; for short durations (3 sand 5 s), there was no significant difference among thethree groups. This indicated that both the ADHD and the controls were liable to underestimate the durations, although theformer underestimated the time most, especially the children with a family history of ADHD.

3.1.3. Time reproduction task 2 (TRT 2)

As shown in Table 2, repeated measure MANOVA showed a main effect of duration [HF-F (1,183) = 18.231, p < 0.001] andgroup [F (2,183) = 22.718, p < 0.001] on absolute difference similar to the pattern for TRT1, with a significant interactionbetween duration and group [HF-F (2,183) = 23.754, p < 0.001]. As shown in see Table 2, Scheffe multiple comparisonshowed that the ADHD (H+) made more mistakes in the 5 s duration condition than the normal controls (p < 0.001), and twogroups of children with ADHD had significantly more mistakes during 15 s than the normal controls (p < 0.001), withoutsignificant differences between the two patient groups.

The patterns of main effects and interaction for accuracy coefficients were similar to that for the absolute difference (seeTable 2). Scheffe multiple comparison showed that the ADHD (H�) were more liable to underestimate the time at 5 s(p < 0.001); and the children in the two ADHD groups were more liable to underestimate the time at 15 s (p < 0.001),compared to the controls, without significant difference between the two patient groups.

In addition to the indices for time estimation, there were indices for inhibition ability (the early errors, the correctnumbers, and the late errors) in SC in TRT2. Rank sum test showed that the early errors in the 5 s condition were significantlydifferent among three groups (x2 = 6.388, v = 2, p = 0.041), and multiple comparison showed that the ADHD (H+) group hadmore early errors than the control group (p < 0.05), but with no significant difference after the Bonferroni corrections, and nosignificant difference in the correct numbers and the late errors among the three groups.

There were significant group differences in early errors (x2 = 9.789, v = 2, p = 0.007) and the correct numbers (x2 = 6.427,v = 2, p = 0.04) in the 15 s condition; multiple comparisons showed that the ADHD (H+) group had more early errors than theADHD (H�) group (p < 0.05) and the normal control group (p < 0.01), and difference between the ADHD (H+) group and thenormal control group remained significant after Bonferroni correction; ADHD (H+) group had significantly less correctresponses than the normal control group (p < 0.05), even after Bonferroni correction. The results of TRT2, thereforeconfirmed that children with ADHD have difficulties in temporal processing and response inhibition.

3.1.4. Duration discrimination task (DDT)

A repeated measures MANOVA, with target durations as dependent variable, group as a between-subjects factor, FIQ as acovariate, showed a main effect of group [F(2,73) = 25.286, p < 0.001] (see Table 2). Pairwise comparison showed that thetime discrimination threshold of the ADHD children was significantly higher than that of the normal controls, with aninteraction effect between group and duration [HF-F(3.274, 119.510) = 3.68, p = 0.012]. The results of pairwise comparisonsfor each target duration showed that the threshold of time discrimination in the ADHD (H�) group was significantly higherthan the normal control group (p < 0.05) at 300 ms, with an effect size of 0.73. At a duration of 800-ms, the threshold for theADHD (H+) group was significantly higher than that of the normal control group children (p < 0.01), with an effect size of 1;while in the 1200 ms condition, the thresholds of the two ADHD groups were significantly higher than the normal controlgroup children (p < 0.001), with effect sizes of 1.15 and 1.23. The results indicated that, compared to controls, the ADHDchildren could distinguish two different durations only when they differed greatly.

3.2. The role of temporal processing tasks in the prediction of ADHD

In a logistic regression analysis (see Table 3), the average Z value of the performances in duration discrimination task(DDT) was considered the predictive factor and with/without ADHD as the dependent variable. The duration discriminationtask could significantly predict ADHD group membership [�2lnL = 65.4, R2 = 0.553, x2 = 41.227, df = 1, p < 0.001]. Thesensitivity of duration discrimination for ADHD category prediction was 83.1%. The absolute discrepancy in timereproduction I, time reproduction II and temporal processing task also had a significant role in predicting ADHD[�2lnL = 184.46, R2 = 0.425, x2 = 70.787, df = 3, p < 0.001]. The sensitivity of the model for ADHD category prediction was76.8%. Another index in these tasks was accuracy coefficient. The accuracy coefficient in time reproduction I, timereproduction II and temporal processing task showed a well-fitting regression equation model [�2lnL = 192.89, R2 = 0.382,x2 = 62.357, df = 3, p < 0.001] and the sensitivity of this model for ADHD category prediction was 76.2%.

The duration discrimination function, time production and temporal processing may also predict of ADHD but not as wellas duration discrimination (see Table 3).

Table 3

Results of two logistic regressions of temporal processing tasks in predicting ADHD and their family history.

Predicting Items ß S.E. Wald p OR

ADHD Duration discrimination 3.13 0.72 18.64 <0.001 22.80

Time reproduction I Abs_Dis 0.76 0.30 6.60 0.010 2.15

Time reproduction II Abs_Dis �0.57 0.20 8.25 0.004 0.56

Time processing Abs_Dis 0.87 0.25 12.49 <0.001 2.38

Time reproduction I Acc_Coe 0.77 0.40 3.66 0.056 2.16

Time reproduction II Acc_Coe �0.63 0.27 5.51 0.019 0.53

Time processing Acc_Coe 0.87 0.27 10.41 0.001 2.38

Family history Duration discrimination �0.41 0.55 0.57 0.450 0.66

Time reproduction I Abs_Dis �0.16 0.41 0.15 0.696 0.85

Time reproduction II Abs_Dis 0.05 0.24 0.04 0.847 1.05

Time processing Abs_Dis �0.57 0.22 6.95 0.008 0.57

Time reproduction I Acc_Coe 0.77 0.40 3.66 0.056 2.16

Time reproduction II Acc_Coe �0.63 0.27 5.51 0.019 0.53

Time processing Acc_Coe 0.87 0.27 10.41 0.001 2.38

Abs_Dis: absolute discrepancy; Acc_Coe: accuracy coefficient.


3.3. The role of temporal processing tasks in the prediction of family history in ADHD

In a logistic regression analysis (see Table 3) were the average Z value of performance in the duration discrimination task(DDT) was the predictive factor and positive or negative family history of ADHD was the dependent variable, the durationdiscrimination task could not predict the family history in ADHD [�2lnL =50.683, R2 = 0.021, x2 = 0.582, df = 1, p = 0.445]. Thesensitivity of duration discrimination for ADHD category prediction was 56.8%. The absolute discrepancy in timereproduction I, time reproduction II and temporal processing task had a role in predicting ADHD [�2lnL = 107.645, R2 = 0.147,x2 = 9.896, df = 3, p = 0.019]. The sensitivity of the model for ADHD category prediction was 67.1%. The accuracy coefficient intime reproduction I, time reproduction II and temporal processing task also showed a well-fitting regression equation model[�2lnL = 99.569, R2 = 0.254, x2 = 17.971, df = 3, p < 0.001] with 67.1% sensitivity for ADHD. Thus, the absolute discrepancyand accuracy coefficient in temporal processing help predict family history in ADHD (see Table 3).

3.4. The effects of the comorbidity and subtypes the ADHD on temporal processing

In order to investigate the effects of the comorbidity and ADHD subtypes on temporal processing, the children with ADHDwere divided into groups with (32 children, 34%) and without comorbidity (62 children, accounting for 66%). In addition thesubtypes of ADHD were examined; ADHD-PI group (24 children, 25.5%), ADHD-CT group (70 children, 74.5%).

A MANOVA analysis with FIQ controlled showed no significant difference in temporal processing abilities between theADHD subtypes (Pillai’s trace = 0.782, F = 0.617, p > 0.05).

4. Discussion

ADHD is characterized by levels of inattention, hyperactivity, and impulsivity that are age-inappropriate. The results ofthe current study provide evidence for specific deficits in temporal processing in ADHD.

4.1. Time processing capacity

ADHD children had poor time processing capacity. ADHD children consistently performed worse than controls asmeasured by absolute time discrepancy and the accuracy coefficient. In duration discrimination tasks, ADHD childrenneeded a greater difference (discrimination threshold) to tell apart two durations, compared to normal control group, evenwhen the impact of inhibitory control was controlled for. The findings are consistent with a number of previous studies(Kerns et al., 2001; Sonuga-Barke, 2003; West et al., 2000).

The time processing deficits in children with ADHD were affected by genetics. Scheffe multiple comparison showed thatthe absolute discrepancy of time measurement in the ADHD (H+) group was significantly greater than that of the ADHD (H�)group for long durations of 6, 12 and 24 s, whereas the accuracy coefficient of the ADHD (H+) group was significantly lowerthan that the ADHD (H�). Duration of 6 and 12 s in TRT1, the accuracy coefficient of the ADHD (H+) group was significantlylower than that of the ADHD (H�) group, with medium effect size. At other durations in TPT and TRT, and in DDT, the ADHD(H�) group’s performance fell in between the ADHD (H+) group and the normal control group, though their absolutediscrepancy and accurate coefficient (or discrimination threshold) was not significantly from the ADHD (H+) group. Thesefindings suggest that time processing in probands with a family history of ADHD is more seriously affected than thosewithout family history.

The results of present study showed that the time production tasks have a higher sensitivity for classification of ADHDthan time reproduction tasks. However, time production tasks were sensitive to family history. This could be due to task


difficulty. The TPT requested the subjects read out the numbers presented randomly, with different stimulation intervals, toprevent counting time by oral or mental count; and the increased difficulty of these tasks could more easily expose a timeprocessing deficit in ADHD children. This explanation is consistent with the effect sizes recorded.

4.2. Comorbidities and subtypes in ADHD

Comorbidities are a potential confound in all studies of ADHD. The results in present study showed no significantdifference in temporal processing between the two groups with and without comorbidities. This could be a false negative,due to the small cell sizes and sub-clinical levels of hyperactivity in the predominantly inattentive group, although, previousstudies also found comorbidities did not significantly affect cognitive function (Nigg, 1999; Oosterlaan, Logan, & Sergeant,1998; Rucklidge & Tannock, 2002).

ADHD is divided into three subtypes of ADHD-PI, ADHD-HI and ADHD-CT according to DSM-IV, and whether thesesubtypes share common genetic risk factors or not remains unclear (Crosbie & Schachar, 2001). Some scholars believethat ADHD-HI is not an ADHD subtype (Milich, Balentine, & Lynam, 2001). In present study, the ADHD children weredivided into ADHD-PI and ADHD-CT, and a MANOVA with FIQ controlled showed that ADHD subtypes had no significanteffect on cognitive function. This is consistent with other studies (Geurts, Verte, Oosterlaan, Roeyers, & Sergeant, 2005)(Riccio, Homack, Jarratt, & Wolfe, 2006). Meta analysis (Lane, 2003) also showed no significant difference in responseinhibition between ADHD-CT and ADHD-PI. However, Nigg, Blaskey, Huang-Pollock, & Rappley (2002) reported that boyswith ADHD-CT had significantly longer SSRT than boys with ADHD-PI, with no significant difference between the twogroups of girls.

4.3. Family history

Although a common environment may contribute to any role played by family history, the heritability of ADHD isconsidered to be as much as 90%. Thus genetic factors are thought to explain more of the variability of ADHD thanenvironmental factors. Twins studies have shown that genetic factors rather than shared environmental factors explain thefamilial aggregation of ADHD [cited in (Acosta, Arcos-Burgos, & Muenke, 2004)]. The results of present study showed asignificant difference in performance for multiple aspects of temporal processing in ADHD children with/without a familyhistory, with the ADHD (H+) group being more impaired than the ADHD (H�) group. Therefore temporal processingfunctions may be closely tied to genetic factors.

4.4. Limitations and conclusion

We collected the data on family history of ADHD through inquiry, asking whether the parents of the probands and thesiblings of the parents had symptoms similar to the ADHD in their childhood. Since there was no firm diagnosis dataavailable, it is difficult to avoid the impact of exaggeration or evasion on retrospective reporting, therefore, thedifferences in cognitive function between the ADHD (H+) group and the ADHD (H�) group should be interpreted withcaution. Never-the-less, adults usually have a general recollection of childhood, and if they experienced behavioralproblems similar to the ADHD parents or teachers may have complained and this memory would remain. Moreover, bydiscussing their understanding of the causes of hospital visits, we found that teachers and parents were highly consistentin evaluating behavioral problems in children with ADHD. This we felt indirectly suggested the probability of the parentsoverestimating or underestimating the seriousness of symptoms, was relatively small. The data on family history ofADHD obtained in present study was also similar to that in collected in another study (Buitelaar et al., 2006). In addition,multiple comparisons by Scheffe Post Hoc Tests was quite a stringent control, leading to more conservative and credibleresults. We therefore believe that differences did exist between the children in the ADHD (H+), ADHD (H�) and normalcontrol group.

Each child received a battery of temporal processing and IQ tests in a standardized order instead of a random order inpresent study, potentially leading to order effects. However, a between-subjects design would partially offset possible ordereffects. ADHD children showed impairment during the whole testing process, from the first tasks (time production task), tothe middle tasks (time reproduction task) and the final tasks (time processing task); and since status changes (under-arousal) or response variability itself is one of the symptoms of ADHD, it is likely that poor test performance was due to thedisorder rather than order effects or fatigue. Other limitations such as the small sub-sample size in ADHD subtypes should beavoided in future studies.

In summary, our study indicated that there are temporal processing deficits in children with ADHD. Multipledifficulties with time production, time reproduction and duration discrimination were associated with ADHD. Furtherresearch should consider whether there are common neural pathways or genetic association for processing in childrenwith ADHD.

Declaration of interest

None.


Acknowledgements

This study was supported partially by the Project-Oriented Hundred Talents Programme (O7CX031003) of the Institute ofPsychology, Chinese Academy of Sciences, the Knowledge Innovation Project of the Chinese Academy of Sciences (KSCX2-EW-J-8), the National Science Fund China Young Investigator Award (81088001), and the Research Initiation Grant from theSun Yat-Sen University (16000-3253182) to Raymond Chan. This study was partially supported by the Young InvestigatorScientific Fund of Institute of Psychology, Chinese Academy of Sciences (YOCX031S01) to Jia Huang. These funding agentshad no role in the study design; collection, analysis, and interpretation of the data; writing of the manuscript; or decision tosubmit the paper for publication.

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Temporal processing impairment in children with attention-deficit-hyperactivity disorder