Beyond the dual pathway model: evidence for the dissociation of timing, inhibitory, and delay-related impairments in attention-deficit/hyperactivity disorder.
ABSTRACT The dual pathway model explains neuro-psychological heterogeneity in Attention Deficit/Hyperactivity Disorder (ADHD) in terms of dissociable cognitive and motivational deficits each affecting some but not other patients. We explore whether deficits in temporal processing might constitute a third dissociable neuropsychological component of ADHD.
Nine tasks designed to tap three domains (inhibitory control, delay aversion and temporal processing) were administered to ADHD probands (n=71; ages 6 to 17 years), their siblings (n=71; 65 unaffected by ADHD) and a group of non-ADHD controls (n=50). IQ and working memory were measured.
Temporal processing, inhibitory control and delay-related deficits represented independent neuropsychological components. ADHD children differed from controls on all factors. For ADHD patients, the co-occurrence of inhibitory, temporal processing and delay-related deficits was no greater than expected by chance with substantial groups of patients showing only one problem. Domain-specific patterns of familial co-segregation provided evidence for the validity of neuropsychological subgroupings.
The current results illustrate the neuropsychological heterogeneity in ADHD and initial support for a triple pathway model. The findings need to be replicated in larger samples.
Article: Impulsive choice behavior in four strains of rats: Evaluation of possible models of Attention Deficit/Hyperactivity Disorder.[show abstract] [hide abstract]
ABSTRACT: Several studies have examined impulsive choice behavior in spontaneously hypertensive rats (SHRs) as a possible pre-clinical model for Attention-Deficit/Hyperactivity Disorder (ADHD). However, this strain was not specifically selected for the traits of ADHD and as a result their appropriateness as a model has been questioned. The present study investigated whether SHRs would exhibit impulsive behavior in comparison to their control strain, Wistar Kyoto (WKY) rats. In addition, we evaluated a strain that has previously shown high levels of impulsive choice, the Lewis (LEW) rats and compared them with their source strain, Wistar (WIS) rats. In the first phase, rats could choose between a Smaller-sooner (SS) reward of 1 pellet after 10 s and a Larger-later (LL) reward of 2 pellets after 30 s. Subsequently, the rats were exposed to increases in LL reward magnitude and SS delay. These manipulations were designed to assess sensitivity to magnitude and delay within the choice task to parse out possible differences in using the strains as models of specific deficits associated with ADHD. The SHR and WKY strains did not differ in their choice behavior under either delay or magnitude manipulations. In comparison to WIS, LEW showed deficits in choice behavior in the delay manipulation, and to a lesser extent in the magnitude manipulation. An examination of individual differences indicated that the SHR strain may not be sufficiently homogeneous in their impulsive choice behavior to be considered as a viable model for impulse control disorders such as ADHD. The LEW strain may be worthy of further consideration for their suitability as an animal model.Behavioural brain research 10/2012; · 3.22 Impact Factor
Article: Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD.[show abstract] [hide abstract]
ABSTRACT: Research and clinical investigations in psychiatry largely rely on the de facto assumption that the diagnostic categories identified in the Diagnostic and Statistical Manual (DSM) represent homogeneous syndromes. However, the mechanistic heterogeneity that potentially underlies the existing classification scheme might limit discovery of etiology for most developmental psychiatric disorders. Another, perhaps less palpable, reality may also be interfering with progress-heterogeneity in typically developing populations. In this report we attempt to clarify neuropsychological heterogeneity in a large dataset of typically developing youth and youth with attention deficit/hyperactivity disorder (ADHD), using graph theory and community detection. We sought to determine whether data-driven neuropsychological subtypes could be discerned in children with and without the disorder. Because individual classification is the sine qua non for eventual clinical translation, we also apply support vector machine-based multivariate pattern analysis to identify how well ADHD status in individual children can be identified as defined by the community detection delineated subtypes. The analysis yielded several unique, but similar subtypes across both populations. Just as importantly, comparing typically developing children with ADHD children within each of these distinct subgroups increased diagnostic accuracy. Two important principles were identified that have the potential to advance our understanding of typical development and developmental neuropsychiatric disorders. The first tenet suggests that typically developing children can be classified into distinct neuropsychological subgroups with high precision. The second tenet proposes that some of the heterogeneity in individuals with ADHD might be "nested" in this normal variation.Proceedings of the National Academy of Sciences 04/2012; 109(17):6769-74. · 9.68 Impact Factor
Beyond the dual pathway model: Evidence for the dissociation of timing,
inhibitory and delay-related impairments in Attention Deficit/Hyperactivity
Edmund Sonuga-Barke PhD, Paraskevi Bitsakou PhD and Margaret Thompson MD
Professor Sonuga-Barke and Drs Bitsakou and Thompson are with the Developmental
Brain Behaviour Laboratory at the School of Psychology, University of Southampton.
Professor Sonuga-Barke is also with the Department of Experimental Clinical &
Health Psychology at Ghent University.
The authors would like to thank the families who participated in this project; Dr. L.
Psychogiou; Dr. A. Weeks, Dr. V. Fiske, Dr. J. Chan, and Dr. A. Shyam for help with
participants’ recruitment and administration of the PACS; Rebecca Barrett, Anna
Maria Re, and Amanda Meliá De Alba for help with data entry and collection; Luke
Phillips for the construction of the tasks and his technical support. This research was
funded in part by an ESRC CASE Award (PTA-033-2003-00046 with Eli Lilley Ltd)
to Edmund Sonuga-Barke & Margaret Thompson for Paraskevi Bitsakou. Clinical
data from the participants included in this paper contributed to the IMAGE project
(Faraone; NIH grand R01 MH62873-01A1).
Correspondence to Edmund Sonuga-Barke, Institute for Disorder of Impulse and
Attention, School of Psychology, University of Southampton, Highfield,
Southampton, SO17 1BJ, UK, e-mail: firstname.lastname@example.org
Objectives: The dual pathway model explains neuro-psychological heterogeneity in
Attention Deficit/Hyperactivity Disorder (ADHD) in terms of dissociable cognitive
and motivational deficits each affecting some but not other patients. We explore
whether deficits in temporal processing might constitute a third dissociable
neuropsychological component of ADHD.
Method: Nine tasks designed to tap three domains (inhibitory control, delay aversion
and temporal processing) were administered to ADHD probands (n=71; ages 6 to 17
years), their siblings (n=71; 65 unaffected by ADHD) and a group of non-ADHD
controls (n=50). IQ and working memory were measured.
Results: Temporal processing, inhibitory control and delay-related deficits
represented independent neuropsychological components. ADHD children differed
from controls on all factors. For ADHD patients the co-occurrence of inhibitory,
temporal processing and delay-related deficits was no greater than expected by chance
with substantial groups of patients showing only one problem. Domain-specific
patterns of familial co-segregation provided evidence for the validity of
Conclusion: The current results illustrate the neuropsychological heterogeneity in
ADHD and initial support for a triple pathway model. The findings need to replicated
in larger samples.
Key words: ADHD, Delay Aversion, Heterogeneity, Inhibitory Control, Timing.
Neuropsychological studies of Attention Deficit/ Hyperactivity Disorder (ADHD)
implicate a broad range of processes. 1 These include executive dysfunction ((EDF 2)
e.g, inhibitory 3 and working memory (WM 4) deficits), non-executive deficits (e.g.
perception5; memory 6; timing 7) and alterations in motivational processes. 8 However,
even the most robust neuropsychological effects are only moderate in size (e.g. .3 to
.6 Cohen’s d; 2) and fall short of the level required for diagnosis. 9 For example, Nigg
et al. 10 found only 30% of patients with deficits on at least three tasks in a large EF
battery. This pattern of limited associations across distinct domains highlights the
neuropsychological heterogeneity in ADHD. 11 The dual pathway model 12-14 explains
this heterogeneity as two, more or less, independent patterns of deficit each affecting
some ADHD patients: One grounded in dorsal fronto-striatal dysregulation mediated
by inhibitory based EDF (I-EDF), the other underpinned by ventral fronto-striatal
circuits and linked to altered signalling of delayed rewards, manifest as delay aversion
(DAv 11,15). Clinical and pre-clinical studies provide support for this model 16-20 (but
see 21). However many patients appear unaffected by either DAv or I-EDF. 17 This
paper is the first to explore whether temporal processing deficits (TPD) in ADHD
represent a dissociable third neuropsychological ‘pathway’. This is biologically
plausible as MRI suggests that although TPD may share neural components (i.e.,
basal ganglia;22,23) with I-EDF and DAv, it is also distinctive in some ways (i.e.,
cerebellum 24). It is clinically plausible as ADHD children have shown TPD across a
range of timing tasks. 25-31 Results on motor timing are less consistent. 29, 32-34 fMRI
confirms alterations within key components of temporal processing circuits in ADHD.
ADHD has a complex causal structure with both genetic and environmental
factors implicated. 36,37,10 Where they mediate genetic effects, neuropsychological
deficits (i.e., endophenotypes 38,39) will be correlated within families and levels of
deficits in unaffected family members will be intermediate between their ADHD
relatives and unrelated controls. Furthermore, if different endophenotypes mediate
specific pathways these familial effects should ‘breed true’ - e.g., siblings of ADHD
children with I-EDF should also show I-EDF. Evidence of familial correlation and
co-segregation has been reported for I-EDF 40,41, TPD 28,42,43 and DAv.15 Here we
explore this further.
We adopted a multivariate methodology with three tasks chosen for each
neuropsychological domain to improve measurement reliability and allow the
underlying latent structure of neuropsychological deficits to be explored.
Performance on the I-EDF tasks (i.e., Stop Signal, Go-No-Go and a Stroop like
response interference tasks) is inter-correlated and associated with ADHD. 3 For DAv
tasks (i.e., Maudsley Index of Delay Aversion; Delayed Frustration Task; Delayed
Reaction Time Task) correlations are smaller. 44 For TPD we assessed time
discrimination, reproduction and motor synchronization. 45, 25 Our battery also
included a simple measure of WM (i.e., WISC digit span). Previous reports suggest
that TPD implicates WM problems 25 (but see 46) and I-EDF and WM are closely
associated processes 47 (but see 48).
We predicted; (a) that neuropsychological domain will form independent
principal components; (b) significant case-control differences in each domain; (c) sub-
groups of ADHD individuals affected by only one deficit; (d) domain specific familial
effects – neuropsychological deficits will breed true and; (e) neuropsychological
domains will show distinctive patterns of associations in terms of: IQ and oppositional
defiant disorder (ODD). Literacy was included because of the possibility of a
common role for the cerebellum in reading disorder and ADHD in children with TPD
49 (but see 50).
Seventy-one families with an ADHD child participated in the Southampton arm of
IMAGE. 51 Seventy-one ADHD probands with a combined type diagnosis (M = 12.03
years, SD = 2.34 years), 65 unaffected siblings (M = 11.46 years, SD = 3.19 years)
and 50 non-ADHD controls (M = 12.15 years, SD = 2.25 years) were included in the
key analyses. Six siblings had ADHD and were excluded from the case-control and
familiality analyses. Cases (aged between 6 and 17 years) with an existing full clinical
diagnosis of ADHD were included in IMAGE if they also fulfilled criteria for a
research diagnosis (see below) and had an IQ of at least 70. Patients were excluded if
they had a history of clinically significant depression and anxiety or other major
mental health problems (e.g., autism, epilepsy). ODD or CD was not an exclusion
criteria. The research diagnostic protocol is described in detail elsewhere (see 51).
Probands and those siblings with T scores > 63 on the Conners’ ADHD subscales
were administered the Parental Account of Childhood Symptoms (PACS 52): a semi-
structured clinical interview (inter-rater reliability ranging from .79 to .96) 53 A
standardized algorithm was applied to derive the 18 DSM-IV ADHD items. To
receive a research diagnosis, children had to; (i) have sufficient PACS symptoms, (ii)
meet the PACS criteria for impairment and (iii) display at least one symptom in both
the hyperactive/impulsive and inattentive domains (i.e., a rating of 2 or 3) on the
Conners. Control children attended local schools. Parent and teacher versions of the
SDQ 53 confirmed that 15 of the 65 controls initially recruited, scored above the
borderline cut-offs for hyperactivity/impulsivity and were excluded. This left a
preponderance of females controls (gender χ2(1) = 9.37, p < .01). Table 1 reports the
background and clinical characteristics for the three groups. .
Insert Table 1 about here
Tasks & Measures
For more detailed descriptions see Bitsakou et al. 3,44
A) I-EDF tasks
i) Stop-Signal Task 54 : On six blocks (the first 2 blocks were practice) of 32 trials
participants responded to ‘go’ stimuli by pressing a response button and inhibited
their response when a auditory stop signal was presented (25% of trials). The go task
consisted of “X” and “O”, presented in the centre of the screen for 1000ms (ISI
2500ms). The interval between the go signal and stop tone varied to ensure
approximately a 50% success rate. The stop signal reaction time (SSRT) was
estimated by subtracting the mean stop signal latency from the mean correct go
response time in each block.
ii) Go/No-Go task (GNG): On 100 trials participants responded as fast and accurately
as they could to “go” stimuli by pressing the left or right computer mouse button
indicating the direction of a green left or right-pointing arrow respectively and
inhibited their response when a double headed arrow (“no-go” stimulus) was
presented (25 % of trials). The probability of a correct inhibition was the main index
of the GNG task.
iii) Modified Stroop Task (MStroop 55). 100 trials of congruent or incongruent stimuli
were presented. Congruent stimuli (75 % of trial) were green left or right pointing
arrows) and participants had to press a left or right computer mouse button indicating
the direction of the green arrows. Incongruent stimuli (25% of trials) were red, left or
right pointing arrows and participants had to press the opposite mouse button to that
indicated by the red arrows. Probability of inhibitions on the incongruent trials was
the dependent variable (MStroop).
B) DAv tasks
i) Maudsley’s Index of Childhood Delay Aversion (MIDA 56): This is a game like
computer-based choice delay task. 12 Individuals choose to either wait for 2 seconds
and shoot one spaceship (1 point) or to wait for 30 seconds to shoot two spaceships (2
points). There was no post-reward delay period. There were 15 trials. Children were
told that they would get either one or two rewards based on their performance,
although the specific cut-off was not revealed. Rewards were stationary items chosen
by participants at the end of the session. The percentage of large delayed choices
made is the dependent variable (MIDA).
ii) Delay Frustration (DeFT 57): A series of simple math questions (55 trials) were
presented on a computer. Participants selected from four possible answers by pressing
buttons on a box. On most trials response was immediately followed by the next trial.
On a minority of trials access to the next question was delayed by 20 seconds (8
trials). On eight distractor trials the delay period varied from 3 to 10 seconds. The
mean total duration of responding per second of delay in the 20 second trials was the
dependent variable. For the present analysis we used responses during the first 10
seconds as analysis showed that participants’ responses during these two periods may
be reflect different processes (i.e. early responses frustration and later responses
iii) Delay Reaction Time (DRT 58): On 12 trials (and 4 practice trials) a stimulus (either
a left or a right green arrow) appeared on the centre of the computer screen for either 3
or 20 seconds. The screen then turned blank and the participants responded as quickly
and accurately as possible to the disappearance of the stimulus, by pressing the left or
right mouse button. A DRT index was calculated by subtracting the mean RT score for
the two delay levels of the DRT task from the RT on a simple RT condition with no
delay (see 44 for details).
C) TPD tasks
i) Tapping 45: This is an auditory computerised task. An auditory tone was presented
every 1200 ms and the child had to tap along at the same pace by pressing a response
button (15 cued trials). In 41 uncued trials, in which the tone was not present, the child
was asked to continue tapping at the previously cued rate. The main index of the task is
the variability of tapping on uncued trials - calculated as the within subject standard
ii) Duration Discrimination 25: Participants were presented with two unfilled intervals
(target and comparison), each defined by two brief tones (50ms, 1000Hz) at the
beginning and end. The target interval of 400ms was randomly presented as either the
first or second duration. The comparison interval was always longer than 400ms and
was adjusted up or down in 10ms increments depending upon the accuracy of the
participant’s responses. The target and comparison interval were separated by 800 ms
and the inter-trial interval was 1000 ms. Participants were instructed to press the left
button on a response box if they thought the first tone was longer and the right button of
a response box if they thought the second tone was longer. An up-down-transformed-
response adaptive procedure was used to track 80% accuracy. 59 The procedure stopped
after 6 reversals of direction. The average of the last 5 reversal values was the
dependent measure. 25
iii) Time anticipation 45: In this game like task participants anticipated when a visual
stimulus would reappear. The child beamed oxygen over to a spaceship to save the
crew. In block 1 the anticipation interval was 400ms and in the block 2 it was 2000ms.
In each block the ally spaceship was visible for the first 10 trials and for the remaining
16 trials participants were asked to press a button to anticipate when it would arrive
(i.e., 400 or 2000ms). The participant was given feedback after every trial. The mean
percentage of total early responses (i.e., made before the ally arrived) was the
Working memory: Forward and backward digit span subscales from the WISC-III 60
were administered. The level at which the participant failed to correctly repeat numbers
on two consecutive trials at one level of difficulty was the dependent measure.
IQ: The vocabulary and block design subtests from the WISC-III 61 were used to
estimate full scale IQ. 62
Reading: The TOWRE test of word reading efficiency 61 was administered. The
combined score from the two sub-scales (sight word efficiency and phonetic decoding
efficiency) was used as a reading ability index.
Children with ADHD were off-medication at least 48 hours before testing. Probands
and siblings were tested by different researchers. Full testing took between 2 to 2 1/2
hours. The tasks within each neuropsychological domain (e.g., MIDA, DeFT and
DRT for DAv) were administered in the same order. The three neuropsychological
constructs (i.e., DAv, I-EDF, TPD) were presented in counterbalanced order. Children
rested during short breaks. The experimenter remained with each child throughout the
task. At the end of the session all children received a £5 voucher for participation in
addition to any MIDA rewards. Ethical approval was received from the University of
Southampton, School of Psychology ethics committee and the local NHS medical
ethics committee. Participants and parents gave written informed consent.
(i) Principal components factor analysis was used to examine the structure
of associations between the tasks. We chose an exploratory over a confirmatory
approach because this was the first analysis of its kind in the literature. To
maximize statistical power and allow a common metric by which controls,
probands and siblings could be compared all participants were included. Given
the correlation between age and performance (8 out of 9 were significant; r > -
.24), test scores were age-adjusted using standard regression procedures.
Factor scores (item to factor loadings as weightings) were calculated
and used to estimate case-control differences using ANOVA. We checked
whether case-control differences were due to group differences in IQ and ODD.
The number of ADHD patients (including affected siblings) with a
deficit in each of the neuropsychological domains identified in the factor analysis
was calculated using cut-offs based on the lowest 10 percent of scores in the
control group (11). We then examined the frequency with which individuals
showed one and not another types of deficit.
The association between these neuropsychological groupings in the
ADHD and comorbid psychiatric problems, IQ and literacy was examined using
Familiality was examined through inter-sibling correlations and
comparisons of; (i) probands, unaffected siblings and controls and (ii) unaffected
siblings of probands with and without domain specific deficit.
Insert Table 2 and Table 3 about here
Correlations (Table 2) were in general larger within domains (Mean r =.22) than
between domains ( Mean r =.11). Correlation between putative I-EDF and TPD
measures were moderate. Correlations between putative DAv measures were weak
and non-specific. WM was associated with TPD measures and DRT and MStroop. For
the principle components analysis there were four factors with eigen values greater
than one (Table 3). Component one (17.25% variance) had high loadings for SSRT,
GNG and MStroop only (factor labelled Inhibition). Component two (14.68%) had
high loadings for TPD items and WM (factor labelled Timing). The third and fourth
components both implicated delay-related tasks. Component three appeared to tap the
negative effect of imposed delay (12.95% of the variance) and was associated with
poorer DRT performance, increased DeFT responding and premature responding
during time anticipation. A preference for the large delayed reward (MIDA), reduced
DRT and better WM loaded on a fourth component (2.68% of the variance) –
suggesting the productive use of delay. Given their differential loadings these
components were labelled Delay-Negative and Delay-Positive respectively.
Insert Table 4 about here
Children with ADHD had poorer scores on all components (Table 4). No gender or
effects were found. The effects sizes (Cohen’s d) were .76 for Inhibition; .79 for
Delay-Negative; .67 for Timing and .51 for Delay Positive. Effects remained
significant controlling for IQ (Inhibition: F(1,116) = 17.53, p<.001; Delay Negative:
F(1,116) = 6.67, p<.05; Delay Positive: F(1,116) = 4.18, p<.05) except for Timing
(F(1,116) = 3.60, p=.06). The presence of ODD had no effect (Inhibition: F(1,67) =
3.24, p=.07; Timing: F(1,67) = 0.30, p=.86; Delay-Negative: F(1,67) = 0.07, p=.78;
Delay-Positive: F(1,67) = 0.001, p=.99).
Insert Figure 1 about here
Figure 1 presents a Venn diagram showing the proportion of ADHD cases who met
threshold for deficits in the Timing, Inhibition and the Delay domains. In order to
simplify the presentation of this categorical data we added those who met threshold
for Delay-Positive and Delay-Negative and included them in one group. Seventy one
percent of cases displayed some neuropsychological deficit. Timing was the most
common deficit and Inhibition the least. Overlap between the different deficits was
uncommon and never greater than expected by chance (Inhibition and Delay –
χ2=0.14; p=.91; Inhibition and Timing - χ2=2.75; p=.10; Timing and Delay - χ2=1.00;
p=.32) with over 70 percent of those affected showing just one deficit. Inhibition
showed the smallest proportion of ‘pure’ cases (31% compared to 56% for Timing
and 60% for any Delay). The three deficit categories were introduced as predictors
into multiple regression models with IQ, ODD and literacy as outcomes. Delay
deficits were associated with IQ (β=-.28; p=.012) and literacy (β=-.33; p=.002) while
Timing was significantly associated with literacy only (β=-.40; p<0.001). When IQ
was added as a predictor the effects of Delay (β=-.17; p=.11) but not Timing on
literacy (β=-.30; p=.004) were significantly reduced. Inhibition was associated with
neither cognitive outcomes (p>.3). No deficit predicted the presence of comorbid
The unaffected sibling scores were intermediate between probands and controls scores
(Table 4). Probands and siblings were impaired compared to controls on Timing,
Delay-Negative and Delay Positive. For Inhibition probands were more impaired than
both unaffected siblings and controls. Trends analysis suggested that siblings’ were
intermediate relative to ADHD probands and control cases except for Delay-Positive.
In contrast proband-sibling correlations were significant only for Inhibition (r=.31,
p=.01) and Timing (r=.34, p=.005; Delay-Negative- r=-.08, p=.48; Delay-Positive;
r=.009, p=.94). Multiple regressions with proband scores in the four domains as the
predictor and sibling scores on each domain as the outcome (forward stepwise
procedure) showed that these associations were homotypic in nature; i.e., sibling
domain scores were specifically predicted only by probands’ scores for Inhibition (R2
=.09; F(1,63)=6.94; p<.05) and Timing (R2 =.11; F(1,63)=8.46; p<.01) respectively.
Furthermore, siblings of probands with Inhibition deficits were more impaired on
Inhibition themselves than siblings of probands without Inhibition deficits
(t(63)=2.71, p<.01) but showed no other deficits (Timing; t(63)=0.04, p=.96; Delay-
Negative; t(63)=-1.21, p=.23; Delay Negative t(63)=0.36, p=.71; Table 5). Likewise,
siblings whose probands had Timing deficits had higher levels of these themselves
(t(63) = -2.17, p<.05) but not Inhibition, Delay-Negative or Delay Positive
(t(63)=0.14, p=.88; t(63)=-0.46, p=.64; t(63)=-.025, p=.80 respectively). No specific
familial effects were evident for the delay factors (Table 5).
Insert Table 5 about here
ADHD is neuropsychologically heterogeneous, with different individuals affected to
different degrees in different domains. 12,21 These results extend and refine the dual
pathway model of ADHD heterogeneity. 12-14 Our data provides the first evidence that
Timing, Inhibition and Delay deficits in ADHD are dissociable from each other and
that substantial sub-groups of patients are affected in only one domain. The results
therefore run counter to a recent suggestion that timing deficits may be the underlying
core of the diverse range of problems seen in ADHD. 35 The strongest evidence for
familial effects came for Inhibition 63-67,40 and Timing. 41-43,28 Indeed siblings of
probands with impairment in one of these domain also tended also to have problems
in these domains: Inhibition and Timing deficits in ADHD breed true. Consistent with
the previous inconsistent literature 68,69,63 evidence was much weaker for the familial
basis of the Delay components: While levels of sibling impairment were intermediate
between controls and probands, sibling correlations were weak and there was no
evidence of co-segregation. Finally, there was a degree of domain specific
association. Timing was associated with reading problems. Delay problems were
associated with low IQ and reading problems - though reading effects were mediated
Our findings challenge the delay aversion model 70 in which delay-related
processes in ADHD are seen as a single overarching construct. In fact, in the present
study, two components were found. The first associated with negative performance in
the face of imposed delay (i.e., DRT and DeFT), including time anticipation. The
second was associated with performance that depended on a commitment to wait for a
desired outcome or persist in a task even when this was not imposed (e.g., MIDA and
working memory). Clearly much more work is required to establish these as separate
components. Our prior analysis of performance on the “DAv” tasks 44 supported a
DAv single factor consisting of loosely associated test scores. When set alongside
tasks tapping other domains, it becomes clear that the situation is more complex than
The current study had a number of limitations. First, the sample used was small for
the examination of sub-groups and in future much larger studies using measures from
multiple domains are required to replicate these findings. The current analysis should
be seen as exploratory and illustrative. Second, measurement of working memory and
intelligence was limited.
From a clinical perspective highlighting the neuropsychological heterogeneity of
ADHD encourages us to explore; (i) the possibility of the existence of
neuropsychological subtypes and (ii) the significance of specific neuropsychological
deficits as both moderators of treatment effects and novel putative treatment targets.
In terms of (i), assuming they can be replicated in larger samples and validated using
clinical outcomes the current results would provide some support for the
establishment of neuropsychological sub-types in ADHD with distinctions drawn
between, for instance, Inhibitory and Timing ADHD subtypes. In terms of (ii), recent
studies suggest that cognitive training on executive tasks may have efficacy as a
treatment for ADHD. 71 The current results highlight the possibility that such training
will be more effective if it is targeted and tailored for children with problems in the
executive domain (e.g., I-EDF), while training that strengthens temporal processing or
delay-related functions might be more effective for patients with these types of