Developmental Psychology
1998, Vol. 34, No. 5, 956-%9
Copyright 1998 hy the American Psychological Association, Inc.
0012-1649/98/$3.00
A Neuropsychological Examination of the Underlying Deficit in
Attention Deficit Hyperactivity Disorder: Frontal Lobe Versus
Right Parietal Lobe Theories
Christine J. Aman, Ralph J. Roberts, Jr., and Bruce F. Pennington
University of Denver
A neuropsychological approach was used to examine the frontal lobe and right parietal lobe theories
of attention deficit hyperactivity disorder (ADHD). Considerable attempts were made to select as
pure a group of ADHD boys as possible. The performance of 10-14-year-old ADHD boys (n =
22), both on and off stimulant medication, was compared with the performance of non-ADHD control
boys (n = 22) on tasks purported to assess frontal lobe functioning (Stopping Task, Antisaccade Task,
Tower of Hanoi) and right parietal lobe functioning (Visual-Spatial Cuing Task, Turning Task, Spatial
Relations). Three important findings emerged: (a) unmedicated ADHD boys exhibited performance
deficits on tasks in both frontal and parietal domains compared with control boys, (b) unmedicated
ADHD boys appeared to be more severely impaired on the frontal tasks than on the parietal tasks,
and (c) medicated ADHD boys performed better in both task domains compared with unmedicated
ADHD boys. Several alternative interpretations of the results are discussed.
Attention deficit hyperactivity disorder (ADHD) is one of
the most commonly diagnosed childhood disorders as well as
one of the most extensively studied (see Barkley, 1990, for a
review). Despite the consideration this disorder has received,
fundamental questions remain unanswered, such as the nature of
the underlying cognitive and neurobiological deficits in ADHD.
Recent neurobiological and neuropsychological evidence suggests that two brain regions, the frontal lobes and the right
parietal lobe, may be implicated in ADHD. In the present study,
a neuropsychological approach was used to examine the frontal
lobe and right parietal lobe theories of ADHD in a carefully
selected group of children with the disorder.
functions, such as planning and implementing goal-oriented
strategies, controlling impulses, inhibiting prepotent responses,
shifting and maintaining strategy sets, and organizing and implementing search strategies (e.g., Fuster, 1985; Stuss & Benson,
1984) in addition to supporting working memory functions
(Goldman-Rakic, 1987). The parietal lobes are thought to be
specialized for integrating sensory input from visual regions of
the brain as well as from other sensory areas. The posterior
parietal cortex has been found to be essential for accurate visually guided motor activity and for spatial perception and spatial
attention (Andersen, 1988). The right parietal lobe appears to
be dominant for these functions, as right-hemispheric lesions
(in right-handed individuals) are associated with more frequent
and more severe deficits (e.g., Piercy, Hecaen, & Ajuriaguerra,
1960), including disturbances involving both hemifields (Heilman & Van Den Abell, 1980).
The frontal lobe theory of ADHD was introduced in the 1930s
when practitioners and investigators noted the behavioral similarities between patients with frontal lobe lesions and children
with ADHD symptoms (Levin, 1938). Both groups, it was observed, exhibit impaired response inhibition, excessive restlessness and distractibility, and inattention. The right parietal lobe
theory of ADHD was introduced more recently by investigators
who have observed that the attentional deficits and hypoarousal
often observed in ADHD children are similar to behavioral
symptoms observed in individuals with right parietal lobe damage (e.g., Mesulam, 1981; Vocller, 1986, 1991; Voeller & Heilman, 1988). Unlike the frontal theory of ADHD, which is associated with an overwhelming degree of face validity, the right
parietal theory of ADHD has received little attention. Tn any
case, evidence exists to support both theories.
Frontal Lobe and Right Parietal Lobe
Theories of A D H D
The frontal lobes of the brain, particularly the prefrontal regions, are thought to play a major role in performing executive
Christine J. Aman, Ralph J. Roberts, Jr., and Bruce F. Pennington,
Department of Psychology, University of Denver.
Portions of this work were presented at the annual meeting of the
American Psychological Society, San Diego, California, 1992, and at
the biennial meeting of the Society for Research in Child Development,
New Orleans. Louisiana, 1993.
This research was supported by grants from the University of Colorado's Developmental Psychobiology Endowment Fund, the MacArthur
Foundation, and the National Institute of Child Health and Human Development Center (HD27802) and by an American Psychological Association Dissertation Research Award, a National Institute of Mental Health
MERIT Award (MH38820), and a Research Scientist Development
Award (MH00419).
We thank A. Olmos-Gallo and S. Wiebke for their technical assistance
regarding the project.
Correspondence concerning this article should be addressed to Christine J. Aman, Department of Psychology, University of Denver, Denver,
Colorado 80208. Electronic mail may be sent to [email protected].
du.edu.
Neurobiological Evidence
Although previous studies using traditional brain imaging
techniques, such as computed tomography (CT) scans, have
956
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UNDERLYING DEFICIT IN ADHD
failed to find structural anomalies associated with the brains of
ADHD children (e.g., Harcherik et al., 1985; Shaywitz, Shaywitz, Byrne, Cohen, & Rothman, 1983), the results of recent
studies with high-resolution magnetic resonance imaging (MR1)
techniques suggest that such aberrations may exist. Hynd, Semrud-Clikeman, Lorys, Novey, and Eliopulos (1990) found that
unlike non-ADHD children whose frontal regions are asymmetrical with the left anterior region being smaller than the right,
ADHD children appear to have symmetrical anterior regions.
Similarly, Hynd et al. (1993) found reversed patterns of asymmetry of the head of the caudate nucleus, a portion of the basal
ganglia that is heavily connected to the prefrontal cortex; the left
region was smaller than the right in ADHD children, whereas it
was larger than the right in normal control children. In addition,
Hynd et al. (1991) have shown that areas of the corpus callosum
containing fibers connecting homologous anterior (frontal) and
posterior (parietal) cortical regions in the left and right hemispheres are smaller in ADHD children than in non-ADHD
children.
Results of functional imaging studies generally corroborate
these structural findings regarding ADHD. Specifically, Lou and
his colleagues (Lou, Henriksen, & Bruhn, 1984; Lou, Henriksen, Bruhn, Borner, & Nielsen, 1989), using regional cerebral
blood flow procedures, found hypoperfusion in the frontal lobes
and caudate-striatal regions of ADHD children at rest. The hypoperfusion of the striatal regions was ameliorated by the administration of stimulant medication (methylphenidate). More recently, Zametkin et al. (1990) found that adults who had ADHD
symptoms persisting since childhood, but who had never been
treated with stimulant medication, showed reduced cerebral glucose metabolism relative to non-ADHD adults in premotor and
superior prefrontal regions as well as in right posterior parietal
regions.
Neuropsychological Evidence
Children with ADHD have been found to perform poorly on
several neuropsychological tasks purported to assess frontal lobe
dysfunction. These tasks include the Wisconsin Card Sorting
Test (e.g., Boucugnani & Jones, 1989; Chelune, Ferguson,
Koon, & Dickey, 1986), the Stroop Test (e.g., Gorenstein, Mammato, & Sandy, 1989; Grodzinsky & Diamond, 1992), the Tower
of Hanoi (Pennington, Groisser, & Welsh, 1993), the Hand
Movements Test (e.g., Breen, 1989), and other motor control
tasks, such as the Go/No-Go Test (e.g., Shue & Douglas, 1992).
Deficits on these tasks involve response preservation, motor
disinhibition, planning difficulties, and inattention.
Neuropsychological evidence implicating the right parietal
lobe in ADHD comes from the Letter Cancellation Task, on
which ADHD children have been found to make significantly
more errors of omission and more left-sided errors than nonADHD children (Voeller & Heilman, 1988). In addition, the
performance of ADHD children has been found to be poor on
mental rotation tasks (Snow, 1990), resembling that of patients
who have sustained right parietal lobe damage (e.g., Ditunno &
Mann, 1990).
The Present Study
The present study was conducted in light of the foregoing
evidence suggesting frontal lobe and right parietal lobe involve-
ment in ADHD. The purpose of this research was to examine
the performance of a well-defined sample of ADHD boys on
frontal as well as parietal tasks in a single study and to examine
the effects of medication on this performance. Specifically, a
neuropsychological approach was used to examine the performance of 10- to 14-year-old ADHD boys, both on and off stimulant medication, on several tasks that are purported to assess
frontal lobe and right parietal lobe functioning compared to the
performance of age- and IQ-matched non-ADHD control boys.
Comparisons between the performance of the ADHD boys on
versus off stimulant medication were also made to assess medication effects on performance.
The tasks were selected because they have been shown to be
sensitive to frontal lobe or right parietal lobe functioning or
because they are similar to tasks that have been shown to be
sensitive to the functioning of one of these brain regions and
are experimentally more rigorous than the original tasks. Three
tasks that are purported to assess frontal lobe functioning (Stopping Task, Antisaccade Task, Tower of Hanoi) and three tasks
that are thought to be sensitive to right parietal lobe functioning
(Visual-Spatial Cuing Task, Turning Task, Spatial Relations)
were included.
Research Questions
There were three main questions addressed in this study. The
primary question of interest concerned which theory, the frontal
lobe theory of ADHD or the right parietal lobe theory of ADHD,
would be supported. Given the existing neuropsychological and
neurobiological findings regarding ADHD, we expected the
ADHD children to exhibit deficits on aspects of tasks in both
the frontal and the parietal domains. A related question was
whether the ADHD boys would exhibit more severe deficits on
one set of tasks compared to the other. Given the lack of studies
that have taken a neuropsychological approach to test both frontal lobe and right parietal lobe deficits in the same group of
ADHD children, no specific predictions were made regarding
the relative severity of these putative deficits. The third, and
final, question of interest involved whether stimulant medication
would differentially affect performance on the frontal and parietal tasks. Specifically, we were interested in whether stimulants
would reduce or even eliminate any deficits exhibited by the
ADHD boys off medication. In general, we expected that stimulant medication would be associated with better overall performance in the ADHD children compared to their off medication
performance.
Method
Participants
The participants were 22 ADHD boys (21 Caucasian, 1 Hispanic)
and 22 non-ADHD control boys (21 Caucasian, 1 Hispanic) 10 to 14
years of age, who were paid for their participation. All of the boys were
right-handed, as demonstrated on the Edinburgh Handedness Inventory
(Oldfield, 1971), and most were from middle- to upper-middle-class
families, as measured by the Two Factor Index of Social Position (Hollingshead, 1957). The boys in the two groups were matched pairwise
on age (within 7 months) and on an estimate of IQ (within 6 points).
Descriptive characteristics of the sample are presented in Table 1.
958
AMAN, ROBERTS, AND PENNINGTON
Table 1
Descriptive Characteristics and Criterion and Related Measures: Mean Scores, Standard Deviations, and Group Differences
Group
Measure
ADHD
Group
Control
Measure
P
ADHD
Descriptive characteristics
Age (years)
M
SD
WISC-R IQ estimate
M
SD
WISC-R Vocabulary
M
SD
WISC-R Block Design
M
SD
Holhngshead Index
M
SD
Mother's education3
M
SD
Father's education"
M
SD
P
1.04
0.09
1.10
0.16
ns
1.95
1.33
0.55
0.60
<.001
12.66
2.00
13.95
2.73
ns
13.09
2.00
13.07
1.92
ns
70.64
8.88
55.95
2.80
<.001
67.86
8.58
55.55
0.91
<.001
0.95
1.40
0.32
0.72
ns
2.86
2.68
2.14
2.88
ns
4.27
3.83
3.14
3.48
ns
7.14
6.16
5.27
6.18
ns
Reading measures
12.14
1.21
12.13
1.21
ns
110.50
8.18
110.00
7.34
ns
12.00
2.27
11.41
1.82
ns
11.55
2.22
12.00
2.07
ns
28.64
15.31
24.14
6.66
ns
2.45
1.14
2.09
0.75
ns
2.32
1.21
1.86
0.64
ns
ADHD criterion measures
CBCL: T score Hyperactive scale
M
SD
DICA: number of ADD symptoms
M
SD
HSQ: % of situations
M
SD
Control
80.41
6.71
55.00
0.00
<.001
17.00
2.90
1.50
1.50
<.001
75.14
17.73
12.36
9.38
<.001
Reading quotient
M
SD
Child Reading Questionnaire
M
SD
Gray Oral Reading age
M
SD
WRAT-R Spelling age
M
SD
Conduct disorder measures
CBCL
M
SD
CBCL
M
SD
RBPC
M
SD
SRED
M
SD
SRED
M
SD
SRED
M
SD
Aggression
Delinquency
Socialized Aggression
Illegal
Norm Violating
Total
Note. ADHD = attention deficit hyperactivity disorder; WISC-R = Wechsler Intelligence Scale for Children—Revised; CBCL - Achenbach
Child Behavior Checklist; DICA = Diagnostic Interview for Children and Adolescents; ADD = attention deficit disorder; HSQ = Home Situations
Questionnaire; WRAT-R = Wide-Range Achievement Test—Revised; RBPC = Revised Behavior Problem Checklist; SRED = Self-Reported Early
Delinquency Instrument.
i
Education level: 1 = graduate/professional degree; 2 = 4-year college degree; 3 = partial college training (including 2-year degree}; 4 = high
school degree; 5 = less than a high school degree.
The ADHD children were recruited through a local support group for
parents of ADHD children and through two suburban school districts
in Denver, Colorado. The control children were recruited through a
participant pool in the Psychology Department at the University of
Denver.
At the time of the study, all of the ADHD children were being treated
with stimulant medication and were responding favorably to this medication on the basis of parental report. Of the 22 ADHD boys, 20 were
taking Ritalin or methylphenidate (14 regular release; 6 sustained release) and 1 each was taking sustained-release Dexedrine or dextroamphetamine and sustained-release Cylert or pemoline. For the boys on
Ritalin or methylphenidate, both the mean and median daily dosages
were about 30 mg, with individual daily dosages ranging from 10 to
100 mg. None of the children were taking concurrent psychotropic medications (e.g., antidepressants) at the time of the study. Parents of the
ADHD children reported that the mean age of onset of their boys'
ADHD symptoms was 2 years 6 months, but ranged from less than 1
year 0 months to 6 years 11 months of age.
Research and Diagnostic Criteria
For this study, considerable attempts were made to reduce the methodological problems associated with previous ADHD research by selecting
as homogenous a group of ADHD boys as possible. Specifically, the
boys were screened for comorbid psychiatric disorders, such as conduct
disorder and reading disability, which have contributed to a conflicting
pattern of findings across the ADHD literature (Barkley, 1990), as well
as for serious problems or conditions that otherwise could confound the
results (e.g., gross neurological damage, sensory-motor handicaps). An
initial phone contact with parents of potential participants and a session
conducted at the University of Denver in which information was obtained
regarding IQ, reading ability, family environment, ADHD symptomatology, and current stimulant medication usage facilitated the screening for
such confounding factors. None of the boys who participated in the
screening session were excluded from participation because of low IQ
(i.e., IQ < 80 on the Wechsler Intelligence Scale for Children—Revised
[WISC-R]; Wechsler, 1974) or because of a severely chaotic, abusive,
959
UNDERLYING DEFICIT IN ADHD
or deprived family environment based on information provided on a
supplemental parent questionnaire. Twenty-two potential ADHD participants and 12 potential control participants were excluded for exhibiting
a reading disability based on the calculation of a reading quotient (described below), 1 potential ADHD participant and 5 potential control
participants were excluded for not meeting the diagnostic criteria for
their respective group (described below), and 1 ADHD boy and 25
control boys who otherwise met the research criteria were excluded
because they could not be matched with a boy in the alternate participant
group.
The primary inclusionary or diagnostic criteria for the ADHD group
were based on the Diagnostic and Statistical Manual of Mental Disorders (3rd ed., rev.; DSM-III-R; American Psychiatric Association
[APA], 1987) although supplemental criteria were added to further restrict our ADHD sample. These criteria are described in Table 2. For
each of the criterion measures, parents rated their child's off-medication
behavior. Restrictive cutoff scores were used for each measure to minimize the chances of including nonhyperactive boys in our ADHD group.
All of the ADHD boys met or surpassed the criterion on each of the
three ADHD measures, with one exception; 1 boy was just below the
criterion on the Child Behavior Checklist (Achenbach & Edelbrock,
1983) Hyperactivity scale (T score == 66) but was included in the ADHD
group because he received a score of 15 on the Attention Deficit Disorder
scale of the Diagnostic Interview for Children and Adolescents (Herjanic, 1983), which is very high.
In light of the recently published Diagnostic and Statistical Manual
of Mental Disorders (4th ed.; DSM-IV; APA, 1994) criteria for ADHD,
it was deemed important to attempt to describe our ADHD sample in
terms of the current classification system. Review of the responses on
the criterion measures suggests that 16 of our ADHD boys would meet
the DSM-IV criteria for both the inattentive and hyperactive-impulsive
subtypes, whereas 4 boys would meet the criteria for the inattentive
subtype only and 2 boys would meet the criteria for the hyperactiveimpulsive subtype only.
Consistent with the DSM-II1-R criteria for ADHD, our sample was
defined primarily by information provided from the boys' parents. Although information was not obtained from the boys' current classroom
teachers for this study, the investigators did request information contained in their cumulative school records. The information that was
provided, although not standard across children, was used to verify that
the boys indeed experienced ADHD symptomatology at school during
kindergarten or first grade. Thus, together with the information provided
by the parents, the information provided by the schools suggests that
this sample of ADHD boys exhibits behavioral difficulties across situations (i.e., both at home and at school).
Table 2
Criteria for Inclusion in the Attention Deficit Hyperactivity
Disorder (ADHD) and Control Groups
Criterion measure
Child Behavior Checklist1
Hyperactive T Score
Diagnostic Interview for Children
and Adolescents^
Number of ADD symptoms
Home Situations Questionnaire0
% of situations
ADHD
Additional Measures and Indexes
Several measures were included to assess the presence of reading
difficulties and the degree of conduct-disordered symptomatology in our
ADHD sample. Two conduct-disorder measures based on parental report
were administered: (a) the Socialized Aggression (SA) scale from the
Revised Behavior Problem Checklist (RBPC; Quay & Peterson, 1987),
which assesses rejection of authority and societal norms and (b) the
CBCL Delinquency and Aggression scales, which assess more general
conduct problems. In addition, each boy was administered the SelfReport Early Delinquency Instrument (SRED; Moffitt & Silva, 1988)
to assess "norm-violating" behaviors such as cheating and more serious
illegal behaviors such as carrying a weapon. Also, a two-subtest, shortform of the WISC-R (Wechsler, 1974), consisting of the Vocabulary
and Block Design subtests, served as a screening device for identifying
boys with below-average IQs as well as a means for matching boys in
the two groups on general intellectual functioning.
Each of the measures included in the study has been found to have
adequate reliability and validity for research purposes (CBCL: Achenbach & Edelbrock, 1983; DICA: Edelbrock & Costello, 1984; Home
Situations Questionnaire [HSQ]: Barkley, Fischer, Newby, & Breen,
1988; RBPC: Quay & Peterson, 1987; SRED: Moffitt & Silva, 1988;
WISC-R estimate: Wechsler, 1974).
A reading quotient (RQ) was calculated for each of the participating
boys to determine reading ability in this study. The RQ, as described
by Finucci, Isaacs, Whitehouse, and Childs (1982), represents the ratio
of observed reading level to expected reading level. In the RQ formula,
the observed reading level reflects the average of the age-equivalent
score obtained on the Spelling subtest from the Wide Range Achievement
Test—Revised (WRAT-R; Jastak & Wilkinson, 1984) and the reading
age score obtained on the Gray Oral Reading Test (Gray, 1963). The
expected reading level reflects the average of the child's chronological
age, mental age (IQ/chronological age), and age equivalent of the child's
grade level. Only children with RQs greater than or equal to .90, which
is considered normal (Finucci et al., 1982), were included.
The Child Reading Questionnaire (CRQ; DeFries, Olson, Pennington, & Smith, 1991) was also included to facilitate the identification
of boys with reading difficulties. The CRQ assesses parental perceptions
of their child's past and current reading problems as well as behaviors
often associated with dyslexia. Children with borderline RQs (i.e., in
the low .90s) and a history of reading problems, as reported on the
CRQ, were excluded to reduce the chances of including remediated
dyslexic children in our study.
Experimental Tasks
The Stopping Task, Antisaccade Task, Visual-Spatial Cuing Task, and
Turning Task were programmed on an IBM-compatible computer with
the Micro Experimental Laboratory software (MEL; Schneider, 1988).
Brief descriptions of the experimental tasks are presented here; more
detailed information may be obtained from Christine J. Aman, Ralph J.
Roberts, Jr., and Bruce F. Pennington.
Control
Frontal Tasks
^70
^60
<6
<33
^50
Note. ADD = attention deficit disorder.
a
Achenbach and Edelbrock, 1983. b Herjanic, 1983.
Edelbrock, 1987.
c
Barkley and
Stopping Task. The Stopping Task is a computerized measure of
inhibitory control that is based on a formal theory of inhibition (Logan &
Cowan, 1984; Logan, Cowan, & Davis, 1984). It is similar to the go/
no-go tasks on which frontally lesioned adult humans (Drewe, 1975)
and nonhuman primates (e.g., Mishkin, 1964) have been found to exhibit
deficits but is experimentally more rigorous (see Logan & Cowan, 1984;
Logan et al., 1984). The Stopping Task may also reflect working memory
because of the association between working memory and the inhibition
of prepotent responses (e.g., Roberts, Hager, & Heron, 1994). Schachar
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AMAN, ROBERTS, AND PENNINGTON
and Logan (1990) found that ADHD children exhibit inhibitory control
deficits on the Stopping Task.
The Stopping Task consists of two types of trials: primary task trials
and stop-signal trials. On primary task trials, the letters X or O are
presented in the center of the video screen and the child responds by
pressing the corresponding key on a keyboard. On stop-signal trials, the
X or O is presented along with a tone, or stop signal, which instructs
the child to inhibit his key press to the primary task stimulus. The tones
were presented randomly at 500 ms, 350 ms, 250 ms, and 100 ms before
the child's mean reaction time (MRT). The child sat in front of a video
monitor with his left and right index fingers on the two randomly labeled
X and O keys. For each trial, a cross-shaped fixation point was presented
in the center of the screen (500 ms), followed by the letter for that trial
(1,000 ms), and then a blank screen (1,500 ms).
The children completed six blocks of trials for this task. The first
block, consisting of 32 primary task trials (16 each of X and O), helped
to familiarize the children with the task and yielded an MRT that was
used for determining the tone intervals for the second block of trials.
The children were instructed to press the key as soon as they had decided
which letter was presented. The second block consisted of 48 practice
trials in which 16 stop-signal trials (4 trials at each of the 4 intervals)
were randomly interspersed with 32 primary task trials. The remaining
four blocks of 48 trials constituted the experimental trials for the study.
These blocks were equivalent to the second block and to each other with
two exceptions: (a) the trials within each block were presented in different random orders and (b) the stop-signal intervals for each block varied
according to the MRT for the primary task trials in the immediately
preceding block. A total of 128 primary task trials and 64 stop-signal
trials were included.
The main dependent measure for this task is the probability of inhibiting a response at each of the stop-signal intervals, with the slope of
this inhibitory function of particular importance. Because ADHD children often exhibit long and highly variable reaction time latencies (e.g.,
Douglas, 1988), it is important to separate deficiencies in primary task
processes from deficiencies in inhibitory processes on the Stopping Task.
This can be done by computing the relative finishing time (RFT) of the
inhibitory process (i.e., the internal reaction time to the stop signal) and
primary task process and converting this score into a Z score (ZRFT,
as described by Logan et al., 1984). If the inhibition functions for the
two groups cannot be aligned at the two sessions by plotting them as a
function of ZRFT. then the steeper functions are thought to reflect better
inhibitory control.
Antisaccade Task. The Antisaccade Task, which is based on a task
described by Hallett and Adams (1980), is thought to measure inhibitory
control and working memory (Roberts et al., 1994) and has been found
to be sensitive to frontal lobe dysfunction in adult humans (Guitton,
Buchtel, & Douglas, 1985). This task involves inhibiting a reflexive
response (a saccade in the direction of a cue) and the generation and
initiation of an alternative response (a saccade in the direction opposite
from the cue). For each trial, a small cross-shaped fixation point (FP)
was presented in the center of a video screen (500-3000 ms), followed
by the cue (a 1° X 1° square) randomly presented 10° to the right or to
the left of the FP (100 ms). Approximately 400 ms after the onset of
the cue, the larget appeared on the side opposite from the cue (150 ms)
and then was masked. The target consisted of a three-sided .]/2° X '4°
square surrounded by a square identical to the cue stimulus. Participants
were told not to look in the direction of the cue but rather an equal
distance from the FP in the direction opposite from the cue. Participants
were additionally instructed to indicate the open side of the target square
by pressing the corresponding left, right, or up arrow key on a keyboard.
Several practice trials preceded the 42 experimental trials for this task.
There were 7 trials in each of the six cells corresponding to the orthogonal combinations of the three gap locations (left, right, and top) and the
two sides on which the cue appeared.
To control for potential confounding factors (e.g., ability to make eye
movements to a target), a Prosaccade Task, on which frontal patients
have not demonstrated deficits (Guitton et al., 1985), was also included.
The Prosaccade Task was identical to the Antisaccade Task, with two
exceptions: (a) participants were instructed to look in the direction of
the cue rather than in the opposite direction and (b) die cue-target onset
asynchrony in the Prosaccade Task was 300 ms rather than 400 ms. The
42-trial Prosaccade Task was performed prior to the Antisaccade Task
to help scaffold the instructions and button press responses for the
more difficult task. Each group at each of the two sessions had a mean
proportion of correct prosaccades of at least .98.
During the saccade tasks, the participant sat in a darkened room with
his chin on a molded chin rest and his forehead leaning against a cloth
restraint to help minimize head movements. The participant's eyes were
about 62 cm from the video monitor. Eye movements were recorded
with a pupil-comeal reflection eye tracker (see Roberts. Brown,
Wiebke, & Haith, 1991). Looking locations were recorded 60 times per
second and were accurate within %° of visual angle. The eye movement
data were scored by hand with reliable heuristics for determining when
saccades occur (Roberts et al., 1991). A brief calibration task was
administered before the saccade tasks. For each trial of the saccade
tasks, the latency and direction of the saccades were recorded. The
primary dependent variable of interest was the accuracy of the saccades.
Tower of Hanoi. The Tower of Hanoi is a measure of planning ability
requiring the formulation and execution of a strategy in accordance with
a set of rules to achieve an externally imposed goal (e.g., Simon, 1975).
Impaired performance on the Tower of Hanoi or a similar task has been
exhibited by frontally damaged adults (Shallice, 1982) and children
(Levin et al., 1994) and, more recently, by ADHD boys compared with
normal and dyslexic controls (Pennington et al., 1993).
The materials for the Tower of Hanoi consist of two identical boards
(one for the child and one for the experimenter), each holding three
tapered vertical pegs arrayed in a straight line and three (or four) plastic
rings of graduated sizes that fit on the pegs. There are three rules: (a)
a larger ring may not be placed on top of a smaller ring, (b) only one
ring may be moved at a time, and (c) a ring has to be moved to one of
the child's pegs {not placed on the table or on the experimenter's board).
The experimenter's board displays the desired goal state, a 3- or 4-ring
pyramidal configuration. The initial setup of the rings on the child's
board (i.e., the start state) differs for each problem.
Five experimental problems were administered in order of increasing
difficulty. The difficulty of a problem is defined by the number of moves
associated with its optimal solution; problems requiring fewer moves to
solution are considered easier than problems requiring more moves. A
solution is correct if the goal state is replicated in the fewest number
of moves. To pass a problem, the child had to correctly solve the problem
on two consecutive trials out of a maximum of six trials. Once a child
passed a problem, the next problem was administered. The task was
terminated when a child failed two consecutive problems. Points were
assigned per problem on the basis of the number of trials the child
needed to pass it (correct solutions on Trials 1 and 2 = 6 points; on
Trials 2 and 3 = 5 points, etc.) as described by Borys, Spitz, and Dorans
(1982). Failed problems received a score of 0. Summing the points
across the individual problems yielded a total score (maximum = 30
points).
Parietal Tasks
Visual-Spatial Cuing Task. The Visual-Spatial Cuing Task is a measure of visual-spatial attention used by several researchers on which
patients with parietal lobe damage have demonstrated difficulty in "disengaging" their attention from invalid cues presented to the ipsilesional
visual field (e.g., Baynes, Holtzman, & Volpe, 1986; Morrow & Ratcliff,
1987; Posner, Inhoff, Friedrich, & Cohen, 1987). In this version of the
961
UNDERLYING DEFICIT IN ADHD
task, two boxes of equal size (1.7 cm X 1.9 cm) and a cross-shaped FP
(3 mm X 3 mm) were displayed horizontally across a video screen,
with the two peripheral boxes positioned approximately 7V2° from the
central FP. Participants were instructed to maintain fixation on the FP
throughout the task. Each trial began when the outline of either one or
both of the peripheral boxes turned bright green, presumably eliciting
a covert shift of attention to that location. This cue was followed randomly at intervals of 100 ms or 500 ms by a target stimulus (an asterisk)
presented in the center of one of the two peripheral boxes. Participants
made a single key press with their right hand as soon as they detected
the target.
There were three types of trials: valid, invalid, and neutral. A valid
trial consisted of the brightening of one of the peripheral boxes followed
by the presentation of the target in the same box. An invalid trial was
one in which the target appeared in the box on the side opposite from
the one that was brightened. On neutral trials, both of the peripheral
boxes brightened and the target appeared in only one of the boxes.
The 240 experimental trials were administered in five blocks of 48
trials. The breakdown of the types of trials within each block was based
on two visual fields (right, left), three cue types (valid, invalid, neutral)
and two cue-target intervals (100 ms, 500 ms). For the visual field and
cue-target interval variables, each of the associated levels occurred with
equal frequency. For the cue type variable, valid cues occurred on two
thirds of the trials, whereas invalid cues and neutral cues each occurred
on one sixth of the trials. The main dependent measures for this task
were the RTs associated with the various types of trials.
Turning Task. The Turning Task (Roberts & Aman, 1993) is thought
to assess mental rotation, a process that has been shown to be sensitive
to the functioning of the right parietal lobe (e.g., Deutsch, Bourbon,
Papanicolaou, & Eisenberg, 1988; Ratcliff, 1979). For this task, an
isosceles triangle (1.2 cm wide at the base, 2.2 cm high) was displayed
in the center of a video monitor. The triangle was displayed at one of
seven orientations, at 0° (facing straight up) and at rotated positions
45°, 90°, and 135° to the left and right of 0°. A small dot was displayed
approximately 3.5 cm to the left or the right side of the base of the
triangle.
The children sat in front of a video monitor with their left and right
index fingers resting, respectively, on left and right arrow keys. The
children were instructed to decide the shortest direction in which the
triangle should turn to point toward the dot and to press the corresponding arrow key as soon as they had made their decision. Prior to the
experimental trials, each child demonstrated his ability to reliably identify the front, back, left, and right sides of the triangle at the various
triangle orientations. The task consisted of 140 trials, with 10 left turns
and 10 right turns at each of the seven triangle orientations. For each
trial, the computer recorded the child's RT and the accuracy of his turn
decision, with the latter measure considered to be the primary dependent
variable.
Spatial Relations. Spatial Relations, a visual processing subtest from
the Woodcock-Johnson Psycho-Educational Battery—Revised (Woodcock & Johnson, 1989), was included as a second measure of mental
rotation. For each of the 33 test items, the child was presented with a
target figure and a series of potential component shapes, from which he
had to choose the two or three shapes that fit together to make the whole
target shape. The dependent measure was the number of items solved
correctly.
Procedure
All children participated in a 1 -hr screening session during which the
parents completed the research questionnaires and the children were
administered the Edinburgh Handedness Inventory, the WISC-R Vocabulary and Block Design subtests, the WRAT-R Spelling subtest and the
Gray Oral Reading Test, and the SRED instrument. The ADHD boys
were tested off medication at this screening session because it was
thought that borderline reading-disabled boys would be more likely to
fall below the cutoff when they were off medication, resulting in their
exclusion from the study. Also, it was thought that the IQ estimates for
the ADHD boys might be lower off medication and that matching the
control boys with the ADHD boys on their off medication IQ scores
would result in a more conservative control group. For this session, the
mean number of hours since the ADHD children's last dose of medication was 16.9 (SD = 20.62; Mdn = 9).
Children who met all of the criteria for the ADHD group or the control
group completed the series of experimental tasks twice, in 1- to 1.5-hr
long sessions approximately 1 week apart. The experimental tasks were
presented in the same fixed order for both of the experimental sessions
(Antisaccade Task, Visual-Spatial Cuing Task, Spatial Relations, Stopping Task, Tower of Hanoi, and Turning Task). The ADHD boys were
on medication at the first experimental session and off medication at the
second experimental session. For this study, a child was considered to
be ' 'off'' medication when he had not taken his medication for at least
9 hr before the beginning of the testing session and " o n " medication
when he had taken his medication approximately 1 hr before the beginning of the testing session. These time intervals reflect the findings that
the sustained-release preparations of Ritalin or methylphenidate, Cylert
or pemoline, and Dexedrine or dextroamphetamine have positive behavioral effects from approximately 1 to 9 hr after ingestion (Pelham et al.,
1990), whereas the behavioral effects for the regular dose of Ritalin or
methylphenidate last from 1 to 4 hr after ingestion (Swanson, Kinsbourne, Roberts, & Zucker, 1978). The mean number of hours since the
ADHD children's last dose of medication was 1.27 hr (SD ~ .63; Mdn
= 1) for Session 1 and 43.32 hr (SD = 35.20; Mdn = 24) for Session
2. Six of the 22 ADHD boys did not take their medication for a full
week prior to Session 2 because they were out of school for the summer
and only took their medication regularly when school was in session.
Medication order was not counterbalanced across sessions because of
the relatively small sample of children and the concern that counterbalancing the medication order might increase the variance of the results
by introducing differences due to the drug order or its interactions. The
" o n " then "off " medication order was chosen because it was thought
that learning effects across the two sessions might minimize the expected
decrease in performance off medication and thus reduce the chances of
detecting differences between the medication conditions.
Results
Child and Family Characteristics
There were no significant differences between the ADHD and
control groups in terms of age, IQ estimate, Block Design or
Vocabulary standard scores, socioeconomic status (Hollingshead Index), mother's education, and father's education (see
Table 1).
Criterion and Related Measures
ADHD Measures
As expected, the ADHD group was rated higher than the
control group on the three ADHD criterion measures (see Table
1).
Reading Measures
The two groups did not reliably differ in terms of RQ, Gray
Oral Reading age, or WRAT-R Spelling age; however, they
were reliably different on the number of problems indicated on
962
AMAN, ROBERTS, AND PENNINGTON
the CRQ, /(42) = 4.54, p < .001, with a greater mean number
of problems for the ADHD boys compared with the controls
(see Table 1). It seems plausible that the higher score for the
ADHD group on the CRQ can be accounted for by the inclusion
of ADHD-like symptoms involving inattention, distractibility,
and fine motor control (e.g., problems remembering complex
instructions and keeping one's place on a page while reading,
poor penmanship), rather than the presence of specific reading
difficulties, especially because the mean scores for both groups
are well below the clinical cutoff on the CRQ. Intercorrelations
between each of the ADHD criterion measures and CRQ scores
support this hypothesis, all rs (42) > .50, p s < .001. In contrast,
RQ, which is an objective measure of reading and spelling skills,
did not correlate with any of the ADHD criterion measures.
Frontal Tasks
p = .001, Session x Interval, F{3, 116) = 2.76, p = .05, and
Group x Session, F ( l , 42) = 7.11, p < .05, interactions. The
three-way interaction involving group, session, and the linear
component of stop-signal interval was not statistically significant, F ( l , 116) - 3.70, ns. For the ADHD group, planned
univariate comparisons revealed significantly worse ability to
inhibit at Session 2 compared with Session 1 at the 250-ms,
350-ms, and 500-ms intervals, all te(21) a 2.40, p < .05.
Planned univariate comparisons for Session 2 showed that the
ADHD group performed significantly worse than the control
group at the 350-ms and 500-ms intervals, all /s(42) > 2.09,
ps < .05; planned univariate comparisons for Session 1 yielded
no reliable differences between the two groups at any of the
stop-signal intervals.
In general, the slope of the inhibition function across the four
stop-signal intervals for the unmedicated ADHD boys (i.e., at
Session 2) was flatter relative to the slope for the control boys
at both of the sessions and relative to their own slope when they
were medicated (at Session 1). This flatter inhibition function
is thought to reflect less efficient and slower inhibitory processes
in the unmedicated ADHD boys (see Logan et al., 1984). The
group main effect was not significant, F ( l , 42) = 1.19, p —
.28; however, the session main effect was significant, F ( l , 42)
= 5.54, p < .05, indicating that performance was worse at
Session 2 than at Session 1 because of the poorer performance
of the unmedicated ADHD boys.
The inhibition functions were plotted as a function of ZRFT
(relative finishing times of the inhibitory process and the primary task process converted to Z scores) to determine whether
the flatter slope exhibited by the unmedicated ADHD group was
due to an inefficient or a slow inhibitory mechanism rather than
to variability associated with primary task processes or with
internal reaction time. These functions, which reflect adjustments for differences in primary task variability and internal
reaction time to the stop signal, are shown at the bottom of
Figure 1. As can be seen, the ZRFT correction does not completely eliminate the differences between the inhibitory functions of the ADHD boys and the controls at Session 2. The
differences in the inhibitory functions remained because the
ADHD boys, while off medication, inhibited their responses
within a smaller range of reaction times compared with the
controls. A test of the linear component of the three-way interaction involving group, session, and stop-signal interval was significant, F ( l , 42) = 9.66, p < .01, indicating that the inhibition
functions of the ADHD boys were not as steep as those of the
control boys, but only when the ADHD boys were off medication (Session 2).
Stopping Task. The main dependent variables involve the
probability of inhibiting the button press to the presented letter
at each of the stop-signal intervals and the slope of the inhibition
function. A MANOVA with session (two levels) and stop-signal
interval (four levels) as repeated measures and group as a between-subject variable was conducted for the probability of inhibition given a stop signal. As shown in Figure 1, the probability
of inhibiting increased with stop-signal interval for both of the
groups at both of the sessions, F(2, 90) = 291.42, p < .001.
However, this effect was expressed differently for the ADHD
and control groups and at the two sessions. These differences
were shown by significant Group X Interval, F(2, 90) = 6.97,
Antisaccade Task. For the Antisaccade Task, the variable of
particular interest was the accuracy of the eye movements, or
saccades. Preliminary analyses revealed that the side on which
the cue was presented was not associated with any significant
main effects or interactions, thus data were collapsed across this
variable for the analyses reported below. The only repeated
measure included in the MANO\5\ for this task was session.
The saccade accuracy for the Antisaccade Task was quite low
for both groups. The mean proportion of correct antisaccades
increased for the control boys from .32 (SD = .22) to .43 {SD
= .25) across the two sessions, whereas it decreased for the
ADHD boys from .38 (SD = .27) to .33 {SD = .20). The
Conduct Disorder Measures
Although the boys in the two groups were screened for overt
behavioral manifestations of delinquency (e.g., fire setting, recurrent shoplifting) and previous conduct-disorder diagnoses,
there were statistically reliable differences between the groups
on two of the conduct-disorder measures (see Table 1). Specifically, the ADHD boys received higher scores than the control
boys on the CBCL Aggression, /(42) = 7.40, p < .001, and
Delinquency, f(42) = 6.70, p < .001, subscales. However, the
ADHD and control boys did not reliably differ on the RBPC
Socialized Aggression scale, the SRED total score, or the SRED
Illegal or Norm Violating scales. Furthermore, the mean scores
for the two groups of boys in this study on these latter measures
are well below the mean scores for boys with known conduct
disorder (RBPC: Quay & Peterson, 1987; SRED: Moffitt &
Silva, 1988).
Experimental Tasks
For each of the experimental tasks, repeated measures multivariate analyses of variance (MANOVAs) were conducted, with
session as a repeated measure (reflecting the ADHD boys' performances " o n " vs. "off" medication) and group as a between-subject variable. For analyses requiring the inclusion of
a second, multilevel repeated measure (e.g., the four stop-signal
intervals for the Stopping Task) the Geisser-Greenhouse correction was applied (Geisser & Greenhouse, 1958) to reduce the
heightened Type I error rate.
963
UNDERLYING DEFICIT IN ADHD
Session 1
-ADHD
Session 2
-Control
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Figure 1. (Top) Probability of inhibition on the Stopping Task as a function of session, group, and stopsignal interval. (Bottom) Probability of inhibition on the Stopping Task as a function of session, group,
and Z score of relative finishing times (ZRFT) of the inhibitory and the primary task processes. ADHD =
attention deficit hyperactivity disorder.
Group X Session interaction was statistically reliable, F( 1, 40)
= 11.86, p < .001. Planned univariate analyses for the Antisaccade Task indicated that the control group's performance significantly improved from Session 1 to Session 2, t(l9) = 3.02,
p < .01, whereas the ADHD group's performance stayed the
same, ((21) = 1.78, ns. The ADHD and the control groups did
not reliably differ from each other in terms of mean proportion
of correct antisaccades at either of the sessions.
Other researchers who have studied the performance of children on the Antisaccade Task have found better overall ability
to suppress reflexive saccades than that obtained in this study
(e.g., Rothlind, Posner, & Schaughency, 1991). One major difference between our version of the task and those used in other
studies may explain the discrepant findings. In the present study,
the fixation point was extinguished before the cue was presented
rather than left on throughout the trial, as in other studies. Our
participants may have found it more difficult to refrain from
making reflexive saccades in the direction of the cue because
they did not have the fixation point on which to maintain their
gaze. In fact, Rothlind et al. found that the ADHD and the
control participants made at least 10% more reflexive saccades
when the fixation point was turned off than when it remained
on. Different versions of the Antisaccade Task consist of variations in terms of scoring of saccades, including or excluding a
secondary task (e.g., indicating the direction of the open side
of the target stimulus), and including or excluding "visually
triggered'' saccades, all of which could contribute to dissimilar
findings regarding accuracy that have been observed across
studies.
Tower of Hanoi. The dependent measure for the Tbwer of
Hanoi consisted of the total score (i.e., the sum of the scores
for the individual three- and four-ring problems). The mean
total scores for the control boys were 19.6 (SD = 4.4) and 26.7
(SD = 3.5) for Session 1 and Session 2, respectively; mean
scores for the ADHD boys were 17.3 (SD = 4.5) and 20.9 (SD
= 5.3) for Session 1 and Session 2, respectively. The control
boys exhibited better overall performance than the ADHD boys,
F ( 1 , 42) = 12.10, p = .001, especially at Session 2, when
the ADHD boys were off medication. Tn addition, both groups
demonstrated improvement from Session 1 to Session 2, F ( l ,
42) = 62.97, p < .001, but greater improvement was noted for
the controls across the two sessions, F( 1, 42) = 6.76, p < .05.
964
AMAN, ROBERTS, AND PENMNGTON
The primary type of error made by the ADHD boys on this task
involved impulsive responding or failure to think through their
plan before responding.
Parietal Tasks
Visual-Spatial Cuing Task. According to Posner (1988), parietal patients show a larger RT difference between validly and
invalidly cued trials presented to the ipsilesional visual field
relative to the contralesional visual field on the Visual-Spatial
Cuing Task. The primary dependent variable is the score reflecting the difference in median response times on validly and
invalidly cued trials (i.e., the validity effect). Trials on which
a neutral cue was presented were, thus, not considered in the
following analyses.
MANOVAs conducted on the validity effect included delay
(100 ms vs. 500 ms), target side (left vs. right) and session as
repeated measures and group as a between-subject variable. The
only main effect that emerged involved session, F(l, 42) =
4.46, /; < .05, and indicated that the validity effect was smaller
at Session 2 than at Session 1. There were no other significant
main effects or interactions associated with this task. Of particular note is that none of the interactions involving the group
variable were significant, indicating that the groups did not reliably differ in terms of the validity effect on this task. There also
were no interactions or main effects involving target side. These
results do not reflect the pattern of performance that Posner
(1988) found for parietal patients; however, both groups of
participants did exhibit the "normal" pattern of results, with
reaction times being longer for the invalidly cued trials compared with the validly cued trials.
Turning Task. Accuracy data for the Turning Task were collapsed across the side on which the cue occurred (i.e., the
direction in which the triangle should turn) as well as the presentation side of the triangle (i.e., rotations reflecting 45C, 90°,
and 135° to the left or right of 0°), as these variables were
counterbalanced within participants and were not of specific
interest. The average number of correct responses for the homologous left and right orientations were computed to equate the
number of trials associated with each of the non-0° orientations
(n = 40) with the number of trials associated with 0° (n - 20).
A repeated measures MANOVA, with orientation (four levels) and session as the repeated measures and group as a between-subjects variable, was used to examine response accuracy. Figure 2 shows that accuracy for both groups decreased
as orientation from 0° increased, F(2, 65) = 43.78, p < .001.
In general, the control boys were more accurate than the ADHD
boys, F( 1, 42) = 3.98, p — .05, but particularly at the orientations further from 0°, as suggested by the significant Group x
Orientation interaction, F{2, 65) = 3.45, p < .05. The Group
X Session x Orientation interaction was also significant, F(2,
77) = 3.63, p < .05, indicating that the Group x Orientation
interaction differed at the two experimental sessions. This was
particularly true for the control group, who demonstrated a more
marked drop-off in accuracy at the 135° orientation at Session
1 than they did at Session 2. In summary, both groups performed
at ceiling levels at 0° but not at orientations away from 0°, in
which the groups were expected to perform dissimilarly. Also,
both groups evinced improvement over the two sessions, but
this was more pronounced for the controls.
In terms of the response latencies on the Turning Task, main
effects for Orientation, F(1,61) = 65.17, p < .001, and Session,
F(l, 42) = 45.98, p < .001, were statistically reliable, as was
the Session X Orientation interaction, F(2, 87) = 9.57, p <
.001. These results indicate that the response times for both
groups increased as the triangle's orientation moved farther
away from 0°, the response times were longer at the first session
that at the second session, and the increase in response times
with increasing orientation was more dramatic at the first session
than at the second session. The ADHD and control groups did
not reliably differ in terms of response latencies, F ( l , 42) =
0.52, and none of the interactions involving the group factor
were statistically reliable.
Spatial Relations. The dependent variable associated with
Spatial Relations was the number of problems solved correctly.
The mean number of correctly solved problems was 23.7 (SD
= 3.1) and 24.0 (SD = 4.5) for the ADHD group at Sessions
1 and 2, respectively, and 22.0 (SD = 4.1) and 25.0 (SD = 3.4)
for the control group at Sessions 1 and 2, respectively. The
repeated measures MANOVA revealed a significant Group x
Session interaction, F ( l , 42) = 5.82, p < .05, indicating that
the control group evinced improvement on this measure at the
second session compared to the first session, whereas the ADHD
group did not. The session main effect was also significant,
F ( l , 4 2 ) = 8.28, p < .01, with overall performance being better
at Session 2 than at Session 1.
Discussion
A neuropsychological approach was used in this study to
examine the frontal lobe and the right parietal lobe theories of
ADHD. Several questions related to the involvement of these
two brain areas in ADHD were addressed.
The main question of interest was whether the frontal lobe
theory or the right parietal lobe theory of ADHD would be
supported. Generally, we found support for both theories, as the
ADHD boys demonstrated impairment when their off medication performance was compared to their on medication performance and when their improvement across the two sessions
was compared to that of the control boys. Specifically, on the
purported tasks of frontal lobe functioning, the ADHD boys
evinced less learning across the two sessions than the control
boys in terms of inhibiting reflexive saccades toward the cue
on the Antisaccade Task and thinking through a plan prior to
executing the plan on the Tower of Hanoi. The ADHD boys also
demonstrated poorer performance off medication (Session 2)
than they did on medication (Session 1) in terms of inhibiting
button-press responses when a tone was presented on the Stopping Task.
On the purported tasks of right parietal lobe functioning,
the ADHD boys showed less learning across the two sessions
compared with the controls in terms of mental rotation of objects
and shapes on the Turning Task and Spatial Relations. There
were no apparent meaningful differences between the two
groups on the Visual-Spatial Cuing Task, and neither of the
groups produced patterns of performance resembling those of
parietal patients on this task. These latter findings are convergent
with those of Swanson et al. (1991), who also failed to find the
"parietal" pattern of performance in ADHD children as well
965
UNDERLYING DEFICIT IN ADHD
Session 2
Session 1
20
19
18
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Figure 2. Number of correct turns on the Turning Task as a function of session, group, and orientation of
the triangle. ADHD = attention deficit hyperactivity disorder.
as unequivocal differences between ADHD and control children
on the Visual-Spatial Cuing Task.
There are several alternative interpretations or explanations
for the findings across the two task domains included in this
study. One obvious interpretation is that the observed differences
between the ADHD and the control children on these tasks
support both the frontal and right parietal theories of ADHD.
Assuming that these tasks do reflect the respective functioning
of either the frontal or the parietal lobes, then deficient performance on them would imply dysfunction involving these brain
regions. The failure to find differences between the groups on
the Visual-Spatial Cuing Task does not pose a problem for this
hypothesis. It could simply mean that this task is only sensitive
to severe parietal lobe damage, such as would be associated
with ablations or lesions, and that the right parietal dysfunction
in ADHD is much more subtle.
A second, less obvious, interpretation regarding the performance deficits and flatter learning effects demonstrated by the
ADHD children is that they are due to dysfunction of the frontal
lobes only rather than to dysfunction of both the frontal and the
right parietal lobes. Support for this notion comes from research
indicating that frontal lobe patients often exhibit global cognitive
and behavioral deficits, including deficits that are typically ascribed to right parietal lobe dysfunction or damage (e.g., Fuster,
1985). Given the vast interconnections between areas of the
prefrontal cortex and the posterior parietal cortex, it seems likely
that damage to the frontal lobes could affect the functioning of
the parietal lobes. Along the same lines, the ADHD group's
poorer performance could be due to some other general or global
neurological deficit that affects both frontal and parietal
functioning.
In addition, it may also be the case that the functioning of
other specific brain systems that were not examined in this study
could explain the deficient performance demonstrated by the
ADHD boys. For example, hippocampal cells in rats have been
tied to behavioral inhibition as measured by go/no-go tasks
(e.g., Sakurai, 1990), suggesting that the specificity of the Stopping Task as a measure of frontal lobe functioning is questionable. However, the Stopping Task does appear to be a fairly
well-validated measure of frontal lobe functioning, as other neu-
robiological evidence is lacking in terms of linking dysfunction
of the hippocampus to ADHD symptomatology.
Two assumptions made by the authors of the present study
are important to keep in mind when interpreting the results.
First, the frontal versus parietal classification of the tasks was
assumed on the basis of evidence from previous research or on
the basis of the similarity of the tasks to other tasks that have
been linked to either the functioning of the frontal lobes or the
right parietal lobe. Second, it was assumed that each of the
experimental tasks is only sensitive to the functioning of one of
these brain areas and not to both of them. Unfortunately, the
specificity of these tasks has not been explicitly tested in terms
of frontal dysfunction versus parietal dysfunction. For example,
Guitton et al. (1985) found that frontal patients demonstrated
impaired ability to inhibit reflexive saccades toward the cue side
on the Antisaccade Task but did not examine the performance
of parietal patients. The controls in their study consisted of
nonlesioned participants and patients who had sustained temporal lobe lesions. Similarly, Drewe (1975) found impaired performance in frontal patients on go/no-go tasks, tasks on which the
Stopping Task is based, but compared the performances of frontal patients with those of nonfrontal lesioned patients, most of
whom had temporal lobe rather than parietal lobe lesions. In
addition, in Ditunno and Mann's study (1990), right parietal
patients were more severely deficient on mental rotation tasks
than were left parietal patients; however, they did not examine
the performance of frontal patients on the same mental rotation
tasks. Given these two caveats regarding the assumptions made
by the authors of the present study, caution is advised when
interpreting the results from the individual tasks included in this
study.
At least two explanations that are not specifically related to
frontal lobe or right parietal lobe dysfunction seem unable to
account for the deficits exhibited by our ADHD group. One
explanation suggests that the ADHD children would perform
poorly on all tasks, not just those that are linked to the functioning of the frontal or the right parietal lobes. This explanation
does not fit because the performance of the two groups did not
reliably differ on all aspects of the tasks (e.g., there were no
reliable differences between the groups at either Session 1 or
966
AMAN, ROBERTS, AND PENNINGTON
Session 2 on Spatial Relations). Furthermore, previous research
has indicated that there are several cognitive tasks on which
ADHD children do not demonstrate deficiencies, including those
involving verbal memory and nonverbal memory (see Douglas,
1988, for a review). There clearly are better ways to examine
the notion that the ADHD group would have performed poorly
on all tasks; unfortunately, such tests were not explicitly built
into this study.
A second, related explanation that does not appear to be able
to account for our results involves a generalized motivational
deficit in the ADHD group. Again, this explanation would be
supported if the ADHD children demonstrated poor performance across all aspects of the experimental tasks. However,
even though there were differences between the two groups
on several of the experimental tasks, with the control group
performing better than the ADHD group, the ADHD group was
often very accurate. For example, the unmedicated ADHD children were very accurate, even at orientations up to 135° from
0° on the Turning Task. This result would not be expected if the
ADHD children were unmotivated or were not trying to do well
on the tasks. Anecdotal evidence also suggests that the ADHD
boys were trying to perform well, in that they frequently expressed their disappointment after making an incorrect response
(e.g., when failing to inhibit their button press response after a
tone was presented on the Stopping Task), and they often corrected themselves on Spatial Relations after providing an initial
response and then changing their minds. Thus, it seems unlikely
that motivational deficits in the ADHD children can sufficiently
explain the differences between the two groups on the experimental tasks.
In summary, the poorer performance of the ADHD group in
the present study can be interpreted as supporting both the frontal lobe and parietal lobe theories of ADHD, as supporting only
the frontal lobe theory of ADHD, or as supporting a global brain
damage theory of ADHD. It appears that the poorer performance
of the ADHD children cannot be explained in terms of either
generalized performance deficits or motivational deficits.
A second question addressed in this study involved the relative severity of the deficits associated with the frontal and the
parietal tasks. In general, the ADHD boys appeared to be more
severely impaired on the frontal tasks than on the parietal tasks,
although only moderately so. On the frontal tasks, the performance of the ADHD boys across the two sessions declined on
the Stopping Task and stayed the same on the Antisaccadc Task.
Also, the ADHD boys demonstrated flatter learning effects than
did the controls on the Tower of Hanoi. On the parietal tasks,
specifically the Turning Task and Spatial Relations, the ADHD
boys tended to show nominal improvement across the sessions,
reliably less than the controls.
Nevertheless, there are two reasons why these results should
be interpreted with caution. First, the ADHD group as well as
the control group performed very well on both the Turning Task
and Spatial Relations. It is unclear whether the relative severity
of the frontal and the parietal deficits would be the same if more
difficult measures of parietal functioning had been included.
Second, the two groups were matched on an estimate of 1Q,
which was based on only two subtests from the WISC-R, Vocabulary and Block Design. Although the IQ estimate and Vocabulary standard scores were found to be unrelated to the
dependent measures from the experimental tasks, Block Design
standard scores were positively correlated with scores on Spatial
Relations and the Turning Task. Even though the ADHD and
control groups did not reliably differ in terms of scores on Block
Design, the ADHD group did exhibit poorer performance on
these two parietal tasks compared with the controls. Thus, it is
unclear whether the ADHD children are truly more adversely
affected on the frontal tasks compared with the parietal tasks or
whether the results obtained in this study regarding the relative
severity of the deficits on the two types of tasks were an artifact
of having matched the groups of boys on IQ, which was heavily
influenced by scores on Block Design.
Finally, the third research question addressed in this study
was whether stimulant medication would differentially affect
performance on the frontal and the parietal tasks. As noted
previously, differences between the ADHD and control groups
on both parietal and frontal tasks were more frequently found
at Session 2, when the ADHD children were off medication,
compared to Session 1, when they were on medication. Thus,
stimulant medication was associated with better performance on
tasks from both the frontal and the right parietal domains.
In general, the medication findings for this study should be
viewed with caution, however, as a fixed rather than random
medication order was used, confounding the medication condition with the order of the experimental sessions. Consequently,
it is important to consider alternative explanations that are independent of the medication condition for observed differences
within the ADHD group at the two sessions as well as differences between the ADHD group and the control group that are
evident at one of the sessions but not at the other. One alternative
explanation for these differences, ignoring the medication condition per se, involves the relative novelty or unfamiliarity of the
experimental tasks, as well as the testing environment in general,
for the ADHD children at the first and second sessions. Support
for this interpretation comes from research indicating that
ADHD children tend to exhibit relatively mild behavioral symptoms in novel or unfamiliar settings, or in situations involving
novel tasks, that become increasingly more deviant as familiarity
with the setting increases (e.g., Zentall, 1985). Thus, the decrements in performance across the two sessions for the ADHD
group or the smaller learning effects shown across the two sessions by the ADHD group compared to the control group can
be explained in terms of the experimental tasks being less novel
and more familiar to die ADHD children at Session 2 than at
Session 1. This explanation cannot be ruled out.
One interpretation or explanation that seems unlikely for the
medication findings in this study involves the rebound effects
that are associated with stimulant use. Rebound effects reflect
the deterioration in behavior, in excess of that expected from
baseline, that occurs as the beneficial effects of the stimulant
medication wear off. These effects are usually observed between
5 and 10 hr following administration of the medication. If rebound effects were a major factor in this study, the off medication deficits observed in the ADHD children would be exaggerated because they would reflect sub-baseline performance rather
than baseline performance or ability. There are two reasons why
the rebound interpretation does not appear to be relevant in our
study. First, the median number of hours since the children had
last taken their medication was 24, which is well beyond the time
UNDERLYING DEFICIT IN ADHD
during which rebound effects are typically observed. Second, of
the two ADHD children for whom stimulant medication was
administered within 10 hr of Session 2, 1 child did not perform
below average on any of the experimental tasks and the other
performed no worse than the other ADHD children who had
not taken their medication for more than 10 hr before performing
the tasks. Furthermore, recent findings by Johnston and her colleagues (Johnston, Pelham, Hoza, & Sturges, 1988) suggested
that rebound effects are not that widespread (occurring in only
about one third of ADHD children who take methylphenidate),
and even when they do occur, their magnitude varies considerably from day to day.
Conclusion
The primary goal of this study was to examine the frontal
and right parietal lobe theories of ADHD. Although our results
support both of these theories, the frontal lobe theory of ADHD
was more strongly supported than the right parietal lobe theory
of ADHD. Perhaps the best conclusion to draw from this study
is that it may be more important to determine why there are
decrements in performance in both task domains and how these
decrements relate to brain functioning rather than to try to explain the underlying deficit in ADHD in terms of either the
frontal lobe theory or the parietal lobe theory.
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Accepted October 10, 1997 •
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