Behavior therapy for Tourettes disorderUtilization in a co.docx

Behavior therapy for Tourette's disorder:
Utilization in a community sample...
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Visual–motor integration functioning in
children with Tourette syndrome.
Schultz, Robert T.. Yale U, School of Medicine, Child Study
Ctr, New Haven, CT,
US
Carter, Alice S., ORCID 0000-0001-9861-1560

Gladstone, Marshall
Scahill, Lawrence, ORCID 0000-0001-5073-1707
Leckman, James F.
Peterson, Bradley S.
Zhang, Heping
Cohen, Donald J.
Pauls, David
Neuropsychology, Vol 12(1), Jan, 1998. pp. 134-145.
Neuropsychology
US : American Psychological Association
US : Educational Publishing Foundation
US : Philadelphia Clinical Neuropsychology Group
United Kingdom : Taylor & Francis
0894-4105 (Print)
1931-1559 (Electronic)
English
neuropsychological test of visual–motor integration skill,
children with Tourette
syndrome
A neuropsychological model of visual–motor integration skill
was proposed and
tested in 50 children with Tourette syndrome (TS) and 23
unaffected control
children matched for age. Children with TS performed
significantly worse than
control children on the Beery Visual–Motor Integration (VMI)
Test. Consistent with
the proposed model, visuoperceptual and fine-motor

coordination subprocesses
were significant predictors of VMI scores. However, the
subprocesses did not fully
account for the diagnostic group difference on the VMI. These
results suggest that
the integration of visual inputs and organized motor output is a
specific area of
neuropsychological weakness among individuals with TS.
(PsycINFO Database
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Journal Article
*Motor Skills; *Neuropsychological Assessment; *Perceptual
Motor
Coordination; *Tourette Syndrome; *Visual Perception; Visual
Motor Integration
Adolescent; Attention Deficit Disorder with Hyperactivity;
Child; Discrimination
(Psychology); Female; Humans; Male; Neuropsychological
Tests; Psychomotor
Performance; Tourette Syndrome
Neurological Disorders & Brain Damage (3297)
Human
Male
Female
Childhood (birth-12 yrs)
Empirical Study
Print
Journal; Peer Reviewed Journal
Accepted: Jun 4, 1997; Revised: Apr 25, 1997; First Submitted:

Mar 18, 1996
20060710
20190211
American Psychological Association. 1998
http://dx.doi.org/10.1037/0894-4105.12.1.134
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http://dx.doi.org/10.1037/0894-4105.12.1.134
Visual–Motor Integration Functioning in Children
With Tourette Syndrome
By:
Robert T. Schultz
Child Study Center, Yale University;
Alice S. Carter
Department of Psychology, Yale University
Marshall Gladstone
Child Study Center, Yale University
Lawrence Scahill
James F. Leckman
Department of Pediatrics, Yale University
Bradley S. Peterson

Heping Zhang
Department of Epidemiology and Public Health, Yale University
Donald J. Cohen
Department of Psychology, Yale University;
Department of Pediatrics, Yale University
David Pauls
Department of Psychology, Yale University
Acknowledgement: This work was supported in part by National
Institute of Mental Health Grant
P01 MH49351 and the National Tourette Syndrome Association.
This work would not have been possible without the help of
Margot Anderson, John Hart, and
Abbe Skolsky.
Tourette syndrome (TS) is a neuropsychiatric disorder of
childhood onset characterized by
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multiple motor and one or more vocal tics that wax and wane in
severity across time. Tourette
syndrome and chronic tics are familial and heritable, with
segregation analyses suggesting major
gene transmission (e.g., Eapen, Pauls, & Robertson, 1993;
Hasstedt, Leppert, Filloux, van de
Wetering, & McMahon, 1995; Pauls & Leckman, 1986; Walkup
et al., 1996). Although motor and
phonic tics constitute the core elements of the diagnostic
criteria for TS, individuals with the
condition frequently have a wide array of difficulties, including
problems with attention,
disinhibition, and obsessive–compulsive symptoms (Cohen,
Detlor, Shaywitz, & Leckman, 1982;
Comings & Comings, 1985; Robertson, Trimble, & Lees, 1988).
Neuropsychological studies of TS have focused on an array of
functions, with the most
consistently observed difficulties occurring on tests of visual–
graphic and motor ability. The ability

to copy designs accurately has been investigated in 10 prior
studies (seeTable 1 ). Nine of the 10
studies reported in the literature found visual–motor integration
deficits (relative to other domains
of functioning). For example, Brookshire and colleagues
(Brookshire, Butler, Ewing-Cobbs, &
Fletcher, 1994) found that visual–motor integration scores in
children and adolescents with TS
were approximately 0.75 SD s below the normative mean. Six
studies employed the Bender–
Gestalt Test, whereas another used a highly similar measure, the
Beery Visual–Motor Integration
(VMI) Test. These measures demand little in the way of
executive function. A more complex
design, the Rey–Osterreith Complex Figure (Rey), was
investigated in three prior studies. In
addition to requiring the integration of visuoperceptual and
fine-motor skills, the Rey requires
executive function organization. Given its executive function
component, it is of interest that the
only study that failed to find significant impairment in TS
employed the Rey.
Visual–Motor Integration Skill
Although this literature provides consistent evidence for a
relative deficit in visual–motor integration
skill in TS, methodological shortcomings limit firm
conclusions. Most studies to date have
employed fairly small sample sizes (i.e., less than 20
participants). More important, 8 of the 10
studies failed to use a control group of any type and instead
relied on normative data. Normative

data are problematic because many measures are poorly normed
with respect to sample size at
each age interval and adequate representation of participants by
region, ethnicity, socioeconomic
status, and general intelligence. Moreover, normative data are
usually collected only for a single
test, whereas neuropsychological studies of patients typically
entail an extensive battery of
measures. With a long battery, fatigue and fluctuations in
motivation will affect performance,
especially in children, thus increasing the chance of spurious
findings when comparisons are made
to normative data.
Only 1 of the 10 studies in the literature tested for comorbid
attention deficit hyperactivity disorder
(ADHD). This is significant because half or more of all clinic-
referred cases of TS also have
comorbid ADHD (Robertson et al., 1988; Walkup, Scahill, &
Riddle, 1995), and children with TS
and ADHD may have a different profile of cognitive abilities
and worse social adjustment than
children with TS alone (Dykens et al., 1990; Stokes, Bawden,
Camfield, Backman, & Dooley,
1991). Moreover, children with ADHD alone show deficits in
visual–motor integration and motor
coordination compared to unaffected controls (Campbell &
Werry, 1986; Frost, Moffitt, & McGee,
1989), indicating that it might be the ADHD component and not
TS per se that is responsible for
observed deficits in drawing ability. In addition, previous
studies have not examined the influence
of depressive symptoms on visual–motor integration, even
though depression is believed to have a
deleterious effect on nonverbal functions.

Tests of visual–motor integration are compound measures,
calling upon visual–perceptual ability
and fine-motor coordination, in addition to the integration of
visual–perceptual analyses into motor
programs for successful performance (seeFigure 1 ). Deficient
visual–motor integration could be a
function of suboptimal capacity in one or both of these
component processes. An important issue,
therefore, is whether individuals with TS have difficulty in
these more rudimentary component
processes that could explain their visual–motor integration
performance, or whether the deficit is
specific to the integration of visual and motor processes. In
addition to separate visual and fine-
motor processes, performance on tests of visual–motor
integration also requires intact sustained
attention and motor impulse control. Vigilance and motor
inhibition are the two pillars of attentional
ability (Barkley, 1990). Effortful maintenance of attention is a
prerequisite for adequate
performance on any test. Motor inhibition can be distinguished
from fine-motor coordination during
a copying task in that the latter refers to the continuous
coordination of the small-muscle groups
employed during a skilled pencil movement, whereas motor
inhibition refers to both the cessation
of activity when appropriate and the delayed onset of activity so
as to allow for planning of the
motor sequence. Thus, at least four separate subprocesses may
contribute to visual–motor
integration ability: visual–perceptual processes, fine-motor
coordination, sustained attention, and
inhibitory motor processes.

Figure 1. Component processes contributing to visual–motor
integration skill
Although motor, attention, and visuoperceptual skills have been
examined in several prior studies
of TS, analyses have not focused on their relationship to visual–
motor integration ability.Table 2
presents results from all studies that employed tests of motor
speed (i.e., Finger Tapping) and
motor coordination (i.e., the Grooved or Purdue Pegboard).
Each of the six studies produced
evidence suggestive of motor skill difficulties, although some
questions about laterality remain.
Pegboard tests involve visually guided movement and are
dependent on adequate somatosensory
ability, but they are primarily measures of relatively complex
motor sequencing and dexterity,
requiring fine manipulation by the fingers and quick, accurate,
and coordinated arm and shoulder
movements. Simple motor speed without visual–perceptual or
somatosensory demands, as
indexed by the Finger Tapping test, appears unimpaired in
samples of subjects with TS (Bornstein,
1990; Bornstein, 1991; Bornstein, Baker, Bazylewich, &
Douglass, 1991; Randolph, Hyde, Gold,
Goldberg, & Weinberger, 1993), suggesting that deficits in
elementary motor skill cannot explain
the deficits on the pegboard tests. Thus, the relative motor
deficits in TS seem to be at a level
“downstream” from simple motor speed, involving more
complex coordination of movements in
space. Moreover, the suggestion is that motor coordination may
account for a significant portion of
visual–motor integration variance, but this has been untested
until now.

Fine-Motor Skill
The literature on possible visuoperceptual deficits in TS is less
clear (seeTable 3 ), in part because
the measures employed differ between studies and in part
because few studies have selected
instruments that are highly specific to this domain of
functioning. The early literature tended to
focus on relative deficits in Wechsler Performance IQ (PIQ)
compared with Verbal IQ (VIQ).
AlthoughShapiro, Shapiro, Bruun, and Sweet (1978)
andSutherland, Kolb, Schoel, Whishaw, and
Davies (1982) found significant PIQ deficits, Incagnoli and
Kane (1981), Golden (1984), Ferrari,
Matthews, and Barabas (1984), and Lanser and colleagues
(Lanser, Van Santen, Jennekens-
Schinkel, & Roos, 1993) did not. Dykens and colleagues
(Dykens et al., 1990) found significantly
lower PIQ among children with TS − ADHD as compared with
TS + ADHD. Bornstein et al. (1991),
on the other hand, reported greater VIQ–PIQ discrepancies in
TS, regardless of the direction.
Other measures with a visuoperceptual or visuospatial
component have also provided mixed
results (seeTable 3 ).
Visuoperceptual Ability
The primary goal of this study was to address the
methodological shortcomings of prior work and
provide a clear test of the hypothesis that children with TS
exhibit relative deficits in visual–motor

integration skill as compared with a sample of age-matched,
unaffected control children. Moreover,
we tested the hypothesis that performance on tests of visual–
motor integration can be predicted by
the four component processes (fine-motor coordination,
visuoperceptual ability, motor inhibition,
and sustained attention) in our model (Figure 1) and that
relative deficits in visual–motor
integration skill can be explained by weakness in one or more
component processes. A second
goal of the study was to assess the role that ADHD and
depressive symptoms play in visual–motor
integration performance by subdividing the TS group into
children with and without comorbid
ADHD and by statistical control for scores on the Childhood
Depression Inventory. These analyses
are critical tests of the specificity of visual–motor integration
weakness in TS.
Method
Participants
Children with a clinical diagnosis of TS were recruited for
participation from the TS specialty clinic
of the Yale University Child Study Center, New Haven,
Connecticut. Before entry into the study, the
children's parents were interviewed and clinical records
reviewed to exclude children with a history
of neurological illness, loss of consciousness, or comorbid
diagnoses of pervasive developmental
disorder, psychosis, or mental retardation. Control children of
the same age were recruited through
newspaper advertisements and announcements within the
university and at local area schools;

they were paid $50 for their participation. Control-participant
exclusion criteria included a lifetime
diagnosis of any psychiatric or neurologic disorder, including
head injury with loss of
consciousness.
Diagnostic Process
To confirm the diagnostic status of the unaffected controls and
the children with a putative
diagnosis of TS, we gathered multiple parent-, child-, teacher-,
and clinician-completed ratings
including the Vineland Adaptive Behavior Scales—Survey
edition (Sparrow, Balla, & Cicchetti,
1984), Child Behavior Checklist (Achenbach, 1991), ADHD
Rating Scale (DuPaul, 1991), Conners
Parent and Teachers ADHD Rating Scales (Conners, 1989),
Yale Global Tic Severity Scale
(Leckman et al., 1989), Children's Yale–Brown Obsessive–
Compulsive Scale (Riddle et al., 1992),
Leyton Obsessional Inventory (Flament et al., 1988), Revised
Children's Manifest Anxiety Scale
(Reynolds & Richmond, 1987), Childhood Depression Inventory
(Kovacs, 1985), review of clinical
records, and a semistructured developmental history interview
with a parent that included
screening questions for psychiatric disorders based on the
Schedule for Affective Disorders and
Schizophrenia for School-Age Children (Orvaschel & Puig-
Antich, 1987). Principal and comorbid
Diagnostic and Statistical Manual of Mental Disorders (3rd ed.,
rev.; DSM–III–R;American
Psychiatric Association, 1987) diagnoses were then formally
established with a best-estimate
diagnostic procedure (Leckman, Sholomskas, Thompson,
Belanger, & Weissman, 1982), which

entailed two experienced clinicians (Lawrence Scahill and
James F. Leckman) reviewing all
available information and independently judging the presence or
absence of the following
diagnoses: TS, chronic motor tics, chronic vocal tics,
obsessive–compulsive disorder (OCD),
obsessive–compulsive personality disorder, ADHD, oppositional
defiant disorder, conduct disorder,
and other major psychiatric disorders. In addition, each
clinician counted the number of DSM–III–R
ADHD diagnostic criteria that the child satisfied. Kappa
statistics were computed on the three
major diagnoses of interest: TS, OCD, and ADHD (.84, 1.0, and
.66, respectively). Subsequently,
disagreements involving the principal and secondary diagnoses,
or both, were resolved by a joint
review of the records by the two clinicians.
The consensus diagnostic process resulted in 12 patients being
dropped from the study for one of
the following reasons: a failure to have a diagnosis of TS (e.g.,
chronic motor tics; n = 5); the
presence of Pervasive Developmental Disorder Not Otherwise
Specified (PDD NOS; n = 2); IQ
less than 75 (n = 1); current major depression (n = 1); history of
psychosis (n = 1); syncopal
induced seizures (n = 1); or insulin-dependent diabetes (n = 1),
which has been associated with
neuropsychological deficits. Three control children were
dropped after participation in the study
because of IQ less than 75 (n = 1), a significant discrepancy
between their IQ and Achievement
test scores suggesting the presence of a learning disability (n =
1), and significant obsessive–

compulsive symptoms (n = 1).
The final sample consisted of 50 children (35 boys and 15 girls)
with TS between the ages of 8.1
and 14.3 years (10.8 ± 1.5). These children were compared with
23 unaffected control children (11
boys and 12 girls) between the ages of 8.2 and 13.7 years (10.8
± 1.8).Table 4 provides the means
and standard deviations for the characteristics of the TS and
control samples. There were no
significant differences in age or handedness between the two
groups, although there was a trend
(p < .10) for more boys than girls in the TS group compared
with the control group. However,
gender did not affect any neuropsychological measure; there
were no significant main or
interaction effects of gender on any of the dependent variables.
There was a trend (p < .10) for
Vocabulary scores to be lower among the TS children. Children
with TS scored significantly higher
on the Childhood Depression Inventory compared with the
unaffected controls, t(1, 69) = 3.01, p <
.01.
Sample Characteristics and Psychiatric Symptoms
Thirty-four (68%) of the children with TS also met criteria for
ADHD (26 boys and 8 girls), and 6
(12%) had comorbid OCD (3 boys and 3 girls). Comparisons
among the controls, TS + ADHD, and
TS − ADHD of the characteristics presented inTable 4 revealed
no significant group differences in
age or handedness, but there was a trend for differences in the
distribution by sex, and a main
effect for Vocabulary scores, F(2, 72) = 3.69, p < .05. However,

none of the posthoc Scheffé F
tests of subgroup differences on Vocabulary were significant.
In addition to possible comorbid OCD and ADHD, 27 of the 50
children with TS had at least one
other diagnosis, 15 had at least two, 7 had at least three, and 4
had four additional diagnoses. The
number of primary (i.e., TS, OCD, ADHD) and secondary
diagnoses was summed to create a
crude index of overall psychopathology, with the mean score of
the TS sample equal to 3.04 ±
1.34. After removing the ADHD and TS diagnoses from the
count, the TS + ADHD and TS −
ADHD groups were not significantly different in terms of
number of additional diagnoses (1.47 ±
1.11 vs. 1.13 ± 1.36).
Neuropsychological Assessment
After informed consent, all children were administered a
comprehensive neuropsychological test
battery in a uniform order, across two testing sessions, each
averaging about 2 hr in duration. The
battery included the Kaufman Brief Intelligence Test (KBIT;
Kaufman & Kaufman, 1990), composed
of a Vocabulary and a Matrices subtest. The KBIT provides a
reliable estimate of general
intelligence that correlates greater than .80 with Full-Scale IQ
scores derived from the Wechsler
Intelligence Scale for Children—Revised (WISC–R; Kaufman &
Kaufman, 1990; Naugle, Chelune,
& Tucker, 1993). Handedness was assessed clinically using the
laterality scale of the Halstead–
Reitan Battery (Reitan & Davison, 1974).

Visual–motor integration was assessed with the Beery–
Buktenica Visual–Motor Integration Test
(VMI; Beery, 1989) and the Rey–Osterreith Complex Figure
(Osterreith, 1944; Rey, 1941), using
theTaylor (1959) scoring system. The component processes
depicted inFigure 1 were measured
as follows: Visuoperceptual skill was assessed with two
measures, the Block Design (BD) subtest
of the WISC–R and the Matrices subtest of the KBIT. Because
each of these subtests load on
general intelligence (g ), g was controlled by having Vocabulary
as a covariate in all analyses of
visual–perceptual skill. Fine-motor coordination was measured
with the Purdue Pegboard (Tiffen,
1968). Dominant, nondominant, and bimanual conditions were
administered sequentially, with a
single repetition of this sequence. The average of the two trials
was taken. In addition, the number
of times pegs were dropped and the number of times the child
“broke set” by taking more than one
pin from the well was recorded to assess whether these might
influence total score. Children with
TS were able to suppress tic activity during each of the timed
trials of the Purdue Pegboard, and in
no case did tic activity appear to directly interfere with
neuropsychological test performance. Motor
inhibition and sustained attention were assessed with a
computer-administered continuous
performance test (CPT; Loong, 1991). The CPT consisted of
two conditions, each 5 min in
duration. The first required the child to press the keyboard
space bar whenever the target letter X
appeared on the monitor and to not respond to any other letter.
During the 5 min, 100 target stimuli
were randomly presented. The second condition required the

child to press the space bar
whenever the X followed the letter A (the AX condition). Fifty
such occurrences were randomly
presented during the 5 min. The number of commissions
(responses to nontarget letters)
constituted the measure of motor inhibition; the number of
omissions (i.e., failures to detect the
target) served as the measure of sustained attention.
Medication Status
Accurate records on medication status for the date of testing
were available for 46 of the 50
participants with TS. Twenty-seven (59%) were taking
medications for treatment of their TS, OCD,
or ADHD, whereas 19 (41%) were not. Two children were
taking two different medications
(neuroleptic and methylphenidate or clomipramine), and one
child was taking three medications
(neuroleptic, clomipramine, and benzotropine). The number of
children taking specific medications
was as follows: clonidine, 13; neuroleptic, 9 (4 taking
haloperidol and 5 taking pimozide);
clomipramine, 4; desipramine, 3; benzotropine, 1; and
methylphenidate, 1. An analysis of variance
assessed whether neuropsychological performance differed by
medication status (none, clonidine,
neuroleptic, or other). No significant differences emerged with
the exception of nondominant hand
performance on the Purdue Pegboard, F(3, 45) = 3.17, p < .05.
Unfortunately, this analysis cannot
disentangle cause and effect, because the reasons why a
medication is prescribed or effective
may in part be a function of the child's profile of
neuropsychological strengths and weaknesses.

Moreover, psychomotor retardation with neuroleptics is typical
only after initiation of these agents
or after a dosage increase, and with time there is habituation
and disappearance of these
unwanted side effects (Cassens, Inglis, Appelbaum, & Gutheil,
1990; King, 1990). None of the
children on a neuroleptic in this study had begun the medication
or had a change in dosage in the
8 weeks before testing, suggesting that these agents were not
causing problems in psychomotor
functioning. Moreover, analyses presented in the Results section
are not changed when the 9
children on neuroleptics are excluded. This is consistent with
prior studies of medication effects on
neuropsychological performance in TS (e.g., Bornstein & Yang,
1991).
Data Analyses
The data analytic plan entailed first testing the hypothesized
relationship between visual–motor
integration and the four putative component processes using
correlational analyses. Next, TS
versus control differences in neuropsychological performance
were assessed with stepwise
discriminant function analyses. These analyses tested the
hypothesis that visual–motor integration
skill differed between participants with TS and controls,
independent of performance on the
component processes in the model. Subsequent analyses
employed multivariate analyses of
covariance (MANCOVAs), discriminant function analyses, and
correlations to assess individual
component processes in our neuropsychological model of
visual–motor integration, the
subgroupings of TS with and without comorbid ADHD, and the
relationship between psychiatric

symptoms and neuropsychological performance. There is a large
general factor of intelligence in
neuropsychological batteries, which, if not removed, would
otherwise inflate correlations between
putative tests of isolable functions (Matarazzo, 1990).
Therefore, in all analyses, Vocabulary, as a
proxy for g, was first removed from each variable by
covariation, so the specificity of the
relationships could be measured without the ubiquitous
influence of general intelligence
(Vocabulary has the highest g loading of any individual
intelligence subtest; Brody, 1992).
Moreover, this covariation was necessary because of a trend for
higher Vocabulary scores among
the controls as compared with the participants with TS.
Results
Component Process Correlations With Visual–Motor Integration
Correlational analyses tested the relationship between each
component process and the
supraordinate domain of visual–motor integration skill. Separate
correlational analyses within the
TS and control groups revealed highly similar patterns; hence,
the results employing the total
sample are reported. The two measures of visual–motor
integration used in this study, the Rey and
the VMI, were significantly correlated (removing Vocabulary,
partial r = .48, p < .0001), suggesting
that they tap a common performance dimension.
Our model (Figure 1) predicted that each of the four component
processes would correlate with the

VMI and the Rey. Partial correlations were significant between
Matrices and the VMI (r = .33, p <
.05), and BD and the VMI (r = .53, p < .0001), supporting the
association between visual–
perceptual skill and visual–motor integration. BD was also
significantly correlated with the Rey
(partial r = .47, p < .0001), but Matrices was not (partial r =
.19, ns ). Next, the relationship between
motor coordination and visual–motor integration skill was
assessed. Significant partial correlations
were observed for dominant, nondominant, and bimanual
performance on the Purdue Pegboard
and the VMI (partial r s = .25, .27, and .29, respectively, all p s
< .05). However, partial correlations
between the Purdue Pegboard and the Rey were not significant.
Thus, both motor and visual–
perceptual reasoning were more strongly associated with the
VMI than with the Rey. Neither motor
control nor sustained attention measures correlated significantly
with the visual–motor integration
measures, after controlling for general intelligence. In a
multiple regression, BD (controlling for
Vocabulary) was the only significant predictor of visual–motor
integration skill, even though in the
absence of BD, the Purdue Pegboard also had shown a
relationship to visual–motor integration
skill.
Discriminant Function Analyses
Stepwise discriminant function analyses were used to test the
hypothesis that children with TS
could be differentiated from the unaffected control children on
the basis of their neuropsychological
performance on measures of visual–motor integration and the
proposed component processes
(controlling for Vocabulary scores).Table 5 presents the mean

scores (±SD) for each of the
measures in the model by diagnostic group. In addition, because
the semipartial correlation
between the Childhood Depression Inventory raw scores and the
VMI (controlling for Vocabulary)
was negative (r = −.24, p < .05), the Childhood Depression
Inventory was also included in the
model. The overall model was significant, Wilks's lambda =
0.74, F(2, 63) = 11.29, p < .0001.
However, only the VMI, F(1, 63) = 11.54, p < .005, and the
number of commission errors on the AX
condition of the CPT, F(1, 63) = 8.15, p < .01, contributed
significantly to the prediction. These two
variables enabled correct classification of 82% of the unaffected
control participants and 80% of
children with TS. The Rey was not a significant contributor to
the model. In fact, the univariate
analysis controlling for g found only a statistical trend (p < .10)
for worse performance on the Rey
by children with TS compared with control participants.
Visual–Motor Integration and Component Process Scores by
Diagnostic Group
Analyses of Component Processes
Next we examined whether each of the measures of the
component processes were related to TS.
Although the discriminant function analysis showed that only
the VMI and motor inhibition were
significant predictors, their inclusion in that model precluded an
understanding of group differences
on lower level processes with which they share variance. To test
for possible group differences in

performance on individual measures of visuoperceptual
processing, fine-motor control, vigilance,
and motor inhibition, a series of MANCOVAs was conducted,
with Vocabulary included as a
covariate. These analyses allow for greater comparability
between this and other studies but do
not supplant the discriminant function analyses.
MANCOVA testing for group difference in the visuoperceptual
ability tests (BD and Matrices) was
significant, Wilks's lambda = .873, F(2, 68) = 4.96, p < .01.
Subsequent analyses of covariance
showed that children with TS performed significantly lower on
Matrices, F(1, 69) = 8.74, p < .001,
with a trend for differences on BD, F(1, 69) = 3.29, p < .10.
Within the fine-motor domain, a
repeated-measures MANCOVA, with the dominant,
nondominant, and bimanual conditions of the
Purdue Pegboard as the dependent measures, was significant,
Wilks's lambda = 0.872, F(3, 69) =
3.36, p < .05, with a significant main effect for diagnostic
group, F(1, 71) = 10.02, p < .005. There
were, however, no significant condition or Condition × Group
interactions, suggesting no laterality
or bimanual effects. Univariate analyses of covariance revealed
that the TS group scored
significantly lower on all three conditions of the Purdue
Pegboard, F(1, 71) = 6.24, p < .05; F(1, 71)
= 8.54, p < .005; and F(1, 71) = 6.73, p < .05, respectively. The
two groups did not differ on the
number of pegs dropped (p s > .60 for each condition) or the
number of losses of set, that is,
picking up two pegs at once (p s > .30), suggesting that the

poorer performance of the TS
participants was due to fine-motor control and speed, not to
gross errors of coordination or
violating the rules of the task. There were no significant
differences on the CPT measures of
vigilance (omission errors). However, the TS group exhibited
more difficulty with motor inhibition,
because they committed significantly more errors of
commission in both the X condition, F(1, 57) =
4.67, p < .05, and the AX condition, F(1, 61) = 9.69, p < .005.
TS Subgroup Analyses
Stepwise discriminant function analysis was used to evaluate
whether neuropsychological
measures could differentiate TS + ADHD from TS − ADHD.
When controlling for Vocabulary, none
of the measures differentiated these two groups. There were no
differences between the two TS
subgroups on Matrices, BD, the three Purdue Pegboard
conditions, the Childhood Depression
Inventory, or any CPT measure. However, when Vocabulary
standard scores were entered into the
model (without first residualizing the other variables), the
model was significant, Wilks's lambda =
0.91, F(1, 48) = 4.90, p < .05. Children with TS + ADHD scored
significantly lower on Vocabulary
than did those with TS − ADHD, F(1, 70) = 4.09, p < .05, and
Vocabulary scores correctly
classified 74% of the children with TS + ADHD and 63% of the
children with TS − ADHD.
Symptom severity of TS and OCD at the time of testing was
assessed using the Yale Global Tic
Severity Scale and Children's Yale–Brown Obsessive–
Compulsive Scale, respectively (seeTable 4
). Compared with the TS + ADHD group, the TS − ADHD group

had a significantly greater total
obsessions score, t(1, 30) = 2.06, p < .05. On the other hand, the
TS + ADHD group had a
significantly greater total phonic tic score, t(1, 33) = 2.09, p <
.05. No group differences were found
for motor tics, compulsions, Childhood Depression Inventory,
or the total score.
Correlational analyses within the TS group with each of these
variables and the cognitive
measures suggested few significant relationships. Total phonic
tic score correlated negatively with
Spelling (r = −.41, p < .05) and positively with CPT X
omissions (r = .42, p < .05). On the Children's
Yale–Brown Obsessive–Compulsive Scale, the total
compulsions score was negatively correlated
with BD (r = −.36, p < .05). Number of DSM–III–R ADHD
symptom criteria correlated negatively
with Reading (r = −.35, p < .05) and Spelling (r = −.41, p < .01)
scores from the Kaufman Test of
Educational Achievement—Brief form (Kaufman & Kaufman,
1985). Our index of general
psychopathology, created by summing the number of DSM–III–
R diagnoses, was negatively
correlated with the VMI (r = −.34, p < .05). Given the number
of multiple comparisons, these
correlations should be interpreted with caution.
Discussion
Consistent with prior studies, we obtained significant
differences between children with TS and
unaffected controls on measures of visual–motor integration.

Children with TS scored
approximately 1 SD below the controls on the VMI. The TS
group also performed significantly
lower on copying the Rey, a more complex design that demands
executive organization, although
the effect size was smaller (about 0.5 SD) and reduced to a
trend when covarying the influence of
general intelligence. Thus, deficits in visual–motor integration
skill among children with TS may be
less pronounced on tests with more of an executive-functioning
component. This is in agreement
with the extant literature (Table 1) because the only negative
finding to date with respect to visual–
motor integration is with a comparison employing the Rey.
Moreover, the VMI, which is a purer
measure of visual–motor integration skill than the Rey, was the
best predictor of TS group
membership in our discriminant function analyses and was more
highly correlated with the
component processes in our model (Figure 1 ).
We obtained partial validation of our neuropsychological model
of visual–motor integration skill.
Even after controlling for general intelligence, visual–
perceptual skill (BD and Matrices) and fine-
motor coordination (Purdue Pegboard) were significantly
correlated with visual–motor integration.
However, we did not find significant correlations between
visual–motor integration and either
sustained attention (CPT omissions) or motor inhibition (CPT
commissions). Thus, two of the four
constructs in our model were shown to share variance with
visual–motor integration independent
of g. Before concluding that sustained attention and motor
inhibition are not essential component
processes of visual–motor integration, further study is

warranted using additional or different
measures of these constructs to test the proposed relationships.
Recent advances in CPTs provide
more sensitive measures of vigilance and motor inhibition (e.g.,
theConners, CPT; Conners, 1994).
A principle aim of the study was to test whether observed
relative deficits in visual–motor
integration might be secondary to problems among one or more
of the component processes. The
literature on fine-motor coordination difficulties in TS is nearly
as compelling as that of visual–
motor integration, but there have been no studies of the impact
of fine-motor coordination deficits
on drawing ability. In agreement with previous studies, TS
children performed about 0.75 SD below
that of controls on the Purdue Pegboard. However, when the
VMI was entered into the
discriminant function analysis, the Purdue Pegboard no longer
contributed unique variance to
distinguish the groups, suggesting that its predictive power was
absorbed by its functional overlap
with the VMI. Although we employed the Purdue Pegboard as a
test of motor coordination,
indisputably there is a visual component to the test. Indeed, it is
difficult to conceive of meaningful
tests of motor coordination that do not involve either direct
visualization or visual imagery (e.g., a
motor test when blindfolded might still engage visual mapping
and imagery of the physical
environment). Comparisons of motor skill among the
congenitally blind with and without TS might
adjudicate the issue, but such samples would be difficult to

ascertain.
The literature on potential visuoperceptual deficits in TS is
smaller, less coherent, and less
persuasive, largely because the measures employed have not
been highly specific to this domain
of functioning. Our measures (Matrices and BD) are open to
that same criticism, because
performance on these tests is multidetermined, with a clear
loading on g. Nevertheless, children
with TS were found to have a relative weakness on both BD and
Matrices (covarying Vocabulary
as a proxy for g ). This finding, however, is complicated by the
fact that the children with TS scored
above the general population mean on both BD and Matrices,
whereas the unaffected controls
scored well above the mean on these measures (but not on
Vocabulary), suggesting that the
samples may not be representative. When entered into the
discriminant function analyses with the
VMI, however, neither of the visual–perceptual measures were
additive independent predictors of
diagnosis. Thus, children with TS scored lower on the VMI
compared with the controls even when
controlling for visual–perceptual skill (BD and Matrices).
Although continuous performance measures of sustained
attention and motor inhibition did not
correlate with visual–motor integration as predicted, motor
inhibition was the other significant
variable in the discriminant function analysis. The children with
TS were much more impulsive than
the controls, and their motor disinhibition as measured with a
CPT was independent of visual–
motor integration deficits. Stepwise discriminant function
analyses showed that, in combination,

visual–motor integration skill and inhibitory control were able
to accurately classify 82% of the
unaffected controls and 80% of the children with TS.
Surprisingly, the CPT measurement of
impulsivity was not predictive of comorbid ADHD among the
children with TS, suggesting that
either our CPT was insensitive or that ADHD in the context of
TS is qualitatively different from
ADHD alone. We also examined the possible impact of
comorbid ADHD on visuomotor integration
skill, a potential confound that had not previously been
addressed in the literature. The TS + ADHD
and TS − ADHD participants were equally impaired on the VMI,
further suggesting that the relative
deficit in visual–motor integration among children with TS is
independent of disorders of attention
and impulse control.
Other investigators have noted that the majority of patients with
TS perform within normal limits on
tests of neuropsychological functioning (±1.5 SD from the
mean), with only a subsample showing
clinically meaningful impairments (Randolph et al., 1993). For
example, Bornstein (1990) showed
that approximately 20% of his sample of 100 children with TS
showed impairment on a summary
index of neuropsychological functioning, with impairments in
sensory and motor functioning being
the most common. Our data are in agreement with this
assessment, because only a fraction of the
participants with TS scored well below the normative mean on
the visual–motor and fine-motor
measures. For example, 32% of the children with TS scored at

least 1 SD below the mean on the
VMI, while 78% scored below the mean. Thus, the entire
distribution of scores appears to be
shifted slightly downward toward more impaired performance
on select neuropsychological
measures. The shift is small enough that the majority of
children with TS functioned within normal
limits, broadly defined, although not so small as to be easily
ignored, especially when one
considers the fact that Full-Scale IQ in this sample was
somewhat above the general population
mean.
The neural basis for deficient visual–motor integration skill in
TS is uncertain. Although the
parallels to developmental disorders such as TS may be
imprecise, considerable knowledge about
systems subserving visual–motor integration and its component
processes has been gleaned from
lesions in adulthood. Both right- and left-hemisphere processes
have been implicated in drawing
ability, but the contributions of each to good performance is
probably different. Right-hemisphere
damage typically results in drawings with sufficiently accurate
detail but distorted spatial relations
among the elements and a failure to capture the gestalt, while
left-hemisphere lesions more often
result in drawings that are slowly executed, oversimplified,
lacking detail, but spatially intact
(Gainotti & Tiacci, 1970; Marshall et al., 1994; McFie &
Zangwill, 1960; Warrington, James, &
Kinsbourne, 1966). The drawing dysfunction among right-
hemisphere-damaged patients appears
to be a result of a primary impairment in perception as it guides
the movement of the hand in
space (e.g., Kirk & Kertesz, 1989; Warrington & James, 1967).

Interpretation of left-brain
mechanisms in drawing disturbance is more difficult and in
many cases is attributable to low-level
errors of motor execution secondary to dominant-hand
hemiparesis (Carlesimo, Fadda, &
Caltagirone, 1993; Gainotti, 1985; Kirk & Kertesz, 1989).
However, ideomotor dyspraxia (i.e.,
deficits in selecting and sequencing movement elements) and
ideational dyspraxia (deficits in the
conceptual organization and planning of movement) can also
cause the simplification of drawing
seen in left-hemisphere constructional dyspraxics (Kirk &
Kertesz, 1989; Piercy, Hécaen, &
Ajuriacurra, 1960; Warrington & James, 1967). Although both
hemispheres may contribute to
visual–motor integration, a more important role for the right is
suggested by the greater frequency
of drawing difficulties with right-hemisphere lesions (Damasio,
1985), especially when patients with
global cognitive deficits are excluded (Villa, Gainotti, & De
Bonis, 1986).
Lesions to the parietal cortex in humans produce impaired
visual perception, particularly when the
injury is in the right hemisphere (for a complete review,
seeAndersen, 1987). The integration of
motor movements with visuoperception is conducted with body-
centered representations of space
(as opposed to retinotopic) within the posterior parietal cortex
(Andersen & Zipser, 1988). Single-
cell recording studies in nonhuman primates and functional
neuroimaging studies in humans
indicate that the posterior parietal cortex codes for the position

of body parts relative to one
another and to the external world and participates in planned
movements in external space
(Andersen, 1987; Bonda, Petrides, Frey, & Evans, 1995). These
processes are essential for
accurate drawing. Posterior parietal lobule lesions result in
reaching errors and deficits in fine-
motor coordination with visual guidance (Andersen, 1987;
Hyvärinen, 1982). Moreover, a small
region within the posterior parietal cortex, the lateral
intraparietal area, appears to be specialized
for the visual–motor integration of saccadic eye movements,
allowing location of targets in space
and planning for subsequent movements (Andersen, Brotchie, &
Mazzoni, 1992). Superior aspects
of the right parietal lobe also subserve somatosensory processes
(Mountcastle, Lynch,
Georgopoulos, Sakata, & Acuña, 1975), which allow for
feedback about the placement of the
pencil on the fingertips and real-time adjustments for fine-
motor control during drawing.
Although considerable evidence documents the role of the
nondominant parietal lobe in
somatosensory and visuospatial processes contributing to
visual–motor integration, it is also clear
that drawing is a complex ability involving multiple brain
regions. The integration of
visuoperceptual, somatosensory, and motor components in
drawing is probably mediated by
bidirectional exchange of information between parietal and
motor areas of the frontal cortex
(Quintana & Fuster, 1993), with a substantial integrative
contribution from subcortical circuits (e.g.,
Alexander, Delong, & Strick, 1986). Indeed, visuomotor
integration deficits may arise from frontal

and subcortical lesions, in addition to parietal lobe lesions.
Marshall and colleagues (Marshall et
al., 1994) studied drawing dysfunction in 37 patients with right-
hemisphere stroke, with lesions
distributed between subcortical, anterior, and posterior cortical
locations. When both drawing and
visuoperceptual function was disturbed, lesions always involved
the temproparietal–occipital
junction. When visual–spatial functions were intact, but
drawings were unrecognizable, lesion
location more often was subcortical, with a point of lesion
overlap across participants in the
anterior limb of the internal capsule and the lateral head of the
right caudate nucleus. Thus, the
basal ganglia may have a specific role in the synthesizing motor
programming and perceptual
inputs. This is consistent with other reports of constructional
apraxia after subcortical lesions in the
nondominant hemisphere (e.g., Agostini, Collette, Orlando, &
Tredici, 1983).
The role of the basal ganglia in drawing disturbance is
particularly intriguing because
neuroimaging, neuropathological, and phenomenological studies
implicate the basal ganglia and
functionally related cortical and thalamic structures in the
pathobiology of TS (Anderson et al.,
1992; Balthazar, 1956; Hyde et al., 1995; Peterson et al., 1993;
Singer, Hahn, & Moran, 1991;
Singer et al., 1993). A specific role for the right caudate in the
pathobiology is suggested by a
magnetic resonance imaging study of 10 pairs of monozygotic
twins concordant for tics (Hyde et

al., 1995). The size of the right caudate nucleus was
significantly reduced in the more severely
affected twin. Abnormalities of the right caudate, therefore,
could have a primary role in both the tic
behavior and the impaired visual–motor integration skills seen
in TS. However, our data suggest
that the pathobiology is probably bilateral because we found
that dominant and nondominant hand
were equally impaired on the Purdue Pegboard.
Interestingly, family studies support an etiologic link between
TS and one form of OCD (Pauls,
Raymond, Stevenson, & Leckman, 1991; Pauls, Towbin,
Leckman, Zahner, & Cohen, 1986), and
OCD also involves relative deficits in visual–motor integration
(Behar et al., 1984; Boone, Ananth,
Philpott, Kaur, & Djenderedjian, 1991; Hollander et al., 1993),
visuoperceptual ability (Aronowitz et
al., 1994), and visual–spatial reasoning (Head, Bolton, &
Hymas, 1989; Savage et al., 1996).
Moreover, neuroimaging findings also implicate the caudate
nuclei in the pathobiology of OCD
(Baxter et al., 1992; Luxenberg et al., 1988; Robinson et al.,
1995), suggesting that the
visuoperceptual and visuomotor integration deficits in TS and
OCD may arise from a common
abnormality in the basal ganglia, and more specifically in the
caudate nuclei and their associated
cortical–striatal networks. This is feasible because the caudate
serves an integrative function,
receiving input from motor areas of the frontal lobe (e.g.,
frontal eye fields, lateral orbital,
supplementary motor and premotor areas) and visuoperceptual
areas of the parietal lobe
(Alexander et al., 1986). The caudate is well situated to
function as a control process for the

integration of motor and perceptual processing streams
important to visual–motor integration.
In summary, our data are in complete agreement with the extant
literature on relative deficits in
visual–motor integration among children with TS. Moreover, we
found no evidence to suggest that
comorbid ADHD or depressive symptomatology could account
for the observed group differences.
The consistency with which drawing difficulties have been
observed across all studies in the
literature suggests that this domain of functioning should be
routinely assessed for all referrals with
TS. In our experience, the manner in which the child's difficulty
with visual–motor integration is
typically manifested is in his or her penmanship. Frequently
these children struggle with legible
handwriting and in many cases it is a significant impediment in
school.
This study also provides partial support for a component
process model of visual–motor
integration. Scores on the VMI were significantly correlated
with tests of visuoperceptual and fine-
motor coordination. Moreover, three putative component
processes, fine-motor skill,
visuoperceptual ability, and response inhibition, were also
significant areas of weakness for
children with TS, irrespective of their ADHD status. However,
none of the measures used for
assessing these three component processes could fully account
for the deficits in visual–motor
integration. Therefore, the integration of sensory and motor

processes appears to be a
fundamental consequence of TS, perhaps arising from
abnormalities in the caudate nuclei. We
advocate the use of a component process approach to
disentangle dimensions of visual–motor
integration. Future studies should consider using motor-free
tests of visuoperceptual and
visuospatial functioning, simple and complex motor tasks with a
limited role for visuoperceptual
analyses, and more extensive measures of motor inhibition and
vigilance.
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Submitted: March 18, 1996 Revised: April 25, 1997 Accepted:
June 4, 1997
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Source: Neuropsychology. Vol. 12. (1), Jan, 1998 pp. 134-145)

Accession Number: 1997-42613-011
Digital Object Identifier: 10.1037/0894-4105.12.1.134
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