Motor functioning has been studied in these disorders using behavioral neurological assessment (Damasio & Maurer, 1978; Teitelbaum, Teitelbaum, Nye, Fryman, & Maurer, 1998), gait analysis (Hallet et al., 1993; Maurer & Damasio, 1982; Vilensky, Damasio, & Maurer, 1981), analysis of postural control (Kohen-Raz, Volkmar, & Cohen, 1992), hand-writing analysis (Beversdorf et al., 2001), standardized motor batteries (e.g. Griffith's gross motor sub-scale, Bruininks–Osertsky test of fine and gross motor skills, Test of Motor Impairment-Henderson Revision, the Movement Assessment Battery for Children and the Pegboard test of motor coordination) (Ghaziuddin & Butler, 1998; Ghaziuddin et al., 1994; Gillberg, 1989; Manjiviona & Prior, 1995; Miyahara et al., 1997; Szatmari, Tuff, Finlayson, & Bartolucci, 1990), finger-tapping tasks (Muller, Pierce, Ambrose, Allen, & Courchesne, 2001; Rinehart et al., 2001a), and more recently, analysis of movement kinematics during reach- and - grasp experimental tasks (Mari et al., 2003; also see Hughes, 1996).

Several studies using standardized tests of motor functioning have directly compared children with high-functioning autism (HFA) and AD. Although it was originally thought that children with AD may have more significantly impaired motor functioning, than children with autism, as manifested by motoric clumsiness (Ghaziuddin, Tsai, & Ghaziuddin, 1992; Gillberg, 1989), more recent studies have reported similarly impaired motor functioning in both groups (Ghaziuddin et al., 1994; Manjiviona & Prior, 1995; Szatmari et al., 1990). DSM-IV-TR (APA, 2000) cites “motor clumsiness” (p. 81) as a feature of AD, whereas autistic disorder is associated with “abnormalities of posture” (p. 71). Motoric clumsiness is referred to in the ICD-10 (World Health Organization, 1992) as a symptom often found in AD; however no mention of motor clumsiness is made in the ICD-10 clinical description of autism (World Health Organization, 1992).

Some of the controversy as to whether motor functioning is indeed differentially impaired in these clinical groups may stem from a failure to consider ‘neuropsychological overshadowing’ of executive impairments. For example, comparative motor studies do not traditionally control for ‘executive’ dysfunction, a neurobehavioral component that may be more impaired in children with HFA than those with AD (Szatmari et al., 1990; Rinehart, Bradshaw, Moss, Brereton, & Tonge, 2001b; Rinehart, Bradshaw, Tonge, Brereton, & Bellgrove, 2002b). We reported subtle motor differences between individuals with HFA and AD using a simple motor reprogramming task (Rinehart et al., 2001a), which was thought to be more likely to tap the motor end of the attention—motor continuum than more cognitively demanding standardized tests of motor function. This experiment used our serial-choice button-pressing task, which yielded separate measures of motor preparation and execution time. Four target buttons (two central and two flanking) could be illuminated by an LED set into the based of each button. Upon illumination of the central buttons, participants made leftward and rightward movements in a repeating sequence as quickly as possible. Reprogramming of direction was manipulated by the introduction of an oddball to the basic reciprocating sequence. The oddball occurred at one of the two flanking buttons, either to the left or right of the central buttons. After detecting the oddball, participants were required to rejoin the reciprocating sequence. Movement preparation time was taken as the time between the illumination of one LED and the release of the previous button. Movement execution time was taken as the time between releasing one button and pressing the next. This study indicated that individuals with autism and AD have atypical movement preparation with an intact ability to execute movement. This finding is comparable to that of Hughes (1996) who used a reach, grasp, and place task. The autism and AD groups displayed different patterns of motor preparation deficits. The participants with AD were slower at the point in the reprogramming sequence following the oddball, in contrast to the normal controls who were able to quickly re-engage in the back and forth reciprocating sequence. The motor preparation anomaly displayed by the autism participants was characterized by a failure to adjust their motor preparation time in response to an ‘expected’ versus ‘unexpected’ movement, in contrast to the normal controls who were, as one would predict, faster at preparing movement for an ‘expected’ versus ‘unexpected’ movement (Rinehart et al., 2001a). The subtle motor preparation deficits observed in these disorder groups were discussed in the context of a possible dissociable involvement of the basal ganglia thalamocortical circuitry, specifically the supplementary motor area and anterior cingulate, the latter area for its involvement in ‘attention for action’ and motivational aspects of behavior (see Pantelis & Brewer, 1996; Rinehart et al., 2001a). The basal ganglia thalamocortical circuitry has also been implicated by Vilensky et al.'s (1981) and Damasio and Maurer's (1978) analyses of gait, and Muller et al.'s (2001) recent study using functional magnetic resonance imaging during a finger-tapping task. In contrast, on the basis of their gait analysis of participants with autism, Hallet et al. (1993) argued that the nature of motor impairment in children with autism is more consistent with dysfunction of the cerebellum than the basal ganglia. Given the neurological and psychiatric complexities of autism/AD, it is more likely that both of these regions are involved to some extent (Bradshaw, 2001). The subtler the motor anomaly, the more difficult it is to ascribe, with any great certainty, to circumscribed neural circuitry. Indeed, Beversdorf et al. (2001) reported that the macrographic hand-writing observed in adults with HFA and AD is seen in both patients with cerebellar and basal ganglia pathology (Phillips, Bradshaw, Chiu, & Bradshaw, 1994a). (Note: Beversdorf et al., 2001, did not provide separate data for the autism and AD participants.)

Mari et al. (2003) have recently applied kinematic analysis techniques to measure movement execution characteristics of children with autism during a reach and grasp task. This study showed that specific deficits in movement kinematics only emerged when children were sub-grouped according to intellectual ability: ‘low’ (full scale IQ below 80) versus ‘average /high’ (full scale IQ between 80 and 109). Mari et al. reported that the low ability group displayed a parkinsonian-like bradykinesia with longer movement duration and deceleration, lower peak velocity, and later time of maximum grip aperture. In contrast, the average/high ability group showed ‘intact’ movement kinematics that were, however, more rapid than both the controls and low ability groups. Mari et al. suggested that the apparent ‘hyperagility and hyperdexterity’ (p. 402) may have a negative impact on every-day goal directed movement for children with HFA/AD because it may result in an inability to use additional external—environmental cues to modulate movement once a program is set in action. Although Mari et al. included children with autism and AD in their sample, separate data were not reported for these groups.

In summary, past research studies and contemporary clinical diagnostic criteria (i.e. DSM-IV-TR & ICD-10) provide conflicting reports about the nature of motor impairment in autism and AD. Moreover, the contribution of past research to the question of whether motor impairment is similar or different in autism and AD is limited by the use of standardized motor assessment batteries which do not separate out executive from motor dysfunction. While some studies have used more careful experimental approaches, for example, Mari et al.'s kinematic analysis of motor impairment, they have failed to consider potential motor differences between autism and AD in their analyses. Our previous examination of motor functioning in autism and AD using a reprogramming task pointed to dissociation in motor planning ability between the disorder groups (in the context of an intact ability to skillfully execute movements) (Rinehart, 2002b). However, this finding is yet to be replicated. Thus a study which provides separate data for autism and AD groups, controls for potentially confounding executive functioning deficits, and separates motor preparation from motor execution, is clearly warranted.

The aim of the present study was to investigate movement kinematics (i.e. movement preparation, movement execution, and the shape of the movement trajectory (time spent in accelerative versus decelerative phases) in children with HFA and AD using a kinematic paradigm similar to that used in previous motor investigations of patients with neurodegenerative disorders (see Phillips, Martin, Bradshaw, & Iansek, 1994b; Bellgrove et al., 1997). The task was designed to also examine the impact of an executive load on movement kinematics by including expectancy and inhibitory components. The basic task involved the movement of a special stylus from a center start position toward either a left or right target according to the presentation of a visual cue (the illumination of an LED directly above the left or right target). There were three different task ‘Levels’. In Level 1, participants were simply required to move to the left or right targets that were presented in a pseudo-random order. Fifty percent of the targets appeared on the left side, and the rest occurred on the right side. Participants were told that half of the targets would appear to the left and the other to the right. This task is therefore analogous to a choice reaction time (RT) task¹ with the addition of a more prolonged motor execution component, i.e. moving a stylus towards the target, rather than merely pressing a button.

In Level 2, 75% of targets appeared to one side and 25% to the other side. Thus, in Level 2 participants were instructed that they should move in the direction indicated by the LED as quickly as possible. Additionally, they were instructed to use the expectancy manipulation to facilitate their movement preparation and execution.

Level 3, was similar to Level 2 except that an additional inhibitory component required participants to always move to the un-cued target location, instead of the cued target location. For example, if the visual cue appeared on the left side, the participant was required to move to the right target, and vice versa. This motoric task is therefore somewhat analogous to antisaccade tasks within the cognitive domain. The expectancy manipulation remained in that the participant was told to expect most cues on one side as opposed to the other.

On the basis of previous studies we predicted that children with HFA and AD would show qualitatively different motor planning deficits (Hughes, 1996; Rinehart et al., 2001a). However, based on the recent findings of Mari et al. (2003) and our previous study (Rinehart et al., 2001a) we predict both groups will show generally intact movement execution. Mari et al.'s kinematic study suggested that individuals with autism and AD (IQ > 80) may be unable to efficiently modulate movement once a motor program is set in action, however, separate data was not provided for each group, so we can not be certain whether this finding relates more to autism or AD. Thus we predict that either or both clinical groups might spend a prolonged time in the more effortful terminal guidance/decelerative phase of movement in which final adjustments are made for target acquisition (see Bellgrove et al., 1997 for a discussion of the components of voluntary movement). In our review of past motor studies we suggested that individuals with autism may perform more poorly on motor tasks than individuals with AD due to their reportedly greater impairment in executive functioning (Szatmari et al., 1990; Rinehart, Bradshaw, Moss, Brereton, & Tonge, 2001b; Rinehart, Bradshaw, Tonge, Brereton, & Bellgrove, 2002b). If motor functioning deficits in children with autism are primarily underpinned by executive functioning deficits, then we would expect deficits in movement preparation time to manifest in the more complex and cognitively demanding Levels 2 and 3 where expectancy and inhibitory components were introduced, but be relatively intact in Level 1.

Consistent with our hypothesis, deficits at the motor planning, rather than execution stage, were more predominate in both clinical groups. These results suggest that the movement deficits observed clinically for these individuals do not reflect a simple motor slowness. Given the high-functioning nature of our sample, this finding is comparable to Mari et al.'s (2003) study which showed movement execution problems were a feature of children with a full scale IQ below 80, and not apparent in more cognitively intact children with HFA/AD.

While the HFA group displayed a clear motor preparation deficit in comparison to controls, across all three Task Levels, there was only a trend towards impaired motor preparation for the AD group, and this occurred only at the least cognitively demanding task level (Level 1). The manifestation of a motor preparation deficit for a simple task, but not for a complex task, might be described as a type of kinesia paradoxa, where “the individual who typically experiences severe difficulties with the most simple of movements may suddenly perform complex, skilled movements…’ (Leary & Hill, 1996, p. 41). Leary and Hill note that this phenomenon is an important manifestation of movement disorder in children with autism spectrum disorders. This description of motor disturbance fits well with the finding that these children may have extreme difficulty with one aspect of motor functioning, for example, mastering pencil grip and writing (e.g. Beversdorf et al., 2001), but show exceptional ability on other motor tasks such as performing a rapid, complex sequence of movements on a computer joy-stick.

While on the surface, this study suggests that motor preparation may be more consistently impaired in children with HFA compared to those with AD, given the four-year age difference between the groups, caution is needed for this interpretation (despite the use of matched-control groups). Indeed, it may be that motor preparation anomalies are more pronounced at a younger age for children with autism, but that the deficit becomes less apparent or manifests as a kinesia paradoxa with age as fronto-striatal-basal ganglia thalamocortical pathways develop. Mapping the manifestation of cognitive-motor impairments in these groups over time could test the existence of such an abnormal motor developmental trajectory.

Analysis of Movement Time for Level 3 indicated the HFA participants were relatively unaffected by the expectancy manipulation. The HFA-control group, on the other hand, was significantly faster for expected than unexpected movements. This finding somewhat parallels our previous study using a motor tapping reprogramming task where movement for the HFA group, relative to matched controls, was characterized by a ‘lack of anticipation’, with motor preparation times not differing regardless of whether the movement was predictable or unpredictable (Rinehart et al., 2001a). However, as AD and AD-control participants also did not show advantages for ‘expected’ movements in Level 3 (a finding which may be developmentally linked), these data need to be interpreted with caution. Nevertheless, the failure of the HFA group to benefit from the expectancy manipulation in order to execute expected movements more quickly than unexpected ones, could reflect a down-stream effect of a motor planning deficit. Indeed, analysis of the Asymmetry Indices suggested that the HFA group tended to spend greater periods in the decelerative/terminal guidance phase for expected movements- a pattern that is indicative of a poorly planned movement.

Some of the controversy amongst studies examining motor features in children with HFA and AD may be a result of the failure to adequately control for executive functioning problems, an area that appears more impaired in HFA than AD (Szatmari et al., 1990; Rinehart et al., 2001b, 2002b). It may be, for example, that contradictory reports of motor dysfunction in HFA and AD have not taken into consideration the possibility that HFA children may have poorer executive ability, which interferes with motor performance. The present study was able, to some extent, to parse out executive and motor dysfunction. For example, if motor functioning deficits in children with autism were primarily underpinned by executive functioning deficits, then we would have expected motor deficits in the more complex and cognitively demanding task levels where attention-set shifting and inhibitory components were introduced, with relatively intact motor functioning on Level 1 that involved a choice decision. The finding that motor preparation deficits were evident across all Levels regardless of cognitive complexity (i.e. the addition of inhibitory and expectancy components) would suggest that executive dysfunction does not confer significant and additional vulnerability for motor planning in individuals with HFA. Nevertheless, as argued above, there was evidence for task complexity effects within the execution phase of movement which might reflect a down-stream manifestation of impaired motor planning, since a poorly planned movement will need to be adjusted and guided on-line. To this extent our results resemble those seen in traditional movement disorders such as Parkinson's disease. For example, patients with Parkinson's disease (a classical hypokinesia disorder) show motor planning and execution deficits when required to perform sequential movements under conditions of reduced ‘advanced’ information; a task manipulation somewhat analogous to the ‘expectancy’ manipulations used in the current motor task (Georgiou et al., 1993, 1994).

The difficulty preparing for/initiating movements observed in the HFA group, and to a lesser extent in the AD group who displayed what might be described as kinesia paradoxa, can potentially be linked to a ‘parkinsonian like’ abnormality in dopaminergic activity resulting in inadequate output to the pre-motor areas of the brain, including the supplementary motor area (SMA). There is some neuroimaging evidence implicating frontostriatal regions such as the striatum, caudate, and putamen in autism (Fernell et al., 1997; Happe et al., 1996; Siegel et al., 1992). Functional neuroimaging studies have also found decreased metabolic and neurotransmitter activity in the thalamus, basal ganglia and cortical regions of individuals with autism (Chugani et al., 1997; Horwitz, Rumsey, Grady, & Rapoport, 1988). Future work will need to determine the neural circuitry that might underpin motor planning deficits in these disorder groups.

As discussed above, the HFA group tended to spend a prolonged period in the decelerative phase of movement when responding to an ‘expected’ but not an ‘unexpected’ target in Level 2. Normal time in the accelerative phase of movement with prolonged time spent in the more effortful terminal guidance phase in which final adjustments are made for target acquisition, is consistent with Mari et al.'s (2003) suggestion that these individuals may be unable to efficiently modulate movement once a program is set in action. Such difficulty with visually guided hand movements is somewhat consistent with the movement of cerebellar patients which is characterized by a failure to accurately modulate later stages of movement in order to efficiently ‘home-in’ on targets (Rosenbaum, 1991). Anecdotally, young adults with HFA report that they have difficulty ‘catching’ a ball because ‘at the last minute’ they do not know what to do as the ball approaches. This might relate to a cerebellar target acquisition deficit. Conversely, patients with Parkinson's disease typically have no difficulty catching a ball (more like a reflex), but have difficulty throwing a ball (a more purely voluntary action) (Georgiou et al., 1994). The cerebellum has been extensively implicated in autism using behavioral, neuroimaging, and postmortem analyses (see Courchesne, 1999; Courchesne, Hesselink, Jernigan, & Yeung-courchesne, 1987; Courchesne et al., 2001; Courchesne, Kilman, Galambos, & Lincoln, 1984; Courchesne, Muller, & Saitoh, 1999; Courchesne et al., 1994a, b; Courchesne, Yeung-courchesne, Press, Hesse-Link, & Jernigan, 1988).

There are two clear limitations of this study; first, while it would have been desirable to directly compare HFA & AD groups, in view of the developmentally critical age-gap between groups it was not deemed appropriate to incorporate age as a covariate in data analyses. It is important to note, however, that the four-year age difference between our HFA and AD sample is entirely consistent with the different ages at which children who meet these diagnostic criteria present to assessment services: HFA (mean age at the time of diagnosis = 5.5 years) and AD (mean age at the time of diagnosis = 11 years) (Howlin & Asharian, 1999). The second limitation of note is that the small sample size is likely to be responsible for the inconsistent between-task findings, for example, the HFA group showing a tendency towards prolonged decelerative phase of movement in Level 2, but not Levels 1 and 3. Again, it is difficult to avoid this type of limitation given the relative difficulty associated with recruiting young people with HFA and AD who are matched intellectually and without comorbid medical conditions.

Notwithstanding these limitations, this research utilizes an innovative methodological approach to address the controversial issue of whether motor functioning is similarly impaired in HFA and AD. The overall finding that motor abnormalities (in particular motor preparatory function) appear more impaired in individuals with HFA than AD, contrasts with findings from standardized test batteries which show, for example, that these groups perform similarly when assessed on tests of ball skill, balance, and manual dexterity (Manjiviona & Prior, 1995; Miyahara et al., 1997). Although one study does not necessarily negate the findings of the other, the inconsistency does suggest that while on some tasks individuals with HFA and AD may share functional motoric impairment, (e.g. difficulty catching a ball), the fundamental underlying nature of motor impairment may be distinct (e.g. differential involvement of the cerebellum and fronto-striatal-basal ganglia motor circuitry).