Difficulties in perceptual–motor coordination of reaching behavior in children with autism spectrum disorder

Increased risk of injury from collisions with objects is an important issue in children with autism spectrum disorder (ASD). The purpose of the present study was to examine whether impaired perceptual e motor coordination may underlie the high frequency of collisions. Speciﬁcally

Autism spectrum disorder (ASD) is a developmental disorder that impairs social communication and both restricted and repetitive patterns in behaviors, interests, and activities (American Psychiatric Association, 2013).These impairments have a significant impact on daily life, often resulting in functional limitations in areas such as education, employment, and interpersonal relationships.In addition, children with ASD are reported to experience more injuries than those without ASD (Jain et al., 2014).A previous study found that the frequency of injury was 20% higher in children with ASD than in those with typical development (TD) (McDermott et al., 2008).However, data from the National Survey of Children's Health indicated that children with ASD were twice as likely to be injured as those with TD (Lee et al., 2008), and that in toddlers, severe injuries such as traumatic brain injury, fractures, and cuts were more frequent in those with ASD.Such injuries are often caused by accidents involving falls or being struck by or crashing into objects (Kalb et al., 2016).These findings suggest that children with ASD are susceptible to injury.
We hypothesized that the high susceptibility to injury observed in children with ASD may be due to impaired perceptualemotor coordination, which refers to the utilization of perceptually derived information (e.g., from vision or touch) in the control of ongoing movements (APA Dictionary of Psychology, 2007).At least two properties can lead to impaired perceptualemotor coordination in children with ASD.The first is an inaccurate perception of the spatial relationship between the body and the environment.A previous study found that adolescents and adults with ASD showed a greater degree of dissociation between estimated movement and actual movement than controls matched for age and IQ.Its effect was particularly evident in an aperture passability task in which participants judged the minimum aperture size their hand could pass through (Linkenauger et al., 2012), suggesting that children with ASD have an inaccurate perception of the spatial relationship between the body and the environment (aperture size).In addition, children with ASD may have difficulty using visual information in motor control for the reason that they prefer motor learning, which relies more on proprioceptive rather than on visual cues (Glazebrook et al., 2009;Haswell et al., 2009;Marko et al., 2015).Such difficulty with body-related spatial perception and the high frequency of collisions with objects that is observed in children with ASD (Kalb et al., 2016) suggest that these children have greater difficulty perceiving the spatial relationship between their bodies and the surrounding environment compared with children with TD.
The second property that may lead to impaired perceptualemotor coordination is inadequate anticipatory motor planning (Kikuchi & Higuchi, 2024).Individuals with ASD have been shown to have difficulty planning the sequence of actions required to achieve a goal (Cattaneo et al., 2007;Fabbri-Destro et al., 2009).More specifically, individuals with ASD are not well prepared (predictive motor planning) within the initial actions in advance of the subsequent actions.This difficulty can be identified when performing chained tasks that comprise initial and subsequent actions.Consistent with these findings, several other studies have also suggested that children with ASD do not sufficiently anticipate and plan for the subsequent movement while planning and executing the initial movement (B€ ackstr€ om et al., 2021;Forti et al., 2011).
Inadequate planning of subsequent movements may stem from a detail-focused processing style, which has been identified as attention to detail in children with ASD.This processing style is characterized by a tendency to focus attention on specific details rather than on the overall context (Happ e & Frith, 2006;Mottron et al., 2006).Gowen and Hamilton (2013) proposed that detail-focused processing may be associated with motor planning strategies in children with ASD.Bodyrelated spatial perception in children with ASD is also thought to be affected by detail-focused processing.Indeed, our previous research revealed that young adults with high autistic traits who might have a similar detail-focused tendency were highly likely to exhibit difficulty with body-related spatial perception (Kikuchi & Higuchi, 2024).Due to their detail-focused processing style, their attentional processing for body-related spatial perception and cognitive processing for motor planning may become vulnerable under load, thus leading to an increased susceptibility to injury.
The purpose of the present study was to evaluate impairment of perceptualemotor coordination in children with ASD and to determine the association of such impairment with susceptibility to injury.Specifically, we investigated the relationship between difficulty with body-related spatial perception and inability to plan movements due to a detail-focused processing style among those with high rates of collision with objects and people.An action-selection task that incorporates elements of the aperture passability task and the chained task was employed for this purpose (Kikuchi & Higuchi, 2024).The task was designed to assess (1) the ability to perceive the spatial relationship between the body and the environment in the subsequent movement and (2) the attentional and motor properties involved in anticipatory planning of subsequent movements during the initial movement phase.In this task, the initial movement was the reaching movement for grasping a marble, and the subsequent movement was transporting the marble from the right side to the left side of an experimental apparatus, along with action selection for avoiding obstacles within the apparatus.Participants made a choice of two actions depending on the size of the aperture between two obstacles located above and below the center of the apparatus: to pass through the aperture or to detour above the obstacles.The width of the aperture at the exit (exit width) was adjusted as the ratio of the participant's hand to the exit width and the width of the aperture at the entrance (entrance width) was designed to be wider than the exit width.In the case that the exit width is narrower than the hand width even when the entrance width is widened, the participant should detour above the obstacles to avoid collision with the obstacle.This task enabled us to examine the hypothesis that children with ASD are unable to predictably perceive environmental information and plan their movements due to their detailfocused processing style, and as a result, are more likely to experience collisions.We assessed the participants' perceptualemotor coordination ability from multiple measures using this task (i.e., collisions with the obstacle, bodyrelated spatial perception, attention properties, and motor planning).
There were three working hypotheses in the present study.First, children with ASD would misjudge apertures that were impassable as being passable, resulting in frequent collisions with the obstacles.Second, children with ASD would not fixate around the aperture at the exit because of their detailfocused processing style.Third, children with ASD would focus on the initial movement, which would lead to the following: 1) inadequate anticipatory motor planning, such as increased impulsive reaching behavior (i.e., they would reach smoothly to grasp the marble as soon as the start signal was given), and 2) less hesitation behavior (i.e., they would attempt to pass through the impassable aperture before finally deciding to detour above the obstacles).If these hypotheses were supported, the findings would suggest impaired perceptualemotor coordination (such as difficulties in perceiving spatial relationships and anticipatory motor planning) in children with ASD.To examine the relationship between susceptibility to injury and impaired perceptualemotor coordination, each participant's parent completed a questionnaire regarding their child's susceptibility to injury (Injury Behavior Checklist; Potts et al., 1997).We expected that children with ASD would have difficulty with perceptualemotor coordination due partly to their detail-focused processing style, and thus be susceptible to injury.

Methods
We report how we determined our sample size, all data exclusions, all inclusion/exclusion criteria, whether inclusion/ exclusion criteria were established prior to data analysis, all manipulations, and all measures in the study.

Participants
Thirteen children with ASD and 13 those with TD were recruited (see  et al., 2007) to estimate the sample size to achieve sufficient power.The power (1-b) was set at .80 and the significance level a was set at .05.The Effect size was set at .50, referring to Linkenauger et al. (2012), which was referenced in the creation of the experimental task.The results of the power analysis showed that power and significance level a could be achieved with N ¼ 12 samples.The sample size was therefore increased to 26 individuals, approximately twice the estimated required sample size.This study was conducted with the approval of the Ethical Review Committee of Tokyo Metropolitan University (approval number: H3-66).The experiments were conducted after obtaining informed assent from children and informed consent from their parents.

Cognitive measure, motor coordination skill, and parental questionnaires
All children were assessed with Raven's Colored Progressive Matrices (RCPM) for intellectual ability and the Movement Assessment Battery for ChildrendSecond Edition (MABC-2) for motor coordination skills.The RCPM test is useful as an intelligence test for Japanese children (Uno et al., 2005).The MABC-2 is a measure of motor coordination skills in children consisting of three component areas: manual dexterity, aiming and catching, and static and dynamic balance (Henderson et al., 2007).In this study, it was used to test participants' manual dexterity including three subtests.The raw scores for each individual subtest are converted to a standardized score, which is used as an indicator of motor difficulty.According to the MABC-2 test manual, scores below 4 points suggest a significant motor problem requiring motor intervention, scores of 5e6 points signify borderline motor difficulty, and scores above 7 points indicate no motor difficulty.Legal copyright restrictions prevent public archiving of RCPM and MABC-2 which can be obtained from the copyright holders in the cited references.
All parents filled out three questionnaires: the Social Responsiveness Scale Second Edition (SRS-2: Constantino & Gruber, 2005), the Edinburgh Handedness Inventory (EHI: Oldfield, 1971), and the Injury Behavior Checklist (IBC: Potts et al., 1997).The Japanese version of the SRS-2 was used to quantitatively assess the severity of social impairments (Kamio et al., 2013).The SRS-2 including a 65-item questionnaire is a parent-and/or teacher-reported measure of a child's social impairments in ordinary social settings.Each item is rated on a 4-point scale, and raw scores are converted to a total T score (M ¼ 50, SD ¼ 10).Higher scores indicate greater severity of social impairments.All TD children did not exceed the cutoff score of 60.With regard to the EHI, the scores generate a laterality quotient (LQ), ranging from À100 (consistent left-hand preference) to 100 (consistent right-hand preference).It was used as a guide to determine which hand (the preferred) was used in the original action-selection task.As a result, 12 of the 13 participants in both the ASD and TD groups were classified as right-handed.The IBC is a 24-item questionnaire that assesses children's risk-taking behaviors (e.g., runs out into the street, plays carelessly around water hazards).It uses a 5-point Likert scale (0 ¼ not at all, 4 ¼ very often) to rate the child's engagement in risk-taking behaviors.The summary scores range from 0 to 96; higher scores indicate the child tends to take more risks.The IBC has acceptable reliability (internal consistency ¼ .87;1-month testeretest ¼ .81)and can significantly differentiate between children who have been injured two or more times and those who have been injured less often in both preschool and school-age samples (Potts et al., 1997;Speltz et al., 1990).Legal copyright restrictions prevent public archiving of SRS-2, EHI and IBC which can be obtained from the copyright holders in the cited references.

Apparatus
The experimental setup was shown in Fig. 1.Participants were presented with the apparatus, which consisted of two obstacles, a marble placed on the container, a target container, and a screen.The marble container was placed on the side of the dominant hand, as determined by LQ.The aperture was created between the upper triangular obstacle and the lower rectangular obstacle.The position of the upper obstacle could be moved up and down to adjust the aperture width of the side of the target container (e.g., the left side of the aperture for right-handed participants), which was defined as the exit width.The exit width could be adjusted to the first decimal place.The aperture width of the other side was defined as the entrance width.To change the entrance width, the shapes of the upper obstacle were altered.The screen (40 cm Â 40 cm white cushioning sheet attached to a clapper board) was placed in front of the apparatus so that the experimental apparatus was concealed from the participant.The screen was manually controlled to open to signal the start of the task.Depending on the participant's dominant hand, the left-right arrangement of the experimental apparatus could be reversed (see Kikuchi & Higuchi, 2024 for more details).Experimental setup.The panel shows the seated posture of a participant performing the original action selection task.As an example, the monitor in the panel shows the participant's viewpoint and gaze point as seen in the Tobii Pro Glasses 2 control software.Since the participant is right-handed, the left side of the aperture is defined as the exit and the right side as the entrance.
Three-dimensional motion analysis OQUS (Qualysis AB., Sweden) was used to evaluate the participants' hand movements at a frequency of 100 Hz.The reflective marker was attached to the dorsal surface of the thenar.Eye-tracking data measured with Tobii Pro Glasses 2 (Tobii AB, Sweden) were processed with Tobii Pro Lab software (version 1.181, Tobii AB, Sweden) at a frequency of 100 Hz.

Task and protocol
The goal of the task was to transport a marble to the target container, either by passing through an aperture between two obstacles or by passing over the upper obstacle.Before beginning a trial, participants sat on a stool in front of a desk, and they positioned their right index finger on black tape affixed to the desk (Fig. 2a).The height of the table was adjusted to be in line with the participant's xiphoid process.
Participants waited in front of a closed screen and initiated their hand movement when the screen was opened (Fig. 2b).They reached to the marble container, grasped the marble (Fig. 2c), and transported it to the plastic container (Fig. 2d and  e).They were instructed to pass through the aperture if they deemed it possible to do so without colliding with the obstacle.
No part of the study analyses or procedures were preregistered prior to the research being conducted.
Participants proceeded in order from left to right.The experimental conditions were set as follows: There were five exit widths: .70,.95,1.10, 1.25, and 1.50 times the hand-width defined by the distance between the second metacarpal head and the first metacarpal head when participants pinched the marble with the thumb and index finger.In addition, there were two entrance widths: 0 cm and 6 cm wider than the exit width.The 6 cm entrance width was used   as the experimental condition to induce passage through the aperture, and the 0 cm entrance width was used as the control condition.The experimental protocol included 40 main trials: four replications for five exit width conditions and two entrance width conditions.Trial order was randomized.

Data analyses
There were five types of dependent variables: the number of collisions, body-related spatial perception, eye-tracking data, motion analysis, and the number of hesitation behavior.

The number of collisions
Among the trials in which participants chose to pass through an aperture, the number of collisions with the obstacle were counted.Collisions were judged by the experimenter's observation and by video recording.

Body-related spatial perception
Following our previous study (Kikuchi & Higuchi, 2024), the ability to perceive the spatial relationship between the body and the environment was evaluated in terms of three measures: the "sensitivity" to changes in the exit width, the "consistency" of hand movement through the aperture, and the "accuracy" in perceiving the aperture width without colliding with an obstacle.Sensitivity is the ability to detect important relationships between the body and the environment.Sensitivity to changes in exit width (e.g., distinguishing between narrow and wide exit widths) allows for flexibility in switching between action-selections.Actions to the perceived environment must be consistent.For example, colliding or not colliding with an obstacle at the same exit width reflects a lack of consistency.Accuracy refers to the congruence between perceived judgments and actual behavioral outcomes.Accuracy is necessary to assure that action-selection is appropriate given the characteristics of the body and the environment.These dependent variables of body-related spatial perception were calculated as follows.First, the performance in each trial was evaluated and assigned to one of three categories: success (S), failure (F), and refusal (R).Success (S) meant that participants successfully passed through the exit aperture without striking the obstacle.Failure (F) indicated that they chose to pass through the aperture but collided with the obstacle or deviated from the trajectory guide tape.Refusal (R) entailed participants taking a detour (i.e., going over the upper obstacle) instead of passing through the aperture.Using the percentage of performances in each category among all trials, we calculated the attempt rate and the success rate.For each participant's hand width ratio multiplied by the aperture at the exit, the attempt rate was calculated as the percentage of trials among all trials in which the participant chose to pass through the aperture.The success rate was calculated as the percentage of trials in which the participant successfully passed through the aperture without striking any obstacles.
The attempt rate ¼ Attempt rate and success rate trends were approximated using a logistic curve (Fig. 3).The decision threshold (DT) as the magnification of the exit width at which the attempt rate reached 50% and the affordance threshold (AT) as the magnification of the exit width at which the success rate reached 50% were estimated using the following equations (Nobusako et al., 2018).
The left graph (a) shows the logistic curves of the DT and AT for the ASD group, and the right graph (b) shows the logistic curves of the DT and AT for the TD group.The plots indicate the probability of the attempt rate and the success rate for the ratio of aperture size at the exit to hand-width.
In the above formulas, r denoted each ratio of each exit width, P(r) was the estimated probability for each ratio of the exit width, a was the slope of the approximated curve, and DT or AT was the 50% probability.The slope of the attempt rate [a (DT)] curve was used for the sensitivity, and the slope of the success rate [a (AT)] was used for the consistency.The absolute difference between the DT and the AT was calculated as the accuracy (jDT-ATj).This value was often positive, but when it was negative, it indicated that the participant evasively chose to pass over, despite the aperture having a high probability of passing through without collision.Therefore, this difference value was absolutized and used as an accuracy (estimation error) value.Estimations of a, DT, and AT were performed by approximating the logistic curve using nonlinear least squares in the curve-fitting toolbox in MATLAB R2020b (MathWorks Inc., USA).Scripts are available at: https://osf.io/brf9y/.

Eye-tracking data
To assess where participants predictably directed their attention to the device, gaze behavior was measured using the eye tracker and quantified the amount of fixation at the aperture at the exit (area of interest: AOI) during the initial movement (time of interest: TOI).Fixations were defined as a gaze that remained on location according to the Tobii I-VT (attention) filter.This filter incorporated a velocity threshold of 100 visual degrees per second ( /s), a criterion for merging the adjacent fixation (maximum angle between fixations: .5 ; maximum time between fixations: 75 ms) and a window length of 20 ms for the I-VT fixation classifier, as set by default in Tobii Pro Lab (Tobii Technology, 2019).The total duration of fixation (TDF) on the exit AOI were calculated to quantify the amount of fixation.Since the duration of the initial reach movement varied between participants, the TDF was converted to a proportion within the reaching duration (RD), as the following equations.The definition of RD is described in the motion analysis section.In addition, to clarify whether the failure to fixate the aperture at the exit during the initial movement was related to the collision, the number of misprediction trials in which no fixations were directed to the aperture at the exit within collision trials was counted.It was measured only under the 6 cm entrance width because it was important to fixate the aperture at the exit under conditions where the entrance width is widened.

Motion analysis
The 3D motion analysis data were smoothed with a 6 Hz Butterworth filter and analyzed using QTM software (version 2020.3,Qualisys AB, Sweden).The movements of a marker attached to the dorsal aspect of the thenar (the thenar marker) were analyzed to assess participants' hand movements.We focused on the initial movement (reaching), which might reflect anticipatory motor planning of subsequent movement.The onset of the reaching duration was the frame where the velocity of the thenar marker exceeded 10 cm/sec, and the offset was the frame where the velocity was below 10 mm/sec.A normalized jerk score (NJS) was used as the smoothness of reaching movement.The NJS was calculated using the following formula.
In the above formula, j is the value of jerk differentiated from the acceleration during the reaching movement, RD (reaching duration) is the same as used in the eye-tracking data section, and WD (wrist displacement) is the amount of positional displacement of the thenar marker from the start to the endpoint.As the NJS was lower, the movement was evaluated smoother.
In addition, the time to start reaching immediately after the screen opening, called the movement initiation (MI) time, was used to analyze the impulsive reaching behavior.A shortened MI time indicates that participants attempted to reach for the marble container without considering the subsequent movement in advance.The onset of MI time was the frame where the velocity of the marker attached on the screen exceeded 10 cm/sec and the offset was the frame where the velocity of the thenar marker exceeded 10 cm/sec (the onset of the reaching phase).

The number of hesitation behavior
In addition to motion analysis, the motor planning was measured as the number of hesitation behavior, a trial in which the participants had tried to pass through an aperture before they finally chose to pass over the upper obstacle (Fig. 4).This behavior was observed between the time after grasping the marble and the time just before passing through the entrance of the aperture.In other words, hesitation behavior represented consideration of an obstacle avoidance path after the initial movement, whereas children with ASD who would have impulsively judged that they could pass through the gap were expected to exhibit less this behavior than children with TD.
The blue line is the participant's hand movement captured by 3D motion analysis.A part of blue line surrounded by a pink

Statistical analyses
Cognitive measures, motor coordination skill, and parent questionnaires were compared between Group (ASD vs. TD) using t-tests.Poisson regression analysis was used to model count data such as the number of collisions, misprediction, and hesitation behavior as objective variables.The explanatory variables were Group (ASD vs. TD) and Entrance-width (0 cm vs. 6 cm: not used in the number of misprediction).In addition to the regression coefficient, the incident rate ratio (IRR) and its 95% confidence interval were calculated.Effect sizes were calculated by dividing the coefficient by the standard error (z ¼ Coeff/SE).The means of the measures obtained from the body-related spatial perception, motion analysis, and eye-tracking data were entered into a repeated-measures two-way ANOVA with Group as between-participant factor and Entrance-width as within-participant factor.When a significant interaction was found, simple main effect analysis was examined with the Bonferroni correction.Effect sizes were reported as partial h 2 (h 2 p) statistics for the relevant main and interaction effects.The t-test and ANOVA are also reported along with the Bayes factor calculations (BF 10 ).Bayes factors greater than 3 and greater than 10 are interpreted as moderate and strong evidence, respectively, and Bayes factors less than .33 and .10 are interpreted as moderate and strong evidence against the null hypothesis, respectively (van Doorn et al., 2021).Bayes factors between .33 and 3 are interpreted as weak and inconclusive evidence.These thresholds were used merely to aid interpretation.Pearson's correlation analysis was performed between the dependent variables except for trial count data, SRS-2 T-score, MABC-2 manual dexterity score, and IBC score under the 6 cm entrance width condition.Since the correlation analysis was performed multiple times, false discovery rate (FDR) correction based on the Betjamini-Hochberg method (a ¼ .1)was performed (Benjamini & Hochberg, 1995).The threshold of significance was set at .05.All statistical analyses were performed using R-4.2.0 (R Core Team, 2022) and JASP .18.3 (JASP, 2024).All data are available at: https://osf.io/brf9y/.

Results
Means and standard deviations for all measures are shown in Table 1.The results of statistical analyses are summarized in Table 2.There were no intellectual differences between the ASD and TD groups [t ( 24

The number of collisions
Results of Poisson regression analysis revealed that Group and Entrance-width were significant predictors of the number of collisions (p ¼ .012,z ¼ 2.507; p ¼ .029,z ¼ 2.182, respectively).
The number of collisions in children with ASD was significantly greater than that in those with TD.The number of collisions in children with ASD was also significantly greater under the 6 cm entrance width than under the 0 cm entrance

Body-related spatial perception
For the accuracy, only the main effect of Group was significant (p ¼ .017,h 2 p ¼ .216,BF 10 ¼ 2.346), indicating that children with ASD show lower accuracy of body-related spatial perception than those with TD even though Bayes factor suggested weak evidence (Fig. 5a).Neither the main effect of Entrance-width nor interactions were significant relative to accuracy.The sensitivity and consistency showed that neither the main effects nor interactions were significant.Boxes denote first-third quartile, solid line indicates median, and whiskers 1.5*interquartile range.* Denotes significant differences (p < .05).

Eye-tracking data
Fig. 6a showed a heat map of participants' fixated locations in both groups.A comparison of the fixations around the aperture at the exit showed that the ASD group had less fixation around the aperture at the exit.The proportion of TDF on the exit AOI result showed a significant main effect of Group (p < .001,h 2 p ¼ .459,BF 10 ¼ 161.434) and Entrance-width (p < .001,h 2 p ¼ .555,BF 10 ¼ 436.480).Significant interaction was found (p ¼ .029,h 2 p ¼ .183,BF 10 ¼ 64843.040),so that simple main effect analysis was performed (Fig. 6b).The result showed that the proportion of TDF on the exit AOI under both entrance widths was larger in children with TD than in those with ASD (0 cm: p ¼ .002,d ¼ À2.489, 6 cm: p < .001,d ¼ À2.771), and the proportion of TDF on the exit AOI under the 6 cm entrance width was larger than that under the 0 cm entrance width in both groups (ASD: p ¼ .036,d ¼ À.624, TD: p < .001,d ¼ À1.120).Moreover, the number of misprediction were observed more frequently in the ASD group than in the TD group (p < .001,z ¼ 3.977).
The heat maps are shown in the left panel (a).The left side of heat maps are ASD group, and the right side of heat maps are TD group.The upper side of heat maps are the 0 cm entrance-width, and the lower side of heat maps are the 6 cm entrance-width.The green dots indicate the locations where the participants fixate their gaze, and the red dots indicate that they fixate on the location for a longer period of time.The aperture at the exit is surrounded by a green rectangle, indicating the area of interest for the analysis of the eye-tracking data.The graph for the proportion of total duration of fixations (TDF) on this area of interest is shown in the right panel (b).Boxes denote first-third quartile, solid line indicates median, and whiskers 1,5*interquartile range.* and ** Denotes significant differences (p < .05 and p < .01,respectively).

Motion analysis
Significant main effects of Group were found only for MI time (p ¼ .036,h 2 p ¼ .170,BF 10 ¼ 1.036).The results showed shorter MI time in children with ASD than those with TD even though Bayes factor suggested weak evidence (Fig. 5b).Neither the main effect of Entrance-width nor interactions were significant relative to MI time.Regarding the NJS, the main effects and interactions were not significant.

Hesitation behavior
Results of Poisson regression analysis revealed that Group was a significant predictor of the number of hesitation behavior (p ¼ .012,z ¼ 2.509).The number of hesitation behavior in children with ASD was significantly larger than that in those with TD.Entrance-width and interactions were not significant.

Correlations analysis results
Correlation coefficients between SRS-2 T-score, M-ABC2 manual dexterity score, IBC score and dependent variables under the 6 cm entrance width are shown in Table 3.The SRS-2 T-score, which indicates the severity of ASD, was significantly correlated with accuracy of body-related spatial perception (r ¼ .557,p ¼ .003),and proportion of TDF on the exit AOI (r ¼ -.524, p ¼ .006).The M-ABC2 manual dexterity score and the IBC score did not significantly correlate with any of the measures failing to survive FDR correction.Among dependent variables, the proportion of TDF on the exit AOI was correlated with MI time (r ¼ .517,p ¼ .007).

Discussions
Overall, the findings of the present study showed that children with ASD have difficulty with perceptualemotor coordination.First, compared with children with TD, those with ASD experienced more collisions with obstacles in the experimental apparatus, regardless of the entrance width.This finding indicates that children with ASD are prone to making incorrect action selection.Second, children with ASD displayed inaccurate body-related spatial perception, suggesting difficulty in differentiating between passable and impassable aperture widths.These results were consistent with the first hypothesis.Third, children with ASD fixated less frequently on the aperture at the exit than did children with TD, indicating that their gaze behavior reflected detail-focused processing style.These results agreed with the second hypothesis.Fourth, in motion analysis, MI time was significantly shorter in children with ASD than in those with TD, which suggests the possibility that children with ASD reached for the marble impulsively.Hesitation behavior was more frequent in children with ASD than in those with TD.When considering the results of MI time alone, as in the third hypothesis, it appears that children with ASD did not sufficiently consider whether the aperture was passable before initiating the movement.However, the more frequent hesitation behavior found in children with ASD suggests that they can modify their action selection immediately before the next movement.Lastly, the correlation analyses showed a significant positive correlation between MI time and the proportion of TDF on the exit AOI, indicating that a shorter MI time is related to reduced fixation on the exit width.This finding supports the possibility that children with ASD do not fixate on the important parts of subsequent movements due to their detail-focused processing style, and that they are therefore more likely to give priority to the initial movement (i.e., inadequate anticipation of the entire action).In addition, the SRS-2 T-score was correlated with the accuracy of body-related spatial perception and proportion of TDF on the exit AOI.This suggests that the higher the severity of ASD, the less attention is paid to the exit width, and the greater the likelihood of inaccurate perception of the aperture width of subsequent movements.In contrast, no correlation was found for the MABC-2 manual dexterity score with any of the measures.In other words, it is unlikely that manual dexterity affected the results of this experimental task.Based on these findings, we concluded that children with ASD have difficulty with perceptualemotor coordination.We failed to find a significant relationship between the difficulty with perceptualemotor coordination and susceptibility to injury.Considering a relatively large individual difference in the IBC score in ASD group (ranged from 0 to 30) a larger sample may have been necessary to find a clear relationship.A previous study testing the injury risk of children with ASD at the age of 0e20 reported that a significantly greater injury risk than children with TD was observed only at the age of 0e5 (Jain et al., 2014).We do not believe that this does not necessarily mean the improvement of issues that lead to injuries because less experience of injuries also results from a lack of sports/physical activity and community participation as they age (Schlenz et al., 2015).Given that the difficulty with perceptualemotor coordination still exists in young adults with higher autistic traits (Kikuchi & Higuchi, 2024), future studies are necessary to further explore the relationship between the difficulty with perceptualemotor coordination and susceptibility to injury.
In the present study, we focused on atypical body-related spatial perception in individuals with ASD.However, previous studies have reported the contradictory finding that such individuals may have greater reliance on proprioceptive motor learning strategies, suggesting superior awareness of the position of limbs in the space surrounding the body (Tse, 2019), and may also have superior visual estimation abilities (Ashwin et al., 2009;Souli eres et al., 2010).Based on the present findings, we tentatively assume that the disagreement among studies might be related to differences in the perceptual information that was evaluated.Souli eres et al. ( 2010) asked participants to estimate perceptual information such as surface, length, and distance, and reported superiority in individuals with ASD.In this case, detail-focused processing style is considered an advantage because it can be accomplished using lower-order sensory information for a single object.In contrast, in the study of Linkenauger et al. (2012) and in the present study, participants were asked to estimate higher-order estimation by integrating spatial perception and motor information.In this case, detail-focused processing style is considered a disadvantage because participants must pay attention to both spatial perceptual estimation and motor information of their own hands.Future research examining whether such an explanation is correct would be desirable.
The reason why the present children with ASD did not fixate on exit width may be related to the tendency of their visual attention to be strongly drawn to certain details.Under the 6 cm entrance width condition shown in the heat map (Fig. 6a), exit width is the most critical in terms of whether a collision will occur, and is more frequently the focus of fixation in children with TD.However, children with ASD paid more attention to other areas.It is known that in individuals with ASD, detail-focused processing is likely to become apparent in tasks that require divided attention; i.e., tasks that require attention to multiple locations at the same time (Plaisted et al., 1999).Our experimental task required attention to both the aperture and the marble container, as shown in the heat map of the fixation locations (Fig. 6a), and fixation in children with ASD was particularly concentrated on the marble container.This finding suggests that they tended to focus exclusively on the initial movement of an object while failing to fixate on exit width during this movement, resulting in collisions.Notably, similar fixation patterns have been found in young adults with higher autistic traits (Kikuchi & Higuchi, 2024).We consider that their detail-focused processing style underlies such gaze behavior.
Based on the present findings, the inadequate planning of subsequent movement observed in children with ASD may also be related to detail-focused processing style.Previous studies have proposed that inadequate planning of subsequent movements may be caused by impulsivity (Hlavat a et al., 2018;McClain et al., 2017) or from reduced ability to monitor the ongoing movement (Grace et al., 2018;Hughes, 1996).Notably, we found that hesitation behavior occurred more frequently in the ASD group than in the TD group, which suggests that the behavior of children with ASD was not necessarily impulsive.This suggests that they can possibly modify their behavior, and that their ability to monitor the ongoing movement was partially spared.Alternatively, hesitation behavior can be regarded as appropriate in terms of safety management.A previous study showed that children with ASD planned movements one-by-one rather than as a whole (Studenka & Myers, 2020).If individuals with ASD are unable to recognize and process the exit width appropriately before and within the initial movement, it is reasonable to consider the exit width when approaching the obstacles.Several previous studies of motor planning have shown that children with ASD are unable to adjust their behavior in advance, and modify their behavior just before the goal (B€ ackstr€ om et al., 2021;Forti et al., 2011).The characteristics of frequent hesitation behavior and faster movement initiation time in children with ASD appear to indicate that although they fail to plan the movement in an anticipatory manner, they are able to react to obstacles with which collisions will likely occur and change their movement to avoid them.In other words, although children with ASD have poor anticipation and planning of subsequent movements due to their detail-focused processing style, they can handle these difficulties adaptively, e.g., in the acquisition of proprioceptive learning mentioned above.
With regard to brain functions corresponding to perceptualemotor coordination, dorsal visual stream dysfunction (DVSD) may be relevant.Problems with the visual motor control of movement are common when there is damage or dysfunction of the dorsal visual pathway (Cooper & O'Sullivan, 2016).A previous study of children with ASD also suggested that DVSD may cause imprecise motion, impairing interactions with objects in the surrounding space and spatial relationships between objects and people (Hay et al., 2020).In addition, the dorsal visual stream and its recipient, the parietal lobe, form two distinct functional pathway systems: the dorso-dorsal stream (d-d stream) concerned with on-line (ongoing) action control, and the ventro-dorsal stream (vd stream) concerned with spatial perception and action understanding (recognition of actions made by others) (Binkofski & Buxbaum, 2013;Rizzolatti & Matelli, 2003).The anticipatory motor planning and body-related spatial perception addressed in the present study could be considered similar to the functions performed by the d-d stream and v-d stream, respectively.The present findings imply that both streams are impaired in children with ASD.
There were several limitations of the present study.First, the small sample size in both the ASD and TD groups prevents generalization of the present findings.Second, intelligence level was simply measured by RCPM score, which may have resulted in a lack of precise control of IQ between TD and ASD children.Third, we did not obtain sufficient measures to understand additional characteristics of participants with ASD that would have been relevant to this study, such as attentiondeficit/hyperactivity disorder and developmental coordination disorder traits.A full screening for ADHD symptoms and to adopt all the MABC-2 subtests, would give a more complete picture of how attentional and motor abilities contribute to the present findings.Last, it is still unclear whether the difficulty with perceptualemotor coordination observed in children with ASD could be related to their susceptibility to injury in daily life.Further analysis or experiments should be designed to investigate this relationship.
In conclusion, we found that children with ASD have difficulty with perceptualemotor coordination in performing an original action-selection task.Such difficulty are likely to stem from two impairments: (a) an inability to perceive the spatial relationship between the body and the environment in the subsequent movement, and (b) inadequate anticipation and planning of subsequent movements during the initial movement phase.We consider that their unique attentional characteristics, referred to as detail-focused processing style, underlie these two impairments.We consider that our evaluation of the difficulty with perceptualemotor of individuals with ASD provides a framework for understanding their high rate of collision-related injuries and could inform strategies for preventing these injuries.

Fig. 1 e
Fig. 1 e The experimental setup.

Fig. 3 e
Fig. 3 e The approximation of the logistic curves under the 6 cm entrance width for the ASD group (a) and the TD group (b).

Fig. 4 e
Fig. 4 e Example of hand movement demonstrating hesitation behavior.

Fig. 5 e
Fig. 5 e (a) Accuracy of the body-related spatial perception and (b) movement initiation time under 0 cm and 6 cm entrance condition for each group.

Fig. 6 e
Fig. 6 e (a) Gaze fixation points on the apparatus shown in the heat map and (b) the graph for the proportion of TDF on aperture at the exit under 0 cm and 6 cm entrance width for each group.

Table 2 e
Results of statistical analyses for each dependent variables.Please cite this article as: Kikuchi, K., et al., Difficulties in perceptualemotor coordination of reaching behavior in children with autism spectrum disorder, Cortex, https://doi.org/10.1016/j.cortex.2024.08.005 width.Interactions between the two factors were not significant.

Table 3 e
Correlation coefficients between SRS-2 T-score, M-ABC2 manual dexterity score, IBC score and dependent variables under the 6 cm entrance width.