static and dynamic visuomotor task performance in children with acquired brain injury

J Head Trauma RehabilVol. 24, No. 5, pp. 363–373

Copyright c© 2009 Wolters Kluwer Health | Lippincott Williams & Wilkins

Static and Dynamic Visuomotor TaskPerformance in Children With AcquiredBrain Injury: Predictive Control DeficitsUnder Increased Temporal Pressure

Karen Caeyenberghs; Dominique van Roon, PhD; Katrijn van Aken;Paul De Cock, MD, PhD; Catharine Vander Linden, MD; Stephan P. Swinnen, PhD;Bouwien C. M. Smits-Engelsman, PhD

Objective: To compare performance of children with acquired brain injury (ABI) on static versus dynamic visuomotortasks with that of control children. Participants: Twenty-eight children with ABI and 28 normal age- and gender-matched controls (aged 6–16 years). Main Measures: Two visuomotor tasks on a digitizing tablet: (1) a static motortask requiring tracing of a flower figure and (2) a dynamic task consisting of tracking an accelerating dot presented ona monitor. Results: Children with ABI performed worse than the control group only during the dynamic trackingtask; the duration within the target was shorter, the distance between the centers of cursor and target was larger,and the number of velocity peaks per centimeter and the number of stops (ie, the number of submovements) werehigher than those of the control group. Rather than resulting from movement execution problems, this might bedue to less adequate processing of fast incoming sensory information, resulting in a decreased ability to anticipatethe movement of the target (predictive control). Conclusion: Deficits in eye-hand coordination require carefulattention, even in the postinjury chronic phase. Keywords: acquired brain injury, anticipation, brain damage, children,eye-hand coordination, manual pursuit, motor control

ACQUIRED BRAIN INJURY (ABI) is a majorcause of impairment and functional disability in

children. ABI is a general term referring to brain injuryas a result of traumatic brain injury (TBI), cerebrovascu-lar accidents, brain infections (meningitis, encephalitis),or brain surgery (tumors, epilepsy). The long-term ef-fects of brain injury, which vary as a function of cause,

Author Affiliations: Research Centre for Movement Control andNeuroplasticity, Department of Biomedical Kinesiology(Ms Caeyenberghs), Department of Rehabilitation Sciences, Faculty ofKinesiology and Rehabilitation Sciences (Ms van Aken), and Departmentof Paediatrics, University Hospital of Leuven (Mr De Cock), KatholiekeUniversiteit Leuven, Leuven, Belgium; Child Rehabilitation Centre,Department of Physical Medicine and Rehabilitation, Ghent UniversityHospital, Ghent, Belgium (Ms Vander Linden); and Avans+, Universityfor Professionals, Breda, the Netherlands (Ms Smits-Engelsman).

The support for this study was provided through a grant from the Research Pro-gram of the Research Foundation-Flanders (FWO, Levenslijn # 7.0004.05).D. van Roon was funded by a visiting postdoctoral fellowship of the Re-search Foundation-Flanders (FWO, GP.026.06N) and the Research Fundof Katholieke Universiteit Leuven (F/06/024). K. Caeyenberghs was fundedby a PhD fellowship of the Research Foundation-Flanders (FWO).

Corresponding Author: Bouwien C. M. Smits-Engelsman, Research Centerfor Movement Control and Neuroplasticity, Department of Biomedical Ki-nesiology, Katholieke Universiteit Leuven, Tervuursevest 101, 3001 Heverlee,Leuven, Belgium ([email protected]).

nature, and severity of the injury, may include changesin personality and deficits in memory, attention, lan-guage, problem solving, academic skills, and motor per-formance. In children with ABI, long-term motor prob-lems have received little attention, although they mayhave substantial negative consequences for the qualityof life. Research on motor performance has mainly usedstandardized motor tests (eg, Bruininks-Oseretsky Testof Motor Proficiency,1,2 Purdue Pegboard, and Develop-mental Hand Function Test3) that typically measure theproduct of task performance (eg, the time it takes to per-form the task or the number of errors). Although suchvariables provide important information regarding mo-tor performance, they address only a limited number ofaspects of motor performance. Less emphasis has beenplaced on the underlying processes of functional mo-tor behavior. Therefore, it is difficult to discover subtledeficits with such tests and to relate results to underly-ing motor control deficits. Wallen and coworkers,4 forexample, did not find deficits in upper-limb function6 months after mild TBI. Unfortunately, studies thatuse quantitative measures of kinematics are scarce.5,6

It was recently shown that, in cases of mild TBI, thecombination of arm and eye motor function assessed

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shortly after injury is a good predictor of outcome (interms of postconcussional symptoms and performanceon everyday tasks) at 3 and 6 months after brain injury,7

predicting outcome even better than early neuropsycho-logical status or self-reported health status. Therefore,the authors suggested that oculomotor function andupper-limb visuomotor performance should always beevaluated after brain injury. However, simple quantita-tive measures were lacking.

It was previously found that predictive visual and man-ual tracking of a target is impaired in adolescents andadults with mild TBI8–10 and persons with stroke,11 evenseveral years after injury. Persons with brain injury pre-dicted the trajectory of the target less accurately, andthe error scores and variability were increased. However,similar research on manual tracking of moving targets inchildren and adolescents with moderate to severe ABIis lacking, despite the fact that visuomotor deficits areoften evident on standard clinical examination.

The aim of the present study was to examine long-term effects of ABI on static and dynamic visuomotortask performance, as well as the underlying processes,in children and adolescents, using a relatively easy taskwith increasing difficulty. We predicted that childrenwith ABI would show deficits in visuomotor task perfor-mance, more pronounced when the parameters of move-ment execution have to be adjusted rapidly on the basisof perceptual error information and predictive informa-tion (ie, information that helps to predict the requiredmovements). Accordingly, participants performed 2 vi-suomotor tasks that differed in degree of time availablefor information processing required for successful per-formance. In the static visuomotor task, a computerizedversion of the flower trail task of the Movement As-sessment Battery for Children (MABC) was used.12,13

Figure 1. The flower trail is a subtest of the Movement Assess-ment Battery for Children. The flowers used in this study havea height of 10 cm and the interline width is 2 mm. Adaptedfrom Henderson and Sugden12 and Smits-Engelsman.13

Figure 2. Schematic representation of the dynamic visuomotortask.

Children traced a flower (Fig 1) as accurately as possiblewith an electronic pen on a digitizing tablet and with-out speed constraints. The task tested the ability to adaptmovement accuracy to spatial constraints based on in-coming visual feedback without temporal pressure.

In contrast, the dynamic task required faster percep-tual information processing and predictive movementcontrol. The children manually tracked a visible, acceler-ating target consisting of a circular configuration (Fig 2).The target accelerated when it was tracked successfully;otherwise, it decelerated to allow reentry. Dependingon its velocity, performance was increasingly based onprospective (predictive) control. Previous studies usingthis tracking task showed clear improvements until theage of 10 to 11 years in typically developing children14

and impaired performance in children with learning dis-abilities (D. van Roon et al, unpublished data, 2009).

In the present study, it was hypothesized that chil-dren with ABI would perform the visuomotor tasks lesssuccessfully than control children because their infor-mation processing is globally impaired and that the dif-ferences would be magnified during the dynamic taskas compared with the static task. With respect to thestatic tracing task, it was expected that children with ABIwould move more slowly, less fluently, and make moreerrors.3,6 On the complex dynamic tracking task, we ex-pected performance of ABI children to be impaired be-cause of less successful tracking of targets, particularlyat high speeds. This was hypothesized to be a conse-quence of (1) deficiencies in fast cognitive processingof the information necessary for online adjustments ofthe hand movements to the discrepancy between targetand cursor location and (2) reduced predictive control,

Static and Dynamic Visuomotor Task Performance 365

which is known to be impaired in patients with closed-head injury.15–17 More specifically, reduced movementfluency was expected as reflected by an increased num-ber of velocity peaks and more movement stops to allow(re)planning. This is also known as the sequential pursuitstrategy18 or the “step-and-hold strategy,”19,20 allowingplanning and successive execution of short parts of thetrajectory.

METHODS

Participants

Fifty-six children (28 boys and 28 girls; age range 6–16 years) participated in the study, including 28 childrenwith ABI and 28 healthy control children. The childrenwith ABI (mean age = 11 years 9 months; SD = 3 years1 month) were recruited from different rehabilitationcenters and hospitals in Belgium and had made a goodneurological recovery after sustaining brain injury dueto trauma (traffic accidents and falls, n = 14), surgery(tumor, epilepsy surgery, n = 6), vascular disease (stroke,hemorrhage, n = 6), or infections (meningitis and en-cephalitis, n = 2). The demographic and clinical charac-teristics of the group with TBI are shown in Table 1. Allchildren with ABI were assessed at least 6 months postin-jury, when neurological recovery had largely plateaued.The interval between age of injury and testing was, onaverage, 2 years 9 months (SD = 1 year 9 months). Theirage at injury was, on average, 9 years 4 months (SD = 3years 6 months). The control group of normally develop-ing children was matched to the ABI children accordingto age and gender. These children were recruited fromregional primary and secondary schools in Belgium. Allcontrol children were screened to ensure that they hadno history of neurological damage.

General motor performance was assessed using theMABC (see the “Movement Assessment Battery forChildren” section). On average, the children with ABIscored at the 15th percentile of the MABC (median per-centile = 6, range = 1–92), and the control childrenat the 41st percentile (median percentile = 35, range= 3–92). Moreover, parents of the children with ABIwere asked to complete the Developmental Coordina-tion Disorder Questionnaire, a questionnaire provid-ing details about the child’s motor control, fine motor/handwriting, and general coordination.21,22 On eachitem, parents compare their child to those of the sameage with regard to specific motor skills (eg, throwing aball), using a 5-point scale. Using this questionnaire, 5children with ABI had a percentile score of 10 or less,indicating deviant motor performance, and 6 scored be-tween the 11th and the 25th percentile, indicating thatthey were at risk for motor problems.

We assessed behavioral problems with the Child Be-havior Checklist (CBCL) for ages 6 to 18 years devel-

oped by Achenbach.23 The CBCL is filled out by par-ents. The CBCL is an instrument well validated in broadpopulation-based studies as well as in studies on chil-dren and adolescents with general psychiatric disordersand with neurological or neuropsychiatric disorders.24

The CBCL has 8 syndrome scales and queries about thechild’s behavior in the past 6 months. Using a t score cut-off of 60 for the total problem score, 10 children withABI were classified as being deviant. The most frequentlyreported behavioral disturbances were problems onscale I (“Withdrawn,” 12 children), scale III (“Anxious/Depressed,” 11 children), and on scale VII (“DelinquentBehavior,” 14 children). A small group of children withABI had elevated scores on scale V (“Thought Prob-lems”) and scale VI (“Attention Problems”).

This study was approved by the local Ethics Com-mittee of Biomedical Research at the Katholieke Uni-versiteit Leuven and was performed in accordance withthe ethical standards laid down in the 1964 Declarationof Helsinki. The parents of all participants and childrenfrom 12 years of age gave written informed consent.

Tasks and procedure

Movement Assessment Battery for Children

First, the children were assessed on the MABC, a testof a child’s daily life motor function, consisting of 8items that vary across 4 age bands (4–6, 7–8, 9–10, and11–12 years). Administration time for the test was ap-proximately 20 to 30 minutes. Performance of older chil-dren was scored according to the norms for 12-year-oldchildren, and for the statistical comparison they wereage matched. Three items measure manual dexterity (egplacing pegs, shifting pegs by rows, threading lace, flowertrail), 2 items measure ball skills (eg throwing bean bag inbox, throwing ball at wall target, catching ball with onehand), and 2 items determine static and dynamic bal-ance ability (eg walking backward, hopping in squares,2-board balance, jumping and clapping). There are 2sorts of tasks at each item level: time related (scored inseconds) and error related (scored by number of goodattempts). Children can score between 0 and 5 on eachitem, and total scores will vary from 0 (very good) to 40(extremely impaired). This total score can be expressed asa percentile that shows the child’s level of performance incomparison with peers. The MABC, a commonly usedtest battery of motor functioning, shows good reliabilityand validity. The MABC has demonstrated validity inidentifying motor impairments in at-risk populations,25

and Van Waelvelde et al26 recently confirmed the concur-rent validity of the total test score and the ball-catchingitem of the second age band of the MABC. Also, concur-rent validity is good when evaluated against other com-monly used tests like the Korperkoordinations Test furKinder and Peabody Developmental Motor Scales.27,28

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TABLE 1 Clinical characteristics of the children and adolescents with acquired braininjury

PercentileTime Glasgow Movement

Current Age at since Coma Assessmentage injury injury Scale Cause of Battery

No. Sex (y; mo) (y; mo) (y; mo) score brain damage Injury type and site for Children

Traumatic brain injury1 M 6; 5 2; 10 3; 8 7 Traffic accident Mild brain trauma (left) 282 M 8; 6 5; 7 3; 0 Traffic accident Contusio cerebri: Subarachnoid

hemorrhage, hemosiderindeposits foramen magnum andclivus

50

3 M 9; 4 8; 3 1; 1 15 Fall Frontoparietal contusions left 614 F 10; 1 9; 4 0; 9 8 Fall off stairs Contusio cerebri: Frontal skull

fracture right, subduralhematoma left parietal

28

5 M 10; 6 8; 9 1; 9 Traffic accident Hemorhagic contusion rightfrontoparietal and left temporal

19

6 F 10; 8 5; 10 4; 10 Traffic accident Severe trauma, cystic fibrosis leftfrontal, minor gliosis frontalright periventricular, generalbrain atrophy (subdural liquidfrontoparietal right, enlargedventricles)

5

7 F 11; 4 6; 11 4; 5 Traffic accident Contusion, brainstem, andventricle hemorrhage

1

8 F 12; 5 11; 9 0; 9 Fall off horse Lesion and location not specifiedin available records

4

9 F 13; 2 8; 2 5; 1 8 Traffic accident Craniocerebral trauma: Frontalbrain edema

35

10 M 14; 7 9; 5 5; 2 Traffic accident Multiple hemorrhagic shearinginjuries bifrontal andhypocampal right, hemorrhageputaminocapsular right, smallhemorrhages thalamus left

1

11 F 15; 3 11; 9 3; 6 3 Fall Severe trauma, cortical andsubcortical. Temporal-parietalcontusions left, enlargedventricles

1

12 F 15; 3 12; 10 2; 5 Traffic accident Commotio cerebri 1213 F 16; 4 15; 9 0; 7 3 Traffic accident Left contusion, subdural

hematoma left parietal-occipital1

14 M 16; 8 15; 5 1; 2 Traffic accident Left frontal and right cerebellarcontusion

6

Surgery15 F 6; 4 3; 3 3; 0 Brain tumor Medulloblastoma fossa posterior,

signs of cerebellar and cerebralatrophy

3

16 F 9; 2 6; 4 2; 10 Brain tumor Medulloblastoma third ventricle 317 M 10; 4 2; 0 8; 5 Brain tumor Oligodendroglioma in brain stem,

signs of cerebellar atrophy1

18 M 9; 3 7; 0 2; 3 Epilepsysurgery

Partial posterior hippocampal andparahippocampal regions

Parahippocampaldysembryoplasticneuroepithelial tumor

12

19 F 14; 2 11; 9 2; 4 Brain tumor Papillar meningioma parietal left 2820 M 16; 4 13; 5 2; 11 Brain tumor Pilocytar astrocytoma in brain

stem92

(continues)


TABLE 1 Clinical characteristics of the children and adolescents with acquired braininjury (continued)

PercentileTime Glasgow Movement

Current Age at since Coma Assessmentage injury injury Scale Cause of Battery

No. Sex (y; mo) (y; mo) (y; mo) score brain damage Injury type and site for Children

Vascular disease21 M 9; 3 7; 6 1; 9 Hemorrhage Cerebellar and cerebral (occipital

and frontal) ischemia17

22 M 11; 2 6; 2 5; 0 Ischemicstroke

Cortical, bilateral temporal, andtemporo-occipital

1

23 M 11; 2 9; 5 1; 10 Ischemicstroke

Ischemic insult in right pons 2

24 F 13; 4 10; 11 2; 5 Ischemicstroke

Infarct in left arteria cerebri mediaaround basal ganglia and incapsula interna

1

25 M 15; 8 13; 6 2; 3 Hemorrhageafter arteri-ovenousmalforma-tion

Right frontal intracranial bleedingright above cerebri medior,

Tissue loss in basal ganglia right(extension to caudal andtemporal right)

1

26 F 16; 4 15; 4 1; 0 Hemorrhageafter arteri-ovenousmalforma-tion

Near vermis cerebellumEnlarged ventricles

1

Infection27 M 11; 0 8; 7 2; 6 Meningitis Meningococcal septicaemia 1028 F 14; 10 13; 8 1; 2 Encephalitis Postinfectious encephalitis with

psychosis and epilepsy7

Croce et al29 reported good test-retest reliability acrossall age bands of the test. A total of 116 children betweenthe ages of 5 and 12 were tested twice, 1 week apart.The kappa coefficients for all groups taken together was0.95 and ranged from 0.92 to 0.98, for each age bandseparately. Smits-Engelsman et al30 recently found thatthe average agreement between a large number of thera-pists in their classification of the children (using video-tapes) was very high. The kappa coefficient ranged from0.95 to 1.00.

Static motor task: Flower trail

One manual dexterity subtest of the MABC is theflower trail. For this study, a computerized version of thissubtest, more specifically the test for age band 2 (7 to 8years) was programmed in OASIS (Nijmegen Institute ofCognition and Information, NICI)31,32 and performedon a digitizing tablet (UD-1218-RE, Wacom, Saitama,Japan) with a wireless electronic inking pen of normalappearance and weight. The digitizer recorded pen tipposition and axial pen force at a frequency of 206 Hz.A trail width of 2 mm was used for all participants. Thechildren were instructed to draw a line between the 2

solid lines of the flower trail (Fig 1), as accurately as pos-sible and without lifting the pen. If the pen was lifted,it had to be placed on the paper at exactly the sameposition where it was lifted so that one continuous lineremained. There was no speed instruction and only thepreferred hand was tested. All children had to complete3 flowers that were printed together on one A4 sheet ofnormal paper. No extra practice trials on the digitizerwere performed, because all children had practice trialsand test trials during the MABC test, which was admin-istered first. The duration of this task was approximately5 to 10 minutes.

Dynamic motor task: Manual pursuit task

This task, also programmed in OASIS,31 consisted ofmanually tracking a red dot (diameter 2.7 cm) presentedon a 19-inch flat screen computer monitor that was ver-tically mounted in front of the participant. A digitiz-ing tablet, used to record the participant’s response, washorizontally mounted on the table top, directly in frontof the participant. The child moved the cursor, a smallyellow dot (diameter 0.53 cm) that was also displayedon the monitor, by moving a wireless, electronic pen



of normal appearance and weight, and with an inklesspen point on a white sheet of paper (A3 format), posi-tioned on the digitizer (Fig 2). The pen had to be heldin the hand with which the child usually writes. The 2-Dposition of the pen on the surface of the digitizer andthe force exerted along the axis of the pen were sampledat a frequency of 206 Hz and with an accuracy of 0.1 mm.At the start of each trial, the target speed was 20

◦/s. The

target speed never dropped below this value throughoutthe task. When tracked successfully (ie, the cursor beingcompletely contained within the target for at least 75% ofa 0.5-second time-slice period), the target slowly acceler-ated with an angular velocity increase of 5%. Otherwise,it quickly decelerated (ie, the angular velocity decreasedwith 23%) to allow reentry. Although acceleration anddeceleration occurred in discrete steps, these steps weresmall, such that the target’s motion was not perceivedas being jerky. Participants were instructed to try to keepthe yellow dot on top of the red target. To make the taskmore appealing, the target represented a villain and thecursor a policeman who had to keep the villain capturedby remaining “on top of” him. Performance feedback(ie, the number of circles drawn) was given after eachtrial. Two conditions were presented, in which the reddot rotated along a circular path with a diameter of ei-ther 3 or 10 cm, clockwise for right-handed participantsand counterclockwise for left-handed participants. Theabove-mentioned diameters of the target, cursor, and thecircular trajectory reflect the sizes on the digitizing tablet.On the computer monitor, the diameters were approx-imately twice as large. After 1 practice trial (duration60 s) with large circular movements, 2 trials lasting 60 sec-onds each were performed within each condition. Halfof the participants started with large circular movementsand the other half with small circular movements. Datacollection started when the distance between the mid-points of cursor and target was less than 4.0 cm for thefirst time. Participants were allowed to rest between trials.Performance of this task typically lasted 10 minutes.

Data analysis

The data of the flower trail were analyzed by meansof a custom-made program using OASIS software.31 Thefollowing kinematic variables were taken as dependentvariables: the number of times that the pen tip crosseda solid line of the flower (ie errors), the total movementtime in seconds needed to complete 1 flower, the meanvelocity (in cm/s; averaged across the time epochs thepen tip was moving), the number of velocity peaks persecond (in which a peak is defined as a point where theslope of the velocity curve changed sign), the trajectorylength (in cm; ie, the distance covered by the pen tip),and the axial pen force (in N) while moving.

The data of the pursuit task were analyzed using bothMATLAB (The MathWorks, Inc, Massachusetts) and

OASIS software.31 The 2-D positional data of the penwere low-pass filtered using a zero phase lag, second-order Butterworth filter with a cutoff frequency of 10 Hzand then differentiated to calculate movement velocityand acceleration (MATLAB). The dependent variableswere subdivided into measures that reflected trackingaccuracy and measures that reflected how informationwas used during tracking.

Measures of accuracy consisted of the number of cir-cles completed during a trial and the maximum velocityof the target. These measures reflect the extent to which aparticipant succeeds in unremittingly keeping the cursorwithin the target, even at higher target velocities. Whentracking success is high, the target keeps accelerating, re-sulting in more circles drawn and a higher target velocity.Additional measures of accuracy were the total amountof time that the cursor was on top of the target and themedian and standard deviation of the distance betweenthe centers of target and cursor throughout a trial.

Measures of low information was used during trackingwere also computed. The first, assumed to indicate cor-rective or predictive actions, was the number of peaksper centimeter (ie, normalized for the distance covered)in the velocity profile of the pen trace. The second andthird measures, assumed to reflect the extent to which astep-and-hold strategy was used, are the number of timesthat the velocity of the pen was below 0.5 cm/s (stop),as well as the duration of these periods (hold).

Statistical analysis

For the MABC, flower and pursuit measures, nonpara-metric Mann-Whitney U tests (2-tailed with an α level of0.05) were performed to compare the children with ABIwith the age- and gender-matched control group. Spear-man correlation coefficients were calculated for the re-lations between the MABC scores and both the flowertrail and manual pursuit variables (for the ABI and con-trol groups, separately). Finally, separate logistic regres-sion analyses (with group as outcome variable) were per-formed to identify the predictive accuracy of the modelwith the MABC variables only and the model wherebyboth MABC and dynamic task variables were included.

RESULTS

Mean values of MABC scores, the flower trail, andmanual pursuit task variables are shown for both groupsin Table 2.

Movement Assessment Battery for Children

The ABI group scored, on average, worse than thecontrol group on all MABC measures: manual dexterity,Z = −3.47, ball skills, Z = −3.30, balance, Z = −3.25,


TABLE 2 Results (Means and SD) of the participant groups on MABC, visuomanualpursuit task, and computerized flower trail

Mean (SD)

Acquired brainControl (N = 28) injury (N = 28) P

MABCManual dexterity 1.5 (2.0) 4.6 (4.0) .001Ball skills 1.2 (1.8) 4.1 (3.7) .001Balance 2.7 (2.3) 6.6 (4.9) .001Total score 5.3 (3.7) 15.3 (10.7) .001Percentile score 40.5 (24.9) 15.4 (21.8) .001

No. of deviants: No. of deviants:2 No. of at risk: 1 14 No. of at risk: 5

Flower trailNo. of errors 0.5 (0.7) 1.0 (1.0) .05Movement time, s 37.0 (11.9) 38.4 (15.4) .91Mean velocity while moving, cm/s 1.4 (0.2) 1.4 (0.3) .69No. of velocity peaks per second 3.5 (0.9) 3.5 (1.3) .83Trajectory length, cm 31.5 (2.6) 30.6 (3.4) .14Mean axial pen force while moving, N 2.00 (0.73) 1.95 (0.65) .71

Visuomanual pursuitNo. of circles 20.5 (4.4) 18.1 (5.8) .10Maximum target velocity, cm/s 12.5 (2.8) 11.1 (3.9) .11Duration in target, s 50.3 (0.9) 49.3 (1.5) .01Median distance between centers, cm 0.57 (0.05) 0.59 (0.05) .03SD of distance between centers, cm 0.45 (0.13) 0.55 (0.38) .02No. of velocity peaks per centimeter when in target 0.54 (0.22) 0.73 (0.30) .02No. of stops 21.1 (12.5) 25.5 (11.3) .03Median duration of stops, ms 82.7 (9.3) 86.7 (17.0) .65Mean axial pen force when in target, N 0.87 (0.54) 1.19 (0.64) .10

Abbreviation: MABC, Movement Assessment Battery for Children.

total score, Z = −4.18, percentile score, Z = −4.18 (allP’s < .001).

Static tracing task

On the flower trail tracing task, with only spatial con-straints, performance of children with ABI was compa-rable to that of the control children. A nearly significanteffect of group was found only for the number of timesthat the pen tip crossed a solid line of the flower; theABI children tended to make more errors, Z = −1.93,P = .054. No significant group differences were foundfor any of the kinematic dependent variables, namely,movement time, mean velocity while moving, numberof velocity peaks per second, trajectory length, and meanaxial pen force. Thus, no striking differences were ob-served between groups in performing precise tracing.

Dynamic manual pursuit task

In contrast, children with ABI showed clear problemsin performing the tracking task, in which both spatial andtemporal constraints had to be dealt with. As compared

with the control children, the children with ABI keptthe cursor within the target for a shorter duration (Z =−2.70, P = .007), showed a larger distance and SD of thisdistance between the centers of cursor and target (Z =−2.21, P = .027 and Z = −2.39, P = .017), showed morevelocity peaks per centimeter during correct tracking (ie,when inside the target) (Z = −2.38, P = .017), and morestops (Z = −2.16, P = .031). A trend was found in thedirection of a smaller number of circles drawn in theABI group (Z = −1.77, P = .077).

Correlations between MABC subscores (manualdexterity and ball skills) and visuomotor taskperformance

To gain insight into possible shared factors for thedifficulties of children with brain damage, we lookedat relations between visuomotor task performance andMABC subscores (Table 3). In the ABI group, significantnegative correlations were found between the manualdexterity subscore on the one hand and the number ofcircles, r = −0.57, P = .002, and the maximum target



TABLE 3 Results of the correlation analyses between MABC subscores (manual dexterityand ball skills) and visuomanual pursuit task

Manual dexterity Ball skills

MABC Control (N = 28) ABI (N = 28) Control (N = 28) ABI (N = 28)

Visuomanual pursuitNo. of circles −0.11 −0.57a −0.46b −0.47b

Maximum target velocity, cm/s −0.08 −0.48b −0.57a −0.38b

Duration in target, s −0.09 −0.35 −0.29 −0.36Median distance between centers, cm −0.41b 0.30 −0.01 0.27SD of distance between centers, cm 0.35 0.37 0.09 0.18No. of velocity peaks per centimeter

when in target0.26 0.34 0.40b 0.19

No. of stops 0.35 0.24 0.42b 0.03Median duration of stops, ms 0.02 −0.12 −0.18 −0.01Mean axial pen force when in target, N −0.07 −0.06 −0.22 0.07

Abbreviations: ABI; Acquired Brain Injury; MABC, Movement Assessment Battery for Children.aP < .01.bP < .05.

velocity, r = −0.48, P = .010, on the other hand, indi-cating that poor scores on the fine motor MABC itemscoincided with bad tracking performance. Also, the ballskills subscore correlated with the number of circles, r =−0.47, P = .012, and the maximum target velocity, r =−0.38, P = .047.

For the control group, the ball skills subscore was neg-atively correlated with the number of circles, r = −0.46,P = .013, and the maximum target velocity, r = −0.57,P = .002, and positively correlated with the number ofvelocity peaks per centimeter, r = +0.40, P = .034, andthe number of stops, r = +0.42, P = .025. Hence, lowerball skill levels are associated with a less successful track-ing control and more corrective actions.

Logistic regression analyses

Considerable changes in classification statistics werefound when conducting separate logistic regression anal-yses on MABC variables only (78.6% correct classifica-tions) or both MABC and dynamic task variables (85.7%correct decisions). In other words, the classification ac-curacy improves if both MABC and dynamic task vari-ables are included in the equation, as compared with theMABC variables alone (7% increase).

DISCUSSION

This study aimed to examine long-term effects of ABIon static and dynamic visuomotor task performanceand the underlying processes. The research question waswhether children with ABI show deficits in visuomo-tor task performance, and if so, whether these deficits

are more pronounced when the parameters of move-ment execution should be adjusted rapidly on the basisof perceptual error information and predictive informa-tion. We hypothesized that children with ABI would per-form more poorly than children without such damageon both visuomotor tasks as a result of lower manualdexterity3,6 and reduced predictive control.15–17 In thefollowing paragraphs, we will discuss the main results.

Motor performance

Negative effects of brain injury on manual dexter-ity, ball skills, and balance were clearly shown on theMABC. For 19 of the 28 children and adolescents withABI, moderate to severe motor problems were found.Half of the children (n = 14) had a 5th percentile scoreor less, indicating deviant motor performance, and 5scored between the 5th and the 15th percentile, indicat-ing that they were at risk for motor problems. It mustbe noted that variability was large: 9 participants scoredin the normal range as compared with peers. Moreover,the results are worse than indicated because the olderchildren are classified by norms for 12-year olds. Theseresults confirm previous results of Kuhtz-Buschbecket al,3 who also showed deficits in fine motor skills,speed, coordination, and balance by using clinical as-sessments, hand function tests, and gait analysis.

Static visuomotor task performance

No differences were found between the kinematicmeasures of children with ABI and control children onthe static visuomotor task (the flower trail). The only(marginally significant) group difference was the greater


number of errors made when tracing between lines thatare only 2 mm apart. Interestingly, without the presenceof a time constraint, children with ABI could move atthe same velocity and as smoothly as control children.

Dynamic visuomotor task performance

Indeed, children with brain damage performed worsethan control children on the manual tracking task withthe accelerating target. They were less successful in con-tinuously keeping the cursor inside the target, reflectedin a shorter duration within the target, a larger distance(and variability of this distance) between the centers ofcursor and target, and more feedback-based corrections(more velocity peaks per centimeter and more stops).These results resemble those of Heitger et al,10 whoshowed increased tracking error and prolonged trackinglag in adults with mild ABI on several manual trackingtasks. However, they did not find impairments on thesine and random tracking tasks 12 months after braininjury. This deviant finding is possibly due to the dif-ferent age groups tested as well as the tasks used. Theirtask was less complex than ours; the movements had tobe made at a lower mean velocity, while in our task thetarget continued accelerating. In addition, it is possiblethat their participants had less severe brain damage.

We suggest that difficulties with processing of fast in-coming sensory information are the main cause of themanual dexterity problems after brain injury rather thana mere execution deficit. As a consequence of the slowerinformation processing, 2 important abilities that arenecessary for successful tracking will be impaired: (1) thetimely use of feedback to correct the error and (2) theuse of predictive control, ie, anticipating the movementof the target.

Worth mentioning in this respect is that in childrenwith ABI, who were predicted to rely more on feedbackthan the typically developing children, due to their pre-dictive control problems, significant correlations werefound between the number of circles and the maximumtarget velocity on the one hand and the manual dexteritysubscore of the MABC on the other hand. For the man-ual dexterity tasks of the MABC, which are all self-paced,the online use of feedback is essential. In the group withtypically developing children, 4 tracking measures ap-peared to be correlated with the ball skills subscore ofthe MABC. We speculate that the underlying mediatingfactor is the use of predictive control in this case. Espe-cially for catching balls, prediction of the ball’s trajectoryand anticipatory behavior of the hands are required.

We hypothesize that simple quantitative computer-ized assessment of visuomotor performance might haveconsiderable potential to contribute to improved assess-ment of children with ABI. The cerebral structures con-cerned with the control of tracking are well mapped and

form extensive and highly complex functional entities,incorporating cortical and subcortical structures, as wellas the cerebellum. Such complex anatomical structuresare highly susceptible to the adverse effects of neuralinjury. Hence, besides slower information processing—asymptom in virtually all children with ABI—the damageto the large-scale communication within their brain net-works might also lead to suboptimal predictive move-ment control, in turn producing impaired tracking inchildren with TBI.33 We believe that the use of recent dif-fusion tensor imaging (DTI) techniques will enable us toinvestigate the white matter disturbance associated withvisuomotor performance. DTI has already been used ina few pediatric TBI studies to investigate the relation ofwhite matter integrity using DTI to cognitive and func-tional outcome.34–36 More DTI data are needed to testwhether deficits in visuomotor performance are relatedto variation in structural properties of the white matterpathways.

Limitations of the current study

A limitation of this study was that the static task didnot include any kind of speed instruction or constraint.Therefore, we cannot rule out that the children with ABImight have shown deficits, as compared with the controlchildren, if they had been instructed to trace the flower asquickly as possible. However, no speed differences werefound between children with TBI and control children,indicating that the group with TBI was not more or lessaccurate because of a speed accuracy trade-off. The aimwas to examine the behavior of the children with ABIunder both predictable and unpredictable conditions.Moreover, we used a computerized version of one of themanual dexterity subtests of the MABC. To maximizecomparability, we applied the standard instructions ofthe MABC.

Testing children with ABI introduces a number ofmethodological factors that may affect interpretation ofresults: ABI is a heterogeneous condition with multipledeficits that evolve over time. Also, findings will likelybe affected by the time of testing relative to the timeof injury (as indicated in Table 1). However, the groupwas relatively homogeneous in terms of injury mecha-nism and neuropathology. Moreover, each control wascarefully selected to match the patient’s demographics(gender and age). Taking into account these limitations,the present study does illustrate the visuomotor perfor-mance deficits after ABI in children.

Clinical implications and conclusions

The results of the present study show that childrenwith ABI have difficulties with visuomotor tasks, in par-ticular with dynamic tasks in which the fast integra-tion of feedback and predictive control is required. We



interpret this decreased ability to anticipate the move-ment of the target as indicating an impairment in feed-forward control. Based on the assumption that motorimagery reflects the ability to represent internal mod-els for prospective actions, motor imagery training hasalready been recognized in sports and rehabilitation(children with developmental coordination disorder andadults poststroke) as being a useful method in learningmotor skills.37–39 We assume that motor imagery trainingmight also help alleviate the impaired ability to representinternally the visuospatial coordinates of movements inchildren with ABI, with concomitant gains in motor skillperformance. On the basis of our previous motor im-agery studies,40,41 the motor imagery training protocolfor children with ABI should comprise 6 main opera-tions: (1) visual imagery exercises involving predictivetiming, (2) mental preparation, (3) visual modeling offundamental motor skills, (4) mental rehearsal of skills

from an external perspective, (5) mental rehearsal of skillsfrom an internal perspective, and (6) overt practice. Al-though these techniques seem to work in stroke patientsand children with developmental coordination disorder,it is not clear whether they can also be used for chil-dren with ABI. More information is needed on trainingregimes to determine the learning conditions that pro-mote improved performance on visuomotor tasks andwhether such gains are transferable to functional move-ments.

Deficits in eye-hand coordination require careful at-tention during rehabilitation, even in the chronic phaseafter brain damage, because for many activities of dailyliving, eye-hand coordination is of great importance.More specifically, these children need to be checked andtrained on their ability to use predictive control, whichenables them to flexibly adjust their behavior to the ever-changing environment.

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static and dynamic visuomotor task performance in children with acquired brain injury

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