effects of interlimb and intralimb constraints on bimanual shoulder-elbow and shoulder-wrist...

Li, Levin, Forner-Cordero & Swinnen

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The effects of interlimb and intralimb constraints on bimanual shoulder-

elbow and shoulder-wrist coordination patterns

Yong Li, Oron Levin, Arturo Forner-Cordero & Stephan P. Swinnen

Laboratory of Motor Control, Dep. of Kinesiology, FABER, Katholieke Universiteit

Leuven, Belgium

Running head: coordinative behavior of multijoint system

Address correspondence to:

Stephan P. Swinnen

Laboratory of Motor Control

Department of Kinesiology

K.U.Leuven

Tervuursevest 101

B-3001 Heverlee Belgium

Tel: 32 16 32 90 71

Fax: 32 16 32 91 97

E-mail: [email protected]

Articles in PresS. J Neurophysiol (May 31, 2005). doi:10.1152/jn.00312.2005

Copyright © 2005 by the American Physiological Society.


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Abstract

The present study addressed the interactions between interlimb and intralimb

constraints during the control of bimanual multijoint movements. Participants

performed eight coordination tasks involving bilateral shoulder-elbow (Experiment I)

and shoulder-wrist (Experiment II) movements. Three principal findings were

obtained. First, the principle of muscle homology (in-phase coordination), giving rise

to mirror symmetrical movements with respect to the mid-sagittal plane, had a

powerful influence on the quality of interlimb coordination. In both experiments, the

accuracy and stability of inter- and/or- intralimb coordination deteriorated as soon as

the anti-phase mode was introduced in one or both joint pairs. However, the mutual

influences between bilateral distal and proximal joint pairs varied across coordination

tasks and effectors. Second, the impact of intralimb coordination modes on the quality

of intralimb coordination was inconsistent between adjacent (Experiment I) and

nonadjacent joint (Experiment II) combinations. Third, the mode of interlimb

coordination affected the quality of intralimb coordination whereas strong support for

the converse effect was not obtained. Taken together, these observations point to a

hierarchical control structure whereby interlimb coordination constraints have a

stronger impact on the global coordination of the system than intralimb constraints,

whose impact is rather effector- and task-dependent. The finding that intralimb

coordination is subordinate to interlimb coordination during the production of

bimanual multijoint coordination patterns indicates that symmetry is a major

organizational principle in the neural control of complex movement.

Keywords: multijoint, bimanual coordination, interlimb, intralimb, interaction torque


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Introduction

Many daily life activities require some degree of interlimb and intralimb

coordination between the joints of the upper limbs, such as pulling or pushing boxes,

waving your arms together, driving a car, etc. Some of these coordination patterns

represent preferred modes and reflect the intrinsic characteristics of the

musculoskeletal system. With respect to interlimb coordination, it has been observed

that mirror symmetrical coordination patterns associated with the simultaneous timing

of activation of homologous muscle groups (in-phase), are performed with higher

accuracy and stability than movements in which the activation of homologous muscle

groups occurs in alternation (anti-phase) (Byblow et al. 1994; Kelso, 1984; Lee et al.

2002; Park et al. 2001; Semjen et al. 1995; Carson et al. 1997; Stucchi and Viviani,

1993; Swinnen, 2002; Swinnen et al. 1997, 1998). For motions towards and away

from the body midline, in-phase patterns are characterized by movements in different

directions in extrinsic space and anti-phase patterns by same direction movements. As

such, muscle grouping and direction appear confounded. Nevertheless, it has also

been demonstrated that there are independent influences of muscle grouping and

direction on coordination, with the former playing a more dominant role than the

latter (Swinnen et al. 1997, 1998).

Much less attention has been devoted to the principles governing the

coordination between joints within a limb. Studies on inter-segmental (intralimb)

coordination have revealed that simultaneous flexion or extension of the elbow and

wrist joints (isodirectional) is associated with higher stability than coordination modes

in which flexion in one joint is performed together with extension in the other joint, or

vice versa (non-isodirectional) (Kelso et al. 1991; Dounskaia et al. 1998). Such

interactions between joints within a limb may arise from dynamical as well as neural


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sources. For example, it has been recognized that mechanical interactions between

adjacent body segments have an important influence on multi-joint control during the

execution of various single-limb tasks (Bernstein 1967; Dounskaia et al. 1998;

Gribble and Ostry 1999; Hollerbach and Flash 1982; Levin et al. 2001).

So far, interlimb and intralimb coordination constraints have predominantly

been explored in relative isolation from each other. This raises questions about the

coalition of these constraints when interlimb and intralimb coordination patterns of

the upper limbs are combined within a single task. Such tasks provide a unique

opportunity to study the mutual interactions between the aforementioned constraints.

In the present study, we investigated bilateral shoulder-elbow (Experiment I) and

shoulder-wrist joint combinations (Experiment II). The interlimb coordination

patterns referred to the in-phase and anti-phase coordination modes. The intralimb

coordination patterns referred to the isodirectional and non-isodirectional modes.

Our aim was to determine whether the higher accuracy/stability of in-phase as

compared to anti-phase and isodirectional as compared to non-isodirectional patterns

was also evident in these complex multijoint tasks. More importantly, three additional

objectives addressed the interactions between interlimb and intralimb coordination

patterns. First, we assessed how the mode of coordination between the bilateral

segments impacts upon the quality of coordination between the joints within a limb,

i.e., the effect of interlimb on intralimb coordination. Second, we also determined

whether the modes of intralimb coordination influenced the quality of interlimb

coordination. More specifically, it was determined whether the coordination mode

adopted within the dominant as compared to the non-dominant limb had a differential

effect on the quality of interlimb coordination. Finally, the convergence of these

principles across both combinations that differed with respect to whether the moving


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joints were adjacent (Experiment I) or nonadjacent (Experiment II) was also focused

upon.

Materials and methods

Participants

Twenty six young healthy adult volunteers without known neuromuscular

disorders participated in this study. Twenty-four were right-handed and two left-

handed (Oldfield 1971). Fourteen participants (all male; aged 19-20) were tested in

Experiment I and 12 (5 male, 7 female; aged 19-25) in Experiment II. The

experimental procedures were conducted in accordance with the Helsinki Declaration

and were approved by the ethical Committee of Biomedical Research at K. U.

Leuven. All participants signed an informed consent before the experiment.

Apparatus

Participants were seated in front of a height-adjustable table with fixation of

the upper and lower torso to a chair and the upper limbs to a fixed frame that was

positioned at the table, to restrict any unintended trunk movements and assure stable

postural control. Their right and left arms were positioned horizontally just above the

table surface with the hands in a neutral position. In Experiment I, a splint secured to

the ventral surface of the forearm, prevented wrist movement (Figure 1a). In

Experiment II, braces were used to restrict unintended elbow movements (Figure 1b).

Single-tone auditory signals, providing pacing for the movements, were presented

with a metronome (Korg digital tuner metronome DTM-12, Keio Electronic Lab.,

Corp.).


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~~~~~~~~~~~~~~~~~ Insert Figure 1 here

~~~~~~~~~~~~~~~~~

Procedure

Participants were instructed to perform cyclical flexion and extension

movements with their shoulders and elbows in the horizontal plane. They were

required to produce one complete movement cycle for each metronome beat (duration

= 752 ms, 1.33 Hz). Participants were instructed to move continuously and to

maintain the pacing rhythm and coordination mode as accurately as possible. All

participants were able to follow the pacing of the movement successfully.

The experimental conditions consisted of a combination of in-phase (IN) or

anti-phase (AN) coordination modes between both shoulders and elbows/wrists

(interlimb) with isodirectional or non-isodirectional coordination modes between the

joints within each limb (intralimb). This resulted in the following eight conditions

(e.g., shoulder-elbow combination): (1) shoulder and elbow in-phase with either

isodirectional (IN-IN Iso-Iso i.e., in-phase shoulder, in-phase elbow, isodirectional

non-dominant limb, isodirectional dominant limb) or (2) non isodirectional (IN-IN

NonI-NonI) coordination modes within both limbs; (3) shoulder in-phase and elbow

anti-phase with non-isodirectional movements at the non-dominant limb and

isodirectional movement at the dominant limb (IN-AN NonI-Iso), or (4) vice versa

(IN-AN Iso-NonI); (5) shoulder anti-phase and elbow in-phase with non-

isodirectional movements at the non-dominant limb and isodirectional movements at

the dominant limb (AN-IN NonI-Iso) or (6) vice versa (AN-IN Iso-NonI); (7) anti-

phase shoulder and elbow coordination with isodirectional (AN-AN Iso-Iso) or (8)


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non-isodirectional (AN-AN NonI-NonI) coordination patterns within each limb

(Figure 2).


~~~~~~~~~~~~~~~~~

All participants performed the eight experimental conditions. Prior to data

recording, they practiced the tasks with the help of computer animations. Following

the practice session, four test trials (duration = 11 s per trial) were registered for each

task condition, resulting in a grand total of 32 trials. To avoid fatigue, short breaks (1

min) were allowed between trials. In addition, participants were allowed a 3 min rest

before starting a new session. No visual cues were presented but participants were

allowed to see their arms during the test session. The order in which the conditions

were presented was randomized across participants.

Motion recording

Angular displacements of both arms were obtained by using an opto-electronic

motion-analysis system (Optotrak 3020). Eighteen markers (infrared-emitting diodes)

were attached to both upper arms and forearms to measure the segmental motion.

Custom software (Angle, Optrotrak Data Analysis Package) was used to calculate the

joint angles in the horizontal plane. The marker displacements were recorded at 150

Hz. The motion data were low-pass filtered (second-order Butterworth with cut-off

frequency at 8 Hz, with zero-lag). Angular motion of shoulders and elbows/wrists

were retained for further analysis.


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Relative phase

The relative phasing between joint angle pairs was obtained from the

instantaneous phase of each signal, derived from the Hilbert transform (Boashash

1992a,b; Carson et al. 2002). The relative phase analyses were conducted, using the

equation adapted from Kelso et al. (1986):

1 21 11 2

1 2

/ / = - = tan ( ) - tan ( )X Xd dt d dtX X

φ θ θ − −

whereby θi refers to the phase of the movement in joint i (i = 1, 2) at each sample, Xi

is the position of the joint after rescaling to the interval [–1, 1] for each cycle of

oscillation, and / Xid dt is the normalized instantaneous velocity. The relative phase

estimate with respect to interlimb coordination (e.g., shoulder-elbow combination)

was:

= - non-dominant dominantshoulder shoulder shoulderφ θ θ , and = - non-dominant dominant

elbow elbow elbowφ θ θ

With respect to intralimb coordination, the following equation was used:

= - shoulder elbownon - dominant non-dominant non-dominantφ θ θ , and = - shoulder elbow

dominant dominant dominantφ θ θ

Circular statistics (Batschelet 1965; Mardia 1972) were used to calculate the mean

continuous relative phase relationship between two displacement signals. The mean

absolute error (AE) score, reflecting the degree of deviation from the target relative

phase was then calculated, i.e., 0° for in-phase interlimb coordination and

isodirectional intralimb coordination, and 180° for anti-phase and non-isodirectional

coordination. The within-trial SD of the relative phase was used as a measure of

relative phase variability or coordinative stability.

The mean AE and SD scores of relative phase between both shoulders and

between both elbows/wrists were calculated to determine the quality of interlimb

coordination. The AE and SD scores of relative phase between the shoulder and


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elbow within the dominant and the non-dominant arm were computed to determine

the quality of intralimb coordination. Data were calculated for each trial and then

averaged across trials within each performance condition, resulting in four mean AE

and SD scores of relative phase for each condition.

Statistical analysis

The analysis is exemplified for the shoulder-elbow combination (Experiment I)

and is comparable with the shoulder-wrist combination (Experiment II).

Interlimb coordination

The mean AE and SD scores of relative phase were computed between both

shoulder and both elbow joints to assess the quality of interlimb coordination. Two

2 × 2 × 2 × 2 [Joint × Shoulder Coordination Mode (Shoulder-INAN) × Elbow

Coordination Mode (Elbow-INAN) × Intralimb Coordination Mode (ISO-NONISO)]

ANOVAs were applied with repeated measures on all factors (Statistica 5.5). The

factors included: (1) joint consisting of the shoulder and elbow joint (Joint); (2) the

coordination pattern at the shoulder, consisting of the in-phase versus the anti-phase

mode (Shoulder-INAN); (3) the coordination pattern at the elbow, consisting of the

in-phase versus the anti-phase mode (Elbow-INAN); (4) the coordination pattern

between the joints within a limb consisting of the isodirectional and non-

isodirectional mode (ISO-NONISO or shortly ISON). Since the analyses involving

the factor intralimb coordination mode revealed very similar findings for the

dominant and non-dominant limb, only the analysis focusing on the coordination

mode within the dominant limb will be reported. Overall, this design allowed us to

assess the effect of interlimb as well as intralimb coordination modes on the quality of

interlimb coordination.

Intralimb coordination


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To assess the quality of intralimb coordination, the mean absolute error and

SD scores of relative phase were computed between the shoulder and elbow joints

within each limb. A 2 × 2 × 2 × 2 [Limb × Intralimb Coordination Mode (ISON) ×

Shoulder Coordination Mode (Shoulder-INAN) × Elbow Coordination Mode (Elbow-

INAN)] ANOVA with repeated measures allowed us to assess the impact of intralimb

and interlimb coordination modes on the quality of intralimb coordination. ‘Limb’

referred to the non-dominant versus dominant arm. ‘Intralimb Coordination Mode’

referred to non-isodirectional (NonI) versus isodirectional (Iso) coordination between

the shoulder and elbow joint within a limb. The remaining factors were similar to

those of the previous ANOVA.

For all the analyses, the probability level was set at p < 0.05. When significant

effects were found, post hoc tests (Tukey HSD) were conducted to identify the loci of

these effects. Since AE and SD of relative phase measures showed similar tendencies,

only the AE measures will be discussed in detail.

Results

The analysis of the group data is presented as follows. First, we describe the

influence of interlimb and intralimb coordination modes (independent variables) on

the quality of interlimb coordination (dependent variable). Second, we will look into

the influence of interlimb and intralimb coordination modes (independent variables)

on the quality of intralimb coordination (dependent variable).

Examples of raw data

Figure 3 shows representative examples of the shoulder-elbow combination

(Experiment I) for an easy (IN-IN Iso-Iso, Figure 3a) and difficult (AN-AN NonI-


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NonI, Figure 3b) task condition. The IN-IN Iso-Iso condition, requiring the

simultaneous activation of homologous muscles groups at all times, was performed

with a high coordination quality both between and within limbs. This was not the case

during the performance of the AN-AN NonI-NonI condition in which far less stable

performance during the non-preferred coordination patterns was noticed between as

well as within limbs.


~~~~~~~~~~~~~~~~~

Experiment I: Shoulder-elbow coordination

Analysis of interlimb coordination relative phase measures

The absolute errors (AE) of relative phase as a function of coordination

conditions in the shoulders and elbows are shown in Figure 4a. The lowest deviations

from target relative phase were observed during the IN-IN Iso-Iso and IN-IN NonI-

NonI conditions with similar levels of accuracy in both the shoulders and elbows. As

soon as the anti-phase coordination mode was performed in one or both bilateral joint

pairs, interlimb coordination deteriorated. Higher deviations from required relative

phase were found in the shoulders than the elbows when the shoulders were prepared

in the anti-phase coordination mode (Figure 4a, right side), whereas smaller

differences between both joints were observed when the shoulders were prepared in

the in-phase coordination mode (Figure 4a, left side).


~~~~~~~~~~~~~~~~~


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This pattern was largely confirmed by the Joint × Shoulder-INAN × Elbow-

INAN × ISON ANOVA on AE measures (Table 1, interlimb coordination). The

effects of interlimb coordination mode in shoulder and elbow revealed that higher

mean AE scores were found during the anti-phase (Mshoulder = 23.22°; Melbow = 22.15°)

than the in-phase modes (Mshoulder = 13.95°; Melbow = 15.03°). However, both

coordination modes also interacted with each other in their effect on the quality of

interlimb coordination (Shoulder-INAN × Elbow-INAN, Table 1, interlimb

coordination, Figure 5). Overall interlimb coordination deteriorated to a comparable

degree as soon as anti-phase coordination was adopted in one or both joint pairs.

Stated differently, the best interlimb performance was obtained during the elbow-IN

shoulder-IN coordination mode whereas the remaining three patterns exhibited

comparable error levels. Thus, no surplus deterioration was observed when both joint

couples were prepared in the anti-phase mode as compared to combinations of in-

phase and anti-phase modes. Post hoc tests revealed that performance error during the

IN-IN condition was significantly lower than in the remaining three conditions (P <

0.01) which did not differ significantly from each other (P > 0.05). Finally, the

aforementioned effects were evident during both the non-isodirectional and

isodirectional coordination modes, albeit to varying extents (Shoulder-INAN × Elbow

INAN × ISON, Table 1 interlimb coordination). Thus, the present findings suggest

that subjects encountered particular difficulties when they were to adopt different

coordination modes in the proximal versus distal joint couples.

~~~~~~~~~~~~~~~~~~~~~~~~ Insert Figure 5 & Table 1 here

~~~~~~~~~~~~~~~~~~~~~~~~


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The significant Shoulder-INAN × Elbow-INAN effect reflected interactions between

coordination modes of both joint pairs but it was less clear whether these effects were

evident in the error scores of only one or both joint pairs (proximal versus distal). For

this reason, those conditions in which both joint pairs adopted a different coordination

mode were further analyzed, i.e., the question was asked what happened with

performance during in-phase coordination in one joint pair when the other joint pair

shifted from in-phase to anti-phase coordination. A 2 × 2 (Joint × Coordination

Condition) ANOVA was applied to all conditions in which the in-phase coordination

mode was adopted in the shoulder. Joint referred to the shoulder and elbow.

Coordination condition referred to the ININ and INAN modes (see Figure 4a, left

side, conditions 1-4 contracted to 2 levels). Compared to in-phase, adopting the anti-

phase coordination mode in the elbow not only resulted in a deterioration of

coordinative accuracy at the bilateral elbow (276% increase of AE as compared to

ININ conditions of this joint pair) but also at the shoulder (82%) joints ( (1,13)F = 8.75,

P < 0.05).

Similarly, the 2 × 2 (Joint × Coordination condition) ANOVA applied to the

elbow-in-phase conditions (Figure 4a, conditions 1, 2, 5, 6) revealed that, relative to

in-phase, preparing the shoulder joints in the anti-phase mode resulted in a

deterioration of shoulder (234%) but also elbow (122%) coordinative accuracy ( (1,13)F

= 13.52, P < 0.01). These findings suggest that shifting from the in-phase to the anti-

phase mode in one joint not only affected the quality of coordination at this joint pair

(local effect) but also had a detrimental influence on the quality of in-phase

coordination in the other joint pair (remote effect). In other words, one joint pair

dragged the other pair into performance deterioration and this effect was exhibited in

a proximal-to-distal as well as distal-to-proximal direction.


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With respect to the effect of intralimb coordination modes on the quality of

interlimb coordination, no significant effects were obtained (P > 0.05). This suggests

that it did not matter for interlimb AE scores whether the ipsilateral joints were

prepared according to the isodirectional versus non-isodirectional coordination mode.

Analysis of intralimb coordination relative phase measures

Figure 4b displays the absolute error of intralimb relative phasing as a function

of interlimb and intralimb coordination modes. As can be observed, the IN-IN NonI-

NonI task was associated with the most accurate intralimb performance, both in the

dominant and the non-dominant limb, as compared with the remaining task conditions.

In order, we will first discuss the effect of intralimb and then interlimb coordination

mode on the AE measures of intralimb coordination (Table 1, intralimb coordination).

The non-isodirectional coordination mode (M = 13.41º) was associated with

lower error scores than the isodirectional mode (M = 19.78º, main effect of intralimb

coordination mode, Table 1, intralimb coordination).

Adopting the anti-phase coordination mode in the shoulders resulted in a

higher disruption of overall intralimb coordination (M = 18.45º) than the in-phase

mode (M = 14.74º, main effect of shoulder coordination mode). No such effect was

found for the elbows (P > 0.05). Moving according to the anti-phase mode either in

the elbow or shoulder invariably destabilized global intralimb coordinative behavior

(Shoulder-INAN × Elbow-INAN, Table 1, intralimb coordination). Overall, this

interaction and the significant main effect of shoulder coordination mode demonstrate

that interlimb coordination modes had an effect on the quality of intralimb

coordination. The remaining main effects and interactions were not significant (F <

4.79, P > 0.05).


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Experiment II: Shoulder-wrist coordination

Analysis of interlimb coordination relative phase measures

The AE of interlimb relative phase as a function of coordination conditions in

the shoulders and wrists are shown in Figure 6a. The lowest error scores were

observed during the IN-IN Iso-Iso and IN-IN NonI-NonI conditions with similar

levels of accuracy in both the shoulders and wrists. The highest error scores were

found in the IN-AN NonI-Iso, IN-AN Iso-NonI and AN-AN NonI-NonI conditions

for the wrist and in the AN-IN Iso-NonI and AN-AN NonI-NonI for the shoulder

joints.


~~~~~~~~~~~~~~~~~

Overall the 2 × 2 × 2 × 2 ANOVA confirmed the aforementioned tendencies.

Higher interlimb relative phasing errors were found during the anti-phase (Mshoulder =

19.87°; Mwrist = 19.44°) than the in-phase mode (Mshoulder = 13.05°; Mwrist = 13.48°,

Table 2, interlimb coordination). The significant Joint × Shoulder-INAN interaction,

Joint × Wrist-INAN interaction, and Shoulder-INAN × Wrist-INAN interactions can

most appropriately be interpreted in view of the significant higher order Joint ×

Shoulder- INAN × Wrist-INAN interaction (Table 2, interlimb coordination, Figure

7a). This interaction indicated that during in-phase coordination of the wrists, shifting

from the in-phase to the anti-phase coordination mode in the shoulders had a similar

negative impact on both the shoulder and wrist joints. During anti-phase coordination

of the wrists, a similar negative effect was observed for the shoulder when shifting

from in-phase to anti-phase coordination in the shoulders whereas the quality of

coordination in the wrists actually improved. This interaction suggests that changing


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the coordination mode in one of both joint pairs not only influenced this particular

joint pair but also the other.

~~~~~~~~~~~~~~~~~~~~~~~~ Insert Table 2 here

~~~~~~~~~~~~~~~~~~~~~~~~

Similar analyses as those used in Experiment I were also applied in the present

study on those conditions in which divergent coordination modes were produced in

both joint pairs simultaneously, i.e., in-phase in the proximal and anti-phase in the

distal joint pair, or vice versa. When looking at the wrist in-phase data separately

(Figure 6a, conditions 1, 2, 5, 6), it was observed that shifting from in-phase to anti-

phase coordination in the shoulder had a detrimental impact on shoulder (170%) as

well as wrist (112%) coordination ( (1,11)F = 1.95, P = 0.19). Conversely, when looking

at the shoulder in-phase conditions (Figure 6a, conditions 1-4), shifting from in-phase

to anti-phase coordination in the wrists had a negative effect on bilateral wrist (214%)

but not shoulder coordination (27%) ( (1,11)F = 11.98, P < 0.01). This suggests that

during the production of different coordination modes in both bilateral joints, the

proximal joint pair (shoulders) had a negative influence on the distal pair (wrists), but

not vice versa.

There was no significant effect of intralimb coordination mode on the quality

of interlimb coordination (P > .05). The only significant interaction containing the

intralimb coordination mode was the Shoulder-INAN x ISON effect (Table 2,

interlimb coordination). This effect suggested that the difference between in-phase

and anti-phase shoulder coordination was more pronounced during non-isodirectional

than during isodirectional coordination within the ipsilateral limb.


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~~~~~~~~~~~~~~~~~

Analysis of intralimb coordination relative phase measures

Figure 6b displays the absolute error of intralimb relative phasing as a function

of interlimb and intralimb coordination modes. It is evident that the isodirectional

mode was not associated with lower intralimb relative phasing error as compared to

the non-isodirectional mode under all circumstances. Higher intralimb error scores

were evident in the non-dominant (M = 22.13º) as compared to the dominant limb (M

= 17.58º, main effect of limb, Table 2, intralimb coordination).

The effect of wrist interlimb coordination mode indicated that adopting anti-

phase coordination in the wrists (M = 22.37º) resulted in a higher disruption of overall

intralimb coordination than the in-phase mode (M = 17.34º). However, this effect also

interacted with the coordination mode performed in the shoulder (Shoulder-INAN ×

Wrist-INAN, Table 2, intralimb coordination). As soon as the anti-phase mode was

adopted in one or both limbs, the intralimb error scores increased (relative to the ININ

condition), reaching similar error levels across the three remaining conditions (INAN,

ANIN, ANAN). This suggests that interlimb coordination mode influenced the quality

of intralimb coordination.

The error scores of intralimb coordination were slightly lower for the non-

isodirectional than isodirectional mode during in-phase coordination of the wrists

whereas error scores were higher for non-isodirectional than for isodirectional

coordination during the anti-phase wrist coordination mode (ISON × Wrist-INAN,

Table 2, intralimb coordination). Furthermore, the aforementioned effect was

somewhat more pronounced in the dominant than in the non-dominant limb (Limb ×

ISON × Wrist-INAN, Table 2, intralimb coordination, Figure 7b). Thus, these


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observations indicate that the difference in coordination quality between the

isodirectional and non-isodirectional coordination mode was primarily affected by the

coordination adopted between the bilateral wrists and was also modulated by limb

dominance.

Discussion

The present studies addressed the coordination between the bilateral shoulder-

elbow (Experiment I) and shoulder-wrist joints (Experiment II). These experiments

provided a means for exploring the interactions between interlimb and intralimb

coordination constraints during the performance of multijoint movements. The present

findings extend the current state of knowledge on how those constraints impact upon

global coordination in the context of multijoint bimanual tasks. The principles

underlying interlimb and intralimb coordination and their (mutual) interactions will be

discussed next.

Interlimb coordination

A general tendency emerged to converge towards symmetrical (in-phase)

movement patterns during the various coordination tasks, reflecting a general

preference for mirror-image movements of the bilateral segments. This was inferred

from the higher relative phase accuracy (and lower variability) between the limbs

when both proximal and distal joints were prepared in the in-phase as compared to the

anti-phase coordination mode. The present observations confirmed and extended

previous findings underscoring the higher intrinsic stability of symmetrical (involving

the simultaneous activation of homologous muscle groups) as compared to

asymmetrical bimanual movements (involving co-activation of non-homologous

muscle groups) to the context of multijoint bimanual coordination (Byblow et al. 1994,


19

1999; Carson et al. 1997; Kelso 1984; Lee et al. 2002; Li et al. 2004; Semjen et al.

1995; Swinnen et al. 1997, 1998). This is a hallmark of dynamic pattern theory in

which the differential stability between coordination modes has been formalized

mathematically for a single joint pair (Haken et al. 1985).

However, new insights were particularly obtained when in-phase and anti-

phase coordination modes were combined across both joint couples. Whereas

previous studies using simpler movements would allow us to extrapolate that a

combination of in-phase modes in both joint couples (IN-IN) would result in the best

performance and a combination of anti-phase modes in the worst (AN-AN), with the

mixed conditions positioned in between (IN-AN, AN-IN), we observed that the

impact of the interlimb coordination modes at both joint couples was not simply

additive. As soon as the anti-phase mode was introduced in only one of both bilateral

joint pairs, interlimb coordination deteriorated and performance levels were

comparable (and sometimes even higher) to those obtained during anti-phase

coordination. This suggests that mixing the interlimb coordination modes across both

joint couples was experienced as a rather difficult task combination.

Moreover, the interactions between coordination modes across proximal and

distal joints also accounted for the non-additive effects. More specifically, the

proximal joints exhibited a stronger impact on the quality of interlimb coordination

than the distal joints during the shoulder-wrist combination whereas the interaction

was mutual during production of the shoulder-elbow combination, i.e., from distal to

proximal, and vice versa. This exemplifies that the impact of interlimb coordination

mode on the quality of overall coordinative performance was also dependent on the

effector combination.

Multiple factors may account for these differences across both coordination

tasks. First, joints were adjacent in the shoulder-elbow and nonadjacent in the

shoulder-wrist task. In the former case, biarticular muscles (biceps and triceps brachii)


20

could have a stronger modulatory impact on coordination between joints than in the

latter case (as no muscle spans simultaneously shoulder and wrist in human beings).

Second, segmental inertial parameters may also play a role, with larger effectors

having more impact on global coordination than segments with smaller inertial

parameters. This may account for the effect of bilateral shoulder on wrist coordination,

but not vice versa, and for the mutual effects between shoulder and elbow

coordination. Due to their larger mass, movements of larger effectors may have a

more disturbing influence on the other effectors. More generally, the impact of inertial

features on coordination during various types of interlimb tasks has been addressed in

previous work (Kelso and Jeka, 1992; Serrien and Swinnen, 1999; Levin et al. 2004).

Finally, our observations revealed virtually no impact of the intralimb

coordination modes on the quality of interlimb coordination in both experiments.

More specifically, performing the isodirectional versus non-isodirectional mode

between the segments within each limb did not significantly influence the quality of

coordination between the homologous joint pairs. Thus, the coalition of constraints

that dominated bimanual multijoint coordination was mainly reflected by the

interaction between the bilateral segments of the neuromuscular system while being

less modulated by the interaction between the ipsilateral segments. In other words, the

impact of the interlimb coordination mode was more powerful than that of the

intralimb coordination mode on the performance measures of interlimb coordination.

Intralimb coordination

No consistent global picture emerged regarding the state of coordination

between the segments within each limb and their consequences for accuracy and

stability of intralimb coordination. With respect to the shoulder-elbow combination

(Experiment I), performing the isodirectional mode between limb segments

(simultaneous flexions and extensions) resulted in a lower quality of intralimb

coordination than the non-isodirectional mode. With respect to the shoulder-wrist


21

combination (Experiment II), the interaction between inter- and intralimb

coordination mode revealed that isodirectional coordination was less successful than

non-isodirectional coordination during in-phase coordination between the wrists

whereas the converse effect was obtained during anti-phase coordination.

These findings deviate from previous work in which isodirectional

coordination modes were produced with higher stability than non-isodirectional

modes (Dounskaia et al. 1998; Kelso et al. 1991; Putnam 1991; Virji-Babul and

Cooke 1995). In a cyclical elbow-wrist coordination study, Kelso and coworkers

demonstrated that the stability of intralimb coordination depended on hand posture,

i.e., when the hand was supine, the isodirectional mode was more stable than the non-

isodirectional mode but the opposite effect was observed with the hand in pronation

(Kelso et al. 1991). Studying a similar task, Dounskaia et al. (1998) showed that the

isodirectional pattern was more in agreement with interactive effects than the less

stable non-isodirectional pattern, thus causing their differential accuracy/stability

under increasing cycling frequencies. The obtained relative differences in the

accuracy/stability of isodirectional versus non-isodirectional intralimb coordination

modes across the aforementioned tasks and those studied by us, may be a

consequence of the differential impact of interactive torques across these various

segment combinations. However, other factors may also play a role, including neural,

biomechanical, musculoskeletal and cognitive factors. Additional research is

warranted to assess the relative impact of each of these factors on the quality of

intralimb coordination as well as the task-specific nature of these influences.

The role of limb dominance in the control of intralimb coordination was found

to be prevalent during shoulder-wrist but not during shoulder-elbow coordination. The

former finding is consistent with the dynamic-dominance hypothesis (Sainburg 2002),

suggesting that the differences in the quality of control between the dominant and

non-dominant limb may modulate the quality of within-limb coordination. As this

phenomenon was only observed for the shoulder-wrist configuration, we hypothesize


22

that the dynamic-dominance effect may have been masked by the supremacy of

interlimb over intralimb coordination modes between adjacent segments during the

production of shoulder-elbow movements.

Whereas the mode of intralimb coordination had a minor impact on the quality

of interlimb coordination (see first section of discussion), the converse effect was

more prevalent. There are several pieces of evidence to support this conclusion. First,

the impact of interlimb on intralimb coordination was so powerful that the direction of

the difference in performance quality between isodirectional and non-isodirectional

coordination modes was determined by the coordination mode adopted between the

bilateral distal joints (see Experiment II). Second, across both experiments, accuracy

and stability of intralimb coordination was highest during in-phase coordination in

both bilateral joint pairs. As soon as anti-phase coordination was introduced in one or

both joints, the quality of intralimb coordination deteriorated. In the shoulder-elbow

task, the coordination mode in the bilateral shoulders had a stronger impact on the

quality of intralimb coordination than the elbow coordination mode. Conversely, in

the shoulder-wrist task (Experiment II), the bilateral wrist coordination mode

appeared to have a stronger impact on intralimb coordination than the bilateral

shoulder coordination mode. In spite of these differences, the converging picture

across both experiments is that the coordination mode adopted in either the bilateral

proximal or distal joints (in-phase versus anti-phase) induced a stronger impact on

intralimb performance than the coordination mode adopted between the segments

within the limbs themselves (isodirectional versus non-isodirectional). Thus, interlimb

constraints ruled over intralimb constraints when evaluating intralimb coordination

performance.

Neural correlates of coordination constraints


23

The present observations offer a different look at the general nature of human

motor control. In studies of motor performance, we are often reminded of the

phenomenon of hand preference/dominance. The dominant limb affords highly

refined control whereas performance with the non-dominant limb is usually less than

optimal (Sainburg and Kalakanis 2000; Sainburg 2002; Swinnen et al. 1996). These

differential behavioral expressions are also associated with a higher degree of

lateralized and more focused neural activation when moving with the dominant as

compared with the non-dominant limb (Haaland et al. 2004). Yet, when moving both

limbs together, control of the individual limbs becomes subordinate to a bilateral

organization that harnesses the coordination between the ipsilateral limb segments.

This ‘symmetrical supremacy’ in movement organization is most likely a

direct consequence of the bilateral musculoskeletal organization that characterizes

many species. Interestingly, there are dense interhemispheric connections between the

homotopic motor networks of both hemispheres to support this symmetrical

organizational supremacy (Cardoso de Oliveira et al. 2001; Donchin et al. 2001). The

removal of these direct connections (such as during callosotomy) has important

implications for bimanual control (Franz et al. 1996; Eliassen et al. 1999). Behavioral

studies support the contention that connectivity between motor networks across

hemispheres is often stronger than within hemispheres. However, strong connectivity

can also hamper the production of differentiated actions in the limbs, giving rise to

patterns of mutual interference. As a consequence, producing the same movements

simultaneously is easier whereas producing different movements is often more

difficult with the bilateral than with the ipsilateral limb segments (Serrien and

Swinnen 1997a,b). More generally, this suggests that the supremacy of bilateral over

ipsilateral coordination during upper limb movements, as inferred from our behavioral

observations, is supported by a distinct neural organization in which the strength of


24

interhemispheric interactions between motor control centers dominates over the

intrahemispheric ones.

With respect to the observed differences among the interlimb coordination

modes and their degree of compatibility across girdles (ININ and ANAN versus

INAN and ANIN), it is reasonable to assume that these behavioral effects are

associated with neural correlates. Previous work has shown that bilateral coordination

modes deviating from mirror symmetry are associated with higher and more extended

brain activation patterns than in-phase coordination modes (for reviews see Swinnen

2002; Wenderoth et al. 2004a). Basically, activations extend to prefrontal, parietal and

temporal areas when bimanual movements become more complex as a function of

their temporal and/or spatial compatibility (Debaere et al. 2003, 2004; Ullen et al.

2003; Wenderoth et al. 2004b, in press). These extended activation patterns are not

only associated with generating more complex command structures that diverge

across joint couples but also with suppression of preferred coordination modes in

order to explore these more complex patterns (Puttemans et al. 2005; Swinnen 2002;

Wenderoth et al. 2004b, in press).

Conclusions

The present experiments underscore three main findings. First, the principle of

muscle homology, giving rise to mirror symmetrical movements with respect to the

mid-sagittal plane, had a powerful influence on global interlimb coordination.

Interactions between distal and proximal joint pairs were clearly evident and varied

across coordination tasks. Second, the mode of coordination within limbs exhibited a

variable impact on the quality of intralimb coordination between adjacent and

nonadjacent ipsilateral joint combinations. Here, the impact of multiple variables,

including musculoskeletal and dynamic, on the quality of intralimb coordination


25

should be further explored in the future. Third, the mode of interlimb coordination

had a much more powerful effect on the quality of intralimb coordination than vice

versa. Taken together, these observations suggest a hierarchical control structure for

multijoint bimanual movement whereby interlimb coordination constraints dominate

over the constraints governing intralimb coordination. This is supported by a distinct

neural organization with profound interhemispheric interactions during the production

of bimanual movement.


26

Figure captions

Figure 1. Schematic view of the experimental setup and marker configuration for the

shoulder-elbow combination in Experiment I (a) and the shoulder-wrist combination

in Experiment II (b).

Figure 2. Experimental conditions of the shoulder-elbow combination (Experiment I).

Arrows indicate the motion direction for a half cycle. Letters above the pictures

indicate intralimb coordination modes. NonI: the non-isodirectional coordination

mode; Iso: the isodirectional coordination mode. Letters on the left side of the pictures

refer to interlimb coordination modes for the bilateral distal and proximal joints. IN:

in-phase coordination mode; AN: anti-phase coordination mode. Letters and numbers

below the pictures indicate the condition name in the following order: 'proximal-distal

joint pair non-dominant-dominant limb'. Note: the distal joint pair refers to the elbows

in Experiment I and to the wrists in Experiment II; proximal joint pair refers to

shoulders in both experiments.

Figure 3. Representative example of performance during IN-IN Iso-Iso (a) and AN-

AN NonI-NonI (b) conditions (Experiment I, shoulder-elbow). Angle versus time

plots are on the left and the corresponding Lissajous figures are presented on the right

side. Bilateral shoulder and elbow motions are shown in the upper two graphs.

Ipsilateral shoulder and elbow motions are shown in the lower two graphs. In the

Lissajous figures, bold-diagonal lines are the target coordination values. Right

diagonal lines represent in-phase modes during interlimb and isodirectional modes

during intralimb coordination and left diagonal lines denote anti-phase/non-

isodirectional movements. ND: non-dominant limb; D: dominant limb.


27

Figure 4. Mean absolute error (AE) with respect to 0o and 180o target relative phase

for interlimb (a) and intralimb (b) coordination with respect to the shoulder-elbow

combination (Experiment I) across all experimental conditions. Note: S-E: interlimb

coordination mode in shoulder and elbow joints. NonDom-Dom: intralimb

coordination mode within non-dominant (NonDom) and dominant (Dom) limbs.

Symbolic label and numbers for each condition are the same as those defined in

Figure 2.

Figure 5. The Shoulder-INAN × Elbow-INAN interaction for AE with respect to

interlimb coordination.

Figure 6. Mean AE with respect to 0o and 180o target relative phase for interlimb (a)

and intralimb (b) coordination with respect to the shoulder-wrist combination

(Experiment II) across all experimental conditions. Note: S-W: interlimb coordination

mode in shoulder and wrist joints.

Figure 7. Joint × Shoulder-INAN × Wrist-INAN (a) interactions for mean AE with

respect to interlimb coordination and Limb × ISON × Wrist-INAN (b) interactions for

mean AE with respect to intralimb coordination.

Acknowledgements

Yong Li was supported by an IRO-scholarship of K.U.Leuven. Support for the

present study was provided through a grant from the Research Council of K.U.

Leuven, Belgium (Contract No. OT/03/61) and the Research Programme of the Fund

for Scientific Research – Flanders (FWO-Vlaanderen # G.0460.04) awarded to S.

Swinnen.


28

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Table legend: Joint: shoulder and elbow (Experiment I), and shoulder and wrist (Experiment II) joints; Limb: non-dominant and dominant limb; SINAN: Shoulder Coordination Mode (Shoulder-INAN); EINAN: Elbow Coordination Mode (Elbow-INAN); WINAN: Wrist Coordination Mode (Wrist-INAN); ISON: Intralimb Coordination Mode.

Table 1. Results of statistical analysis with respect to Relative Phase of Experiment I

Interlimb Coordination Intralimb Coordination

df (1, 13) AE (F) SD (F) AE (F) SD (F)

Joint 4.34 5.18* Limb 1.00 2.46

SINAN 51.17** 54.70** ISON 7.78* 6.66**

EINAN 54.53** 48.86** SINAN 20.22** 18.45**

ISON 0.02 2.81 EINAN 3.08 1.85

Joint x SINAN 15.16** 13.06** Limb x ISON 0.10 0.96

Joint x EINAN 11.88** 6.97* Limb x SINAN 0.25 0.19

SINAN x EINAN 49.68** 44.08** ISON x SINAN 3.82 3.08

Joint x ISON 0.17 0.00 Limb x EINAN 0.02 0.09

SINAN x ISON 0.02 1.33 ISON x EINAN 0.08 0.01

EINAN x ISON 7.91* 9.32* SINAN x EINAN 6.76* 10.44**

Joint x SINAN x EINAN 0.24 0.02 Limb x ISON x SINAN 0.12 0.73

Joint x SINAN x ISON 0.02 0.61 Limb x ISON x EINAN 0.18 0.04

Joint x EINAN x ISON 0.14 3.43 Limb x SINAN x EINAN 1.10 0.89

SINAN x EINAN x ISON 9.14* 3.82 ISON x SINAN x EINAN 1.08 0.76

Joint x SINAN x EINAN x ISON 0.06 0.41 Limb x ISON x SINAN x EINAN 0.70 0.10

* P < 0.05, ** P < 0.01


Table 2. Results of statistical analysis with respect to Relative Phase of Experiment II

Interlimb Coordination Intralimb Coordination

df (1, 11) AE (F) SD (F) AE (F) SD (F)

Joint 3.40 4.79 Limb 18.10** 19.31**

SINAN 27.69** 24.62** ISON 0.81 1.52

WINAN 15.01** 12.12** SINAN 3.54 4.85*

ISON 0.37 0.00 WINAN 7.37* 6.30*

Joint x SINAN 11.53** 9.62* Limb x ISON 3.88 0.55

Joint x WINAN 10.96** 10.71** Limb x SINAN 0.15 0.39

SINAN x WINAN 13.78** 17.33** ISON x SINAN 1.89 0.35

Joint x ISON 0.75 0.65 Limb x WINAN 2.14 1.18

SINAN x ISON 8.67* 12.65** ISON x WINAN 6.25* 12.44**

WINAN x ISON 0.06 0.06 SINAN x WINAN 17.31** 20.45**

Joint x SINAN x WINAN 9.11* 11.85** Limb x ISON x SINAN 0.06 0.03

Joint x SINAN x ISON 0.55 1.23 Limb x ISON x WINAN 5.78* 0.57

Joint x WINAN x ISON 0.47 2.43 Limb x SINAN x WINAN 0.69 1.13

SINAN x WINAN x ISON 2.61 2.89 ISON x SINAN x WINAN 0.19 1.02

Joint x SINAN x WINAN x ISON 3.22 3.91 Limb x ISON x SINAN x WINAN 1.97 1.35

* P < 0.05, ** P < 0.01

Optotrak Camera

brace brace

Marker

brace brace

MarkerHand braces

(a) Shoulder-Elbow combination (Experiment I)

(b) Shoulder-Wrist combination (Experiment II)Optotrak Camera

Figure 1

Experimental conditions (shoulder-elbow)

NonI NonIIso Iso Iso NonINonI Iso

IN

IN

IN

IN

AN

IN

AN

IN

1. IN-IN Iso-Iso 2. IN-IN NonI-NonI 3. IN-AN NonI-Iso

AN

AN

AN

AN

IN

AN

NonI Iso

IN

AN

NonI NonIIso IsoIso NonI

4. IN-AN Iso-NonI

7. AN-AN Iso-Iso5. AN-IN NonI-Iso 6. AN-IN Iso-NonI 8. AN-AN NonI-NonI

Figure 2

IN-IN Iso-IsoShoulder (IN)

elbow (IN)

Non-Dominant limb (Iso)

Dominant limb (Iso)

Dis

plac

emen

t (de

gree

)

ND shoulder

D s

houl

der

D e

lbow

ND elbow

ND

sho

ulde

r

ND elbow D elbow

ND elbow ND shoulder

D elbow D shoulder

D s

houl

der

ND shoulder D shoulder

Figure 3a1 10 155 Time (second)

ND elbow

40

D elbow

AN-AN NonI-NonIShoulder (AN)

elbow (AN)

Non-Dominant limb (NonI)

Dominant limb (NonI)

ND shoulder

D S

houl

der

ND shoulder D shoulder

ND elbow D elbow

ND elbow ND shoulder

D elbow D shoulder

Dis

plac

emen

t (de

gree

)

D e

lbow

ND elbow

ND

sho

ulde

r

ND elbow

40

D s

houl

der

Figure 3b1 10Time (second)5 15 D elbow

(a) Mean AE RPH Interlimb Coordination

0

10

20

30

40

50

AE

RP

H (d

egre

e) Shoulder

Elbow

1 2 4 53 6 7 8

IN-INIso-Iso

IN-INNonI-NonI

IN-ANNonI-Iso

IN-ANIso-NonI

AN-INNonI-Iso

AN-INIso-NonI

AN-ANIso-Iso

AN-ANNonI-NonI

S-E:NonDom-

Dom:

(b) Mean AE RPH Intralimb Coordination

0

10

20

30

40

AE

RP

H (d

egre

e) NonDomDom

1 2 4 53 6 7 8

IN-INIso-Iso

IN-INNonI-NonI

IN-ANNonI-Iso

IN-ANIso-NonI

AN-INNonI-

Iso

AN-INIso-NonI

AN-ANIso-Iso

AN-ANNonI-NonI

S-E:NonDom-

Dom:

Coordination conditions

Figure 4

Mean AE RPH Interlimb Coordination

Shoulder-INAN x Elbow-INAN interaction

IN ANShoulder

0

10

20

30

40A

E R

PH

(deg

ree)

Elbow: IN Elbow: AN

Figure 5


0

10

20

30

40

50

AE R

PH (d

egre

e) ShoulderWrist

1 2 4 53 6 7 8

IN-INIso-Iso

IN-INNonI-NonI

IN-ANNonI-Iso

IN-ANIso-NonI

AN-INNonI-

Iso

AN-INIso-NonI

AN-ANIso-Iso

AN-ANNonI-NonI

S-W:NonDom-

Dom:


0

10

20

30

40

50

AE

RP

H (d

egre

e)

NonDomDom

1 2 4 53 6 7 8

IN-INIso-Iso

IN-INNonI-NonI

IN-ANNonI-Iso

IN-ANIso-NonI

AN-INNonI-Iso

AN-INIso-NonI

AN-ANIso-Iso

AN-ANNonI-NonI

S-W:NonDom-

Dom:

Coordination conditions

Figure 6


Joint x Shoulder-INAN x Wrist-INAN interaction

ShoulderShoulder: IN AN

0

10

20

30

40

AE

RP

H (D

egre

e)

WristShoulder: IN AN

Wrist: IN Wrist: AN


LIMB x ISON x Wrist-INAN interaction

NonDominantISON: Iso NonI0

10

20

30

40

50

AE

RP

H (D

egre

e)

DominantISON: Iso NonI

Wrist: IN Wrist: AN

Figure 7

effects of interlimb and intralimb constraints on bimanual shoulder-elbow and shoulder-wrist...

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