Experimental Brain Research

, Volume 163, Issue 4, pp 515–526

Interactions between interlimb and intralimb coordination during the performance of bimanual multijoint movements

Authors

  • Yong Li
    • Laboratory of Motor Control, Department of KinesiologyKatholieke Universiteit Leuven
  • Oron Levin
    • Laboratory of Motor Control, Department of KinesiologyKatholieke Universiteit Leuven
  • Arturo Forner-Cordero
    • Laboratory of Motor Control, Department of KinesiologyKatholieke Universiteit Leuven
    • Laboratory of Motor Control, Department of KinesiologyKatholieke Universiteit Leuven
Research Article

DOI: 10.1007/s00221-004-2206-5

Cite this article as:
Li, Y., Levin, O., Forner-Cordero, A. et al. Exp Brain Res (2005) 163: 515. doi:10.1007/s00221-004-2206-5

Abstract

The simultaneous performance of movements involving different effectors gives rise to neural and biomechanical interactions between and within limbs. The present study addressed the role of interlimb and intralimb constraints during the control of bimanual multijoint movements. Thirteen participants performed eight tasks involving the bilateral elbows and wrists under different coordination conditions. With respect to interlimb coordination, coordination patterns referred to the in-phase and anti-phase coordination modes, involving the simultaneous timing of homologous versus non-homologous muscles, respectively. With respect to inter-segmental (intralimb) coordination, the isodirectional mode referred to simultaneous flexions and extensions in the ipsilateral wrist and elbow joints, whereas the non-isodirectional mode involved simultaneous flexion in one joint together with extension in the other joint, or vice versa. The analysis of the data focused upon measures of relative phasing between proximal and distal joints within a limb as well as between the homologous joints of both limbs. With respect to interlimb coordination, findings revealed that adoption of the in-phase mode resulted in a higher quality of interlimb coordination than the anti-phase mode. However, the mode adopted in the distal joints had a larger impact on the quality of interlimb coordination than the mode adopted in the proximal joints. More specifically, in-phase coordination of the distal joints had a positive, and anti-phase coordination a negative, influence on the global coordinative behavior of the system. Minor effects of intralimb coordination modes on interlimb coordination were observed. With respect to intralimb coordination between the ipsilateral elbow and wrist, the isodirectional mode was performed with higher stability than the non-isodirectional mode. The mode of interlimb coordination also affected the quality of intralimb coordination, such that generating anti-phase coordination patterns in the distal joints had a negative influence on the accuracy and stability of intralimb coordination. Taken together, the present findings suggest a hierarchical structure whereby interlimb coordination constraints have a stronger impact on the global coordinative behavior of the system than intralimb coordination constraints. Moreover, the global coordinative state of the system is more affected by the coordination between the distal than between the proximal joints. Overall, the findings suggest that the mirror-image symmetry constraint has a powerful influence on bimanual multijoint coordination.

Keywords

MultijointBimanual coordinationConstraintsHomologyDirectionalityInterlimbIntralimb

Introduction

Many daily life activities require some degree of interlimb and intralimb coordination between the joints of the upper limbs. Some of these coordination patterns represent preferred modes that reflect the intrinsic behavior of the system (Kelso 1984). 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). Whereas the in-phase pattern often results in movements that are mirror symmetrical with respect to the longitudinal axis of the body, they typically (but not exclusively) proceed in different direction(s) in extrinsic space. The reverse is usually true of the anti-phase pattern. However, other muscular-directional combinations are also possible and have generally resulted in the identification of a coalescence of both muscular and directional constraints that impact upon bimanual coordination (Swinnen et al. 1997, 1998).

Much less attention has so far been devoted to the principles governing the coordination between joints within a limb. Studies on inter-segmental 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 might arise from dynamical as well as neural sources. For example, it has been recognized that mechanical interactions between adjacent body segments have an important influence on multi-joint control (Gribble and Ostry 1999; Hollerbach and Flash 1982). Further studies have revealed that different strategies are implemented by the CNS for controlling the proximal and distal joints during performance of various types of single-limb tasks (Bernstein 1967; Dounskaia et al. 1998, 2002; Levin et al. 2001). Interactive torques in the joints have been shown to produce a dual effect on limb motion. On the one hand, interaction torques acting in the same direction as the motion patterns may facilitate interlimb control, and this appears to be the case during isodirectional intralimb coordination. The leading joint hypothesis was formulated as an interpretation of a control strategy that benefits from such interactive torques (Dounskaia et al. 1998). On the other hand, the effect of joint mechanical interactions may limit the possible movement combinations if the coordination patterns require the performer to act against such torques. In this case, the neuromuscular system may encounter difficulties when coping with the dynamical effects imposed by the directional specifications of the coordination task, for example during non-isodirectional coordination. This has been supported by the observation of a deterioration in distal joint control with increasing cycling frequency during the performance of various unilateral intralimb coordination patterns (Dounskaia et al. 1998, 2002).

So far, interlimb and intralimb coordination constraints have predominantly been explored in relative isolation of each other. This raises questions about the coalition of these constraints that govern complex multijoint coordination involving the proximal and distal joints of the upper limbs. For example, it is not clear how the mode of coordination between the bilateral segments impacts upon the quality of coordination between the joints within a limb, or vice versa. Furthermore, so far it has also remained unclear whether the interlimb coordination modes between the proximal as compared to the distal segments have a differential influence on the quality of intralimb coordination. Another relatively unexplored issue is whether the coordination mode adopted within the dominant as compared to the non-dominant limb has a differential effect on the quality of interlimb coordination. Therefore, the goal of the present study was to explore the principles underlying multi-joint coordination involving the bilateral elbows and wrists. Participants produced eight bimanual tasks that differed from each other with respect to the relative movements among the four joints (Fig. 1), imposing restrictions on phase and direction. The experimental conditions resulted from a combination of in-phase (IN) versus anti-phase (AN) coordination modes between the bilateral elbows and wrists (interlimb), and isodirectional (Iso) versus non-isodirectional (NonI) intralimb modes in the dominant (Dom) or non-dominant (NonDom) limb, resulting in the eight combinations depicted in Fig. 1. Results were primarily analyzed according to the accuracy and stability of the coordinative patterns between the homologous joint pairs (interlimb) as well as between joints within the dominant and non-dominant limb (intralimb).
Fig. 1

Experimental conditions. Arrows indicate the motion direction for a half cycle. Letters above the pictures indicate intralimb coordination modes. Letters to the left of the pictures refer to interlimb coordination modes for individual joints. Letters below the pictures indicate the condition name in the following order: NonDom non-dominant limb; Dom dominant limb; NonI the non-isodirectional coordination mode; Iso the isodirectional coordination mode; IN in-phase coordination mode; AN anti-phase coordination mode

Based on previous evidence, we hypothesized that tasks involving the in-phase coordination mode would be produced more accurately than those involving the anti-phase mode. With respect to intralimb coordination, the isodirectional mode between the elbow and wrist was hypothesized to be more stable and accurate than the non-isodirectional mode (Kelso et al. 1991; Dounskaia et al. 1998). The latter prediction is consistent with the observation that rotations of the wrist and elbow in opposite directions disrupt performance (Dounskaia et al. 1998; Gribble and Ostry 1999; Hollerbach and Flash 1982; Virji-Babul and Cooke 1995). In view of the paucity of research evidence on the coalition of the aforementioned coordination constraints, it was less straightforward to make specific predictions with respect to the influence of interlimb on intralimb coordination, and vice versa. Based on the bilateral symmetrical nature of the organization of the human musculoskeletal system, it was hypothesized that interlimb coordination constraints would have a stronger impact on the global coordinative behavior of the system than intralimb coordination constraints. In the present context, global coordinative behavior is defined as the coordination between all four joints of the upper limb. With respect to the relative role of proximal versus distal joints, it was predicted that the control of bilateral distal joints would be more difficult and therefore more disruptive for global coordination than that of proximal joints. This was inferred from previous observations on single-limb multijoint movements, that control at the distal joints is more complex than at the proximal joints, partly because interaction torques have a greater influence in the proximal to distal than in the converse direction (Dounskaia et al. 1998; Levin et al. 2001). Finally, intralimb coordination patterns were expected to proceed more successfully in the dominant limb than in the non-dominant limb (Sainburg and Kalakanis 2000; Sainburg 2002). The dynamic-dominance hypothesis (Sainburg 2002) predicts that there is stronger representation of limb dynamics and a better coordination of muscle torques in the dominant as compared to the non-dominant limb. As a consequence, participants were expected to produce the required elbow-wrist patterns with higher accuracy and stability with their dominant limb as compared to the non-dominant limb.

Materials and methods

Subjects

Thirteen healthy young adult volunteers (aged 20–25) without known neuromuscular disorders participated in this experiment. All were right-handed (Oldfield 1971). The experimental procedures were approved by the ethical Committee of Biomedical Research at K. U. Leuven. All participants signed an informed consent. The experiment was conducted in accordance with the Helsinki Declaration.

Apparatus

Participants were seated in front of a table with both upper arms supported by custom-made braces that restricted any unintended movements of the shoulder and trunk. Their right and left forearms and hands were positioned horizontally and were stabilized in a semi-prone position. A splint secured the ventral surface of the hand, preventing finger movement (Fig. 2). Single-tone auditory signals, providing pacing for the movements, were presented with a metronome (Korg digital tuner metronome DTM-12, Keio Electronic Lab.).
Fig. 2

Schematic view of the experimental set-up and marker configuration

Procedure

Participants were instructed to perform cyclical bilateral movements with their elbows and wrists across eight coordination conditions. They were required to produce one complete movement cycle for each beat of the metronome while maintaining the prescribed mode of coordination. The cycle duration was 752 ms (1.33 Hz). Participants were instructed to try to maintain the pacing rhythm and coordination mode as accurately as possible, without stopping. 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 elbows and wrists (interlimb) with isodirectional or non-isodirectional coordination modes between the joints within each limb (intralimb). This resulted in the following eight conditions or test sessions: (1) elbow and wrist in-phase with either isodirectional (IN-IN Iso-Iso, that is, in-phase elbow, in-phase wrist, isodirectional right limb, isodirectional left limb) or (2) non isodirectional (IN-IN NonI-NonI) coordination modes within both limbs; (3) elbow in-phase and wrist 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) elbow anti-phase and wrist 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 elbow and wrist coordination with isodirectional (AN-AN Iso-Iso) or (8) non-isodirectional (AN-AN NonI-NonI) coordination patterns within each limb (Fig. 1).

Prior to data recording, participants were allowed some practice to become familiar with the tasks. To help participants with performing the required coordination pattern, computer animations provided a demo of the movement at the onset of each practice session. Following the practice session, four trials (duration=11 s) were registered for each task condition in the absence of the computer animation, resulting in a grand total of 32 trials. To avoid fatigue, short breaks (1 min) were allowed between trials. In addition, subjects were allowed a 3 min rest after each test session. No visual cues were presented during the test session, but participants were allowed to see their arms. The order in which the conditions were presented was counterbalanced across subjects.

Motion recording

Angular displacements of both arms were obtained using an opto-electronic motion-analysis system (Optotrak 3020). Sixteen markers (infrared-emitting diodes) were attached to the upper arms and forearms of each limb to measure the segmental motion. Custom software (Angle, Optrotrak Data Analysis Package) was used to express the motion of each joint according to an anatomical coordinate system. The marker displacements were recorded at 100 Hz. The motion data were low-pass-filtered (second-order Butterworth with cut-off frequency at 8 Hz, with zero-lag). Angular motion data for the wrists and elbows were retained for further analysis.

Relative phase

The relative phasing between joint angle pairs was obtained from the instantaneous phase of each signal, derived from the Hilbert transform. Circular statistics (Batschelet 1965; Mardia 1972) were used to calculate the mean continuous relative phase relationship between two displacement signals. The mean direction of relative phase, which is a measure of central tendency, was calculated following Mardia (1972). The absolute error score (AE) that reflected the degree of deviation from the target relative phase (0° for in-phase and 180° for anti-phase) was then calculated. The within-trial SD of relative phase was used as a measure of relative phase variability or coordinative stability.

The relative phase between both elbows and between both wrists was calculated to determine the quality of interlimb coordination, while the relative phase between the elbow and wrist within the dominant and the non-dominant arm were computed to determine the quality of intralimb coordination. This resulted in four AE and SD scores of relative phase.

Cycling frequency

Continuous measures of movement frequency were determined using the Hilbert transform. The practical utility of the Hilbert transform is that it yields the temporal variation of amplitude, phase and frequency, at a resolution equal to the original digital sampling frequency. In the analyses reported below, we used the monocomponent of the instantaneous frequency (IF) as an estimate of the movement frequency.

Statistical analysis

Interlimb coordination

The mean absolute error and SD scores of relative phase were computed between both elbow and both wrist joints to assess the quality of interlimb coordination. Two 2×2×2×2 [Joint×Elbow Coordination Mode (Elbow-INAN)×Wrist Coordination Mode (Wrist-INAN)×Intralimb Coordination Mode] ANOVAs were applied with repeated measures on all factors. The factors included: (1) joint consisting of the elbow and wrist joint (Joint); (2) the coordination pattern at the elbow joint, consisting of the in-phase versus the anti-phase mode (Elbow-INAN); (3) the coordination pattern at the wrist joint, consisting of the in-phase versus the anti-phase mode (Wrist-INAN); (4) the coordination pattern between the joints within the dominant limb consisting of the isodirectional and non-isodirectional mode (Dom-IsoNonI) (Statistica 5.5). Since the analyses involving the factor intralimb coordination mode revealed very similar findings for the dominant and non-dominant limb (NonDom-IsoNonI), only the analysis focusing on the coordination mode within the dominant limb (Dom-IsoNonI) will be reported. Overall, the design allowed us to assess the effect of interlimb as well as intralimb coordination modes on the quality of interlimb coordination.

Intralimb coordination

To assess the quality of intralimb coordination, the mean absolute error and SD scores of relative phase were computed between the elbow and wrist joints within each limb. A 2×2×2×2 [Limb×Intralimb Coordination Mode (Iso-NonI)×Elbow Coordination Mode (Elbow-INAN)×Wrist Coordination Mode (Wrist-INAN)] ANOVA with repeated measures allowed us to assess the impact of 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 elbow and wrist joint within a limb.

For all of 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.

Results

Analysis of interlimb coordination

Typical relative motion plots of elbow and wrist are shown in Fig. 3 for a more and for a less stable/accurate experimental condition. The Lissajous plots of the elbow versus wrist angular displacements are illustrated in the right-hand column. Performance of the IN-IN Iso-Iso condition, requiring the simultaneous activation of homologous muscles groups at all times, is shown in the upper plots (Fig. 3a). As can be seen, this pattern of interlimb coordination, requiring mirror movements, is performed with a high degree of stability in both the elbow and wrist joints without any noticeable phase deviations. A less stable pattern was predicted for the AN-AN NonI-NonI condition, requiring anti-phase coordination between the joints of both limbs and non-isodirectional coordination modes between the joints within the limb (Fig. 3b).
Fig. 3a–b

Examples of interlimb coordination trials of a single subject under ININ Iso-Iso (a) and ANAN NonI-NonI (b) conditions of bilateral wrist (top figures) and elbow motions (bottom figures). Angle versus time plots are on the left and the corresponding Lissajous figures are presented on the right side. In the Lissajous figures, the X-axis refers to displacement of the non-dominant limb, whereas the Y-axis refers to the dominant limb. Right diagonal lines represent in-phase movements and left diagonal lines anti-phase movements. Bold-diagonal lines are the target coordination values

Absolute error of relative phase

The absolute errors of relative phase as a function of coordination conditions in the elbows and wrists are shown in Fig. 4a. The lowest deviations from required relative phase were observed during the IN-IN Iso-Iso and IN-IN NonI-NonI conditions with similar levels of accuracy in both elbows and wrists. The highest deviations were found during the IN-AN NonI-Iso, IN-AN Iso-NonI and AN-AN NonI-NonI conditions. In the latter conditions, increased phasing errors were observed during anti-phase coordination of the wrist, not only at the wrist but also at the elbow. For the remaining conditions, with the elbow in anti-phase, AN-IN NonI-Iso, AN-IN Iso-NonI and AN-AN Iso-Iso, error scores in the wrists appeared to be lower than in the previous set of conditions, whereas those of the elbow did not differ much from those conditions in which the wrists moved according to the anti-phase mode (IN-AN NonI-Iso, IN-AN Iso-NonI and AN-AN NonI-NonI).
Fig. 4a–b

Mean absolute error (AE) from 0° and 180° target relative phase (a) and relative phase variability (SD) scores (b) for interlimb coordination between the bilateral elbow and wrist joints across all experimental conditions. E-W interlimb coordination mode in elbow and wrist joints: NonDom-Dom is the intralimb coordination mode within non-dominant (NonDom) and dominant (Dom) limbs; the other labels for each condition are the same as those defined in Fig. 1

The results of the 2×2×2×2 (Joint×Elbow-INAN×Wrist-INAN×Dom-IsoNonI) ANOVA are presented in Table 1 (left column) and confirm the previous observations. Coordination between the bilateral elbows (M=25.14°) was more accurate than between the wrists (M=38.20°), as inferred from the significant main effect of joint. The main effect of elbow coordination mode was not significant whereas that of the wrist was: larger errors for interlimb relative phasing were found during the wrist anti-phase (M=42.21°) than during the in-phase (M=21.12°) mode. The effect of intralimb coordination mode was not significant, suggesting that there were minor effects of this factor on the quality of interlimb coordination. The significant interactions are illustrated in Fig. 5a. The significant Joint×Wrist-INAN interaction (F(1,12)=6.68, P<0.05) suggested that the anti-phase mode in the wrists had a differential impact on the quality of coordination in the two joints: during in-phase coordination of the wrists, the degree of accuracy of elbow (M=21.47°) and wrist (M=20.77°) interlimb coordination was similar (P>0.05). Conversely, anti-phase coordination in the wrist affected the coordination between both wrists (M=52.62°) more than between both elbows (M=28.80°) (P<0.01), even though error scores were increased in both wrists and elbows (Fig. 5a, top). This suggests that anti-phase coordination between the wrists had not only a negative influence on coordination quality of the wrists but also of the elbows. The Elbow-INAN×Wrist-INAN interaction was also significant (F(1,12)=9.86, P<0.01). Whereas in-phase coordination in the wrists was associated with lower interlimb relative phase error during elbows in-phase (M=12.00°) than elbows anti-phase (M=30.24°) coordination (P<0.05), anti-phase coordination in the wrists was associated with higher relative phase error during elbows in-phase (M=46.01°) than elbows anti-phase (M=38.41°) coordination, although differences did not reach significance (P=0.08) (Fig. 5a, bottom). The remaining interaction effects were not significant (Table 1, left column).
Table 1

Results of statistical analysis of relative phase absolute error (AE) and variability (SD) with respect to interlimb coordination

df

Interlimb coordination

Mean AE (F)

SD (F)

Joint

1, 12

7.9*

22.00**

Elbow-INAN

1, 12

1.41

0.37

Wrist-INAN

1, 12

20.00**

34.83**

Dom-IsoNonI

1, 12

2.67

2.85

Joint×Elbow-INAN

1, 12

3.46

4.56

Joint×Wrist-INAN

1, 12

6.68*

5.82*

Elbow-INAN×Wrist-INAN

1, 12

9.68**

12.33**

Joint×Dom-IsoNonI

1, 12

1.43

0.68

Elbow-INAN×Dom-IsoNonI

1, 12

0.78

0.00

Wrist-INAN×Dom-IsoNonI

1, 12

2.96

10.41**

Joint×Elbow-INAN×Wrist-INAN

1, 12

0.52

1.51

Joint×Elbow-INAN×Dom-IsoNonI

1, 12

0.32

0.02

Joint×Wrist-INAN×Dom-IsoNonI

1, 12

0.26

0.31

Elbow-INAN×Wrist-INAN×Dom-IsoNonI

1, 12

0.33

2.52

Joint×Elbow-INAN×Wrist-INAN×Dom-IsoNonI

1, 12

0.00

1.87

* P<0.05; ** P<0.01

Fig. 5a–b

The Joint×Wrist-INAN (top) and Elbow-INAN×Wrist-INAN (bottom) interaction for absolute error (AE) of relative phase with respect to interlimb coordination (a), and the Joint×Wrist-INAN (top), Elbow-INAN×Wrist-INAN (middle) and Wrist-INAN×Dom-IsoNonI (bottom) interaction for relative phase variability (SD) with respect to interlimb coordination (b)

SD of relative phase

Figure 4b reveals tendencies that are similar to those observed for the absolute error of relative phase. Table 1 (right column) presents the results of the 2×2×2×2 (Joint×Elbow-INAN×Wrist-INAN×Dom-IsoNonI) ANOVA on the SD of relative phase. The main effect of Joint was significant: more stable interlimb coordination patterns were observed between the bilateral elbow (M=17.99°) than wrist (M=26.59°) joints. Moreover, the in-phase coordination mode (M=14.89°) in the wrists was associated with higher global interlimb coordination stability than the anti-phase mode (M=26.69°). Such an effect was not observed with respect to the elbow. Figure 5b illustrates the significant interactions. The significant Joint×Wrist-INAN interaction (F(1,12)=5.82, P<0.05) indicated that only marginal differences in SD interlimb phasing scores between the elbows (M=13.03°) and wrists (M=16.76°) were observed when the wrists were prepared in the in-phase mode (P>0.05). During anti-phase coordination of the wrists, the SD scores increased substantially in both elbows and wrists, but this effect was more pronounced in the wrist (M=36.43°) than elbow (M=22.95°) joints (P<0.01) (Fig. 5b, top).

The significant Elbow-INAN×Wrist-INAN interaction (F(1,12)=12.33, P<0.01) can be interpreted as follows: whereas overall SD interlimb phasing scores were lower when the elbow was prepared in the in-phase (M=9.90°) as compared to the anti-phase coordination mode (M=19.88°) during in-phase coordination of the wrists (P<0.01), the SD scores were higher when the elbow was prepared in the in-phase (M=32.31°) as compared to the anti-phase coordination mode (M=27.07°) during anti-phase coordination mode of the wrists (P>0.05) (Fig. 5b, middle). Stated differently, this interaction suggests that there was some benefit in sharing the same coordination modes between the bilateral proximal and distal joints: when the wrists were prepared in the in-phase mode, higher stability was obtained when the elbows were also prepared in the in-phase mode. However, when the wrist were prepared in the anti-phase mode, higher stability was obtained when the elbow joints were in the anti-phase rather than the in-phase mode. This finding is counterintuitive and suggests that the effects obtained at the elbow and wrist joints are not simply additive.

The only remaining interaction reaching significance included the intralimb coordination mode factor, Wrist-INAN×Dom-IsoNonI (F(1,12)=10.41, P<0.01) (Fig. 5b, bottom). Whereas in-phase coordination between the wrists resulted in a small decrease of SD relative phasing scores from the isodirectional (M=16.64°) to the non-isodirectional (M=13.14°) intralimb coordination mode (P>0.05), anti-phase coordination between the wrists induced a significant increase in SD scores from the isodirectional (M=23.96°) to the non-isodirectional coordination mode (M=35.42°) (P<0.01). This suggested an interaction effect between interlimb and intralimb coordination modes on the SD of interlimb relative phasing. Whereas the overall stability of interlimb coordination was not much different between isodirectional and non-isodirectional intralimb coordination during in-phase coordination between the wrists, interlimb stability was more disrupted during non-isodirectional than isodirectional intralimb coordination when the wrists were prepared in anti-phase. This suggests some effect of intralimb coordination on the quality of interlimb coordination that only became evident when the wrists were moved according to the anti-phase coordination mode.

Analysis of intralimb coordination

Graphical representation of the displacements in the elbow and wrist of the dominant and non-dominant limbs are shown in Fig. 6 for the IN-IN Iso-Iso and the AN-AN NonI-NonI conditions. The corresponding angular displacements of elbow versus wrist are illustrated in the right-hand column. As can be observed, high stability of intralimb coordination was found for the isodirectional pattern. On the contrary, AN-AN NonI-NonI was relatively less stable than the IN-IN Iso-Iso condition.
Fig. 6a–b

Examples of intralimb coordination trials of a single subject under ININ Iso-Iso (a) and ANAN NonI-NonI (b) conditions for the elbow and wrist joints within the non-dominant (top figures) and dominant limb (bottom figures). Displacement-time figures are placed on the left side while Lissajous figures are presented on the right side. In the Lissajous figures, the X-axis refers to displacement of the wrist and the Y-axis to displacement in the elbow. Right diagonal lines represent isodirectional movements whereas left diagonal lines refer to non-isodirectional movements. Bold diagonal lines are the target coordination values

Absolute error of relative phase

Figure 7a displays the absolute error of relative phasing as a function of interlimb and intralimb coordination modes. It is evident that the isodirectional mode is not associated with lower intralimb relative phasing error than the non-isodirectional mode under all circumstances. The results of the 2×2×2×2 (Limb×Iso-NonI×Elbow-INAN×Wrist-INAN) ANOVA are shown in Table 2 (left column). Only the main effect for wrist interlimb coordination mode was significant: the anti-phase coordination mode in the wrist resulted in a higher disruption of overall intralimb coordination (M=37.87°) than the in-phase (M=29.80°) coordination mode. This effect was not significant for the elbow coordination mode. Thus, the effect of mode of interlimb coordination on the quality of intralimb coordination was limited to the wrist joint. None of the remaining main effects or interactions reached significance.
Fig. 7a–b

Mean absolute error (AE) from 0° and 180° target relative phase (a) and relative phase variability (SD) scores (b) for intralimb coordination in non-dominant and dominant upper limbs across all experimental conditions

Table 2

Results of statistical analysis of relative phase absolute error (AE) and variability (SD) with respect to intralimb coordination

df

Intralimb coordination

Mean AE (F)

SD (F)

Limb

1, 12

3.13

1.23

Iso-NonI

1, 12

0.19

7.15*

Elbow-INAN

1, 12

0.58

0.47

Wrist-INAN

1, 12

6.16*

35.29**

Limb×Iso-NonI

1, 12

1.15

6.29*

Limb×Elbow-INAN

1, 12

1.6

1.04

Iso-NonI×Elbow-INAN

1, 12

0.14

2.64

Limb×Wrist-INAN

1, 12

1.26

1.39

Iso-NonI×Wrist-INAN

1, 12

0.21

0.65

Elbow-INAN×Wrist-INAN

1, 12

3.49

4.66

Limb×Iso-NonI×Elbow-INAN

1, 12

3.08

2.22

Limb×Iso-NonI×Wrist-INAN

1, 12

0.42

0.13

Limb×Elbow-INAN×Wrist-INAN

1, 12

0.02

0.63

Iso-NonI×Elbow-INAN×Wrist-INAN

1, 12

3.24

0.98

Limb×Iso-NonI×Elbow-INAN×Wrist-INAN

1, 12

0.23

6.73*

* P<0.05; ** P<0.01

SD of relative phase

The SD scores of intralimb relative phasing (Fig. 7b) showed similar tendencies across coordination conditions to those observed with respect to absolute error of relative phase (Fig. 7a). The 2×2×2×2 (Limb×Iso-NonI×Elbow-INAN×Wrist-INAN) ANOVA results are presented in the right column of Table 2. The main effect for intralimb coordination mode was significant, suggesting that intralimb coordination was performed with higher stability during the isodirectional (M=21.16°) than during the non-isodirectional mode (M=26.98°). The effect for wrist coordination mode was also significant: intralimb coordination performance was more stable during in-phase (M=18.21°) than anti-phase wrists coordination (M=29.93°). The significant Limb×Intralimb Coordination Mode interaction will not be discussed here since post hoc analyses did not reveal any significant differences across conditions. The significant four-factor interaction will not be discussed here either because it did not reveal insights that contribute to the principal objectives of the present study. To examine the role of the dominant versus the non-dominant limb in affecting intralimb coordination, a 2×2×2 (Limb×NonDom IsoNonI×Dom IsoNonI) ANOVA was conducted and revealed that the higher stability during isodirectional as compared to non-isodirectional intralimb coordination was only evident when these modes were manipulated in the dominant but not in the non-dominant limb [dominant limb, F(1,12)=11.50, P<0.01; non-dominant limb F(1,12)<1]. Intralimb SD scores during isodirectional and non-isodirectional coordination modes in the dominant limb were 19.46° and 28.68°, respectively.

Cycle duration

The target cycle duration was 752 ms (1.33 Hz). Mean cycle durations were 788 ms (non-dominant elbow), 776 ms (dominant elbow), 785 ms (non-dominant wrist) and 792 ms (dominant wrist). Modulations in mean cycle duration and cycle duration variability scores across the eight task conditions were not significant (Mean: F(7,84)=1.45, P>0.05; Variability: F(7,84)=1.89, P>0.05). Main effects and interactions were not significant (P>0.05) or were of minor interest with respect to the principal objectives of the present study.

Discussion

In the present study, we explored the principles underlying interlimb and intralimb coordination and their potential interactions during performance of bilateral movements with the elbows and wrists. Two major findings emerged from this work.

With respect to interlimb coordination, multijoint movements requiring the simultaneous activation of homologous muscle groups were performed more accurately and consistently than those requiring simultaneous activation of non-homologous muscles (Byblow et al. 1999; Kelso 1984; Lee et al. 1995; Semjen et al. 1995; Swinnen et al. 1997). This was inferred from the higher relative phase accuracy and lower variability between the limbs when the wrists were prepared in the in-phase as compared to the anti-phase coordination mode. The mode of coordination between the elbow joints did not appear to have such an impact on the quality of interlimb coordination.

With respect to intralimb coordination, the isodirectional coordination mode between the ipsilateral elbow and wrist joint was performed with higher consistency than the non-isodirectional mode, but this effect was only prominent in the dominant limb. Whereas the mode of intralimb coordination did not have a strong influence on the quality of interlimb coordination, the converse effect was more prominent whereby bilateral wrist coordination played a more dominant role than bilateral elbow coordination. These interactions between interlimb and intralimb coordination constraints refer to new observations and will therefore be discussed in more detail next.

Effects of interlimb and intralimb constraints on the quality of interlimb coordination

The present study extended previous observations in which a general preference for moving the limbs towards or away from the longitudinal axis of the body in a symmetrical fashion was found to increase the dynamic stability of the coordination patterns, relative to other conditions in which this symmetry was not evident (Kelso and Jeka 1992; Mechsner et al. 2001; Swinnen et al. 1997, 1998). More specifically, in-phase patterns in both elbows and wrists (IN-IN) displayed higher relative phase accuracy and lower variability than movements engaging anti-phase conditions in either one or both joint combinations. However, closer inspection of the data requires a more refined specification of this general statement: (1) the effects were not completely additive, and (2) there was a difference in impact between the proximal and distal joints, discussed next.

Even though in-phase coordination in both the elbow and wrist joints resulted in the highest accuracy and stability, it is not the case that anti-phase patterns in both bilateral joints led to the lowest interlimb accuracy and stability. As such, the predicted effects of coordination mode were not simply additive. In this respect, it was observed that during in-phase coordination of the wrists, the highest stability was observed when the elbows were also prepared in the in-phase as compared to the anti-phase mode. However, during anti-phase coordination between the wrists, better results were obtained when the elbows were prepared according to the anti-phase rather than the in-phase mode. It appears that the parallel (anti-phase) motions between the wrists also dragged the elbow joints into parallel motions. This suggests that the adopted coordination mode between the bilateral wrists was more decisive about the quality of global interlimb coordination than that in the elbow joints. This is supported by the experimental findings: the main effect of wrist but not elbow coordination mode was significant. Moreover, overall interlimb relative phasing error and SD scores were higher in the wrist than elbow joints. The observed interaction effects provide more detailed information about the coupling between the elbow and wrist joints. The Joint×Wrist Coordination Mode interaction indicated that interlimb relative phasing between both elbows and wrists was very similar in accuracy and stability during in-phase coordination between the wrists. However, during anti-phase coordination of the wrists, the quality of interlimb coordination deteriorated in both joints even though the effect was more pronounced in the wrists than elbows. The Elbow Coordination Mode×Wrist Coordination Mode effect provided additional insights into joint interactions. Whereas interlimb relative phasing accuracy and consistency was higher (lower error and SD) during elbow in-phase than elbow anti-phase coordination when the wrists were prepared in the in-phase coordination mode, it tended to be lower (higher error and SD) for elbow in-phase than elbow anti-phase during anti-phase coordination in the wrists. This suggests that anti-phase wrist coordination was more disruptive for global interlimb coordination when the elbow muscles were prepared in the in-phase as compared to the anti-phase mode. In general, these observations suggest that the impact of the wrist coordination mode was larger than that in the elbows for the global quality of interlimb coordination.

The effect of intralimb on interlimb coordination was small, as the main effect for intralimb coordination mode did not reach significance. This suggests that interlimb relative phasing accuracy and stability did not differ between tasks in which the isodirectional as compared to the non-isodirectional intralimb coordination mode was adopted. The data presented in Fig. 4 show convincingly that the mode of interlimb coordination was more decisive than the mode of intralimb coordination for the overall quality of interlimb coordination. For example, when inspecting the conditions in which both the elbow and wrist joints adopted the in-phase coordination modes, no differences were observed between isodirectional and non-isodirectional coordination modes within both limbs (IN-IN Iso-Iso versus IN-IN NonI-NonI). This underscores that mirror-image symmetry represents a powerful constraint on interlimb coordination. The production of symmetrical movements is likely to result in stronger synchronization in the activity of bilateral motorneuron pools (Cardoso de Oliveira et al. 2001; Donchin et al. 2001; Gerloff and Andres 2002). The privileged connections between neural control centers (through the corpus callosum) results in stronger synchronization of activity of bilateral motorneuron pools during simultaneous production of symmetrical movements (in-phase iso- or non-isodirectional modes) but also less successful desynchronization during production of dissimilar movements (anti-phase modes). This powerful symmetrical or mirror-image constraint during bimanual coordination is reminiscent of a similar constraint in perception of two stimuli (Wagemans 1997).

When the wrist joints adopted the anti-phase coordination mode, isodirectional intralimb coordination was found to result in higher interlimb coordination consistency than non-isodirectional coordination. This suggests that, in the absence of bilateral symmetry, intralimb coordination constraints influenced interlimb coordination performance. Again, this indirectly emphasizes the superior role of bilateral symmetry in coordination.

The effects of interlimb and intralimb constraints on the quality of intralimb coordination

As predicted, it was generally observed that isodirectional coordination modes between the proximal and distal joint within a limb resulted in a higher consistency of intralimb coordination than non-isodirectional coordination modes. The superior quality of isodirectional coordination can partly be accounted for by the effect of interaction torques among the limb segments (Dounskaia et al. 1998). Previous studies using unilateral limb tasks have shown that movements at the distal joint are partly produced but also controlled by the movements of the proximal joint (Dounskaia et al. 1998, Dounskaia and Stelmach 2001; Levin et al. 2001; Putnam 1991; Zajac and Gordon 1989). In line with the leading joint hypothesis (Dounskaia et al. 1998), elbow and wrist muscles play a differential role in the control of forearm movements: whereas elbow muscles generate the movement of the whole linkage, wrist muscles are hypothesized to be responsible for making the fine adjustments and to compensate for inter-segmental interactions. More specifically, it has been demonstrated that inter-segmental interactions support wrist acceleration during the performance of isodirectional elbow-wrist movement but oppose it during the performance of non-isodirectional movements (Dounskaia et al. 1998).

Whereas the impact of intralimb coordination modes on the quality of interlimb coordination was limited, the converse effect was more prominent. However, it was not the case that in-phase coordination in both joint combinations invariably resulted in the highest quality of intralimb coordination and anti-phase coordination in the lowest quality. The interlimb coordination mode adopted between the bilateral wrists had a more powerful impact on accuracy and stability of intralimb coordination than that between the elbows. Compared to in-phase coordination, anti-phase coordination in the bilateral wrists had a disruptive effect on intralimb coordination. No significant effect of elbow coordination mode was evident. These findings underscore again that the coordination adopted between the wrists had a more powerful impact than between the elbows for the coordinative behavior of the global multijoint system. Finally, the role of limb dominance in the control of bimanual multijoint coordination was not found to be prevalent. This implies that the well-known differences in the quality of control between the dominant and non-dominant limb did not affect the global coordinative behavior at the multijoint level. Perhaps these effects were masked by the supremacy of interlimb coordination between symmetrical body parts.

Whereas the aforementioned discussion of principal findings was primarily inspired by current knowledge about preexisting interlimb and intralimb coordination constraints, it is worth noting that when coordination patterns become increasingly complex, cognitive strategies that refer to task conceptualization or spatial representation of the movement become increasingly important (Swinnen and Wenderoth 2004). This was not the primary focus of the present study in which we wanted to establish some basic principles of multijoint upper limb coordination. However, addressing the impact of cognitive strategies on complex action may prove to be a fruitful avenue for future research using similar task paradigms.

Conclusions

The present findings on multijoint bilateral coordination not only confirm previous observations on the impact of interlimb and intralimb coordination constraints but also extend current knowledge in important ways. First, the principle of muscle homology giving rise to mirror symmetrical movements with respect to the longitudinal axis of the body had a powerful influence on the coordinative quality of the global multijoint system. However, the distal joints exhibited a stronger impact on the quality of multijoint coordination than the proximal joints. Second, the findings on intralimb coordination revealed that isodirectional coordination between adjacent limb segments (simultaneous flexions and extensions) resulted in a higher quality of intralimb coordination than non-isodirectional coordination modes. This effect was primarily evident in the dominant (right) limb. Third, whereas the impact of intralimb coordination mode on the quality of interlimb coordination was minor, the mode of interlimb coordination affected the quality of intralimb coordination more profoundly. Again, interlimb wrist coordination affected the quality of intralimb coordination whereas the effect of elbow interlimb coordination was minor. These observations suggest a hierarchical control structure for multijoint bimanual movement whereby interlimb coordination constraints dominate over those governing intralimb coordination. Moreover, the distal joints play a more superior role in their effects on the global coordinative system than the proximal joints. Additional studies with other joint combinations are required to determine the generalizability of these observations.

Acknowledgements

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).

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© Springer-Verlag 2005