Abstract

Whereas the cerebral representation of bimanual spatial coordination has been subject to prior research, the networks mediating bimanual temporal coordination are still unclear. The present study used functional imaging to investigate cerebral networks mediating temporally uncoupled bimanual finger movements. Three bimanual tasks were designed for the execution of movements with different timing and amplitude, with same timing but different amplitude, and with same timing and amplitude. Functional magnetic resonance imaging results showed an increase of activation within right premotor and dorsolateral prefrontal, bilateral inferior parietal, basal ganglia, and cerebellum areas related to temporally uncoupled bilateral finger movements. Further analyses showed a decrease of connectivity between homologous primary hand motor regions. In contrast, there was an increase of connectivity between motor regions and anterior cingulate, premotor and posterior parietal regions during bimanual movements that were spatially or both temporally and spatially uncoupled, compared with bimanual movements that were both spatially and temporally coupled. These results demonstrate that the extent of bihemispheric coupling of M1 areas is related to the degree of temporal synchronization of bimanual finger movements. Furthermore, inferior parietal and premotor regions play a key role for the implementation not only of spatial but also of temporal movement parameters in bimanual coordination.

Introduction

The physiology of coordinating the 2 hands has been investigated in several ways (for review, see Swinnen and Wenderoth 2004). One approach is the investigation of different movements simultaneously performed by both hands, that is, one hand performs a postural role, while the other hand takes on a manipulative role (Johansson et al. 2006). This approach comes close to daily life movements, but the results of such studies may be difficult to interpret as multiple different muscle groups and joints are involved. Therefore, recent studies have focused on bimanual movements requiring that both hands perform similar movements, with a limited number of muscles and joints involved. The execution of bimanual movements performed in antiphase or with polyrhythmic coordination employs common neural control circuitries, eliciting fronto–parieto–temporal activations (Sadato et al. 1996; Goerres et al. 1998; Stephan et al. 1999; Immisch et al. 2001). Further studies assign a critical role to bilateral superior parietal cortex and dorsolateral prefrontal cortex (DLPFC) (Eliassen et al. 1999; Serrien et al. 2001; Wenderoth et al. 2005). Furthermore, a recent study has shown that spatial coordination of bimanual continuous movements is related to the bihemispheric synchronization of primary motor cortex activity (Maki et al. 2008). The exact mechanism of this bihemispheric synchronization is unclear; it is assumed that subcortical gating plays a crucial role (Ivry and Richardson 2002).

In contrast to spatial coordination of bimanual movements, the functional representation of temporal coordination of movements of the 2 hands is not yet clear. Behavioral studies have shown that bimanual movements are highly synchronized in the temporal domain, with or without spatial constraints (Kelso et al. 1990). Temporal synchronization occurs automatically, and subjects are usually not aware that they couple movements with respect to timing. During discrete bimanual movements, even the acceleration pattern and the termination of movements without spatial constraints are well synchronized (Kelso et al. 1990). Thus, temporal synchronization of bimanual movements is a highly stable behavior.

The present study investigated the differential involvement of motor network regions during bimanual movements that were performed either in temporally coupled or temporally uncoupled fashion. Specifically, 2 hypotheses were tested:

  1. Temporal uncoupling of bimanual finger movements requires involvement of dorsolateral prefrontal and inferior parietal regions that are related to movement planning in the temporal domain (Sakai et al. 2002; Garraux et al. 2005; Aramaki et al. 2006).

  2. The extent of bimanual coupling of finger movements is related to the degree of synchronization between bihemispheric primary motor areas, that is, temporal uncoupling of bimanual movements will reduce the connectivity between bilateral M1 hand areas. A recent study showed that spatial coordination of bimanual continuous movements is related to the interhemispheric synchronization of primary motor cortex activity (Maki et al. 2008).

Materials and Methods

Subjects

We studied 13 normal volunteers (5 women, 8 men) with a mean age of 29.4 ± 6.1 (standard deviation) years. All volunteers were right handed, according to the Edinburgh handedness inventory (Oldfield 1971). Informed consent was obtained from all participants prior to the experimental procedures, and the experiments were approved by the National Institute of Neurological Disorders and Stroke institutional review board.

Motor Tasks and Movement Control

Three different bimanual motor tasks requiring bilateral index finger movements were performed by each subject. Finger movements were assessed with 2 self-constructed devices one for each hand. Each hand was fixed with tape on the device that supported a comfortable neutral hand–wrist position. The index finger was fixed to a flexible lever that was attached to each device. Thus, the index finger could be moved up and down with reference to the palm. The movements of the lever were measured with a fiber optical sensor (S720; Measurand Inc., Fredericton, Canada) that was attached to the lever. The data were transferred to a 2 channel data acquisition system (S270; Measurand Inc., Fredericton, Canada) connected to a computer and stored for off-line analysis. The devices enabled us to measure index finger position with a sampling rate of 120 Hz. Finger movements were analyzed with respect to movement onset, duration, amplitude, maximum slope, and time-to-peak. Slope was determined by division of changes of hand position between 2 sampling time points by the sampling time interval (8.33 ms). As the main parameter of interest regarding movement amplitudes was the relation of small to large amplitudes, relative amplitudes (average small amplitude divided by average large amplitude for each task and each subject) were used for further analysis.

Each motor task consisted of 12 blocks of 30-s duration (starting with rest, activation, rest, and so on). During activation periods, small circles appeared every 2 s (duration 0.5 s) on a monitor (out of scanner training session) or on a screen that could be seen via a mirror mounted on the scanner head coil (as used in the functional magnetic resonance imaging [fMRI] session). Subjects were instructed to perform the required movements with a visual cue. There were 3 main tasks: During the on-periods of task “same timing and same amplitude (sTsA), subjects performed right and left index finger flexions and extensions simultaneously with identical amplitude on both sides. In particular, they started to move both fingers synchronously, reach maximum flexion of both index fingers synchronously, and return to baseline position. To minimize external influence, all movements were performed without finger (or lever) contact with a surface serving as end or start position. During activation periods 1, 3, and 5, movements with large amplitude were required, and during activation periods 2, 4, and 6, movements with small amplitude should be performed. The smaller movement amplitude was meant to be approximately half of the amplitude of the larger one. This task was especially designed to evaluate whether movement amplitude affects brain activation other than primary motor cortex and cerebellum. Task “same timing and different amplitude” (sTdA) also consisted of synchronous movements. During activation periods 1, 3, 5, movements with large amplitude on the left and small amplitude on the right were required, and vice versa during activation periods 2, 4, and 6. During the training session, it was evident that in all participants timing of movements was highly coupled, that is, they started and ended synchronously, and, in general, subjects were not aware that they coupled movements with respect to timing features. The task “different timing and different amplitude” (dTdA) was similar to the task sTdA, except that subjects were asked to uncouple movements with respect to movement timing. Although movements started synchronously, the finger performing the smaller amplitude was required to reach maximum flexion before the finger performing the larger amplitude (see Fig. 1 for an overview of the movement characteristics of tasks sTdA and dTdA). It is important to note that the temporal and spatial uncoupling tasks as tested in the present study did not require fully independence of bilateral movements in the temporal or spatial domain; rather the kinematic profile in the temporal or spatial domain, which would be identical in the case of coupled movements, was different between fingers (however, e.g., starting and ending points were congruent for all tasks).

Figure 1.

Time course of finger movements (average of 60 movements) during task sTdA requiring spatial but not temporal finger movement uncoupling (upper trace) and task dTdA requiring temporal and spatial finger movement uncoupling (lower trace) in subject 6. During task sTdA time-to-peak amplitude of small and large index finger movements were synchronous, whereas time-to-peak amplitude for the small movement was shorter during task dTdA. The amplitude of the small movement is shown with respect to the large movement (normalized to 1).

Figure 1.

Time course of finger movements (average of 60 movements) during task sTdA requiring spatial but not temporal finger movement uncoupling (upper trace) and task dTdA requiring temporal and spatial finger movement uncoupling (lower trace) in subject 6. During task sTdA time-to-peak amplitude of small and large index finger movements were synchronous, whereas time-to-peak amplitude for the small movement was shorter during task dTdA. The amplitude of the small movement is shown with respect to the large movement (normalized to 1).

Motor Training, Motor Skills, and Psychological Assessment

As the study focused on bilateral finger movements, we evaluated motor skills of all subjects prior to the experiments using a questionnaire. Uncoupled finger movements are important for movements like playing a music instrument or typing computer keyboards. Subjects were asked if and when they regularly played a music instrument and/or used a computer keyboard. The individual performance should be self-rated on a scale from 1 (beginner) to 4 (excellent).

Subjects were trained to perform the motor tasks one day prior to the fMRI experiments. Subjects practiced for 60 min with the training blocks being identical to the experimental session in the fMRI machine. Visual feedback of movement performance and accuracy was provided on a computer screen after each training block with the stored movement data. During the fMRI session, no feedback was provided.

Functional MRI

fMRI employing blood oxygenation level–dependent (BOLD) contrast was performed on a 3 T GE scanner using a multishot multislice gradient-echo echoplanar T2*-weighted sequence. Functional imaging parameters were set as follows: time repetition: 2000 ms, time echo: 30 ms, functional area: 90°, Matrix 64 × 64, field of view: 220 × 220 mm, 22 contiguous slices parallel to the anterior commissure–posterior commissure line, slice thickness 5 mm, and slice gap 1 mm. The voxel size was 3 × 3 mm. In total, 184 images were acquired for each functional run with the first 4 scans being discarded to allow for magnetic saturation. The 3 functional runs (tasks sTsA, sTdA, and dTdA) were performed in pseudorandom and balanced order across subjects to control for possible time effects.

Functional MRI Data Analysis

The data were analyzed using SPM2 software implemented in Matlab (Mathworks Inc., Sherborn, MA). The scans obtained for each subject and each condition were realigned to the first image of each task using a 6-parameter rigid body transformation. Then images were transformed into the standard stereotactic space (template provided by the Montreal Neurological Institute) using linear and nonlinear spatial deformations. Individual transformations were applied to each set of realigned images to spatially normalize the images. Each normalized scan (voxel size 3 × 3 × 3 mm) was smoothed with a Gaussian kernel (full-width half-maximum 9 × 9 × 9 mm) to increase the signal-to-noise ratio.

For whole-brain BOLD analysis, a boxcar model was applied, convolving images with the modeled hemodynamic response and eliminating low-frequency noise (time constant 128 s) for each condition and each subject. Activated voxels were identified by the general linear model approach. The following analysis of variance (ANOVA) group data analysis was based on these contrast images.

Task-specific effects were determined using within-subjects ANOVA comprising contrasts of single subject data for the different tasks versus rest. These constituted a 3×2 factorial design (factors: “task” [sTsA, sTdA, and dTdA], “amplitude right hand” [small, large]). The statistical threshold was set to P < 0.05, corrected (family wise-error). Only clusters larger than 30 adjacent voxels are reported.

Connectivity Analysis

To identify the areas in which the degree of coupling with an index region is modulated significantly by the nature of the task, the functional connectivity analysis was assessed using a psychophysiological interaction (PPI) model (Friston et al. 1997). PPI analyses were conducted with 6 index areas: left and right M1 hand areas, premotor regions, and posterior parietal regions. These regions have been shown to constitute the core network of movement planning (Fink et al. 1997; Rijntjes et al. 1999; Rizzolatti and Luppino 2001) and therefore were selected for connectivity analysis. The mean corrected and high-passed-filtered time series in the index areas were obtained on a subject-by-subject basis (Stephan et al. 2003; Garraux et al. 2005) by extracting the first principal component from all voxel time series in a 4-mm-radius sphere centered at the coordinates peak level activations. The PPI terms (referred to as “PPI regressor”) were computed as the element-by-element product of the deconvolved extracted time series and a vector coding for the main effect of task. The PPI regressor was mean corrected to remove subject-specific effects and convolved by the canonical hemodynamic response function to account for possible hemodynamic lag. For each subject, the PPI regressor, the task regressor, and the extracted time series were entered in a first-level model of functional connectivity. The PPI analysis was specific for movement amplitude and movement timing influences that occurred over and above any task effects and task-independent influences. The brain areas receiving context-dependent influences, that were stronger during the task of interest (sTsA, sTdA, or dTdA) than rest, were determined by testing for positive slopes of the PPI regressor, that is, by applying a t-contrast that was 1 for the PPI regressor and 0 elsewhere. The 3 PPI maps of all the subjects were taken into a second-level analysis (one sample t-test) to reveal the task-dependent coupling. For instance, to isolate task-specific effects which were stronger during dTdA than dTsA, we compared the task using an appropriate contrast at the second-level analysis that was 1 for the PPI maps of dTdA, −1 for the PPI maps of sTdA, and 0 elsewhere. The statistical threshold was set to P < 0.001, uncorrected with a required cluster size of at least 20 adjacent voxels.

Results

The results of the questionnaire assessing motor skills revealed that all subjects played a music instrument for at least 1 year with an average of 8.2 ± 7.0 years. Subjects rated their performance as “good” (1.92 ± 0.79). All subjects used a computer keyboard regularly with an average self-rated performance of “very good” (2.54 ± 0.66).

Movement Control

Movement duration was slightly prolonged during dTdA compared with sTdA (overall average movement duration sTdA: 1.00 ± 0.08 s (standard error), dTdA: 1.14 ± 0.08 s), but the statistical pairwise comparison of movement duration for all tasks did not reach significance. Likewise movement onset of both index fingers did not differ significantly during the motor tasks.

During sTdA, the peak amplitude was reached nearly simultaneously with both index fingers (average difference: 0.028 ± 0.008 s). In contrast, a distinct difference was observed during dTdA with the index finger performing the small movement reaching the peak amplitude earlier than the finger performing the large movement as expected (average difference of time points of peak amplitude between right and left index finger: 0.259 ± 0.036 s; see Fig. 1). The statistical comparison of the time-to-peak differences of both fingers between task sTdA and dTdA using Student's t-test was significant (P < 10−12). As a further measure of correct movement execution, the initial slope of the movement curves was compared for both fingers for tasks sTdA and dTdA. Whereas task sTdA required different slopes for both fingers, task dTdA required similar slopes (Fig. 1). Analysis of the slopes of the movement curves (which had time as parameter on the x-axis and finger position as parameter on the y-axis) confirmed this expectation: whereas for task sTdA, the slopes of the movement curves differed by 14.9 ± 1.2°/s in average, during task dTdA, the slopes of the movement curves differed only by 6.8 ± 1.6°/s between fingers in average (statistical comparison between tasks sTdA and dTdA using Student's t-test: P = 0.00046). Thus subjects fulfilled the requirements of the task dTdA during the scanning sessions, starting with similar velocity for both fingers but then reaching a movement plateau for one finger, whereas the other finger reached a higher amplitude. The amplitude of the index finger performing the small movement was 0.44–0.57 times the large movement amplitude, with no significant difference for sTdA and dTdA.

For all parameters reported here (movement duration, difference of movement onset between fingers, bilateral difference between the time points until the amplitude peak of the finger movement is reached, and initial slope differences between movement curves of both fingers), statistical comparisons for the 2 task variants (right finger large amplitude vs. right finger small amplitude) using Student's t-test were carried out. None of these comparisons were significant, confirming consistent motor performance of all tasks during the scanning sessions.

The group results for sTdA and dTdA are summarized in Table 1.

Table 1

Movement control parameters

 Task sTsA (R/L)
 
Task sTsA (r/l)
 
Task sTdA (R/l)
 
Task sTdA (r/L)
 
Task dTdA (R/l)
 
Task dTdA (r/L)
 
 
Duration 0.91 ± 0.25 0.91 ± 0.24 0.90 ± 0.22 0.89 ± 0.22 1.00 ± 0.30 0.98 ± 0.28 0.98 ± 0.30 1.04 ± 0.33 1.18 ± 0.31 1.15 ± 0.32 1.09 ± 0.29 1.15 ± 0.28 
Amplitude 0.42 ± 0.13 0.44 ± 0.18 0.57 ± 0.14 0.47 ± 0.13 0.45 ± 0.14 0.45 ± 0.16 
Onset difference 0.01 ± 0.01  0.01 ± 0.01   0.02 ± 0.02 0.02 ± 0.01   0.04 ± 0.02 0.05 ± 0.03  
Peak difference 0.01 ± 0.01  0.02 ± 0.01  0.04 ± 0.01   0.05 ± 0.03 0.22 ± 0.10   0.31 ± 0.17 
 Task sTsA (R/L)
 
Task sTsA (r/l)
 
Task sTdA (R/l)
 
Task sTdA (r/L)
 
Task dTdA (R/l)
 
Task dTdA (r/L)
 
 
Duration 0.91 ± 0.25 0.91 ± 0.24 0.90 ± 0.22 0.89 ± 0.22 1.00 ± 0.30 0.98 ± 0.28 0.98 ± 0.30 1.04 ± 0.33 1.18 ± 0.31 1.15 ± 0.32 1.09 ± 0.29 1.15 ± 0.28 
Amplitude 0.42 ± 0.13 0.44 ± 0.18 0.57 ± 0.14 0.47 ± 0.13 0.45 ± 0.14 0.45 ± 0.16 
Onset difference 0.01 ± 0.01  0.01 ± 0.01   0.02 ± 0.02 0.02 ± 0.01   0.04 ± 0.02 0.05 ± 0.03  
Peak difference 0.01 ± 0.01  0.02 ± 0.01  0.04 ± 0.01   0.05 ± 0.03 0.22 ± 0.10   0.31 ± 0.17 

Note: Results of the behavioral movement analysis for the 3 tasks that required simple large or small bilateral index finger movements (task sTsA), spatial uncoupling of bimanual movements (sTdA of both hands), or spatial and temporal uncoupling of bimanual movements (dTdA of both hands). Upper and lower case writing of r and l denotes large or small left or right index finger movements.

fMRI Results

Activation Maps

During all experimental tasks, a bilateral motor network comprising bilateral primary motor cortex, inferior parietal and premotor regions, basal ganglia and cerebellum was found to be active (Supplementary Fig. S1).

ANOVA analysis of the main effects of the factor task revealed the following results (Fig. 2):

Figure 2.

Networks recruited during spatial and temporal uncoupling of bilateral finger movements according to the ANOVA data analysis (P < 0.05, family wise-error corrected). Above, task dTdA versus sTsA, that is, the network recruited for both temporal and spatial movement uncoupling of bilateral finger movements compared with simple finger movements. Middle, task sTdA versus sTsA. This contrast compared spatial uncoupling of bilateral finger movements with simple finger movements showing a right parietal region. Below, tasks dTdA versus sTdA, that is, the network involved in temporal uncoupling of bilateral finger movements. Temporal uncoupling required involvement of bilateral inferior parietal and right frontal cortical regions as well as bilateral basal ganglia and cerebellum regions.

Figure 2.

Networks recruited during spatial and temporal uncoupling of bilateral finger movements according to the ANOVA data analysis (P < 0.05, family wise-error corrected). Above, task dTdA versus sTsA, that is, the network recruited for both temporal and spatial movement uncoupling of bilateral finger movements compared with simple finger movements. Middle, task sTdA versus sTsA. This contrast compared spatial uncoupling of bilateral finger movements with simple finger movements showing a right parietal region. Below, tasks dTdA versus sTdA, that is, the network involved in temporal uncoupling of bilateral finger movements. Temporal uncoupling required involvement of bilateral inferior parietal and right frontal cortical regions as well as bilateral basal ganglia and cerebellum regions.

The contrast sTdA versus sTsA showed a large activation of the right inferior parietal cortex and a small activation within the left sensorimotor cortex. These regions were involved during execution of spatially uncoupled compared with coupled bilateral finger movements (Table 2). The reverse contrast sTsA versus sTdA did not reveal any significant activations.

Table 2

Regions showing additional fMRI activation related to spatially or temporally uncoupled bimanual movements

Region Brodmann area x y z Z-score Cluster size [voxel] 
Task sTdA versus sTsA 
    Right inferior parietal cortex 40 38 −42 50 5.87 931 
    Left postcentral gyrus −52 −26 44 4.62 36 
Task dTdA versus sTdA 
    Right premotor cortex 46 48 5.95 312 
    Right DLPFC 46 46 30 18 5.04 79 
    Left inferior parietal cortex 40 −38 −52 54 5.42 291 
    Right inferior parietal cortex 40 40 −46 44 5.20 334 
    Right cerebellum, posterior lobe  34 −60 −38 5.15 80 
    Left cerebellum, posterior lobe  −34 −64 −36 4.98 120 
    Left globus pallidus  −16 −6 10 4.96 77 
    Right putamen  16 −2 14 5.63 291 
Region Brodmann area x y z Z-score Cluster size [voxel] 
Task sTdA versus sTsA 
    Right inferior parietal cortex 40 38 −42 50 5.87 931 
    Left postcentral gyrus −52 −26 44 4.62 36 
Task dTdA versus sTdA 
    Right premotor cortex 46 48 5.95 312 
    Right DLPFC 46 46 30 18 5.04 79 
    Left inferior parietal cortex 40 −38 −52 54 5.42 291 
    Right inferior parietal cortex 40 40 −46 44 5.20 334 
    Right cerebellum, posterior lobe  34 −60 −38 5.15 80 
    Left cerebellum, posterior lobe  −34 −64 −36 4.98 120 
    Left globus pallidus  −16 −6 10 4.96 77 
    Right putamen  16 −2 14 5.63 291 

Note: Coordinates of the peak voxels for the main task effect of the ANOVA data analysis for comparison of the tasks sTsA versus sTdA (above) and dTdA versus sTdA (below) (P < 0.05, corrected [family wise-error]). The first comparison sTsA versus sTdA shows regions additionally recruited for spatial uncoupling of finger movements, whereas the second comparison dTdA versus sTdA shows regions additionally recruited for temporal uncoupling of finger movements.

The comparison of tasks dTdA versus sTdA revealed brain regions that were engaged during temporal uncoupling of bilateral finger movements. The contrast dTdA versus sTdA showed activations within bilateral inferior parietal regions, right premotor and dorsolateral prefrontal areas, bilateral putamen, cerebellum, and thalamus (Table 2).

The contrast sTdA versus dTdA revealed no significant differences.

The comparison between tasks sTsA and dTdA showed the network that is additionally active during both spatial and temporal uncoupling of bilateral finger movements. Analysis of the contrast dTdA versus sTsA showed bilateral premotor, dorsolateral prefrontal, and inferior frontal regions with a slight right hemispheric predominance, bilateral inferior parietal regions, bilateral basal ganglia (putamen and globus pallidus), and cerebellum activations. These regions are well known to play a crucial role for motor planning and coordination (Fink et al. 1997; Rizzolatti and Luppino 2001). The reverse contrast sTsA versus dTdA showed no significant activations.

ANOVA analysis of the factor main “amplitude right hand” and the interaction between the factors “amplitude right hand” and “task” revealed no significant fMRI activations, indicating that the laterality during task execution (i.e., the fact that either the left or the right hand performed movements with large amplitude) was not critical for the functional imaging results reported above.

Connectivity Maps

The functional connectivity changes due to spatial and temporal uncoupling of finger movements (contrasts dTdA-sTsA, dTdA-sTdA, and sTdA-sTsA and vice versa) were tested using PPI modeling of 3 critical regions of the motor network for each hemisphere: posterior parietal cortex (PPC), premotor cortex, and primary motor cortex. Analysis of decreases of cortical connectivity with increasing task complexity showed that the interhemispheric M1 connectivity was significantly reduced during tasks sTdA and dTdA compared with sTsA and also for the comparison of task dTdA with sTdA (Fig. 3). This effect was more pronounced on the dominant left hemisphere but also detectable in right M1 (the effect size estimates for bilateral M1 regions are provided in Supplementary Fig. S2). This result shows that spatial and temporal uncoupling of finger movements also leads to bihemispheric M1 uncoupling.

Figure 3.

Regions showing a decrease in functional connectivity with the left primary motor cortex for comparison of spatially but not temporally uncoupled bimanual movements (a) or temporally and spatially uncoupled movements (b) with simple finger movements (which were spatially and temporally coupled). The connectivity between bihemispheric primary hand motor regions is higher for the coupled bimanual movements and decreases with spatial and temporal uncoupling. The comparison of left M1 connectivity changes of spatially but not temporally uncoupled bimanual movements with spatially and temporally uncoupled movements revealed that temporal uncoupling led to a decrease of bihemispheric M1 connectivity (c) and connectivity of left M1 with other regions on the right hemisphere, as well.

Figure 3.

Regions showing a decrease in functional connectivity with the left primary motor cortex for comparison of spatially but not temporally uncoupled bimanual movements (a) or temporally and spatially uncoupled movements (b) with simple finger movements (which were spatially and temporally coupled). The connectivity between bihemispheric primary hand motor regions is higher for the coupled bimanual movements and decreases with spatial and temporal uncoupling. The comparison of left M1 connectivity changes of spatially but not temporally uncoupled bimanual movements with spatially and temporally uncoupled movements revealed that temporal uncoupling led to a decrease of bihemispheric M1 connectivity (c) and connectivity of left M1 with other regions on the right hemisphere, as well.

For the analysis of increases of cortical connectivity with increasing task complexity, overall changes were more pronounced for all 3 right hemispheric regions compared with their left hemispheric counterparts (an overview on the results is given in Figs 4, S3 and in Table 3). For both tasks which required just spatial uncoupling of movements (sTdA) and spatial and temporal uncoupling of movements (dTdA), comparison with the simple sTsA task revealed a stronger connectivity of the right M1 and bilateral premotor cortex (PMC) with the anterior cingulate cortex (ACC) (for right M1 and PMC these contrasts were significant on the P < 0.05 corrected cluster level), and the bilateral DLPFCs. During the task dTdA, which required spatial and temporal uncoupling, the right PPC (and to a slightly lesser degree also left PPC) showed stronger functional connectivity with bilateral DLPFC compared with the sTsA task. Thus, the premotor and posterior parietal areas did not show bihemispheric uncoupling, but stronger functional connectivity within the ipsilateral and, in part also, the contralateral parieto–frontal network.

Table 3

Connectivity changes according to spatial and temporal uncoupling of bimanual movements

Region Brodmann area x y z Z-score Cluster size [voxel] 
Task sTdA versus sTsA 
    Right M1 connectivity 
        Bilateral anterior cingulate 32 10 48 −2 4.55 975 
        Right dorsolateral prefrontal 20 46 46 4.18 412 
        Left dorsolateral prefrontal −16 32 48 4.14 213 
        Left inferior frontal gyrus 11 −32 30 −24 3.68 24 
        Right PPC 39 54 −62 36 3.6 155 
        Left posterior cingulate 31 −10 −44 30 3.43 30 
    Right dorsal premotor cortex connectivity 
        Left medial frontal gyrus/ anterior cingulate 10 −8 56 −8 4.11 399 
        Right medial frontal cortex 34 58 3.66 67 
        Left dorsolateral prefrontal −38 24 38 4.29 96 
        Right dorsolateral prefrontal 44 26 38 3.51 43 
        Right ventrolateral prefontal 10 42 54 3.45 55 
        Right premotor 48 50 3.95 79 
        Left posterior parietal 40 −58 −52 46 3.94 23 
        Right posterior parietal 39 44 −74 36 3.74 120 
    Right PPC connectivity 
        Right medial frontal 12 34 52 3.39 60 
        Left dorsolateral prefrontal 10 −32 54 22 3.94 160 
    Right dorsolateral prefrontal 10 24 64 20 4.4 62 
54 28 34 3.49 56 
        Left premotor −36 50 4.49 320 
        Right premotor 50 10 54 3.92 90 
        Left inferior frontal gyrus 47 −34 36 −10 3.73 119 
        Right inferior frontal gyrus 45 56 34 3.91 85 
        Right middle temporal gyrus 37 54 −54 −12 4.23 164 
        Left temporoparietal junction 13 −46 −44 18 4.15 65 
        Left cingulate 24 −2 −16 40 3.7 88 
Task dTdA versus sTsA 
    Right M1 connectivity 
        Right medial frontal/ anterior cingulate 10 14 48 12 4.62 1795 
        Left dorsolateral prefrontal −16 34 48 4.06 142 
        Left premotor −14 18 62 3.53 24 
        Right temporoinsular junction 13 36 −16 10 4.73 147 
        Left temporoparietal junction 39 −50 −70 26 3.95 139 
        Right PPC 39 54 −62 34 4.11 167 
    Right dorsal premotor cortex connectivity       
        Left medial frontal gyrus/ anterior cingulate 10 −10 52 −4 4.65 425 
        Left dorsolateral prefrontal −14 46 44 3.91 63 
        Right premotor 34 50 4.37 129 
        Left superior temporal gyrus 38 −38 20 −24 3.86 45 
        Left posterior parietal 39 −52 −64 32 3.48 118 
        Right posterior parietal/operculum 13/40 −46 −20 16 3.86 53 
    Right PPC connectivity 
        Left medial frontal/ anterior cingulate 10 64 −4 3.6 133 
        Left dorsolateral prefrontal −28 26 38 3.83 44 
        Right dorsolateral prefrontal 38 24 38 4.11 434 
16 28 54 3.77 285 
        Left inferior frontal gyrus 7/ 40 -40 −72 44 3.43 31 
        Right posterior cingulate 31 16 −48 38 3.53 38 
        Left superior temporal cortex 41 −52 −36 12 3.61 56 
        Left precuneus −8 −52 44 3.47 46 
Region Brodmann area x y z Z-score Cluster size [voxel] 
Task sTdA versus sTsA 
    Right M1 connectivity 
        Bilateral anterior cingulate 32 10 48 −2 4.55 975 
        Right dorsolateral prefrontal 20 46 46 4.18 412 
        Left dorsolateral prefrontal −16 32 48 4.14 213 
        Left inferior frontal gyrus 11 −32 30 −24 3.68 24 
        Right PPC 39 54 −62 36 3.6 155 
        Left posterior cingulate 31 −10 −44 30 3.43 30 
    Right dorsal premotor cortex connectivity 
        Left medial frontal gyrus/ anterior cingulate 10 −8 56 −8 4.11 399 
        Right medial frontal cortex 34 58 3.66 67 
        Left dorsolateral prefrontal −38 24 38 4.29 96 
        Right dorsolateral prefrontal 44 26 38 3.51 43 
        Right ventrolateral prefontal 10 42 54 3.45 55 
        Right premotor 48 50 3.95 79 
        Left posterior parietal 40 −58 −52 46 3.94 23 
        Right posterior parietal 39 44 −74 36 3.74 120 
    Right PPC connectivity 
        Right medial frontal 12 34 52 3.39 60 
        Left dorsolateral prefrontal 10 −32 54 22 3.94 160 
    Right dorsolateral prefrontal 10 24 64 20 4.4 62 
54 28 34 3.49 56 
        Left premotor −36 50 4.49 320 
        Right premotor 50 10 54 3.92 90 
        Left inferior frontal gyrus 47 −34 36 −10 3.73 119 
        Right inferior frontal gyrus 45 56 34 3.91 85 
        Right middle temporal gyrus 37 54 −54 −12 4.23 164 
        Left temporoparietal junction 13 −46 −44 18 4.15 65 
        Left cingulate 24 −2 −16 40 3.7 88 
Task dTdA versus sTsA 
    Right M1 connectivity 
        Right medial frontal/ anterior cingulate 10 14 48 12 4.62 1795 
        Left dorsolateral prefrontal −16 34 48 4.06 142 
        Left premotor −14 18 62 3.53 24 
        Right temporoinsular junction 13 36 −16 10 4.73 147 
        Left temporoparietal junction 39 −50 −70 26 3.95 139 
        Right PPC 39 54 −62 34 4.11 167 
    Right dorsal premotor cortex connectivity       
        Left medial frontal gyrus/ anterior cingulate 10 −10 52 −4 4.65 425 
        Left dorsolateral prefrontal −14 46 44 3.91 63 
        Right premotor 34 50 4.37 129 
        Left superior temporal gyrus 38 −38 20 −24 3.86 45 
        Left posterior parietal 39 −52 −64 32 3.48 118 
        Right posterior parietal/operculum 13/40 −46 −20 16 3.86 53 
    Right PPC connectivity 
        Left medial frontal/ anterior cingulate 10 64 −4 3.6 133 
        Left dorsolateral prefrontal −28 26 38 3.83 44 
        Right dorsolateral prefrontal 38 24 38 4.11 434 
16 28 54 3.77 285 
        Left inferior frontal gyrus 7/ 40 -40 −72 44 3.43 31 
        Right posterior cingulate 31 16 −48 38 3.53 38 
        Left superior temporal cortex 41 −52 −36 12 3.61 56 
        Left precuneus −8 −52 44 3.47 46 

Note: Coordinates of the peak voxels for the PPI connectivity analysis for comparison of the tasks sTdA versus sTsA (above) and dTdA versus sTsA (below). The table shows peak voxel coordinates and size of clusters that showed an increase of connectivity with right primary motor cortex (M1), dorsal premotor cortex, and PPC during spatial uncoupling (task sTdA) and spatial plus temporal uncoupling (task dTdA) of bimanual finger movements compared with simple coupled finger movements (task sTsA).

Figure 4.

Regions showing an increase in functional connectivity during task sTdA, requiring spatial uncoupling and task dTdA, requiring spatial and temporal uncoupling of finger movements compared with control task sTsA (simple finger movements which were spatially and temporally coupled). Connectivity of right primary motor cortex, premotor, and posterior parietal regions with anterior cingulate and dorsolateral prefrontal regions increased during spatial and temporal uncoupling of finger movements.

Figure 4.

Regions showing an increase in functional connectivity during task sTdA, requiring spatial uncoupling and task dTdA, requiring spatial and temporal uncoupling of finger movements compared with control task sTsA (simple finger movements which were spatially and temporally coupled). Connectivity of right primary motor cortex, premotor, and posterior parietal regions with anterior cingulate and dorsolateral prefrontal regions increased during spatial and temporal uncoupling of finger movements.

Discussion

In the present study, we experimentally dissociated the effect of movement timing from the effect of movement amplitude on the brain activation patterns during the execution of bimanual movements. The dTdA condition required different movement timing and amplitudes of both index fingers (the small movement ended before the large one). The sTdA condition required similar movement timing but different movement amplitudes. The differences in movement amplitude were similar in both conditions to allow isolating the brain network specifically related to the control of the timing of uncoupled bimanual movements. We observed an increase of fMRI activation within bilateral inferior parietal regions, right premotor and dorsolateral prefrontal areas, bilateral putamen, cerebellum, and thalamus related to the control of movement timing; additionally, an increase of functional connectivity between the bilateral dorsal premotor area (PMd) and inferior PPC was found. In contrast, bihemispheric connectivity of primary motor cortex areas decreased with increasing task complexity. In the following section, we discuss the different contributions of the DLPFC, premotor, parietal, and primary motor cortices in the control of movement timing and in performance optimization of uncoupled bimanual movements.

Contributions of the Motor Areas in the Control of Uncoupled Bimanual Movements

The connectivity analysis of M1 regions showed that spatial and temporal uncoupling of bimanual index finger movements corresponded with a decrease in connectivity between bihemispheric M1 regions. These connectivity results demonstrate a covariation of bilateral M1 activation patterns. Prior electrophysiological studies have consistently shown a reciprocal functional modulation of bilateral M1 areas through the corpus callosum (Ferbert et al. 1992; Wahl et al. 2007). We assume that the connectivity results seen in the present study reflect reciprocal functional modulation between bilateral M1 regions and not only similar activation patterns due to the requirements of the experimental tasks used. Our results show that lesser coupling of bimanual finger movements is paralleled by lesser coupling of bilateral M1 regions. This result shows that temporal synchronization of bimanual movements is paralleled by coherence of M1 activity. This notion is in line with a recent report showing that spatial coordination of bimanual continuous movements is related to the interhemispheric synchronization of primary motor cortex activity (Maki et al. 2008). The bihemispheric M1 uncoupling in the present study was found both for the spatial and the temporal domain, as the comparison of solely spatially uncoupled with spatially and temporally uncoupled movements showed a further reduction of bihemispheric M1 connectivity. We speculate that the reciprocal influence of M1 regions that is essential for identical bilateral finger movements decreases when finger movements are less similar in the temporal or spatial domain and higher-order motor areas such as premotor cortex and especially parietal cortex become more important.

Whereas M1 did not show differential fMRI activation across tasks, the premotor cortex showed a higher fMRI activation during temporal uncoupling of bimanual movements. That is, the reduction of bihemispheric M1 connectivity was complemented by a stronger involvement of premotor planning regions (and in addition parietal, prefrontal, basal ganglia, and cerebellar areas) during task execution. The right PMd showed higher fMRI activation during the control of bimanual movements of temporal uncoupling than during the control of bimanual movement requiring temporal coupling. Patients with lesions of the PMd showed impaired production of rhythmic sequences (Halsband et al. 1993). The PMd is involved in the control of unimanual movement timing (Bengtsson et al. 2005). We suggest that the PMd could be involved in creating and updating such timing representations during movement execution.

The observed differences in brain activation comparing both tasks may have different causes. One possible explanation would be that the differential involvement of motor areas reflects a different overall extent of movements as defined by movement force, frequency, and amplitude across conditions. Indeed, movement force (Dettmers et al. 1995), movement amplitude (Waldvogel et al. 1999), and movement frequency (Schlaug et al. 1996) affect the degree of activation in motor areas. To exclude a relevant effect of movement amplitude on the cerebral activation patterns reported for sTdA and dTdA, the baseline condition with sTsA was employed either with large or with small bimanual movement amplitude during half of the trials each. Furthermore, behavioral results revealed no significant difference in motor output between dTdA and sTdA, both having the same movement amplitude differences. Taken together, it is unlikely that the observed differences in premotor areas when comparing sTdA and dTdA are related to the control of movement amplitude. However, a possible influence of unspecific task effort on the activation patterns cannot be completely ruled out, although we consider it likely that task effort does only account for a small proportion (if any) of the fMRI effects seen, as all tasks were performed correctly during the fMRI experiment.

Connectivity analyses revealed that both M1 and PMd showed an increase of coupling with the ACC during both dTdA and sTdA compared with sTsA. ACC is active during a large variety of cognitive tasks (Paus et al. 1998) and also has been described as a crucial part of the motor network that is active during manual movements (Fink et al. 1997; Hanakawa et al. 2008). It is related to cognitive control of actions (Cole and Schneider 2007) and plays a crucial role for generation of feedforward commands in the context of motor behavior (Grafton et al. 2008). There were no significant differences between the functional connectivity changes of ACC when we compared dTdA and sTdA. Therefore, the increase of coupling between ACC and M1 and PMd was not related to movement timing. ACC activation thus may reflect the higher demands regarding cognitive control and feedback integration during spatially and temporally uncoupled bimanual finger movements.

Role of the Parietal Cortex in the Control of Movement Timing

The parieto-premotor regions found to be involved in all tasks, with increasing activations and functional connectivity when tasks demands were higher, are well established components of a sensorimotor and visuomotor core network related to movements in space (Rizzolatti and Luppino 2001). The parietal regions play an important role within the cortical motor system, providing the integration of sensory information of different modalities into a single coordinate system, which serves as a reference frame for movement planning (Cohen and Andersen 2002). Accordingly, it has been shown that amplitude and movement direction interference in bimanual coordination (Wenderoth et al. 2005), bimanual out-of-phase cyclic finger movements (Debaere et al. 2004), and antiphase fingertapping Ullén et al. 2003) involves bilateral parietal regions. Parietal activity also has been demonstrated for the processing of sensory feedback (Grafton et al. 1992; Seitz and Roland 1992), and right inferior parietal regions are essentially involved in processing of simultaneity and temporal order (Battelli et al. 2007). However, there also is growing evidence that the parietal cortex is directly involved in the forming of intentions (Andersen and Buneo 2002; Fogassi et al. 2005). Thus, in the context of the bimanual movements investigated here, the parietal cortex may subserve 2 processes:

First, it may provide the spatial reference for the intricate motor planning processes required for both movement amplitude and movement timing. The execution of bimanual movements that are directionally incompatible requires a higher computational effort and involves the parietal cortex (Wenderoth et al. 2004). We show that this is also the case when bimanual movements have uncoupled timing. Thus, we suggest that the parietal cortex does not only provide a spatial reference frame but is also crucially involved in timing during movement planning.

The second process would be related to intentional maps described in parietal cortex. These maps are devoted to highly synchronized bimanual movement patterns that depend on a continuous interplay of leading and assisting hand (Johansson et al. 2006). This predisposition is challenged during the dTdA task that required the overcoming of the preferred synchronous movement plans.

The Role of DLPFC in Movement Timing of Uncoupled Bimanual Movements

The right DLPFC, which we found to be involved in the control of bimanual movements with temporal uncoupling, is known to play a crucial role for movement selection and action monitoring. Activation of right DLPFC in the present study may be related to the pattern of movement execution and also to task difficulty. During sTdA, short and large movement amplitudes were carried out synchronously and continuously with no apparent interruption or stumble during motor performance. However, during dTdA, subjects performed the initial phase of large and short amplitude movements with similar movement parameters (i.e., initiation of movements and acceleration pattern were almost identical). In order to accomplish the short movement amplitude, subjects were constrained to discontinue one of the hand movement that has the natural tendency to follow the movement of the other hand. This process may require inhibition of predominant movement patterns that involves DLPFC and anterior cingulate regions found to be active during task dTdA (de Zubicaray et al. 2000; Garavan et al. 2002; Nakata et al. 2008).

It has been shown that the interplay between the parieto-premotor network and the DLPFC is critical for automatic processes of left–right hand synchronization (Aramaki et al. 2006) and amplitude interference in bimanual movements (Wenderoth et al. 2005). Thus, the dTdA condition used in the present study represented a specific challenge to this parieto-premotor network that is virtually designed to establish bimanual synchrony. This notion is supported by stronger PPC-DLPFC connectivity during temporal and spatial uncoupling of bimanual movement than when the bimanual movements were coupled in space and time (contrast dTdA-sTsA). The contrast isolating the effect of temporal uncoupling (dTdA-sTdA), however, did not show significant connectivity changes in the PPC-DLPFC network. This indicates that the coupling between these regions is not strictly related to uncoupled bimanual movements with temporal uncoupling.

Cerebellar and Basal Ganglia Activation

In addition to the cortical activations discussed above, bilateral basal ganglia and cerebellar structures were found to show higher activation during the task requiring temporal uncoupling compared with both control tasks. The cerebellar and basal ganglia activation were not related to bimanual uncoupling per se but to timing processes because it was significantly higher during task dTdA than during sTdA. Both cerebellum and basal ganglia have been proposed to play a crucial role for implementation of precise timing of movements (Ivry and Spencer 2004; Bullock 2004; Meck et al. 2008), and it is highly plausible that these structures are part of the cortico-subcortical loops that represent the temporally uncoupled bimanual movements tested here. We speculate that the basal ganglia may be more involved in precise bimanual movement initiation, whereas the cerebellum is related to timing of the finger movement during task execution. Thus, both regions showed an increase of fMRI activity during the uncoupled finger movement timing task.

In conclusion, we show that both spatial and temporal uncoupling of bimanual movements lead to an uncoupling of the interhemispheric connectivity of the primary motor cortices. Furthermore, the results of the present study highlight the crucial role of dorsolateral prefrontal, premotor, and inferior parietal regions as well as basal ganglia and cerebellum for performance of temporally uncoupled bimanual finger movements. Inferior parietal and premotor regions play a key role for the implementation not only of spatial but also of temporal movement parameters in bimanual coordination; we suggest that the PPC does not only provide a spatial reference frame but is also crucially involved in timing during movement planning for bimanual movement coordination.

Supplementary Material

Supplementary material can be found at: http://www.cercor.oxfordjournals.org/.

Funding

“Rotationsprogramm” of the Medical Faculty of the University of Aachen to H.F.; Interdisziplinäres Zentrum für Klinische Forschung of the Medical Faculty of the University of Aachen and the Intramural Program of the National Institute of Neurological Disorders and Stroke, National Institutes of Health; Deutsche Forschungsgemeinschaft (German Research Organisation, grant ME 2104/3-1 to I.G.M.).

Conflict of Interest: None declared.

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