Neuropsychologia 58 (2014) 81–87
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Handedness consistency influences bimanual coordination: A behavioural and electrophysiological investigation Dimitrios Kourtis n, Lien De Saedeleer, Guy Vingerhoets Department of Experimental Psychology, Ghent University, Ghent, Belgium
art ic l e i nf o
a b s t r a c t
Article history: Received 31 October 2013 Received in revised form 10 March 2014 Accepted 4 April 2014 Available online 13 April 2014
Previous research has shown that handedness consistency might be a more important factor than direction of hand dominance in the performance of various cognitive and motor tasks. We investigated the effect of handedness consistency in bimanual coordination. We employed a task where participants had to respond to visual cues and perform symmetrical or asymmetrical bimanual movements towards cue-designated targets. Response and movement times were recorded in parallel with electroencephalography (EEG). Behavioural analyses showed that participants with inconsistent hand preference were equally fast in initiating symmetrical and asymmetrical bimanual movements, whereas participants with consistent hand preference were slower in initiating (the more demanding) asymmetrical movements. Moreover, the amplitudes of the Movement Related Potential and the suppression of the 10 Hz-mu rhythm were larger in participants with inconsistent hand preference over premotor and primary sensorimotor areas, although it is possible that the suppression of the mu rhythm may also depend on hand dominance. Our findings suggest that individuals with inconsistent hand preference have an advantage in the planning and organization of bimanual movements, which may not be related to the direction of their hand dominance. & 2014 Elsevier Ltd. All rights reserved.
Keywords: Bimanual movements Coordination Handedness Hand preference consistency Movement planning EEG
1. Introduction About 10 to 15% of the human population prefers using their left hand for the performance of skilled motor actions. Interestingly, this percentage has remained fairly constant across human history and it does not seem to depend on the culture or the industrialization of human societies (Llaurens, Raymond, & Faurie, 2009; McManus, 2009; Schaafsma et al., 2012). The persistence of such asymmetric polymorphism suggests that left-handedness is not a neutral trait, but actually provides certain advantages to the left-handed population. Such advantages of left-handers over right-handers have been documented in competitive interpersonal activities (Faurie & Raymond, 2013; Hagemann, 2009) and also in the performance of bimanual tasks, especially the ones that require visuomotor coordination (Gorynia & Egenter, 2000; Judge & Stirling, 2003). It has been argued that the dichotomy of the population in leftand right-handers is rather simplistic, as it does not take into account the number of people who are not consistent in their hand
n
Corresponding author. Tel.: þ 32 9 264 64 77. E-mail addresses: [email protected], [email protected] (D. Kourtis). http://dx.doi.org/10.1016/j.neuropsychologia.2014.04.002 0028-3932/& 2014 Elsevier Ltd. All rights reserved.
preference and often use their non-dominant hand for the performance of certain actions (Annett, 1967). People with inconsistent (or mixed) handedness are typically characterized by left hand dominance, but there is also a small percentage of the population who can be considered as inconsistent right-handers (McManus, Porac, Bryden, & Boucher, 1999; Searleman & Porac, 2003). This observation suggests that direction and consistency of handedness may be two different but somehow related dimensions of lateral preference. The classification of people according to handedness consistency is by no means trivial, since it has been shown that inconsistent handers often outperform consistent handers in (visuo)motor as well as in cognitive tasks (Gorynia & Egenter, 2000; Kopiez, Galley, & Lee, 2006; Lyle, Hanaver-Torrez, Hackländer, & Edlin, 2012; Peters & Servos, 1989; Propper & Christman, 2004; Prichard, Propper, & Christman, 2013). Furthermore, a small number of neurophysiological studies have reported different patterns of brain activity between inconsistent and consistent left-handers (Bernard, Taylor, & Seidler, 2011; Dassonville, Zhu, Uǧ urbil, Kim, & Ashe, 1997; Volkmann, Schnitzler, Witte, & Freund, 1998). The objective of the present study was to seek for behavioural and electrophysiological evidence for the potential advantage of inconsistent- over consistenthanders in the performance of a spatio-temporally coordinated bimanual task.
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It is rather surprising that, although the assessment of handedness typically includes actions performed with both hands (e.g. the Edinburgh Handedness Inventory, Oldfield, 1971), only a handful of behavioural studies investigated the effect of handedness consistency in bimanual coordination (Gorynia & Egenter, 2000; Kopiez et al., 2006; Peters & Servos, 1989). These studies have shown that handedness consistency may be disadvantageous in certain tasks that require fast intermanual coordination (e.g. bimanual finger tapping). Notably, these studies have only investigated the effect of handedness consistency in participants with left hand dominance. In the present study, we recruited left- as well as right-handed participants in order to investigate the effect of handedness consistency on the performance of a bimanual visuomotor task. The participants were instructed to make fast visually-cued bimanual movements, initiated simultaneously and terminated on two target-buttons located at various distances from the starting locations. The movements were either symmetrical (i.e. each hand had to travel the same distance) or asymmetrical. Our hypothesis was that participants with inconsistent hand preference will outperform participants with consistent hand preference and that the difference in performance will possible be larger in the more demanding asymmetrical condition. To further support our hypothesis, we recorded EEG in order to investigate the neural mechanisms that operate during the performance of a bimanual task. Our analyses were focused on two indices of (pre)motor activation, the Movement Related Potential (MRP) and the suppression of the 10 Hz mu rhythm. The MRP is a slow rising negativity, which develops progressively during the planning of self-generated or externally-cued movements and peaks at approximately movement onset (Deecke, Scheid, & Kornhuber, 1969; Jankelowitz & Colebatch, 2002; Kristeva, Cheyne, Lang, Lindinger, & Deecke, 1990). The MRP is typically stronger over the vertex and during its late stages it is believed to originate from primary sensorimotor cortices as well as the Supplementary Motor Area (SMA), a brain area associated with movement planning and coordination (Ikeda et al., 1995; Urbano et al., 1998). The suppression of the 10-Hz mu rhythm refers to the amplitude decrease of the EEG signal within the frequency range of 7–13 Hz, which is observed prior and during the execution of a movement and is considered an index of activation of primary sensorimotor areas as well as of the SMA (Arroyo et al., 1993; Pfurtscheller, Neuper, Andrew, & Edlinger, 1997; Pineda, 2005). The 10-Hz mu suppression and the MRP can be considered as two complementary indices of cortical activation; the former reflects a rather general decrease of the background sensorimotor oscillations, whereas the latter represents a more task-specific increase in post-synaptic potentials in the underlying brain areas (Babiloni et al., 1999; Filipović, Jahanshahi, & Rothwell, 2001; Pfurtscheller & Lopes da Silva, 1999). With regards to our experiment, we expected that participants with inconsistent hand preference would be better in planning and coordinating bimanual action, thus engaging primary sensorimotor areas and the SMA to a greater extent compared to participants with consistent hand preference. Thus, we expected to record larger MRP amplitude and greater mu suppression before and during movement execution in participants with inconsistent hand preference.
2. Methods 2.1. Participants 28 healthy volunteers with normal or corrected-to-normal vision took part in the experiment. They had no history of hand or arm injuries or diseases or any mental, cognitive, and other neurological disorder. All participants provided their informed consent after full explanation of the study.
Fig. 1. Response box and task. Schematic drawing of the response box with two hands placed on the home keys (i.e. starting position). The green and black circles on the box represent the LEDs and the buttons respectively. The length of the box (distance from (A) to (E)), the diameter of the buttons (distance from (B) to (C)), the distance from of the home keys from the edges of the box (A) to (B) and the diameter of the target buttons (distance from (B) to (C)) are displayed under the box. The participant had to respond to the illumination of two LEDs and press the target buttons that were located directly under the LEDs. The possible (symmetrical and asymmetrical) movement combinations are illustrated at the top of the figure. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) Two participants were excluded from the analysis: one due to extremely slow responses and another one due to malfunction of the EEG equipment. The remaining 26 participants were categorized according to the degree and the direction of handedness, based on the Edinburgh Handedness Inventory (Oldfield, 1971). Lateralization indices (LI) ranged from 100 for pure lefthanders to þ 100 for pure right-handers1. The median value of the absolute lateralization indices was 80, which is consistent with the median score of the large population sample studied by Prichard et al. (2013). Participants with absolute lateralization index Z 80 were categorized as consistent handers (CH) and participants with absolute lateralization index o80 were categorized as inconsistent handers (ICH). 13 participants were categorized as consistent handers [LI¼ 96.8 (SD¼ 7.9), 11 females and 2 males, 10 right-handers and 3 left-handers, age¼ 22.5 yr (SD¼ 2.3)] and 13 participants were categorized as inconsistent handers [LI¼ 47.6 (SD ¼ 48.4), 10 females and 3 males, 3 right-handers and 10 left-handers, age¼ 23.2 yr (SD¼ 4.3)].
2.2. Experimental setup The experiment was run in a quiet, normally illuminated room. The experimental setup and task were similar to those used by Kelso, Southard, and Goodman (1979). The participants were seated comfortably on a chair with their arms resting on a table. A custom-made response box (80.35 cm 10.5 cm 5 cm, see Fig. 1) was placed on the table in front of the participants. Two release/home keys (diameter: 1 cm) were positioned at 3 cm from the left and the right edge of the box, and 8 press/target keys (diameter: 1 cm) were positioned at equidistant (7.15 cm) locations between the release buttons. A green Light Emitting Diode (LED) was placed 2 cm above each of the response buttons. The response box was divided in two halves by a 2 cm strip wide of black duct tape.
2.3. Task The participants had to place their index fingers on each of the release buttons (i.e. home keys). The illumination of two LEDs (one at each hemispace) instructed the participants to swiftly and simultaneously release both home keys and press the target keys located directly under the illuminated LEDs. The movements were either symmetrical (i.e. each hand had to travel the same distance) or asymmetrical. Although there were 12 possible combinations for asymmetrical movements, we included only 4 of them in our experiment (Fig. 1) in order to have an equal number (i.e. 4) of symmetrical and asymmetrical bimanual movements. In addition, the average distance that each hand had to travel in the asymmetrical movements was equal to the average distance in the symmetrical movements.
1 The Lateralization index was 57.7 (SD ¼ 8.2) for left-handed participants and 85.7 (SD ¼7.0) for right-handed participants.
D. Kourtis et al. / Neuropsychologia 58 (2014) 81–87 The experiment consisted of 12 blocks of 32 randomized trials each, preceded by a practice block of equal length, which resulted in 192 trials per condition (i.e. symmetrical and asymmetrical movements). Each condition occurred with equal probability within each block. The duration of the intertrial interval was randomized between 3050 and 3950 ms. 2.4. Data acquisition and processing EEG was recorded continuously with Ag/AgCl electrodes from 64 scalp electrodes relative to an (off-line) average mastoid reference. The electrodes were placed according to the 10–10 extension of the International 10–20 electrode system (American Electroencephalographic Society, 1994; Chatrian, Lettich, & Nelson, 1985) using a carefully positioned nylon cap. Vertical and horizontal eye movements were monitored using two pairs of electro-oculography (EOG) electrodes positioned below the eyes and lateral to the left and the right eye. EEG and EOG signals were amplified with a band-pass of 0–128 Hz by a BioSemi Active-Two Amplifier (BioSemi B.V., Amsterdam, Netherlands) and sampled at 512 Hz. 2.4.1. Behavioural data Behavioural data were registered by BrainVision Recorder Software. We focussed our analysis on two epochs: response time (RT) and movement time (MT). The RT was defined as the time interval from the LEDs onset until the release of a home-key. The MT was defined as the time interval from the release of a home key until the press of a target key. Trials where the participants did not respond and trials where they were too fast or too slow to release the target keys (i.e. the difference with the mean RT for each LED combination was larger than 2 standard deviations) were removed from subsequent analysis. In addition, trials where the participants failed to press the correct target key and trials containing too slow or too fast movement times (i.e. the difference with the mean MT for each LED combination was larger than 2 standard deviations) were also removed from subsequent analysis. The total percentage of errors was 12.2% (SD¼ 2.4) and 13.3% (SD ¼3.9) for symmetrical and asymmetrical movements respectively. 2.4.2. EEG data EEG data processing was performed using the BrainVision Analyzer software (V.1.05, Brain Products GmbH, Gilching, Germany). Initially, the data were converted from.bdf to BrainVision Analyzer compatible.cnt format using the PolyRex V.1.2 software (Kayser, 2003). Subsequently, the data were referenced to the average mastoid reference and then they were filtered with a low cut-off filter of 0.05 Hz (24 dB/octave) and a high cut-off filter of 40 Hz (24 dB/octave) in order to remove slow drifts and excessive noise, respectively. Ocular correction was performed using the Gratton–Coles algorithm (Gratton, Coles, & Donchin, 1983). The corrected EEG data were segmented off-line into epochs from 500 ms before LEDs onset to 1700 ms after LED onset. In addition to the trials that have been removed because they did not meet our behavioural criteria, individual trials containing remaining eye movement or other EEG-related artefacts were also removed before averaging. Averages were constructed separately for each condition and each participant. The baseline was defined as the time period from 200 ms before until the LEDs onset. The release-MRP and the press-MRP amplitudes were quantified by pooling the mean activity from neighbouring electrodes on the basis of grand average topographies during the relevant time intervals (see Section 3). Time–frequency analysis was performed by means of a continuous complex Morlet waveform transformation as implemented in the BrainVision Analyzer software. Absolute values of wavelets coefficients were calculated in the frequency range of 6–30 Hz with 20 frequency steps, and Morlet parameter of c ¼4. After averaging, we extracted the frequency layer from 6.39 to 10.66 Hz (central frequency¼ 8.53 Hz) for subsequent analysis, similar to the ERPs.
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respectively, whereas MTs were 483 ms (SD¼63) and 510 ms (SD¼64) for symmetrical and asymmetrical movements respectively (Fig. 2). Statistical comparisons were made using a 2 2 2 mixed ANOVA, with the between-subjects factor Consistency (CHs vs. ICHs) and two within-subjects factors: Epoch (Response vs. movement times) and Symmetry (symmetrical vs. asymmetrical movements). The analysis revealed a significant effect of Epoch [F (1,24) ¼ 35.7, po .001], because MTs were significantly longer that RTs and a main effect of Symmetry [F(1,24) ¼82.1, p o.001], because participants needed more time to perform asymmetrical movements. In addition, we found a significant 2-way interaction between Epoch and Symmetry [F(1,24)¼17.7, p o.001], because the difference in MTs between symmetrical and asymmetrical action was significantly larger than the difference in RTs [t(25) ¼ 3.8, p ¼.001]. No other main or two-way interaction effects reached statistical significance. The three-way interaction between consistency, Epoch and Symmetry was also statistically significant [F(1,24) ¼6.9, p¼ .015]. In order to identify the source of this interaction, we examined RTs and MTs separately. A mixed 2 2 ANOVA on RTs (Fig. 2, top) with consistency as between-subject factor and Symmetry as withinsubject factor showed a significant main effect of symmetry [F (1,24) ¼ 6.7, p¼ .016] and also a significant interaction [F(1,24) ¼ 4.7, p¼ .041], because CH participants were significantly slower in initiating asymmetrical compared to symmetrical movements [t(25) ¼3.0, p ¼.011], whereas ICH participants were equally fast in either condition (p ¼.73). There was no main effect of consistency (p ¼.95).
3. Results 3.1. Behavioural analyses 3.1.1. Response and movement times Similar to Kelso et al. (1979), we found no difference in RTs or MTs between the dominant and the non-dominant hand (ps 4.57), thus all subsequent behavioural analyses were performed on the average response and movements times of the two hands. For Consistent Handers (CHs), RTs were 360 ms (SD¼ 46) and 373 ms (SD¼45) for symmetrical and asymmetrical movements respectively, whereas MTs were 424 ms (SD¼96) and 443 ms (SD¼ 89) for symmetrical and asymmetrical movements respectively. For Inconsistent Handers (IHs), RTs were 367 ms (SD¼31) and 368 ms (SD¼ 23) for symmetrical and asymmetrical movements
Fig. 2. Behavioural data. Response times (top) and movement times (bottom) from participants with consistent (CH) and inconsistent hand preference (ICH) in the performance of symmetrical (Sym) and Asymmetrical (Asym) bimanual movements. Error bars represent standard error of mean. The symbol “n” indicates statistically significant differences, whereas “n.s.” indicates non-significant differences.
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On the other hand, a mixed 2 2 ANOVA on MTs (Fig. 2, bottom) with consistency as between-subject factor and Symmetry as within-subject factor showed a significant main effect of symmetry with asymmetrical movements being slower [F(1,24)¼ 113.3, po .001], but no interaction [F(1,24)¼2.9, p¼ .10]. Interestingly, CH participants were faster than ICH participants, although this difference failed to reach statistical significance [F(1,24)¼ 4.1, p ¼0.054]. In addition to this analysis, we divided our participants into two different groups based on their hand dominance, which resulted in 13 left-handers (3 CHs þ10 ICHs) and 13 righthanders (10 CHs þ3 ICHs) and performed the same analysis, but with hand dominance as the between-subject factor. The results showed no significant main effect of hand dominance nor a significant interaction that involved hand dominance (ps 4.2). This suggests that the factor that dissociated our participants’ behavioural performance was not hand dominance, but handedness consistency instead. 3.1.2. Errors In order to investigate the effect of handedness consistency on performance accuracy, we performed statistical comparisons on the errors that the participants made in initiating and performing the movements. Consistent Handers (CHs) made response-related errors in 2.0% (SD ¼1.5) and 3.2% (SD ¼1.8) of symmetrical and asymmetrical movements respectively, and movement-related errors in 10.4% (SD ¼2.2) and 10.7% (SD ¼3.3) for symmetrical and asymmetrical movements respectively. Inconsistent Handers (ICHs) made response-related errors in 2.5% (SD ¼ 1.4) and 3.2% (SD ¼1.1) of symmetrical and asymmetrical movements respectively, and movement-related errors in 9.6% (SD ¼2.5) and 9.4% (SD ¼2.9) for symmetrical and asymmetrical movements respectively. Statistical analyses similar to the ones performed for RTs and MTs showed that participants made more movement-related errors than response related errors [F(1,24)¼217.3, p o.001]. There were no other significant effects or interactions (ps 4 .1), thus handedness consistency had no significant influence on the accuracy of the participants’ performance. As with the RT/MT data, we performed the same analysis replacing the between-subject factor with hand dominance. The effect of hand dominance and its interaction with the other factors did not reach statistical significance (ps 4.05), which suggests that hand dominance had no significant influence on the accuracy of the participants’ performance. 3.2. EEG analyses 3.2.1. Movement related potential (MRP) The ERP analysis revealed a slow-rising negativity over midpremotor areas, which peaked approximately at the time of the release of the home keys (Fig. 3, top). This negativity was present in all experimental conditions and corresponds to the MRP (from now release-MRP). The release-MRP was followed by a positive deflection, probably associated with reafferent sensory input, which in turns was followed by another slow-rising negativity, which corresponded to the MRP associated with the press of the target keys (from now, press-MRP). The MRP amplitude was quantified by pooling the mean activity from electrodes FCz, Cz, CPz, C1 and C2 from 380 to 480 ms after LED onset (i.e. release-MRP) and from 650 to 750 ms after LEDs onset (i.e. press-MRP). These electrodes are located over mid-(pre)motor areas, that are typically associated with the MRP, and over which the difference between ICHs and CHs was larger (see Fig. 3, scalp topography of ICHs vs. CHs). Statistical comparisons were made using a 2 2 2 mixed ANOVA, with the
Fig. 3. ERP waveforms and scalp topographies. MRPs were larger in participants with inconsistent hand preference (ICHs) over participants with consistent hand preference (CHs). Also, MRP during asymmetrical movements (Asym) were larger than MRPs during symmetrical movements (Sym). The grey rectangles represent the time intervals of interest. (Bottom)—Scalp topographies (flat view) of the release-MRP and press-MRP for ICH and CH participants and the difference between the two groups. The electrodes from which the activity was included in the statistical analysis are represented as grey circles on the topography of the difference (ICHs vs. CHs).
between-subjects factor consistency (CHs vs. ICHs) and two within-subjects factors: Action (Release vs. Press) and Symmetry (symmetrical vs. asymmetrical movements). The analysis revealed a significant effect of Action [F(1,24) ¼36.9, p o.001], because the press-MRP was significantly larger that the release-MRP and a main effect of Symmetry [F(1,24)¼18.4, p ¼.001], because the MRP was significantly larger when the participants performed asymmetrical movements. Most importantly, there was a significant main effect of handedness consistency [F(1,24)¼4.4, p ¼.046], as the MRP was significantly larger in participants with inconsistent hand preference. No other main or interaction effects reached statistical significance (ps 4.5). Relevant to the main objective of our study, the absence of a significant consistency action interaction shows that the effect of handedness consistency on the MRP amplitude was equally large in the selected intervals of analysis. As with the behavioural data, we performed the same analysis replacing the between-subject factor with hand dominance. Similar to the response and movement times, the effect of hand dominance and its interaction with the other factors did not reach statistical significance (ps 4.1). This again suggests that the factor that dissociated the MRP amplitude in our participants was not hand dominance, but handedness consistency instead.
3.2.2. Time—Frequency analysis: The 10-Hz mu rhythm The time–frequency analysis showed that there was a larger suppression of the (lower) 10-Hz mu rhythm over mid-sensorimotor areas for ICH-participants compared to CH-participants soon after LEDs onset. The mu amplitude decrease was quantified by pooling the mean activity from electrodes Cz, C1, C2, CPz, CP1 and CP2, in the time interval from 120 to 420 ms after LEDs onset. These electrodes are located over mid sensorimotor areas, that are typically associated with
D. Kourtis et al. / Neuropsychologia 58 (2014) 81–87
Fig. 4. Time–frequency plot and scalp topography. Time–frequency plot (electrode Cz) of the difference between participants with inconsistent handedness and participants with consistent handedness. The difference was more prominent in the (lower) alpha/mu band over mid-sensorimotor areas. The dotted rectangle represents the time interval of interest and the selected frequency range. The electrodes from which the activity was included in the statistical analysis are represented as grey circles on the topography of the difference.
the mu-rhythm suppression and over which the difference between ICHs and CHs was larger (Fig. 4, scalp topography). Statistical comparisons were made using a 2 2 mixed ANOVA, with the betweensubjects factor Consistency (CHs vs. ICHs) and the within-subjects factor Symmetry (symmetrical vs. asymmetrical movements). The analysis revealed a significant effect of Consistency [F(1,24)¼5.2, p¼ .032], because mu suppression was larger in participants with inconsistent hand preference. The effect of Symmetry and the consistency–symmetry interaction was not significant (ps4.4). As with the behavioural and the ERP data, we performed the same analysis replacing the between-subject factor with hand dominance. Contrary to the previous analyses, there was a significant main effect of hand dominance because the musuppression was larger in left-handers [F(1,24) ¼12.1, p¼ .002]. The effect of Symmetry and the Dominance-Symmetry interaction was not significant (ps 4.4).
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hands have to travel unequal distances (for reviews in bimanual control, Cardoso de Oliveira, 2004; Swinnen & Wenderoth, 2004). However, this was not the case for participants with inconsistent hand preference, who did not seem to be affected by increased coordination demands, and were equally fast in initiating symmetrical and asymmetrical movements. Importantly, there were no differences in behavioural performance when the participants were categorized as left- or right-handers, which suggests that the direction of hand dominance may not always be of relevance in bimanual coordination. Previous studies reported that the performance of ICH lefthanders was often (although not always) superior to CH lefthanders in various unimanual and bimanual tasks (Gorynia & Egenter, 2000; Kopiez et al., 2006; Peters & Servos, 1989). Notably, inconsistent right-handers have not been systematically studied, possibly due to their relatively small numbers. However, the presence of handedness inconsistency in right-handers is well documented and it has been related to a more optimal performance of tasks such as unimanual pointing (Bishop, Ross, Daniels, & Bright, 1996), production of rapid movement sequences (Ponton, 1987) and intermanual coordination (Annett, 1976), although these studies have not explicitly studied groups of inconsistent right-handers. Such findings are in agreement with the results of the present study. It should be noted that the advantage of ICHs was only present in the response times, which suggests that ICHs may be better in planning and initiating a bimanual movement. However, ICHs and CHs were equally accurate in initiating and performing symmetrical as well as asymmetrical movements, and in fact CHs were marginally faster than ICHs in movement execution. Previous studies have shown that CHs do not always perform worse than ICHs (e.g. Peters & Servos, 1989). The task we employed required the coordination of the two hands, but it was very simple in terms of execution (i.e. button pressing). It is possible that differences between ICHs and CHs arise mainly in tasks the execution of which requires complex motor skills. This could conceivably be the reason for the lack of significant difference in movement times between the two groups; however, the fact that CHs were marginally faster implies that the relationship between handedness consistency and bimanual coordination is a topic that requires further investigation. 4.2. Electrophysiological correlates of bimanual control
4. Discussion We investigated the effect of handedness consistency on the performance of coordinated symmetrical and asymmetrical bimanual movements. Our results showed that, contrary to participants with consistent hand preference (CHs), participants with inconsistent hand preference (ICHs) were not affected by the increased coordination demands of asymmetrical bimanual movements. In addition, our EEG analyses showed that ICHs were characterized by increased activation over sensorimotor areas that are typically associated with planning and execution of bimanual movements. However, we need to acknowledge that the EEG findings (i.e. main effect of handedness consistency) are not in alignment with the behavioural findings (i.e. consistency–symmetry interaction); therefore, no correlation or causal relationship can be established by the present study. 4.1. Behavioural performance Participants with consistent hand preference were slower in initiating an asymmetrical movement compared to a symmetrical one. This finding was expected on the basis that humans have a natural tendency to synchronize the motor output of their upper limbs, so bimanual coordination is more demanding when the two
The ERP analysis showed that the Movement Related Potential (MRP) was larger in participants with inconsistent hand preference. The difference was more prominent around response time and remained significant (although gradually fading) throughout movement execution (Fig. 3). The MRP is a slow rising negativity that peaks around (unimanual, bimanual, or imaginary, Jankelowitz & Colebatch, 2002) movement onset and it is regarded as an index of movement preparation and organization (Ikeda et al., 1995; Kutas & Donchin, 1980). Accordingly, in our experiment, the larger MRP in ICHs could be considered as an indication of the superior ability of ICHs in planning and organizing a bimanual movement. In addition, there was no difference in MRP amplitude when the participants were divided into left- and right-handers, which may be taken as additional evidence that the direction of hand dominance may not be the most important factor in bimanual control. In addition to the ERPs, the time–frequency analysis showed that the suppression of the sensorimotor 10-Hz mu rhythm was larger in ICHs compared to CHs in a time window that corresponded with the planning and initiation of a bimanual movement. Considering that mu-suppression is a reliable index of sensorimotor activation (Hari, 2006; Pfurtscheller et al., 1997; Pineda, 2005), this finding seems to be consistent with the ERP analysis. However, contrary to the previous analysis we found that
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when we divided the participants according to their hand dominance, the mu-suppression was significantly larger in left-handed participants. This discrepancy is not entirely surprising when we consider that ERPs and frequency-specific changes in EEG oscillatory activity represent different brain phenomena. ERPs result from the summation of transient post-synaptic potentials, whereas the increase/suppression of neuronal oscillations represents changes in the temporal dynamics of functionally-related network of neurons (Pfurtscheller & Lopes da Silva, 1999; Salinas & Sejnowski, 2001). Previous research suggests that the suppression of 10-Hz sensorimotor oscillations and slow-rising movementrelated ERPs represent different brain processes, the former a more general state of sensorimotor alerting/readiness, whereas the latter task-specific responses of sensorimotor areas (Babiloni et al., 1999; Deiber, Ibañez, Caldara, Andrey, & Hauert, 2005; Filipović et al., 2001). This seems to be particularly the case for the suppression of the lower ( o10 Hz) mu rhythm (Pfurtscheller, Neuper, & Krausz, 2000), which was the frequency band where we recorded the larger difference in the amplitude of mu suppression (Fig. 4). Moreover and contrary to the MRPs, the amplitude of the mu suppression did not differ between asymmetrical and symmetrical movements, which also suggest that the mu suppression was not related to the specific coordination demands of our task. Taken together, our EEG analyses cannot tell us whether the state of readiness of the sensorimotor system prior to bimanual movements depends more on the actor's hand dominance or on handedness consistency (or to both). On the other hand, the planning and organization of a specific bimanual movement seems to depend mostly on the actor's handedness consistency. The topographies of the contrasts between ICHs and CHs both with regards to the MRP and to the mu-suppression were focal over mid sensorimotor areas (Figs. 3 and 4). We need to point out at this point that EEG records electrical activity at the surface of the head, so any claims regarding the brain areas that might be involved on a given task should be treated with great caution. Keeping this in mind, we should note that a large number of EEG and intracortical studies have consistently associated the MRP and the mu-rhythm with activation in the SMA and primary sensorimotor areas (Donchin, Gribova, Steinber, Bergman, & Vaadia, 1998; Donchin et al., 2002; Ikeda, Lüders, Burgess, & Shibasaki, 1992, Ikeda et al., 1995; Pfurtscheller et al., 1997), which are considered to be pivotal in the organization and the execution of bimanual movements (Jäncke et al., 2000; Serrien, Strens, Oliviero, & Brown, 2002; Toyokura, Muro, Komiya, & Obara, 1999; Walsh, Small, Chen, & Solodkin, 2008). Although precise localization is beyond the scope and the capabilities of the present study, activation of the SMA and primary sensorimotor areas is consistent with the MRP and the mu-suppression topographies as well as with the nature of our task. This implies that the ability of people with inconsistent hand preference in planning and initiating a bimanual action may be related to the stronger activation of these areas. 4.3. Limitations A limitation of the present study is that there is a certain misbalancing of the population sample. Due to the scarcity of people with inconsistent handedness in the general population, the group of consistent handers comprised of 10 right-handers and 3 left-handers, whereas the group of inconsistent handers comprised of 3 right-handers and 10 left-handers. Although we did find significant differences between ICHs and CHs in terms of RTs and MRP amplitudes, the inconclusiveness of the results regarding MTs and mu-suppression, along with the relatively small population sample, suggests that equal and larger numbers of participants per sub-group are needed in order to fully
understand the importance of handedness consistency and of hand dominance in the planning and execution of bimanual movements. In addition, an overall larger population sample would presumably provide us with the opportunity to examine whether behavioural and EEG measures can be parametrically correlated to the degree of handedness (see, Annett, 1976). Another possible limitation regarding our population sample is that the majority of the participants were females. Previous studies suggest the existence of gender differences in the cortical organization of hand movements (Amunts, Jäncke, Mohlberg, Steinmetz, & Zilles, 2000) and more importantly in bimanual control (Mickevičienė et al., 2011; Smolders, Rijpkema, Franke, & Fernàdez, 2012), however not in relation to handedness consistency. Thus, although we cannot derive specific predictions from the literature regarding a possible interaction between gender and handedness consistency in bimanual control, we cannot exclude the possibility that the inclusion of additional male participants would have an effect on our results. Another limitation of the present study was that our analyses did not show any evidence of correlation between behavioural and EEG data. However, although a correlation between EEG and behavioural measures seems plausible in motor tasks, it is not that common in EEG research. Regarding our experiment, there are a number of possible reasons that may account for the lack of correlation, such as different sources of noise for behavioural data (e.g. biomechanical constraints) and EEG data (e.g. random fluctuations of the signal), relatively small number of participants, different optional number of trials for each measurement (i.e. reliable EEG signals are obtained after a large number of trials, but this inevitably leads to a certain degree of fatigue and boredom) etc. Finally, another possible limitation that we already mentioned earlier was that the successful performance of the selected task only depended on intermanual coordination, but it did not require any other motor skill such as manual dexterity, strength etc. Further studies using a variety of tasks assessing different motor skills could shed more light on the (dis)advantages of handedness consistency in motor control.
5. Conclusion The present study provides evidence that handedness (in) consistency has an effect on the performance of bimanual movements, which to an extent seems to be independent of hand dominance. Our results show that the increased coordination demands of an asymmetrical bimanual movement do not seem to affect individuals with inconsistent hand preference, whereas they delay movement initiation by individuals with consistent hand preference. Furthermore, handedness inconsistency is associated with enhanced brain activity, which is believed to reflect an increased ability in the planning and organization of bimanual movements. In addition, handedness inconsistency seems also to be associated with a higher state of readiness of the sensorimotor system prior to a movement, although this effect may well be attributed to left hand dominance. It should be noted though that the electrophysiological findings cannot be causally linked to the behavioural findings; instead they should be considered as two unconnected sources of evidence regarding the influence of handedness (in)consistency on the coordination of bimanual movements. To our knowledge this is the first study that provides behavioural as well as electrophysiological evidence for the importance of handedness (in)consistency in bimanual control; however, more work is needed in order to elucidate its precise role and its relationship with hand dominance.
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Contents lists available at ScienceDirect
Neuropsychologia journal homepage: www.elsevier.com/locate/neuropsychologia
Handedness consistency influences bimanual coordination: A behavioural and electrophysiological investigation Dimitrios Kourtis n, Lien De Saedeleer, Guy Vingerhoets Department of Experimental Psychology, Ghent University, Ghent, Belgium
art ic l e i nf o
a b s t r a c t
Article history: Received 31 October 2013 Received in revised form 10 March 2014 Accepted 4 April 2014 Available online 13 April 2014
Previous research has shown that handedness consistency might be a more important factor than direction of hand dominance in the performance of various cognitive and motor tasks. We investigated the effect of handedness consistency in bimanual coordination. We employed a task where participants had to respond to visual cues and perform symmetrical or asymmetrical bimanual movements towards cue-designated targets. Response and movement times were recorded in parallel with electroencephalography (EEG). Behavioural analyses showed that participants with inconsistent hand preference were equally fast in initiating symmetrical and asymmetrical bimanual movements, whereas participants with consistent hand preference were slower in initiating (the more demanding) asymmetrical movements. Moreover, the amplitudes of the Movement Related Potential and the suppression of the 10 Hz-mu rhythm were larger in participants with inconsistent hand preference over premotor and primary sensorimotor areas, although it is possible that the suppression of the mu rhythm may also depend on hand dominance. Our findings suggest that individuals with inconsistent hand preference have an advantage in the planning and organization of bimanual movements, which may not be related to the direction of their hand dominance. & 2014 Elsevier Ltd. All rights reserved.
Keywords: Bimanual movements Coordination Handedness Hand preference consistency Movement planning EEG
1. Introduction About 10 to 15% of the human population prefers using their left hand for the performance of skilled motor actions. Interestingly, this percentage has remained fairly constant across human history and it does not seem to depend on the culture or the industrialization of human societies (Llaurens, Raymond, & Faurie, 2009; McManus, 2009; Schaafsma et al., 2012). The persistence of such asymmetric polymorphism suggests that left-handedness is not a neutral trait, but actually provides certain advantages to the left-handed population. Such advantages of left-handers over right-handers have been documented in competitive interpersonal activities (Faurie & Raymond, 2013; Hagemann, 2009) and also in the performance of bimanual tasks, especially the ones that require visuomotor coordination (Gorynia & Egenter, 2000; Judge & Stirling, 2003). It has been argued that the dichotomy of the population in leftand right-handers is rather simplistic, as it does not take into account the number of people who are not consistent in their hand
n
Corresponding author. Tel.: þ 32 9 264 64 77. E-mail addresses: [email protected], [email protected] (D. Kourtis). http://dx.doi.org/10.1016/j.neuropsychologia.2014.04.002 0028-3932/& 2014 Elsevier Ltd. All rights reserved.
preference and often use their non-dominant hand for the performance of certain actions (Annett, 1967). People with inconsistent (or mixed) handedness are typically characterized by left hand dominance, but there is also a small percentage of the population who can be considered as inconsistent right-handers (McManus, Porac, Bryden, & Boucher, 1999; Searleman & Porac, 2003). This observation suggests that direction and consistency of handedness may be two different but somehow related dimensions of lateral preference. The classification of people according to handedness consistency is by no means trivial, since it has been shown that inconsistent handers often outperform consistent handers in (visuo)motor as well as in cognitive tasks (Gorynia & Egenter, 2000; Kopiez, Galley, & Lee, 2006; Lyle, Hanaver-Torrez, Hackländer, & Edlin, 2012; Peters & Servos, 1989; Propper & Christman, 2004; Prichard, Propper, & Christman, 2013). Furthermore, a small number of neurophysiological studies have reported different patterns of brain activity between inconsistent and consistent left-handers (Bernard, Taylor, & Seidler, 2011; Dassonville, Zhu, Uǧ urbil, Kim, & Ashe, 1997; Volkmann, Schnitzler, Witte, & Freund, 1998). The objective of the present study was to seek for behavioural and electrophysiological evidence for the potential advantage of inconsistent- over consistenthanders in the performance of a spatio-temporally coordinated bimanual task.
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It is rather surprising that, although the assessment of handedness typically includes actions performed with both hands (e.g. the Edinburgh Handedness Inventory, Oldfield, 1971), only a handful of behavioural studies investigated the effect of handedness consistency in bimanual coordination (Gorynia & Egenter, 2000; Kopiez et al., 2006; Peters & Servos, 1989). These studies have shown that handedness consistency may be disadvantageous in certain tasks that require fast intermanual coordination (e.g. bimanual finger tapping). Notably, these studies have only investigated the effect of handedness consistency in participants with left hand dominance. In the present study, we recruited left- as well as right-handed participants in order to investigate the effect of handedness consistency on the performance of a bimanual visuomotor task. The participants were instructed to make fast visually-cued bimanual movements, initiated simultaneously and terminated on two target-buttons located at various distances from the starting locations. The movements were either symmetrical (i.e. each hand had to travel the same distance) or asymmetrical. Our hypothesis was that participants with inconsistent hand preference will outperform participants with consistent hand preference and that the difference in performance will possible be larger in the more demanding asymmetrical condition. To further support our hypothesis, we recorded EEG in order to investigate the neural mechanisms that operate during the performance of a bimanual task. Our analyses were focused on two indices of (pre)motor activation, the Movement Related Potential (MRP) and the suppression of the 10 Hz mu rhythm. The MRP is a slow rising negativity, which develops progressively during the planning of self-generated or externally-cued movements and peaks at approximately movement onset (Deecke, Scheid, & Kornhuber, 1969; Jankelowitz & Colebatch, 2002; Kristeva, Cheyne, Lang, Lindinger, & Deecke, 1990). The MRP is typically stronger over the vertex and during its late stages it is believed to originate from primary sensorimotor cortices as well as the Supplementary Motor Area (SMA), a brain area associated with movement planning and coordination (Ikeda et al., 1995; Urbano et al., 1998). The suppression of the 10-Hz mu rhythm refers to the amplitude decrease of the EEG signal within the frequency range of 7–13 Hz, which is observed prior and during the execution of a movement and is considered an index of activation of primary sensorimotor areas as well as of the SMA (Arroyo et al., 1993; Pfurtscheller, Neuper, Andrew, & Edlinger, 1997; Pineda, 2005). The 10-Hz mu suppression and the MRP can be considered as two complementary indices of cortical activation; the former reflects a rather general decrease of the background sensorimotor oscillations, whereas the latter represents a more task-specific increase in post-synaptic potentials in the underlying brain areas (Babiloni et al., 1999; Filipović, Jahanshahi, & Rothwell, 2001; Pfurtscheller & Lopes da Silva, 1999). With regards to our experiment, we expected that participants with inconsistent hand preference would be better in planning and coordinating bimanual action, thus engaging primary sensorimotor areas and the SMA to a greater extent compared to participants with consistent hand preference. Thus, we expected to record larger MRP amplitude and greater mu suppression before and during movement execution in participants with inconsistent hand preference.
2. Methods 2.1. Participants 28 healthy volunteers with normal or corrected-to-normal vision took part in the experiment. They had no history of hand or arm injuries or diseases or any mental, cognitive, and other neurological disorder. All participants provided their informed consent after full explanation of the study.
Fig. 1. Response box and task. Schematic drawing of the response box with two hands placed on the home keys (i.e. starting position). The green and black circles on the box represent the LEDs and the buttons respectively. The length of the box (distance from (A) to (E)), the diameter of the buttons (distance from (B) to (C)), the distance from of the home keys from the edges of the box (A) to (B) and the diameter of the target buttons (distance from (B) to (C)) are displayed under the box. The participant had to respond to the illumination of two LEDs and press the target buttons that were located directly under the LEDs. The possible (symmetrical and asymmetrical) movement combinations are illustrated at the top of the figure. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) Two participants were excluded from the analysis: one due to extremely slow responses and another one due to malfunction of the EEG equipment. The remaining 26 participants were categorized according to the degree and the direction of handedness, based on the Edinburgh Handedness Inventory (Oldfield, 1971). Lateralization indices (LI) ranged from 100 for pure lefthanders to þ 100 for pure right-handers1. The median value of the absolute lateralization indices was 80, which is consistent with the median score of the large population sample studied by Prichard et al. (2013). Participants with absolute lateralization index Z 80 were categorized as consistent handers (CH) and participants with absolute lateralization index o80 were categorized as inconsistent handers (ICH). 13 participants were categorized as consistent handers [LI¼ 96.8 (SD¼ 7.9), 11 females and 2 males, 10 right-handers and 3 left-handers, age¼ 22.5 yr (SD¼ 2.3)] and 13 participants were categorized as inconsistent handers [LI¼ 47.6 (SD ¼ 48.4), 10 females and 3 males, 3 right-handers and 10 left-handers, age¼ 23.2 yr (SD¼ 4.3)].
2.2. Experimental setup The experiment was run in a quiet, normally illuminated room. The experimental setup and task were similar to those used by Kelso, Southard, and Goodman (1979). The participants were seated comfortably on a chair with their arms resting on a table. A custom-made response box (80.35 cm 10.5 cm 5 cm, see Fig. 1) was placed on the table in front of the participants. Two release/home keys (diameter: 1 cm) were positioned at 3 cm from the left and the right edge of the box, and 8 press/target keys (diameter: 1 cm) were positioned at equidistant (7.15 cm) locations between the release buttons. A green Light Emitting Diode (LED) was placed 2 cm above each of the response buttons. The response box was divided in two halves by a 2 cm strip wide of black duct tape.
2.3. Task The participants had to place their index fingers on each of the release buttons (i.e. home keys). The illumination of two LEDs (one at each hemispace) instructed the participants to swiftly and simultaneously release both home keys and press the target keys located directly under the illuminated LEDs. The movements were either symmetrical (i.e. each hand had to travel the same distance) or asymmetrical. Although there were 12 possible combinations for asymmetrical movements, we included only 4 of them in our experiment (Fig. 1) in order to have an equal number (i.e. 4) of symmetrical and asymmetrical bimanual movements. In addition, the average distance that each hand had to travel in the asymmetrical movements was equal to the average distance in the symmetrical movements.
1 The Lateralization index was 57.7 (SD ¼ 8.2) for left-handed participants and 85.7 (SD ¼7.0) for right-handed participants.
D. Kourtis et al. / Neuropsychologia 58 (2014) 81–87 The experiment consisted of 12 blocks of 32 randomized trials each, preceded by a practice block of equal length, which resulted in 192 trials per condition (i.e. symmetrical and asymmetrical movements). Each condition occurred with equal probability within each block. The duration of the intertrial interval was randomized between 3050 and 3950 ms. 2.4. Data acquisition and processing EEG was recorded continuously with Ag/AgCl electrodes from 64 scalp electrodes relative to an (off-line) average mastoid reference. The electrodes were placed according to the 10–10 extension of the International 10–20 electrode system (American Electroencephalographic Society, 1994; Chatrian, Lettich, & Nelson, 1985) using a carefully positioned nylon cap. Vertical and horizontal eye movements were monitored using two pairs of electro-oculography (EOG) electrodes positioned below the eyes and lateral to the left and the right eye. EEG and EOG signals were amplified with a band-pass of 0–128 Hz by a BioSemi Active-Two Amplifier (BioSemi B.V., Amsterdam, Netherlands) and sampled at 512 Hz. 2.4.1. Behavioural data Behavioural data were registered by BrainVision Recorder Software. We focussed our analysis on two epochs: response time (RT) and movement time (MT). The RT was defined as the time interval from the LEDs onset until the release of a home-key. The MT was defined as the time interval from the release of a home key until the press of a target key. Trials where the participants did not respond and trials where they were too fast or too slow to release the target keys (i.e. the difference with the mean RT for each LED combination was larger than 2 standard deviations) were removed from subsequent analysis. In addition, trials where the participants failed to press the correct target key and trials containing too slow or too fast movement times (i.e. the difference with the mean MT for each LED combination was larger than 2 standard deviations) were also removed from subsequent analysis. The total percentage of errors was 12.2% (SD¼ 2.4) and 13.3% (SD ¼3.9) for symmetrical and asymmetrical movements respectively. 2.4.2. EEG data EEG data processing was performed using the BrainVision Analyzer software (V.1.05, Brain Products GmbH, Gilching, Germany). Initially, the data were converted from.bdf to BrainVision Analyzer compatible.cnt format using the PolyRex V.1.2 software (Kayser, 2003). Subsequently, the data were referenced to the average mastoid reference and then they were filtered with a low cut-off filter of 0.05 Hz (24 dB/octave) and a high cut-off filter of 40 Hz (24 dB/octave) in order to remove slow drifts and excessive noise, respectively. Ocular correction was performed using the Gratton–Coles algorithm (Gratton, Coles, & Donchin, 1983). The corrected EEG data were segmented off-line into epochs from 500 ms before LEDs onset to 1700 ms after LED onset. In addition to the trials that have been removed because they did not meet our behavioural criteria, individual trials containing remaining eye movement or other EEG-related artefacts were also removed before averaging. Averages were constructed separately for each condition and each participant. The baseline was defined as the time period from 200 ms before until the LEDs onset. The release-MRP and the press-MRP amplitudes were quantified by pooling the mean activity from neighbouring electrodes on the basis of grand average topographies during the relevant time intervals (see Section 3). Time–frequency analysis was performed by means of a continuous complex Morlet waveform transformation as implemented in the BrainVision Analyzer software. Absolute values of wavelets coefficients were calculated in the frequency range of 6–30 Hz with 20 frequency steps, and Morlet parameter of c ¼4. After averaging, we extracted the frequency layer from 6.39 to 10.66 Hz (central frequency¼ 8.53 Hz) for subsequent analysis, similar to the ERPs.
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respectively, whereas MTs were 483 ms (SD¼63) and 510 ms (SD¼64) for symmetrical and asymmetrical movements respectively (Fig. 2). Statistical comparisons were made using a 2 2 2 mixed ANOVA, with the between-subjects factor Consistency (CHs vs. ICHs) and two within-subjects factors: Epoch (Response vs. movement times) and Symmetry (symmetrical vs. asymmetrical movements). The analysis revealed a significant effect of Epoch [F (1,24) ¼ 35.7, po .001], because MTs were significantly longer that RTs and a main effect of Symmetry [F(1,24) ¼82.1, p o.001], because participants needed more time to perform asymmetrical movements. In addition, we found a significant 2-way interaction between Epoch and Symmetry [F(1,24)¼17.7, p o.001], because the difference in MTs between symmetrical and asymmetrical action was significantly larger than the difference in RTs [t(25) ¼ 3.8, p ¼.001]. No other main or two-way interaction effects reached statistical significance. The three-way interaction between consistency, Epoch and Symmetry was also statistically significant [F(1,24) ¼6.9, p¼ .015]. In order to identify the source of this interaction, we examined RTs and MTs separately. A mixed 2 2 ANOVA on RTs (Fig. 2, top) with consistency as between-subject factor and Symmetry as withinsubject factor showed a significant main effect of symmetry [F (1,24) ¼ 6.7, p¼ .016] and also a significant interaction [F(1,24) ¼ 4.7, p¼ .041], because CH participants were significantly slower in initiating asymmetrical compared to symmetrical movements [t(25) ¼3.0, p ¼.011], whereas ICH participants were equally fast in either condition (p ¼.73). There was no main effect of consistency (p ¼.95).
3. Results 3.1. Behavioural analyses 3.1.1. Response and movement times Similar to Kelso et al. (1979), we found no difference in RTs or MTs between the dominant and the non-dominant hand (ps 4.57), thus all subsequent behavioural analyses were performed on the average response and movements times of the two hands. For Consistent Handers (CHs), RTs were 360 ms (SD¼ 46) and 373 ms (SD¼45) for symmetrical and asymmetrical movements respectively, whereas MTs were 424 ms (SD¼96) and 443 ms (SD¼ 89) for symmetrical and asymmetrical movements respectively. For Inconsistent Handers (IHs), RTs were 367 ms (SD¼31) and 368 ms (SD¼ 23) for symmetrical and asymmetrical movements
Fig. 2. Behavioural data. Response times (top) and movement times (bottom) from participants with consistent (CH) and inconsistent hand preference (ICH) in the performance of symmetrical (Sym) and Asymmetrical (Asym) bimanual movements. Error bars represent standard error of mean. The symbol “n” indicates statistically significant differences, whereas “n.s.” indicates non-significant differences.
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On the other hand, a mixed 2 2 ANOVA on MTs (Fig. 2, bottom) with consistency as between-subject factor and Symmetry as within-subject factor showed a significant main effect of symmetry with asymmetrical movements being slower [F(1,24)¼ 113.3, po .001], but no interaction [F(1,24)¼2.9, p¼ .10]. Interestingly, CH participants were faster than ICH participants, although this difference failed to reach statistical significance [F(1,24)¼ 4.1, p ¼0.054]. In addition to this analysis, we divided our participants into two different groups based on their hand dominance, which resulted in 13 left-handers (3 CHs þ10 ICHs) and 13 righthanders (10 CHs þ3 ICHs) and performed the same analysis, but with hand dominance as the between-subject factor. The results showed no significant main effect of hand dominance nor a significant interaction that involved hand dominance (ps 4.2). This suggests that the factor that dissociated our participants’ behavioural performance was not hand dominance, but handedness consistency instead. 3.1.2. Errors In order to investigate the effect of handedness consistency on performance accuracy, we performed statistical comparisons on the errors that the participants made in initiating and performing the movements. Consistent Handers (CHs) made response-related errors in 2.0% (SD ¼1.5) and 3.2% (SD ¼1.8) of symmetrical and asymmetrical movements respectively, and movement-related errors in 10.4% (SD ¼2.2) and 10.7% (SD ¼3.3) for symmetrical and asymmetrical movements respectively. Inconsistent Handers (ICHs) made response-related errors in 2.5% (SD ¼ 1.4) and 3.2% (SD ¼1.1) of symmetrical and asymmetrical movements respectively, and movement-related errors in 9.6% (SD ¼2.5) and 9.4% (SD ¼2.9) for symmetrical and asymmetrical movements respectively. Statistical analyses similar to the ones performed for RTs and MTs showed that participants made more movement-related errors than response related errors [F(1,24)¼217.3, p o.001]. There were no other significant effects or interactions (ps 4 .1), thus handedness consistency had no significant influence on the accuracy of the participants’ performance. As with the RT/MT data, we performed the same analysis replacing the between-subject factor with hand dominance. The effect of hand dominance and its interaction with the other factors did not reach statistical significance (ps 4.05), which suggests that hand dominance had no significant influence on the accuracy of the participants’ performance. 3.2. EEG analyses 3.2.1. Movement related potential (MRP) The ERP analysis revealed a slow-rising negativity over midpremotor areas, which peaked approximately at the time of the release of the home keys (Fig. 3, top). This negativity was present in all experimental conditions and corresponds to the MRP (from now release-MRP). The release-MRP was followed by a positive deflection, probably associated with reafferent sensory input, which in turns was followed by another slow-rising negativity, which corresponded to the MRP associated with the press of the target keys (from now, press-MRP). The MRP amplitude was quantified by pooling the mean activity from electrodes FCz, Cz, CPz, C1 and C2 from 380 to 480 ms after LED onset (i.e. release-MRP) and from 650 to 750 ms after LEDs onset (i.e. press-MRP). These electrodes are located over mid-(pre)motor areas, that are typically associated with the MRP, and over which the difference between ICHs and CHs was larger (see Fig. 3, scalp topography of ICHs vs. CHs). Statistical comparisons were made using a 2 2 2 mixed ANOVA, with the
Fig. 3. ERP waveforms and scalp topographies. MRPs were larger in participants with inconsistent hand preference (ICHs) over participants with consistent hand preference (CHs). Also, MRP during asymmetrical movements (Asym) were larger than MRPs during symmetrical movements (Sym). The grey rectangles represent the time intervals of interest. (Bottom)—Scalp topographies (flat view) of the release-MRP and press-MRP for ICH and CH participants and the difference between the two groups. The electrodes from which the activity was included in the statistical analysis are represented as grey circles on the topography of the difference (ICHs vs. CHs).
between-subjects factor consistency (CHs vs. ICHs) and two within-subjects factors: Action (Release vs. Press) and Symmetry (symmetrical vs. asymmetrical movements). The analysis revealed a significant effect of Action [F(1,24) ¼36.9, p o.001], because the press-MRP was significantly larger that the release-MRP and a main effect of Symmetry [F(1,24)¼18.4, p ¼.001], because the MRP was significantly larger when the participants performed asymmetrical movements. Most importantly, there was a significant main effect of handedness consistency [F(1,24)¼4.4, p ¼.046], as the MRP was significantly larger in participants with inconsistent hand preference. No other main or interaction effects reached statistical significance (ps 4.5). Relevant to the main objective of our study, the absence of a significant consistency action interaction shows that the effect of handedness consistency on the MRP amplitude was equally large in the selected intervals of analysis. As with the behavioural data, we performed the same analysis replacing the between-subject factor with hand dominance. Similar to the response and movement times, the effect of hand dominance and its interaction with the other factors did not reach statistical significance (ps 4.1). This again suggests that the factor that dissociated the MRP amplitude in our participants was not hand dominance, but handedness consistency instead.
3.2.2. Time—Frequency analysis: The 10-Hz mu rhythm The time–frequency analysis showed that there was a larger suppression of the (lower) 10-Hz mu rhythm over mid-sensorimotor areas for ICH-participants compared to CH-participants soon after LEDs onset. The mu amplitude decrease was quantified by pooling the mean activity from electrodes Cz, C1, C2, CPz, CP1 and CP2, in the time interval from 120 to 420 ms after LEDs onset. These electrodes are located over mid sensorimotor areas, that are typically associated with
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Fig. 4. Time–frequency plot and scalp topography. Time–frequency plot (electrode Cz) of the difference between participants with inconsistent handedness and participants with consistent handedness. The difference was more prominent in the (lower) alpha/mu band over mid-sensorimotor areas. The dotted rectangle represents the time interval of interest and the selected frequency range. The electrodes from which the activity was included in the statistical analysis are represented as grey circles on the topography of the difference.
the mu-rhythm suppression and over which the difference between ICHs and CHs was larger (Fig. 4, scalp topography). Statistical comparisons were made using a 2 2 mixed ANOVA, with the betweensubjects factor Consistency (CHs vs. ICHs) and the within-subjects factor Symmetry (symmetrical vs. asymmetrical movements). The analysis revealed a significant effect of Consistency [F(1,24)¼5.2, p¼ .032], because mu suppression was larger in participants with inconsistent hand preference. The effect of Symmetry and the consistency–symmetry interaction was not significant (ps4.4). As with the behavioural and the ERP data, we performed the same analysis replacing the between-subject factor with hand dominance. Contrary to the previous analyses, there was a significant main effect of hand dominance because the musuppression was larger in left-handers [F(1,24) ¼12.1, p¼ .002]. The effect of Symmetry and the Dominance-Symmetry interaction was not significant (ps 4.4).
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hands have to travel unequal distances (for reviews in bimanual control, Cardoso de Oliveira, 2004; Swinnen & Wenderoth, 2004). However, this was not the case for participants with inconsistent hand preference, who did not seem to be affected by increased coordination demands, and were equally fast in initiating symmetrical and asymmetrical movements. Importantly, there were no differences in behavioural performance when the participants were categorized as left- or right-handers, which suggests that the direction of hand dominance may not always be of relevance in bimanual coordination. Previous studies reported that the performance of ICH lefthanders was often (although not always) superior to CH lefthanders in various unimanual and bimanual tasks (Gorynia & Egenter, 2000; Kopiez et al., 2006; Peters & Servos, 1989). Notably, inconsistent right-handers have not been systematically studied, possibly due to their relatively small numbers. However, the presence of handedness inconsistency in right-handers is well documented and it has been related to a more optimal performance of tasks such as unimanual pointing (Bishop, Ross, Daniels, & Bright, 1996), production of rapid movement sequences (Ponton, 1987) and intermanual coordination (Annett, 1976), although these studies have not explicitly studied groups of inconsistent right-handers. Such findings are in agreement with the results of the present study. It should be noted that the advantage of ICHs was only present in the response times, which suggests that ICHs may be better in planning and initiating a bimanual movement. However, ICHs and CHs were equally accurate in initiating and performing symmetrical as well as asymmetrical movements, and in fact CHs were marginally faster than ICHs in movement execution. Previous studies have shown that CHs do not always perform worse than ICHs (e.g. Peters & Servos, 1989). The task we employed required the coordination of the two hands, but it was very simple in terms of execution (i.e. button pressing). It is possible that differences between ICHs and CHs arise mainly in tasks the execution of which requires complex motor skills. This could conceivably be the reason for the lack of significant difference in movement times between the two groups; however, the fact that CHs were marginally faster implies that the relationship between handedness consistency and bimanual coordination is a topic that requires further investigation. 4.2. Electrophysiological correlates of bimanual control
4. Discussion We investigated the effect of handedness consistency on the performance of coordinated symmetrical and asymmetrical bimanual movements. Our results showed that, contrary to participants with consistent hand preference (CHs), participants with inconsistent hand preference (ICHs) were not affected by the increased coordination demands of asymmetrical bimanual movements. In addition, our EEG analyses showed that ICHs were characterized by increased activation over sensorimotor areas that are typically associated with planning and execution of bimanual movements. However, we need to acknowledge that the EEG findings (i.e. main effect of handedness consistency) are not in alignment with the behavioural findings (i.e. consistency–symmetry interaction); therefore, no correlation or causal relationship can be established by the present study. 4.1. Behavioural performance Participants with consistent hand preference were slower in initiating an asymmetrical movement compared to a symmetrical one. This finding was expected on the basis that humans have a natural tendency to synchronize the motor output of their upper limbs, so bimanual coordination is more demanding when the two
The ERP analysis showed that the Movement Related Potential (MRP) was larger in participants with inconsistent hand preference. The difference was more prominent around response time and remained significant (although gradually fading) throughout movement execution (Fig. 3). The MRP is a slow rising negativity that peaks around (unimanual, bimanual, or imaginary, Jankelowitz & Colebatch, 2002) movement onset and it is regarded as an index of movement preparation and organization (Ikeda et al., 1995; Kutas & Donchin, 1980). Accordingly, in our experiment, the larger MRP in ICHs could be considered as an indication of the superior ability of ICHs in planning and organizing a bimanual movement. In addition, there was no difference in MRP amplitude when the participants were divided into left- and right-handers, which may be taken as additional evidence that the direction of hand dominance may not be the most important factor in bimanual control. In addition to the ERPs, the time–frequency analysis showed that the suppression of the sensorimotor 10-Hz mu rhythm was larger in ICHs compared to CHs in a time window that corresponded with the planning and initiation of a bimanual movement. Considering that mu-suppression is a reliable index of sensorimotor activation (Hari, 2006; Pfurtscheller et al., 1997; Pineda, 2005), this finding seems to be consistent with the ERP analysis. However, contrary to the previous analysis we found that
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when we divided the participants according to their hand dominance, the mu-suppression was significantly larger in left-handed participants. This discrepancy is not entirely surprising when we consider that ERPs and frequency-specific changes in EEG oscillatory activity represent different brain phenomena. ERPs result from the summation of transient post-synaptic potentials, whereas the increase/suppression of neuronal oscillations represents changes in the temporal dynamics of functionally-related network of neurons (Pfurtscheller & Lopes da Silva, 1999; Salinas & Sejnowski, 2001). Previous research suggests that the suppression of 10-Hz sensorimotor oscillations and slow-rising movementrelated ERPs represent different brain processes, the former a more general state of sensorimotor alerting/readiness, whereas the latter task-specific responses of sensorimotor areas (Babiloni et al., 1999; Deiber, Ibañez, Caldara, Andrey, & Hauert, 2005; Filipović et al., 2001). This seems to be particularly the case for the suppression of the lower ( o10 Hz) mu rhythm (Pfurtscheller, Neuper, & Krausz, 2000), which was the frequency band where we recorded the larger difference in the amplitude of mu suppression (Fig. 4). Moreover and contrary to the MRPs, the amplitude of the mu suppression did not differ between asymmetrical and symmetrical movements, which also suggest that the mu suppression was not related to the specific coordination demands of our task. Taken together, our EEG analyses cannot tell us whether the state of readiness of the sensorimotor system prior to bimanual movements depends more on the actor's hand dominance or on handedness consistency (or to both). On the other hand, the planning and organization of a specific bimanual movement seems to depend mostly on the actor's handedness consistency. The topographies of the contrasts between ICHs and CHs both with regards to the MRP and to the mu-suppression were focal over mid sensorimotor areas (Figs. 3 and 4). We need to point out at this point that EEG records electrical activity at the surface of the head, so any claims regarding the brain areas that might be involved on a given task should be treated with great caution. Keeping this in mind, we should note that a large number of EEG and intracortical studies have consistently associated the MRP and the mu-rhythm with activation in the SMA and primary sensorimotor areas (Donchin, Gribova, Steinber, Bergman, & Vaadia, 1998; Donchin et al., 2002; Ikeda, Lüders, Burgess, & Shibasaki, 1992, Ikeda et al., 1995; Pfurtscheller et al., 1997), which are considered to be pivotal in the organization and the execution of bimanual movements (Jäncke et al., 2000; Serrien, Strens, Oliviero, & Brown, 2002; Toyokura, Muro, Komiya, & Obara, 1999; Walsh, Small, Chen, & Solodkin, 2008). Although precise localization is beyond the scope and the capabilities of the present study, activation of the SMA and primary sensorimotor areas is consistent with the MRP and the mu-suppression topographies as well as with the nature of our task. This implies that the ability of people with inconsistent hand preference in planning and initiating a bimanual action may be related to the stronger activation of these areas. 4.3. Limitations A limitation of the present study is that there is a certain misbalancing of the population sample. Due to the scarcity of people with inconsistent handedness in the general population, the group of consistent handers comprised of 10 right-handers and 3 left-handers, whereas the group of inconsistent handers comprised of 3 right-handers and 10 left-handers. Although we did find significant differences between ICHs and CHs in terms of RTs and MRP amplitudes, the inconclusiveness of the results regarding MTs and mu-suppression, along with the relatively small population sample, suggests that equal and larger numbers of participants per sub-group are needed in order to fully
understand the importance of handedness consistency and of hand dominance in the planning and execution of bimanual movements. In addition, an overall larger population sample would presumably provide us with the opportunity to examine whether behavioural and EEG measures can be parametrically correlated to the degree of handedness (see, Annett, 1976). Another possible limitation regarding our population sample is that the majority of the participants were females. Previous studies suggest the existence of gender differences in the cortical organization of hand movements (Amunts, Jäncke, Mohlberg, Steinmetz, & Zilles, 2000) and more importantly in bimanual control (Mickevičienė et al., 2011; Smolders, Rijpkema, Franke, & Fernàdez, 2012), however not in relation to handedness consistency. Thus, although we cannot derive specific predictions from the literature regarding a possible interaction between gender and handedness consistency in bimanual control, we cannot exclude the possibility that the inclusion of additional male participants would have an effect on our results. Another limitation of the present study was that our analyses did not show any evidence of correlation between behavioural and EEG data. However, although a correlation between EEG and behavioural measures seems plausible in motor tasks, it is not that common in EEG research. Regarding our experiment, there are a number of possible reasons that may account for the lack of correlation, such as different sources of noise for behavioural data (e.g. biomechanical constraints) and EEG data (e.g. random fluctuations of the signal), relatively small number of participants, different optional number of trials for each measurement (i.e. reliable EEG signals are obtained after a large number of trials, but this inevitably leads to a certain degree of fatigue and boredom) etc. Finally, another possible limitation that we already mentioned earlier was that the successful performance of the selected task only depended on intermanual coordination, but it did not require any other motor skill such as manual dexterity, strength etc. Further studies using a variety of tasks assessing different motor skills could shed more light on the (dis)advantages of handedness consistency in motor control.
5. Conclusion The present study provides evidence that handedness (in) consistency has an effect on the performance of bimanual movements, which to an extent seems to be independent of hand dominance. Our results show that the increased coordination demands of an asymmetrical bimanual movement do not seem to affect individuals with inconsistent hand preference, whereas they delay movement initiation by individuals with consistent hand preference. Furthermore, handedness inconsistency is associated with enhanced brain activity, which is believed to reflect an increased ability in the planning and organization of bimanual movements. In addition, handedness inconsistency seems also to be associated with a higher state of readiness of the sensorimotor system prior to a movement, although this effect may well be attributed to left hand dominance. It should be noted though that the electrophysiological findings cannot be causally linked to the behavioural findings; instead they should be considered as two unconnected sources of evidence regarding the influence of handedness (in)consistency on the coordination of bimanual movements. To our knowledge this is the first study that provides behavioural as well as electrophysiological evidence for the importance of handedness (in)consistency in bimanual control; however, more work is needed in order to elucidate its precise role and its relationship with hand dominance.
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