- freely available
Sensors 2007, 7(6), 960-978; doi:10.3390/s7060960
Abstract: Previous brain electrophysiological research has studied the interregional connectivity during the tapping task and found that inter-hemispheric alpha coherence was more significant under bimanual task conditions than that under unilateral conditions, but the interregional connectivity situation in the unilateral tapping condition was not explored clearly. We have designed a unilateral repetitive finger-tapping task to delineate the anterior and posterior cortex contributions to unilateral finger movement. Sixteen right handed college students participated in this study. Event related potentials (ERPs) and the strength of event related coherence (ERCoh) were analyzed to examine the antero-postero dominance of cortical activity in the phase of early visual process (75-120ms), pre-execution (175-260ms), execution (310-420ms) and post-execution (420-620ms). Results showed that the occipital (Oz, O1 and O2), frontal (Fz, F3, and F4), fronto-central (Fz, Cz, F3 and C3), and parietal regions were the most pronounced in the early visual, pre-execution, execution, and post-execution phases, respectively. Moreover, among four inter-hemispheric pairs only the Coh (C3 and C4) was significantly correlated to reaction time (RT) of tapping in the execution phase. In conclusion, the aforementioned variability of electrophysiological data (ERPs and coherence) and the change of antero-postero regional dominance with time reflect the relative importance of different mechanisms in different phases. The mechanisms of visual processing, motor planning, motor execution and feedback reward were operational, respectively.
Previous electrophysiological brain research has studied the interregional connectivity during the tapping task and found that the inter-hemispheric interaction was more significant in the bimanual task condition than that of unilateral tasks [1-5]. Knyazeva et al.  found that the inter-hemispheric alpha coherence of C3-C4 and P3-P4 in 7-8 year-old children increased while conducting bimanual rhythmic tasks. Both coherence values were negatively correlated with the time difference between the left and right hand intertap intervals. Knyazeva et al.  further found the inter-hemispheric coherence of acallosal children were shown to be smaller comparing with those of normal children in frontal, central and parietal pairs in both right-hand tapping and bimanual tapping. Rissman et al.  used the general linear model to survey the inter-regional interaction. They compared their data with the previous findings of EEG and fMRI studies and further concluded that greater bimanual coordination induced stronger connectivity between motor regions of left and right hemisphere.
Similar to the effect of bimanual finger task on brain mechanism, sequential finger movements can also result in more bilateral activation of sensorimotor areas than single-step movements. Many researchers have mentioned that the greater intercommunication between bilateral and mesial central and prefrontal regions could be enhanced by sequential finger movements [3,4,6,7].
Different from the aforementioned studies, the reported study explored the brain mechanism during execution of unilateral finger movements. Although we know sequential and bimanual finger movements might result in bilateral activation, the mechanism of unilateral finger movement has not been explored clearly. The coherence and synchronization in alpha band have been studied often while surveying the effect of unilateral finger movement on brain mechanisms. Stancak et al.  found a coherence between the left and right S1/M1 areas after movement onset in the lower alpha band (7.8-9.8 Hz) correlated with the size of the callosal body in both unilateral and bilateral movement in normal right handed adults. Pfurtscheller et al.  conducted en experiment to justify the maximal event related desynchronization happening in the 10-12 Hz band close to C3 and C4 electrodes during voluntary finger movement. Sailer and coworkers  found a pronounced bilateral activation of sensorimotor regions for the alpha band in the elderly while executing a simple finger task. Interestingly, Andrew and Pfurtscheller  found the relationship of intrinsic mu rhythm between sensorimotor (mu rhythm) and supplementary motor was more desynchronized during the unilateral finger movement than the resting state.
Besides these coherence and synchronization studies, other studies of the alpha band have also been conducted. For example, the ratio of alpha and tapping frequencies was close to 2:1 during the tapping movement in most habitual smokers . Moreover, Deiber and colleagues  found the 7.8-9.8 Hz task related power of EEG for right tapping movement was more prominent than comparing with those for left and bimanual movements; therefore, the sensitivity of lower alpha band to task difficulty was inferred.
Moreover, the aforementioned studies neglected the tapping effect on activities in the occipital region. The occipital region was not the main area of interest in studies related to the brain mechanism of finger tapping, but in fact, the occipital region might occupy an important role during finger movement [1,13,14]. The occipital activation was pronounced while conducting precise movements . Van der Lubbe et al.  suggested that the occipital component reflected the process of direction code and the following parietal-temporal component reflect a link between visual perception to action. Furthermore, while observing complex or simple movements the occipital regions were obviously activated [15,16]. Therefore, we inferred if the goal directed movements guided by visual information would activate the occipital regions. This present study will also substantiate this important issue. In this study we only focused on the issue of unilateral and simple finger movement. All the participants conducted one-step and unilateral tapping task without bimanual and sequential characteristics.
Sixteen right handed college students (2 males and 14 females) aged 19 to 24 (mean= 20.19, SD=1.38) without any neuromuscular or cerebral disease voluntarily participated in the present study. The averaged handedness quotient of self reported Edinburgh handedness inventory  was 95.56 (±8.19). The averaged eyedness quotient of five tasks was 76.25%. The tasks included (1) to look through a small opening formed by crossed index fingers and thumbs of both hands (Miles test); (2) to look through a kaleidoscope; (3) to look through a hole in a card (Dolman method); (4) to cover one eye with one hand; and (5) to close one eye. Item 4 and 5 were decided by us and item 1, 2 and 3 were cited from related articles [18,19].
We took the individual finger (the index, middle, or 4th finger) which is used to press a computer key as an independent variable. Dependent variables included the reaction time (the period between seeing the number and the action of pressing the corresponding key) and the mean amplitude of event related potentials at four anterior-posterior electrodes over midline, left and right scalp locations in early visual, pre-execution, execution, and post-execution phases. Besides, the brain coherence strength (value from 0 to 1) between electrodes F3 and F4 [Coh(F3, F4)], C3 and C4 [Coh(C3, C4)], P3 and P4 [Coh(P3, P4)], as well as O1 and O2 [Coh(O1, O2)] in the alpha band (8-12 Hz) was treated as the indication of inter-hemispheric integration.
2.3. Experimental Design
Participants were presented with the three Arabic numerals 2, 3, and 4. Their responsibility was to look at the center of the screen and respond to these stimuli by pressing the corresponding keys on the keyboard with their index, middle and 4th finger respectively [20,21]. There were 600 attempts in total, and the inter-stimulus interval was set as 2000 ms. Therefore, it took 20 minutes to complete the task (please see Figure 1). Their EEGs and reaction times were recorded during the process for later analyses.
2.4. Stimulus presentation and key pressing performance
The timing of the stimulus presentation was controlled and subject responses (accuracy and reaction time) were recorded using Stim II Software (Neuroscan, Inc. Sterling, VA, USA). The stimuli included the Arabic numerals 2, 3, and 4.
2.5. Experimental Procedure
Each participant was required to respond by pressing the specified keys on the keyboard with their right-hand fingers. When the number 2 appeared on the screen, the participants pressed the corresponding key with their index finger as soon as possible. Likewise, participants pressed the corresponding keys using their middle or 4th fingers if they saw the numbers 3 or 4, respectively [20,21]. There were 200 attempts each of these three conditions, and the order of these 600 attempts was totally randomized (Figure 1).
2.6. Electroencephalogram (EEG) acquisition and ERP recording
EEGs were recorded from 17 Sintered electrodes (Fz, FCz, Cz, Pz, Oz, F4, FC4, C4, P4, O2, F3, FC3, C3, P3, O1, Heog, and Veog; 12 of them were of interest in this study as shown in Figure 2) attached according to the standard 10-20 system, using a Brain-Amp-MR amplifier (Brain Products GmbH) and the software Brain Vision Recorder Version 1.01 (Brain Products GmbH). All electrode impedances were brought to below 10 kΩ. The EEG was band pass filtered (1-30 Hz) and digitized at a sampling rate of 1000 samples/s. The baseline for ERP measurements was the mean voltage of a 100ms pre-stimulus interval. Attempts exceeding ± 100μV at horizontal and vertical electrooculogram (EOG) were excluded immediately. Furthermore, attempts with eye blinks, eye movement deflections, and over ± 60μV at any electrode were also excluded from ERP averages.
2.7. Calculating the coherences
According to the Brain Vision Analyzer User Manual Version 1.04 , the correlation/autocorrelation was the coherence method obtained in the frequency domain. The formulas are described as follows. “The first method calculates the coherence using the following formula. In the second formula, totaling is carried out via the segment number i. Formation of the average also relates to segments with a fixed frequency f and a fixed channel c”.
The aforementioned words appeared in Italics and the formulas were all adapted from the cited reference .
One-way repeated measure ANOVAs were used to compare the differences of event related potentials among anterior-posterior electrodes over midline scalp locations (Fz, Cz, Pz, and Oz), right hemispheric locations (F4, C4, P4, and O2) and left hemispheric locations (F3, C3, P3, and O1) in four different phases (early visual, pre-execution, execution, and post-execution). The coherence strengths in alpha band among inter-hemispheric pairs (F3-F4, C3-C4, P3-P4, and O1-O2) were also compared by one-way repeated measure ANOVAs. The Greenhouse-Geisser correction was applied where appropriate to correct for violations of sphericity . After the difference reaching the significant level (p < .05), the least significant difference (LSD) post hoc test was used to compare between electrodes or between coherence pairs. LSD is an adjustment equivalent to no adjustment for multiple comparisons after the result of repeated ANOVA reaching the significant level. Furthermore, Spearman's r correlations were conducted between the reaction time and the inter-hemispheric coherence of combinations of channels in four phases. The nonparametric Spearman's r was used because of the lack of normal distribution in reaction time and coherence strength within the 16 subjects.
3.1. Behavioral results
The mean accuracy of all 12 subjects was 97.03%. The mean reaction time of correct responses ranged from 412.27 ms to 599.69 ms (mean=476.91, SD=48.69).
3.3. A comparison of coherence strength between inter-hemispheric pairs
The strength values of all coherence pairs are listed in Appendix 1. The four inter-hemispheric coherence pairs (O1-O2, P3-P4, C3-C4, and F3-F4) in four phases were compared by one-way repeated measure ANOVAs (Table 5) and post hoc comparisons (Table 6).
3.3.1. Early visual phase
The one-way repeated-measure ANOVA revealed a statistically significant difference existed among four pairs (F(1.818,27.274)=5.553, p = 0.011) (Table 5). The coherence of F3-F4 was the smallest. The LSD post hoc test (Table 6) revealed that the coherence of F3-F4 was significantly smaller than that of O1-O2 (mean difference = -0.141, p = 0.008), P3-P4 (mean difference = -0.127, p = 0.000), and C3-C4 (mean difference = -0.121, p = 0.001). Conversely, there was no significant difference among other pair comparisons.
3.3.2. Pre-execution, execution, and post-execution phases
The one-way repeated-measure ANOVA (Table 5) revealed a statistically significant difference existed among four pairs in the pre-execution (F (1.816,27.243) = 5.167, p = 0.015), execution (F(2.133,31.991) = 3.362, p = 0.044), and post-execution (F(1.461,20.459) = 5.689, p = 0.017) phases, respectively. The LSD post hoc test (Table 6) revealed the same statistical result in those three phases, which is the coherence of F3-F4 was significantly smaller than that of P3-P4 and C3-C4 and there was no significant difference among other pair comparisons. The detailed results were shown in Table 6.
3.4. The correlation coefficients between RT and inter-hemispheric coherence pairs
Only the coherence strength of C3-C4 in the execution phase was negatively correlated to the reaction time (Spearman's r = -.585, p = 0.017). The coherence of other combinations of inter-hemispheric channels (O1-O2, P3-P4, and F3-F4) in any phase did not show any statistically significant relationship with reaction time (Table 7). Although the present study focused on the comparison of inter-hemispheric pairs, the detailed Spearman's r and p values of the relationship between reaction time and all combinations of channels were still listed in Appendix 2. Besides the aforementioned significant findings, the Coh(O1, P3) and Coh(O1, P4) in the early visual phase, Coh(C3, O1) in the pre-execution phase and Coh(C3, P3) in the execution phase were also negatively correlated with RT respectively (Appendix 2 & Figure 6).
4. Discussion and Conclusions
The findings of this study supported that even the simple unimanual movement is worked with the interactions of spatial and temporal aspects in the brain (Tables 1, 2, 3 and 4 and Figures 3, 4 and 5). While considering the ERPs findings, we found the occipital regions activated dominantly in the early visual phase. After that, the frontal regions activated to plan the movement initiation and the ongoing process. Thirdly, the central and frontal regions worked together to execute the movement. Finally, the parietal regions were activated to give internal feedback for improving the performance the next time (also see Appendix 3). The similar findings and statements were also delineated by some researchers recently [4,24]. The major features of the brain potential signals were summarized in Table 8.
Few studies have substantiated the contributions of occipital regions to explain the brain mechanism of tapping movements, partly because their experimental tapping tasks lacked the visual characteristics [1,3-5]. In fact, the occipital-parietal regions can be activated during the observation of simple finger movements [15,16]. Therefore, it is reasonable to hypothesize that the occipital regions will activate while executing the task with both of visual and motor components. Consequently, in the present study, the occipital activation was obvious especially in the early phase.
That the frontal regions are working dominantly in the pre-execution phase is also reasonable. Many studies found and mentioned the role of frontal areas during the movement planning process. The timing of pronounced frontal areas was compatible with those findings since movement planning mainly occurred in the stage after the visual processing and before the movement execution.
Pollok at al.  thought the coupling at 8-12Hz (alpha) in a cerebello-thalamic-cortical network reflects one possible mechanism of the motor system during the execution of simple motor tasks. The present study also explored brain issue in the alpha band and found the coherence of inter-hemispheric pairs in alpha band is a sensitive index that can be used to delineate the differences among different electrodes pairs. Besides, the negatively significant relationship between Coh(C3, C4) and RT found in this study is theoretically reasonable. Therefore, combining these results with other studies (e.g. [11, 12]) to explore connectivity issues in alpha band is appropriate.
Kristeva et al.  studied a completely deafferented patient. The movement-evoked potential of this patient could not be observed during simple self-paced index finger flexion with or without visual feedback although the patient's motor behavioral performance was not worse than the controls that was being clear movement-evoked potential. The authors inferred this patient switched his learning strategy from a sensory feedback-driven to a feed-forward mode so that he can compete with the controls. In the experiment of this present study, the movements were guided by visual numbers and the participants were all with intact sensory. Therefore, we can figure out the participants might mainly use the feedback strategy to conduct the unimanual movement so that the movement related potentials were obvious in this present study (Figures 3, 4, and 5). Not surprisingly, in the final post-execution phase, the pronounced negative potentials observed in the parietal regions (Pz, P3, and P4). This also strongly suggests that the feedback mechanism might be run after the movement (execution phase) was conducted.
Obviously, the early positive peaks of Oz, O1 and O2 showed larger and occurred earlier than those of the electrodes in other regions (Figures 3, 4 and 5). Therefore, it is also interesting to further know the coherences during the time lags. We set the time interval of the lags from 100 ms to 150 ms (between the early visual and pre-execution phase). The one-way repeated-measure ANOVA revealed a statistically significant difference among four pairs in this time interval (F(3, 45) = 4.951, p = 0.005). The LSD post hoc test (Table 8) showed the coherence of O1-O2 (0.270) was significantly larger than that of C3-C4 (0.204) and F3-F4 (0.130) and the coherences of P3-P4 (0.222) and C3-C4 were respectively significantly larger than that of F3-F4. There was no significant difference between the pair of O1-O2 and P3-P4 and between the pair of P3-P4 and C3-C4. Similar to the early visual phase, the Coh (O1, O2) pair was the strongest. However, the Coh (O1, O2) pair did not show differences when compared with the pair Coh (P3, P4). This means that the inter-hemispheric connection activates in the occipitoparietal region before the pre-execution phase. After the pre-execution phase is initiated, the inter-hemispheric connection in the centroparietal region will be dominant (Table 5).
In conclusion, the occipital regions functionally work in the early process of visually guided tapping movement. The frontal, central and parietal regions are also responsible for motor planning (pre-execution), motor execution, and action monitoring respectively. The brain potentials and inter-hemispheric coherences of anterior and posterior regions vary with times during visually guided unimanual movements.
The authors thank the participants of this study for their participation. Moreover, this research was supported in part by the grants from the Chang Gung Memorial Hospital (BMRP 424) in Taiwan.
|Coherence values of all electrode pairs in four phases.|
|Coherence pairs||Early visual||Pre-execution||Execution||Post-execution|
|Correlations between reaction time and the interhemispheric coherence of combinations of channels in four phases. The significant findings were highlighted in bold.|
|Coherence pairs||Early visual||Pre-execution||Execution||Post-execution|
- Knyazeva, M.; Koeda, T.; Njiokiktjien, C.; Jonkman, E.J.; Kurganskaya, M.; de Sonneville, L.; Vildavsky, V. EEG coherence changes during finger tapping in acallosal and normal children: a study of inter- and intrahemispheric connectivity. Behav. Brain Res. 1997, 89, 243–258. [Google Scholar]
- Knyazeva, M.G.; Kurganskaya, M.E.; Kurgansky, A.V.; Njiokiktjien, C.J.; Vildavsky, V.J. Interhemispheric interaction in children of 7-8: analysis of EEG coherence and finger tapping parameters. Behav. Brain Res. 1994, 61, 47–58. [Google Scholar]
- Manganotti, P.; Gerloff, C.; Toro, C.; Katsuta, H.; Sadato, N.; Zhuang, P.; Leocani, L.; Hallett, M. Task-related coherence and task-related spectral power changes during sequential finger movements. Electroen. Clin. Neuro. 1998, 109, 50–62. [Google Scholar]
- Rissman, J.; Gazzaley, A.; D'Esposito, M. Measuring functional connectivity during distinct stages of a cognitive task. Neuroimage 2004, 23, 752–763. [Google Scholar]
- Stancak, A.; Lucking, C.H.; Kristeva-Feige, R. The size of corpus callosum and functional connectivities of cortical regions in finger and shoulder movements. Cogn. Brain Res. 2002, 13, 61–74. [Google Scholar]
- Bai, O.; Mari, Z.; Vorbach, S.; Hallett, M. Asymmetric spatiotemporal patterns of event-related desynchronization preceding voluntary sequential finger movements: A high-resolution EEG study. Clin. Neurophysiol. 2005, 116, 1213–1221. [Google Scholar]
- Lewis, P.A.; Wing, A.M.; Pope, P.A.; Praamstra, P.; Miall, R.C. Brain activity correlates differentially with increasing temporal complexity of rhythms during initialisation, synchronisation, and continuation phases of paced finger tapping. Neuropsychologia 2004, 42, 1301–1312. [Google Scholar]
- Pfurtscheller, G.; Neuper, C.; Berger, J. Source localization using event-related desynchronization (ERD) within the alpha band. Brain Topogr. 1994, 6, 269–275. [Google Scholar]
- Sailer, A.; Dichgans, J.; Gerloff, C. The influence of normal aging on the cortical processing of a simple motor task. Neurology 2000, 55, 979–985. [Google Scholar]
- Andrew, C.; Pfurtscheller, G. Event-related coherence during finger movement: a pilot study. Biomed. Tech. 1995, 40, 326–332. [Google Scholar]
- Roth, N.; Battig, K. Effects of cigarette smoking upon frequencies of EEG alpha rhythm and finger tapping. Psychopharmacology 1991, 105, 186–190. [Google Scholar]
- Deiber, M.P.; Caldara, R.; Ibanez, V.; Hauert, C.A. Alpha band power changes in unimanual and bimanual sequential movements, and during motor transitions. Clin. Neurophysiol. 2001, 112, 1419–1135. [Google Scholar]
- Kudo, K.; Miyazaki, M.; Kimura, T.; Yamanaka, K.; Kadota, H.; Hirashima, M.; Nakajima, Y.; Nakazawa, K.; Ohtsuki, T. Selective activation and deactivation of the human brain structures between speeded and precisely timed tapping responses to identical visual stimulus: an fMRI study. Neuroimage 2004, 22, 1291–301. [Google Scholar]
- van der Lubbe, R.H.; Wauschkuhn, B.; Wascher, E.; Niehoff, T.; Kompf, D.; Verleger, R. Lateralized EEG components with direction information for the preparation of saccades versus finger movements. Exp. Brain Res. 2000, 132, 163–178. [Google Scholar]
- Babiloni, C.; Babiloni, F.; Carducci, F.; Cincotti, F.; Cocozza, G.; Del Percio, C.; Moretti, D.V.; Rossini, P.M. Human cortical electroencephalography (EEG) rhythms during the observation of simple aimless movements: a high-resolution EEG study. Neuroimage 2002, 17, 559–572. [Google Scholar]
- Babiloni, C.; Del Percio, C.; Babiloni, F.; Carducci, F.; Cincotti, F.; Moretti, D.V.; Rossini, P.M. Transient human cortical responses during the observation of simple finger movements: a high-resolution EEG study. Hum. Brain Map. 2003, 20, 148–157. [Google Scholar]
- Olfield, R. C. The assessment and analysis of handedness: The Edinburgh handedness inventory. Neuropsychologia 1971, 9, 97–113. [Google Scholar]
- Ehrenstein, W. H.; Arnold-Schulz-Gahmen, B. E.; Jaschinski, W. Eye preference within the context of binocular function. Graefe's Arch. Clin. Exp. Ophthalmol. 2005, 243, 926–932. [Google Scholar]
- Mendola, J. D.; Conner, I. P. Eye dominance predicts fMRI signals in human retinotopic cortex. Neurosci. Lett. 2007, 414, 30–34. [Google Scholar]
- Meng, L. F.; Lu, C. P.; Chen, B. W.; Chen, C. H. Fatigue induced reversed hemispheric plasticity: A brain electrophysiological study. Lecture Notes in Computer Science: Neural Information Processing 2006, 4232, 65–71. [Google Scholar]
- Meng, L. F.; Lu, C. P.; Chen, C. H. Unskilled finger key pressing and brain coherence. Lecture Notes in Computer Science: Computers Helping People with Special Needs 2006, 4061, 437–441. [Google Scholar]
- Brain Products GmbH. In Brain Vision Analyzer User Manual; 2002; BrainProducts: Munich; pp. 55–56.
- Geisser, S.; Greenhouse, S. On methods in the analysis of profile data. Psychometrika 1959, 24, 95–112. [Google Scholar]
- Calmels, C.; Holmes, P.; Jarry, G.; Hars, M.; Lopez, E.; Paillard, A.; Stam, C. J. Variability of EEG synchronization prior to and during observation and execution of a sequential finger movement. Hum. Brain Map. 2006, 27, 251–266. [Google Scholar]
- Pollok, B.; Gross, J.; Muller, K.; Aschersleben, G.; Schnitzler, A. The cerebral oscillatory network associated with auditorily paced finger movements. Neuroimage 2004, 24, 646–655. [Google Scholar]
- Kristeva, R.; Chakarov, V.; Wagner, M.; Schulte-Monting, J.; Hepp-Reymond, M.C. Is the movement-evoked potential mandatory for movement execution? A high-resolution EEG study in a deafferented patient. Neuroimage 2006, 31, 677–685. [Google Scholar]
|Table 1. The one-way repeated measures ANOVAs were used to compare the mean amplitudes among anterior-posterior electrodes in different phases over midline, left and right scalp locations.|
|F-value||F(1.246, 18.695)||F(1.634, 24.513)||F(1.991, 29.860)||F(1.522, 22.837)|
|= 23.376; p=.000||= 6.833; p=.007||= 11.496; p=.000||= 15.670; p=.000|
|F-value||F(1.269, 19.035)||F(1.461, 21.910)||F(1.636,24.534)||F(1.608, 24.124)|
|= 16.094; p=.000||= 19.628; p=.000||= 8.637; p=.002||= 13.453; p=.000|
|F-value||F(1.113, 16.700)||F(1.919, 28.781)||F(1.840, 27.594)||F(1.414, 21.210)|
|= 16.896; p=001||= 18.599; p=.000||=7.127; p=.004||= 13.543; p=.001|
|Table 2. LSD post-hoc tests to compare the differences of mean amplitudes between the pairs of electrodes on the midline during the four phases.|
|Oz vs. Pz||2.673**||001||-0.417||.250||-0.473||.138||1.790***||.000|
|Oz vs. Cz||4.474***||.000||0.402||.403||-1.588***||.000||1.276**||.001|
|Oz vs. Fz||4.232***||.000||1.226*||.034||-1.612**||.002||0.676||.096|
|Pz vs. Cz||1.801***||.000||0.819**||.005||-1.116***||.000||-0.514*||.032|
|Pz vs. Fz||1.559**||.001||1.643**||.001||-1.139*||.014||-1.113**||.003|
|Cz vs. Fz||-0.243||.202||0.823**||.001||-0.024||.925||-0.600**||.001|
Note.*p < .05**p < .01***p< .001
|Table 3. LSD post-hoc tests to compare the differences of mean amplitudes between the pairs of electrodes in the left hemisphere during the four phases.|
|O1 vs. P3||1.623*||.021||-0.580*||.028||-0.942**||.002||1.296***||.000|
|O1 vs. C3||3.550**||.001||0.702||.114||-1.566**||.001||0.898**||.005|
|O1 vs. F3||3.265**||.001||1.646**||.001||-1.379*||.011||0.222||.485|
|P3 vs. C3||1.927***||.000||1.282***||.000||-0.623*||.014||-0.398*||.042|
|P3 vs. F3||1.641***||.000||2.226***||.000||-0.437||.231||-1.074**||.001|
|C3 vs. F3||-0.285||.147||0.944***||.000||0.187||.453||-0.676***||.000|
Note.*p < .05**p < .01***p < .001
|Table 4. LSD post-hoc tests to compare the differences of mean amplitudes between the pairs of electrodes in the right hemisphere during the four phases.|
|O2 vs. P4||2.251**||.004||-0.779*||.011||-.504||111||1.155***||.000|
|O2 vs. C4||4.120***||.000||0.121||.752||-1.469**||.003||1.129***||.000|
|O2 vs. F4||3.835**||.001||1.708**||.002||-1.556*||.013||0.268||.431|
|P4 vs. C4||1.870***||.000||0.900**||.002||-.965**||.002||-0.026||.873|
|P4 vs. F4||1.584**||.001||2.488***||.000||-1.053*||.038||-0.887**||.004|
Note.*p < .05**p < .01***p < .001
|Table 5. The one-way repeated measure ANOVAs applied to compare the coherence strength among inter-hemispheric pairs during the different phases.|
|F-value||F(1.818,27.274) =5.553; p=011||F(1.816,27.243) =5.167; p=015||F(2.133,31.991) =3.362; p=.044||F(1.461,20.459) =5.689; p=017|
|Table 6. LSD post-hoc tests applied to compare the difference of coherence strength between anterior posterior inter-hemispheric electrode pairs.|
|O1-O2 vs. P3-P4||.014||.784||-.061||174||-.053||.304||-.042||.382|
|O1-O2 vs. C3-C4||.020||.697||-.084||.193||-.070||.254||-.046||.434|
|O1-O2 vs. F3-F4||.141**||.008||.095||.188||.075||.270||.125||.101|
|P3-P4 vs. C3-C4||.005||.836||-.023||.502||-.016||.606||-.003||.913|
|P3-P4 vs. F3-F4||.127***||.000||.156**||.002||.129**||.004||.167***||.000|
|C3-C4 vs. F3-F4||.121**||.001||.179**||.001||.145*||.012||.170***||.000|
Note.*p < .05**p < .01***p < .001
|Table 7. Spearman's r correlations between reaction time and the inter-hemispheric coherence of combinations of channels in four phases. Only the pair of C3-C4 in the execution phase significantly correlated to reaction time (highlighted in bold).|
|Coherence pairs||Early visual||Pre-execution||Execution||Post-execution|
|Table 8. Summarized major localized features of the brain potential signals.|
|Potentials & Coherences||Early visual||Pre-execution||Execution||Post-execution|
|P310-420||C3||Fz, Cz||F4, C4|
Note.1.L = left hemisphere electrodes (O1, P3, C3, F3), M = electrodes on midline location (Oz, Pz, Cz, Fz), R = right hemisphere electrodes(O2, P4, C4, F4).2.The strongest electrode(s) in each phase were listed in the table according to the results of post hoc LSD statistics (also see Table 2, 3, 4, 6).
|Table 9. LSD post-hoc tests applied to compare the difference of coherence strength between anterior posterior inter-hemispheric electrode pairs from.|
|To compare the|
|p||To compare the|
|O1-O2 vs. P3-P4||.048||.243||P3-P4 vs. C3-C4||.018||.554|
|O1-O2 vs. C3-C4||.066*||.039||P3-P4 vs. F3-F4||.092**||.008|
|O1-O2 vs. F3-F4||.141*||.010||C3-C4 vs. F3-F4||.074*||.043|
Note.*p <.05**p < .01***p <.001
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