1. Introduction
1.1. Importance of perceptual process for goal-directed movements
Goal directed movements are organized via perceptual information that is relevant to movement situation. Even in a simple movement of reaching out a glass on a table and grasping it, the configuration and orientation of hand and fingers should be organized with respect to the size, shape, and orientation of the glass. According to the study on prehensile movements, the size of aperture shaped by an index finger and a thumb to grasp an object was organized with respect to the size of the object such that the peak aperture was observed well before the hand reaches the object and the peak value was linearly scaled to the object’s size (Jeannerod, 1981, 1984). When a mechanical perturbation was applied to an upper arm during a prehensile movement to assist or disturb the hand reaching an object, the well-coordinated reaching and grasping components was observed in terms of timing the grasping movement with respect to the moment of the hand reaching the object (Haggard & Wing, 1995). For pre-shaping the aperture and temporally organizing the reaching-grasping components, perceptual information about the object size and the time to the hand-object contact is crucial. Therefore, how perceptual process plays a role for organizing a movement and what/how perceptual information is utilized for the movement organization have been major issues in the study of motor control.
1.2. Two cortical pathways for visual information processing
According to the study on the cortical function for visual processing, there are two visual streams from the primary visual cortex to the posterior parietal cortex (the dorsal stream) and to the inferotemporal cortex (the ventral stream). Lesions to one of these visual pathways induce different types of perceptual-motor deficits. The lesions associated with the dorsal stream (e.g., the occipitoparietal region) induce the inability to shape the prehensile aperture for reaching and grasping an object properly but with no difficulty in visually discriminating one such object from another. Contrary to it, the lesions associated with the ventral stream (e.g., the ventrolateral region) leads to the reverse deficit (i.e., the inability to visually discriminate the object with the intact aperture control for grasping). Therefore, these findings have been regarded as the evidence of two visual processing pathways, one for visuomotor control via the dorsal stream, and the other for cognitive visual processing via the ventral stream (Goodale et al., 1994).
1.3. Cognitive aspect of perceptual-motor process for executing task performances
From a computational or information processing point of view(e.g., Schmidt& Lee, 1999), the cognitive process of recognizing the identity of an object to be grasped and planning how to produce a grasping movement with respect to the recognized object’s shape, size, and orientation is central for organizing a prehensile movement.Such cognitive aspect of visual information processing for achieving perceptual-motor tasks with respect to a target object has been studied by an experimental paradigm using an target object, such as, the Ebbinghaus figure or Müller-Lyer figure that induces a visual illusion about the object size.
In this experimental paradigm, the following two perceptual-motor tasks have been used: 1) reaching out toward and grasping a visual object with an index-thumb pinch grip, and 2) assessing the size of the same visual object and indicating the estimated size by the same aperture as used to grasp the object. These two tasks share a qualitatively similar perceptual-motor process in terms of producing the same aperture configuration based on the same visual information about the target figure.However, the involvement of cognitive process (i.e., recognizing the target object, estimating its size, and deciding the grasping aperture size with respect to the perceived object size) seems to be different. In the size-estimation task, the production of the aperture configuration requires explicit identification of the size of the figure and the particular aperture size needs to be associated arbitrary with respect to the particular perceived size of the figure. In this sense, executing this task is cognitive process-oriented (Ranganathan& Carlton, 2007). As for the reaching-grasping task, the study on modeling a prehensile movement with nonlinear equations of motion, which include a perceptual variable as a parameter to modulate the dynamics of the movement, demonstrated the spatial and temporal characteristics of upper limb kinematics in the prehensile motion(Schöner, 1994; Zaal, 1998). This result supports the idea in the theoretical frameworks of the ecological perspective (Lee, 1980; Turvey & Kugler, 1984; Warren, 1990) and dynamical system account (e.g., Kelso, 1995; Schöner & Kelso, 1988) for motor coordination such that organizing a prehensile movement may not necessarily involve a cognitive process, such as the object identification and the arbitral object-aperture size association. From the above perspective, the perception of a target object and an action with respect to it are mutually dependent in the grasping task, whilst those in the size-estimation task are uncoupled and mediated via the cognitive process.
The original findings in the seminal studies using the paradigm were such that visual discrimination or perception about the object’s size was susceptible to the illusory object, but the grasping aperture with respect to it was not (e.g., Aglioti et al., 1995; Haffenden & Goodale, 1998). An argument based on these findings has been such that cognitive perceptual processing and motor production process can be dissociable (Goodale & Milner, 1992) and the theoretical confrontation between the cognitive account for information processing in organizing a movement (e.g., Schmidt & Lee, 1999) and the ecological perspective for the perceptual-motor process (e.g., Lee, 1980; Turvey & Kugler, 1984; Warren, 1990) can be ascribed to these two visual streams (Tresilian, 1995). However, contradictory result has been reported such that the effect of the misperception about the object size was also observed in a prehensile movement (e.g., Franz, et al., 2000; Franz, et al., 2001). Other studies also found the susceptibility to the illusory object in a prehensile movement and suggested: the involvement of the ventral stream involved in a grasping motion with respect to a complex object (McIntosh, et al., 2004); the partial, not exclusive, dissociation between the two pathways (Ellis, et al., 1999); a multiple visuomotor process involving both pathways (Westwood, et al., 2000b); and the execution of prehensile movements by involving the ventral stream via the supplementary motor areas (Lee & van Donkelaar, 2002).
1.4. Examination of cortical activities in perceptual-motor performances
The above findings suggest that integrated function of cortical networks for executing the visuo-motor task needs to be considered for fully understanding the mechanism of the perceptual-motor process. From this view, the present study examines the cortical activation pattern during the reaching-grasping and the size-estimation performances. A particular focus for this investigation is on how cortical activities associated with the dorsal and ventral streams are involved in the perceptual-motor process for the task performances.
For this investigation, it is necessary to assess the effect of the perception of the target object size on the task execution. Therefore, the two task movements were produced with respect to a neutral object and an object inducing a size illusion (the Ebbinghaus figure). The illusion effect on the aperture configuration indicates that cognitive processing is involved in the task execution. In the case of the size-illusion effect observed in the size-matching performance but in the grasping, the observed cortical activitiesare interpreted in terms of the differences in association between cognitive processing and movement execution.If distinctive activation patterns between the two task performances are observed, it may be attributed to the difference in the perceptual-motor process associated with the involvement of cognitive processing. Conversely, if no difference in the cortical activity patterns between them, it may suggests some qualitative similarity in the cortical process between the different task executions.
On the other hand, the illusion effect on both of the tasks performances indicates that cognitive process is involved even in the reaching-grasping performance. In this case, the point of comparison in cortical activities between the two task conditions may not whether the dorsal and ventral streams are exclusively functioned, but how worked as an integrated cortical network. If difference in the pattern of cortical activities is observed, it reflects qualitative difference in the participation of cognitive process in the task movement execution.
1.5. Examination of the brain dynamics related to task execution
To investigate the cortical activity,electroencephalograph (EEG) during the task performance was analyzed in terms of frequency domain. Two different analyses, which potentially shed light on the different aspects of cortical activities, were conducted: the change of the EEG frequency power spectrum that was time-locked to the task event (Event-related spectral perturbation: Makeig, 1993; for review, Pfurtscheller et al., 1999a) and the coherence between EEGs of two electrodes (Event-related coherence: e.g., for review, Hummel & Gerloff, 2006; Schlögl & Supp, 2006; Pfurtscheller& Andrew, 1999).
Event-related spectral perturbation (ERSP) quantifies the degree to which the amplitude of a particular frequency band of ongoing EEG attenuates or enhances in response to a stimulus event, which is termed event-related desynchronization (ERD) or synchronization (ERS), respectively. ERD has been regarded as representing an activated cortical state with which the processing of sensory, motor, or cognitive information is enhanced and the excitability of cortical neurons is increased (Pfurtscheller, 2001; Steriade et al., 1991),whilst ERS has been thought that it reflects a deactivated cortical state with reduced information processing or none at all and decreased cortical excitability(Neuper &Pfurtscheller, 2001; Pfurtscheller, 1992). However, the knowledge about the ERS has been accumulated such that the meaning of ERS is more than the state of decreased cortical excitability. The inhibitory activity of ERS can play a functional role to accentuate a task-related information processing by inhibiting other cortical areas and/or to deactivate some cortical network depending on a task context/situation (Neuper &Pfurtscheller, 2001;Hummel et al., 2002, 2006; Suffczynski et al., 1999).
Coherence refers to correlation between two sets of time-series in frequency domain. Given a cross-spectral density matrix by two time series (i.e., EEG data from two electrodes), coherence is obtained by the ratio of cross-spectral to spectral of each time series, whichindicates the degree of relative synchrony between the two time series, as shown below:
where
For these two analyses, the author and his colleagues analyzed ERSP in the reaching-grasping and the size-estimation performances (Katsumata, et al., 2009). Given the findings by the previous analysis that revealed the cortical activation pattern for the task execution, the present study conducts the EvDirCoh analysis for the data to investigate the cortical communication across different sites. Thereby, it is attempted to capture the brain dynamics characteristic to the perceptual-motor process for the task execution. In this chapter, experimental and analytical methodology for both of ERSP and EvDirCoh and those results are reported, and the dynamics of cortical activation is discussed in terms of the association of cognitive aspect with respect to the perceptual-motor process.
2. Methods
2.1.Participants
10 healthy participantsvolunteered for the experiment (seven males and three females with an average age of 29 ± 6.7 years).Their preferred hands for performing task movements were right hand and they were assessed as being right-handed by the Edinburgh inventory. All procedures were approved by an ethics committee. Each participant signed an informed consent form after the experimenter explained the purpose and procedure of the experiment.
2.2. Task and task conditions
Two types of perceptual-motor tasks were examined (Figure 1): (1) the participants reached out with their right hands to a target object displayed on the computer screen and touched it so as to grasp it with a pinch grip produced by the index finger-thumb aperture (
Two different figures were usedas the target objects: (1) a single circle with a diameter of 3 cm (
2.3. Setup
The aperture movementwas measured in terms of the angular excursion of the metacarpophalangeal joint by attaching a Goniometer (DKH, Tokyo, Japan) to the index finger. To this end, casts were attached to the proximal and distal interphalangeal joints of index finger and thumb. Thereby, the motions of these joints were constrained such that the aperture size was produced by only the movement of the index finger-metacarpophalangeal joint. This measure of the joint excursion was used to examine the grasping aperture. A 64-channel data collection system (ESI-64 Channel System, Neuroscan, Charlotte, NC) was used to collect Electroencephalogram (EEG). The visual display of the target figure, a beep sound to cue the participant to initiate the task movement, a trigger pulse to synchronize the Goniometer data with EEG data were operated by a data collection software (LabView, National Instruments, Austin, TX)
2.4. Procedure
Preliminary to the data collection, the effect of the Ebbinghaus figure for each participant was tested by the method of limit. By verbally judgingthe comparisonbetween the size of a center circle of the Ebbinghaus figure with a comparison object of a single circle with different sizes, the perceptual threshold for detecting the size difference was examined (mean and standard deviation: 2.8±0.15 cm, as opposed to 3 cm of the center circle diameter of the Ebbinghaus figure). A t-test confirmedthat the participants visually perceived the
The procedure of data collection was as follows(Figure 2). At the beginning of each trial, a “+” symbol was displayed at the center of the screen as avisual fixationpoint. After the participant clicked a computer mouse with their left hands, the fixation point disappeared. 2000 ms after the fixation offset, the target figure was shown at the center of the display. 2000 ms after thetarget onset, a beep sound was produced to cue the participants to initiate the task movements. 5000 ms after the auditory cue, the target figure disappeared,and it was enough time for the movement to be completed.Thereafter, the fixation point appeared for next trial. In instructing a task procedure to the participants, it was emphasized that the task was not for testing a reaction time nor a speed of task movement (The mean time of the movement initiation after the beep: 502±203 ms).The 80 trials of task movements for each condition were divided into two blocks consisting of 40 trials and performed in series. The order of
2.5. Data collection and reduction
The movement of index finger metacarpophalangeal joint was recorded (400Hz) by the Goniometer and a second order band-pass filter with a cutoff frequency of 5 Hz was used for smoothing the data. The angular velocity of the joint was obtained by numerical differentiation and smoothed by a second order band-pass filter (cutoff frequency of 5 Hz).EEG was collected from 64 scalp electrodes of the international 10-20 system referenced to the left earlobe (AC-mode, a sampling rate of 1000 Hz, a gain of 500, and a pass-band of 0.05-100 Hz). All electrodes were required a resistance of less than 2 Ω. To detect horizontal and lateral eye movements as well as blinks, electrooculography (EOG) of the right eye was collected. The data sets of EEG, joint movements, and auditory beeps were stored in the hard-drive of a desktop PC for off-line analysis.In the analysis, the EEG data was down-sampled to 300 Hz to conserve the memory of the PC and to save time consuming for calculating the coherence for each time-window within each frequency band. Failed trials due to initiating the movement before the auditory cue were eliminated from the analysis. The trials with an eye blink and noisy EEG data were also eliminated through visual inspection of EEG data profiles. EEG data was investigated with respect to the moments of the target onset and the initiation of the joint motion. To this end, EEG data sets for each trial were epoched from 500 ms before to 1000 ms after the target onset as well as after the initiation of the joint motion. Given the time from the movement onset to the maximum aperture of626±198 msec, this time window was enough to cover the movement duration to produce the aperture configuration.For analysing EEG data with respect to specific frequency components, following frequency bands were used, delta: 0.5-4 Hz, theta: 4-8 Hz, alpha: 8-13 Hz, beta: 13-30 Hz, gamma: 30-45 Hz, and higher gamma: 45Hz-100Hz.
2.6. Analysis
2.6.1. Kinematics of task performances
While reaching to grasp an object, the maximum aperture by the index finger and thumb is linearly related to the object’s size (Jeannerod, 1981, 1984). Since this maximum preshape aperture is formed well before the hand has any contact with the object, this measure has been interpreted as reflecting the size estimate used in the perceptual-motor process in the prehensile activities. Based on this finding, the maximum aperture has been used as a dependent variable in many studies to investigate the influences of visual illusions on grasping (e.g., Haffenden & Goodale, 1998; Westwood,et al, 2000a; Franz et al., 2001).Because of this, the peak joint angle measured by the Goniometer was used as the measure of the maximum aperture for the prehensile movement. The time of the joint movement initiation was determined by the start of flexion movement of the metacarpophalangeal joint,at which the velocity of the joint kinematics started to show a positive value. This measure was used to epoch the EEG with respect to the onset of task movement.
2.6.2. Analysis of the event-related spectral perturbation
The event-related spectral perturbation (ERSP) analysis was conducted by using a toolbox with graphic interface, EEGLAB, that is operated under the MATLAB environment (Delorme & Makeig, 2004). The epoched window of 1500 msec in a single trial was divided into brief subwindows of 214 msec with a sliding latency of 3.3 msec, corresponding to 98 % overlapping between the successive subwindows. Wavelet analysis using sinusoidal transform was conducted for each of the subwindowed-epochs, and itobtained power spectrum estimates ranging from 0.59 Hz to 99.6 Hz with a frequency increment of 0.59 Hz. The power spectra over the sliding latency windows were computed for each trial, and normalized by subtracting baseline spectrum from each spectrum estimate. The baseline spectra were obtained by computing the mean spectra of the EEG data windowed for 500 msec before the moment of the target onset. Mean ERSP was obtained on each participant basis by computing the average of the baseline-normalized ERSP across all trials. To capture visually the global picture of ERSP, the grand average ERSP across the participants was plotted on the 3Dtime-frequency space (a spectrogram) on which the power spectrum of each frequency (in dB) at each sliding time-window was indicated by a colored surface.
The significance of increase/decrease in the power spectra with respect to the baseline spectra was examined for the mean ERSP in each time-frequency component of the spectrogram on each participant basis.To this end, non-parametric tests (a two-tailed Wilcoxon signed-rank test) was conducted with the null-hypothesis of no difference between the baseline spectra and spectra of each time-frequency components (i.e., ERSP value is zero) and the significant level of
In the previous study by the author and his colleagues (Katsumata et al., 2009), the ERSP analysis described above was conducted for 55 electrodes over the cortex with further analysis to summarize the characteristics of those ERSP profiles.For reporting the results in this chapter, ERSPs of the electrodes on the left-hemisphere were focused.
2.7. Analysis of event-related directed coherence
Event-related directed coherence (EvDirCoh) was calculated by the program operated under the MATLAB environment, which was developed by Takahasi, Baccalá and Sameshima (2008). For the calculation, the EEG time series were detrended before coherence calculation, Nuttall-Strand algorithm was used for estimating multivariate autoregressive models (MAR), and Akaike information criterion (AIC) was used for the criterion to choose theMAR order.The coherence was calculated with the time-window of 60ms with 30 ms increment, resulting in 15 time-windows from 500 ms to 1000 ms after the onset of target figure and task movement, and with respect to each of frequency bins. The time windows and frequency bins were set coarser than those used for the ERSP analyzes, since executing the program for calculating directed coherence was much more time consuming, given the number of electrode combinations for calculating the coherence. However, the preliminary analysis, for some of the data, using the finer time windows and frequency bins confirmed that this does not lose information about the global picture of coherence pattern over time and across frequencies.
Mean EvrDirCoh across trials within each participant was obtained for
Calculating the coherence of all the electrodes available was redundant. Even in the left-hemisphere, there were 24 electrodes leading to 23 time-frequency plots in one direction of EvDirCoh and another 23 plots for the other direction. Therefore, the present study focused on the electrodes in the left-hemisphere, which cover the cortical sites associated with the dorsal/ventral stream and visuomotor process in a hand movement against a visual target (O1, PO3, PO7, P3, P7, CP3, TP7, C3, T7, FC3, FT7, F3, and F7), but it still lead to 299 plots for coherence in the one direction and another 299 for the other direction. Since the primary aim of the study was to capture the global characteristics of EvDirCoh pattern over the cortex, it was attempted to summarize the results of the EvDirCoh plots in the following procedures.
2.7.1. Electrode combinations showing marked EvrDirCoh
To capture what electrode combinations revealed marked EvrDirCoh, the rate of significant EvrDirCoh was calculated for each time-frequency plot. To this end, the number of time-frequency components on a time-frequency plane within a particular time-window, which showed the significant EvrDirCoh, was divided by the total number of time-frequency components within the corresponding time-window, and multiplied by 100 to show the result in percent. The ranges of time window were: (1) 500 ms from the target onset; (2) 500 ms before the onset of task movement to 100 ms after the onset; and (3) 100 ms after the movement onset. The same calculation was done for EvrDirCoh in the other direction. In the figure, the higher value means that more time-frequency components revealed the significant EvrDirCoh.
2.7.2. Pattern of change in EvrDirCoh over time
To capture the change of EvrDirCoh over time with respect to the onset of target figure and task movement, the significant EvrDirCoh values within each time window across all the frequency bins, were summed up respectively, and plotted over time. The reason for summing up the values rather than obtaining mean was to accentuate visually the overall change of EvrDirCoh pattern that appeared on the time-frequency plane
2.7.3. Frequency band showing marked EvrDirCoh
To capture what frequency band revealed marked EvrDirCoh, the rate of significant EvrDirCoh was calculated by the number of time-frequency components, within the frequency band, showing the significant EvrDirCoh, divided by the total number of time-frequency components within the corresponding frequency band. The rate was obtained for each of the focused electrode by all the time-frequency plots across all the electrode combinations.
3. Results
3.1. The maximum aperture
The perception about the size of the target figure was examined in terms of the maximum angle of the index finger metacarpophalangeal joint during the aperture motion. A 2×2 repeated-measure ANOVA with the main effects of the tasks (
3.2. ERS/ERD with respect to the target onset
Figure 5-a shows exemplary spectrograms in F3, FC3, C3, CP3, P3, PO3, and O1 with respect to the target onset in
3.3.ERS/ERD. with respect to the movement onset
Exemplary spectrograms with respect to the movement onset in
In summary, both of
3.4. Electrode combinations showing the marked coherence (EvDirCoh)
The rate of significant EvDirCoh on each time-frequency plane across electrode combinations was visualized in Figure 7 to Figure 9. Based on these figures,the results of electrode combinations that showed the characteristics of remarked coherences were reported as below. Refer to Figure 6 for the electrode locations on the left-hemisphere, which correspond to the location of each cell on the plot. Figure 7 shows the rate of significant EvDirCoh after the target onset, and Figure 8 and Figure 9 show the rate before and after the movement onset (i.e., the movement preparation and execution phase), respectively.
3.4.1. The occipital region (O1) in response to the target onset and during the movement production
As appeared in O1, prominent EvDirCoh were observed after the onset of target figured, which implies response to the visual input about the target. The coherences between O1 and other sites were more prominent in response to the visual target, after which those were restricted to a few electrodes. In
3.4.2. Electrodes relevant to the dorsal stream of visual processing (PO3, P3, and CP3)
After the target onset, in
3.4.3. Electrodes relevant to the ventral stream of visual processing (PO7, P7, TP7, and T7)
After the target onset, PO7/P7/PT7/T7 in
3.4.4. Electrodes located on the frontal region (F7, F3, FC3, and FT7)
After the target onset, EvDirCoh from F7/FT7/FC3 to posterior temporal region (PO7/P7) was observed in
3.4.5. The electrode located on the motor cortex for movement production (C3)
The focus of coherence in C3 is on the preparation and execution of task movements. The remarkable feature before the movement initiation was that C3 received EvDirCoh from divergent areas in
3.5. Coherence profile over time
According to Figure 10, all most all of the analyzed electrodes showed increase in the coherence after the target onset, which lasted for 500-600 ms. This indicates that there were communications across different cortical sites, possibly for processing information about the target figure for the up-coming task execution. Regardless of task conditions (
O1 that corresponds to the visual cortex in the left-hemisphere showed the increase in some of coherences before the initiation of the movement and lasted during the movement execution. This was remarked in
As for
3.6. Frequency band showing the remarked coherence
Figure 12 shows the rate of significant EvDirCoh within each frequency band. In this figure, higher value indicates that more time-frequency components revealed significant EvDirCohwithin corresponding frequency band. The figure can also indicate what frequency band was dominant across all the frequency bands.
With respect to the target onset, the lower frequency bands (delta, theta, and alpha) appeared to be more dominant compared to the beta, gamma, and higher gamma bands in the most of electrodes. Some of the electrodes in
4. Discussion
4.1. The size-illusion effect for Grasping and Matching
The comparison of task performances in terms of the peak aperture angle showed a significant difference between the tasks (
The effect of visual illusion on a prehensile movement task to the illusory object as well as on a perceptual discrimination task have also reported in some earlier studies (e.g., Franz et al., 2000, 2001; Glover & Dixon, 2002; Mendoza et al., 2005), which contradicts to the hypothesis of dissociative systems for perception and action by the ventral/ dorsal stream (Aglioti et al., 1995; Goodale& Jakobson, 1992; Haffenden & Goodale, 1998). These illusion effects are attributed to the task conditions, such as, complex target figures (McIntosh et al., 2004), movement production in an open-loop manner (i.e., movements to a remembered object: Heath et al., 2005; Westwood et al., 2000a), and online reorganization of the grasping aperture in response to the change of object size (Heath et al., 2006b). These findings have led to arguments such that: the motor system integrates the ventral and dorsal streams (Ellis et al., 1999); the sensorimotor system can operate independently of the cognitive/perceptual system (Flanagan & Beltzner, 2000); a prehensile movement is produced through multiple visuomotor processes (Westwood et al., 2000b); the ventral stream has connection to the prefrontal areas and, thereby, it may associate with the visuomotor control of a prehensile action (Lee & van Donkelaar, 2002); and online prehensile control may be produced through egocentric and allocentric visual information processing (Heath et al., 2006a).
Even though there are functionally and anatomically distinctive visual pathways at the cortical level, executing a visuomotor task may be achieved through an integrative process of these pathways. These visual pathways may be involved differentially in task-dependent manner. For instance, if a pure visual discrimination task such that participants are asked to discern which of two objects looks larger/smaller, it is expected that a cortical activity associated with the ventral stream may be dominant (Farrer et al., 2002; Westwod et al., 2000b). Likewise, if reaching or grasping needs to be produced in an open-loop manner (e.g., a visual object is occluded before or right after the onset of a prehensile movement), the movement production needs to be based on the memory of the object shape (Heath et al., 2005; Westwood et al., 2000a; Westwood et al., 2000b). In these cases, the nature of task performance requires cognitive processing, which will be achieved via the ventral stream dominantly. Given the above results about the Ebbinghaus effect, cortical activation patterns revealed in ERSP and EvDirCoh need to be interpreted in terms of how cortical sites associated with the dorsal/ventral stream in an integrated fashion. In this sense, the difference in the ERSP and/or EvDirCoh pattern between
4.2. Comparison of ERSP pattern between the task conditions
4.2.1. ERD observed in Grasping and Matching
ERD has been regarded as representing an activated cortical state and thereby sensory, motor, and/or cognitive processing is enhanced. Therefore, the cortical regions showing ERD during the task performances can be regarded as functionally associating with the perceptual-motor process for the tasks. The comparison of the ERSP patterns between
The ERD after the target onset were observed not only in the occipital region (i.e., visual area), but also in the central-parietal regions. This implies some visual processing rather than just responding to the visual stimulus, which could possibly be associated with the task execution. The ERD in occipital-parietal regions was observed with respect to the aperture movement onset as well as after the target onset. Based on that the posterior parietal cortex functions for the integration of the sensory information as well as the visuomotor coordination (Buneo & Andersen, 2006; Burnod et al., 1999; Culham et al., 2006; Darling et al., 2007; Stein, 1995), the occipital-parietal ERD can be interpreted that the visual information was further processed via the higher level of visual areas toward the movement execution.
The ERD in F3, F4, FC3, FC4, C3 and C4 in Figure 5 indicates that the frontal and pre-frontal areas were involved in the task execution. This frontal area ERD was observed not only in
4.2.2. ERS as the characteristic of Grasping
The notable feature in the ERSP spectrogram was the ERS observed not in
Given the above findings, the gamma band ERS pattern during
In this analysis, the two oscillatory components, one showing ERD and the other ERS, were observed in a single electrode in the parietal-occipital regions. Different frequency oscillations embedded at a single electrode are interpreted as one neural network generating different types of oscillations (Pfurtscheller & Lopes da Silva, 1999). Therefore, the ERD in both of
4.3. Cortical communication in terms of EvDirCoh and the nature of task execution process
According to the feature of the rate of significant EvDirCoh, which captures the pattern of coherence appeared on the time-frequency plane, the following characteristic EvDirCoh was observed in each of the task performances. The coherence analysis has been applied to time series of neural system based on the assumption that the coherence reflects the functional connectivity, neural communication and/or signal transmission between two or more neural activities (Sameshima & Baccalá, 1999). The results in the present study are interpreted from this perspective.
After the target onset, the significant coherences were dominant amongst the lower frequency (the delta, theta, and alpha bands in Figure 12). This implies that the visual processing in response to the target object was achieved by the neural communication with those frequency bands. As opposed to it, the gamma and higher gamma bands became prominent after the movement onset. Those prominent frequency bands were observed particularly in CP3, C3, FC3, PO7, P3, P7, and T7 in
As for the temporal characteristics of EvDirCoh, the most of the analyzed electrodes showed increase in EvDirCoh after the target onset and lasted for approximately 500 ms. This EvDirCoh increase may reflect the communications across different cortical sites for processing information about the target figure for the up-coming task execution. With respect to the movement execution in
4.3.1. Coherence relevant to the task events (the target onset and the movement preparation-execution)
After the target onset, the visual cortex (O1) and other areas showed coherence to/from different cortical site. This may implies the response to the visual target. Particularly, the parietal-occipital region (PO3 and PO7) in
In the movement preparation phase, PO7 and PO3 in
The remarkable feature of EvDirCoh in
4.3.2. EvDirCoh characteristics associated with the dorsal/ventral streams
The visual information from the primary visual cortex is transmitted further via the dorsal stream to the middle temporal area and the medial superior temporal area, as well as via the ventral stream to the posterior inferior temporal cortex and the anterior inferior temporal cortex(Kandel et al., 2000; Zigmond et al., 1999). The electrodes PO3, P3, and CP3 are relevant to the dorsal stream, and PO7, P7, TP7, and T7 to the ventral stream. In the present study, EvDirCoh patterns associated with these electrodes showed following characteristics.In
These results revealed that the involvement of the dorsal and ventral streams for the task execution was not exclusive between
5. Conclusion
The involvement of cognitive processing in the perceptual-motor process for achieving a motor task goal was examined by
Acknowledgement
This study was founded by the Grant-in-Aid for Scientific Research (#20500507) in Japan Society for the Promotion of Science, and the Research Grant in Daito-Bunka University (#220102). EEG data collection was conducted by the support of Dr. Kuniyasu Imanaka and his doctoral students at Tokyo Metropolitan University.
References
- 1.
Aglioti S. De Souza J. F. X. Goodale M. A. 1995 Size-contrast illusions deceive the eye but not the hand. Current Biology,5 679 685 - 2.
Basar E. Bullock T. H. 1992 Induced Rhythms in the Brain. Birkhäuser, Basel - 3.
Buneo C. A. Andersen R. A. 2006 The posterior parietal cortex: Sensorimotor interface for the planning and online control of visually guided movements. Neuropsychologia,44 2594 2606 - 4.
Burnod Y. Baraduc P. Battaglia-Mayer A. Guigon E. Koechlin E. Ferraina S. Lacquaniti F. Caminiti R. 1999 Parieto-frontal coding of reaching: An integrated framework. Experimental Brain Research,129 325 346 - 5.
Caminiti R. Ferraina S. Mayer A. B. 1998 Visuomotor transformations: early cortical mechanisms of reaching. Current Opinion in Neurobiology,8 753 761 - 6.
Culham J. C. Cavina-Pratesi C. Singhal A. 2006 The role of parietal cortex in visuomotor control: What have we learned from neuroimaging? Neuropsychologia,44 2668 2684 - 7.
Darling W. G. Seitz R. J. Peltier S. S. Tellmann L. Butler A. 2007 Visual cortex activation in kinesthetic guidance of reaching. Experimental Brain Research,179 4 607 619 - 8.
De France J. Sheer D. E. 1988 Focused arousal,40 Hz EEG and motor programming. In: The EEG of Mental Activities, D. Giannitrapani & K. Murri (Eds), 153-168, Karger, Basel - 9.
Delorme A. Makeig S. 2004 EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods,134 9 21 - 10.
Ellis R. R. Flanagan J. R. Lederman S. J. 1999 The influence of visual illusions on grasp position. Experimental Brain Research,125 109 114 - 11.
Flanagan J. R. Beltzner M. A. 2000 Independence of perceptual and sensorimotor predictions in the size-weight illusion. Nature Neuroscience,3 7 737 741 - 12.
Franz V. H. Fahle M. Bulthoff H. H. Gegenfurtner K. R. 2001 Effects of visual illusions on grasping. Journal of Experimental Psychology: Human Perception and Performance,27 5 1124 1144 - 13.
Franz V. H. Gegenfurtner K. R. Bulthoff H. H. Fahle M. 2000 Grasping visual illusions: No evidence for a dissociation between perception and action. Psychological Science,11 1 20 25 - 14.
Galambos R. Makeig S. Talmachoff P. J. 1981 A 40-Hz auditory potential recorded from the human scalp. Proceedings of the National Academy of Sciences,78 2643 2647 - 15.
Gerloff C. Hadley J. Richard J. Uenishi N. Honda M. Hallett M. 1998 Functional coupling and regional activation of human cortical motor areas during simple, internally paced and externally paced finger movements. Brain,121 1513 1531 - 16.
Glover S. Dixon P. 2002 Dynamic effects of the Ebbinghaus illusion in grasping: Support for a planning/control model of action. Perception and Psychophysics,64 2 266 278 - 17.
Goodale M. A. Jakobson L. S. 1992 Action systems in the posterior parietal cortex. Behavioral and Brain Sciences,15 4 747 - 18.
Goodale M. A. Milner A. D. 1992 Separate visual pathways for perception and action. Trends in Neuroscience,15 1 20 25 - 19.
Goodale M. A. Meenan J. P. Bulthoff H. H. Nicolle D. A. Murphy K. J. Racicot C. I. 1994 Separate neural pathways for the visual analysis of object shape in perception and prehension. Current Biology,4 7 604 610 - 20.
Haffenden A. M. Goodale M. A. 1998 The effect of pictorial illusion on prehension and perception. Journal of Cognitive Neuroscience,10 1 122 136 - 21.
Haggard P. Wing A. 1995 Coordinated responses following mechanical perturbation of the arm during prehension. Experimental Brain Research,102 483 494 - 22.
Heath M. Rival C. Neely K. 2006a Visual feedback schedules influence visuomotor resistance to the Muller-Lyer figures. Experimental Brain Research,168 3 348 356 - 23.
Heath M. Rival C. Neely K. Krigolson O. 2006b Muller-Lyer figures influence the online reorganization of visually guided grasping movements. Experimental Brain Research,169 4 473 481 - 24.
Heath M. Westwood D. A. Rival C. Neely K. 2005 Time course analysis of closed- and open-loop grasping of the Muller-Lyer illusion. Journal of Motor Behavior,37 3 179 185 - 25.
Hummel F. C. Andres F. Altenmuller E. Dichgans J. Gerloff C. 2002 Inhibitory control of acquired motor programs in the human brain. Brain,125 404 420 - 26.
Jeannerod M. 1981 Intersegmental coordination during reaching at natural visual objects. In: Attention and performance, J. Long & A. Baddeley (Eds),9 153 168 Erlbaum, Hillsdale, NJ - 27.
Jeannerod M. 1984 The timing of natural prehension movements. Journal of Motor Behavior,16 235 254 - 28.
Kamitake T. Harashima H. Miyakawa H. Saito Y. 1984 A time-series analysis method based on the directed transinformation. Electron. Commun. Jap.,67 1 9 - 29.
Kandel E. R. Schwartz J. H. Jessell T. M. 2000 Principles of Neural Science. McGraw-Hill, New York - 30.
Katsumata H. Suzuki K. Tanaka T. Imanaka K. 2009 The involvement of cognitive processing in a perceptual-motor process examined with EEG time-frequency analysis. Clinical Neurophysiology,120 484 496 - 31.
Kelso J. A. S. 1995 Dynamic Patterns: the self-organization of brain and behavior. The MIT press, Cambridge, Massachusetts - 32.
Klimesch W. 1996 Memory processes, brain oscillations and EEG synchronization. Journal of Psychophysiology,24 61 100 - 33.
Lee D. N. 1980 Visuo-motor coordination in space-time. In: Tutorials in Motor Behavior, G.E. Stelmach & J. Requin (Eds),281 295 North-Holland Pub., Amsterdam - 34.
Lee J. H. van Donkelaar P. 2002 Dorsal and ventral visual stream contributions to perception-action interactions during pointing. Experimental Brain Research,143 440 446 - 35.
Makeig S. 1993 Auditory event-related dynamics of the EEG spectrum and effects of exposure to tones. Electroencephalography and clinical Neurophysiology,86 283 293 - 36.
Mc Intosh R. D. Dijkerman H. C. Mon-Williams M. Milner A. D. 2004 Grasping what is graspable: Evidence from visual form agnosia. Cortex,40 695 702 - 37.
Mendoza J. Hansen S. Glazebrook C. M. Keetch K. M. Elliott D. 2005 Visual illusions affect both movement planning and on-line control: A multiple cue position on bias and goal-directed action. Human Movement Science,24 760 773 - 38.
Neuper C. Pfurtscheller G. 2001 Event-related dynamics of cortical rhythms: Frequency-specific features and functional correlates. International Journal of Psychophysiology,43 41 58 - 39.
Neuper C. Wortz M. Pfurtscheller G. 2006 ERD/ERS patterns reflecting sensorimotor activation and deactivation. In: Progress in Brain Research, C. Neuper & W. Klimesch (Eds),159 211 222 Elsevier - 40.
Pfurtscheller G. 1992 Event-related synchronization (ERS): an electrophysiological correlate of cortical areas at rest. Electroencephalography and Clinical Neurophysiology,82 62 69 - 41.
Pfurtscheller G. 1998 EEG event-related desynchronization (ERD) and event-related synchronization (ERS). In: Electroencephalography: Basic Principles, Clinical Applications and Related Fields, 4th Edition., E. Niedermeyer & F.H. Lopes da Silva (Eds).958 967 Williams and Wilkins, Baltimore, MD - 42.
Pfurtscheller G. 2001 Functional brain imaging based on ERD/ERS. Vision Research,41 1257 1260 - 43.
Pfurtscheller G. Andrew C. 1999 Event-related changes of band power and coherence: Methodology and interpretation. Journal of Clinical Neurophysiology,16 6 512 - 44.
Pfurtscheller G. Lopes da. Silva F. H. 1999a Event-Related Desynchronization. Elsevier Science, Amsterdam - 45.
Pfurtscheller G. Lopes da. Silva F. H. 1999b Functional meaning of event-related desynchronization (ERD) and synchronization (ERS). In: Event-Related Desynchronization: Handbook of Electroencephalography and Clinical Neurophysiology, G. Pfurtscheller & F.H. Lopes da Silva (Eds),6 51 65 Elsevier Science, Amsterdam - 46.
Pfurtscheller G. Neuper C. 1994 Event-related synchronization of mu rhythm in the EEG over the cortical hand area in man. Neuroscience Letter,174 93 96 - 47.
Ranganathan R. Carlton L. G. 2007 Perception-action coupling and anticipatory performance in baseball batting. Journal of Motor Behavior,39 5 369 380 - 48.
Rizzolatti G. Fogassi L. Gallese V. 1997 Parietal cortex: from sight to action. Current Opinion in Neurobiology,7 4 562 567 - 49.
Saito Y. Harashima H. 1981 Tracking of information within multichannel EEG record-causal analysis in EEG. In: Recent Advances in EEG and Meg data processing, Yamaguchi, N. & Fujisawa, K. (Eds),133 146 Elsevier, Amsterdam - 50.
Sameshima K. Baccalá L. A. 1999 Using partial directed coherence to describe neuronal ensemble interactions. Journal of Neuroscience Methods,94 93 103 - 51.
Schlögl A. Supp G. 2006 Analysing event-related EEG data with multivariate autoregressive parameters. In: Progress in Brain Research, Neuper & Klimesch (Eds),159 135 147 Elsevier, Amsterdam, The Netherlands - 52.
Schmidt R. A. Lee T. D. 1999 Motor control and learning: a behavioral emphasis. Human Kinetics, Champaign, IL - 53.
Schöner G. 1994 Dynamic theory of action-perception patterns: The time-before-contact paradigm. Human Movement Science,13 415 439 - 54.
Schöner G. Kelso J. A. S. 1988 A dynamic pattern theory of behavioral change. Journal of Theoretical Biology,135 501 524 - 55.
Singer W. 1993 Synchronization of cortical activity and its putative role in information processing and learning. Annual Review of Physiology,55 349 374 - 56.
Stein J. 1995 The posterior parietal cortex, the cerebellum and the visual guidance of movement. In: Neural Control of Skilled Human Movement, F.W.J. Cody (Ed).31 49 The Physiological Society, London - 57.
Steriade M. Gloor P. Llinas R. R. Lopes da. Silva F. H. Mesulam M. M. 1991 Basic mechanisms of cerebral rhythmic activities. Electroencephalography and clinical Neurophysiology,76 481 508 - 58.
Suffczynski P. Pijn P. J. M. Pfurtscheller G. Lopes da. Silva F. H. 1999 Event-related dynamics of alpha band rhythms: a neuronal network model of focal ERD/surround ERS. In: Event-Related Desynchronization: Handbook of Electroencephalography and Clinical Neurophysiology, G. Pfurtscheller & F.H. Lopes da Silva (Eds),6 Elsevier, Amsterdam - 59.
Takahashi D. Y. Baccalá L. A. Sameshima K. 2008 Partial directed coherence asymptotics for VAR processes of infinite order. International Journal of Bioelectromagnetism,10 1 31 36 - 60.
Turvey M. T. Kugler P. N. 1984 An ecological approach to perception and action. In: Human Motor Actions: Bernstein Reassessed, H.T.A. Whiting (Ed),373 412 North-Holland, Amsterdam - 61.
Wang G. Takigawa M. 1992 Directed coherence as a measure of interhemispheric correlation of EEG. International Journal of Psychophysiology,13 119 128 - 62.
Warren H. W. 1990 The perception-action coupling. In: Sensory-Motor Organizations and Development in Infancy and Early Childhood, H. Bloch & B.I. Bertenthal (Eds),23 37 Kluwer Academic Pub., Netherlands - 63.
Westwood D. A. Chapman C. D. Roy E. A. 2000a Pantomimed actions may be controlled by the ventral visual stream. Experimental Brain Research,130 545 548 - 64.
Westwood D. A. Heath M. Roy E. A. 2000b The effect of a pictorial illusion on closed-loop and open-loop prehension. Experimental Brain Research,134 456 463 - 65.
Zaal F. T. J. M. Bootsma R. J. van Wieringen P. C. 1998 Coordination in prehension: Information-based coupling of reaching and grasping. Experimental Brain Research,119 427 435 - 66.
Zigmond M. J. Bloom F. E. Landis S. C. Roberts J. L. Squire L. R. 1999 Fundamental Neuroscience. Academic Press, San Diego, CA