Neural evidence for impaired action selection in right hemiparetic cerebral palsy

BR A IN RE S EA RCH 1 3 49 ( 20 1 0 ) 5 6 –67

available at www.sciencedirect.com

www.elsevier.com/locate/brainres

Research Report

Neural evidence for impaired action selection in right hemiparetic cerebral palsy M. van Elk a,⁎, C. Crajé a,b , M.E.G.V. Beeren a , B. Steenbergen b , H.T. van Schie b , H. Bekkering a a

Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands Behavioural Science Institute, Radboud University Nijmegen, Nijmegen, The Netherlands

b

A R T I C LE I N FO

AB S T R A C T

Article history:

Recent studies suggest that in addition to low-level motor impairments, individuals with

Accepted 22 June 2010

hemiparetic cerebral palsy (HCP) are characterized by anticipatory action planning deficits

Available online 28 June 2010

as well. In the present EEG study we investigated the neural and temporal dynamics of

Keywords:

subjects (n = 10). An anticipatory planning task was used in which participants were required

Hemiparetic cerebral palsy

to grasp and rotate a hexagonal knob over different angles (60°, 120° or 180°). At a behavioral

Motor planning

level, participants with HCP were slower in their movements and often selected an

Action selection

inappropriate grip when grasping the object. At a neural level, individuals with HCP showed

Event-related potentials

a strong reduction in the amplitude of the P2 component, likely reflecting an impaired

P2

process of action selection. In addition, a strong correlation was observed between the P2

action planning in participants with right-sided HCP (n = 10) and in left-handed control

amplitude and grasping and rotation times. The P2 component was localized to sources in the dorsal posterior cingulate cortex (dPCC), an area that is known to be involved in orienting visual body parts in space. Together these findings suggest that anticipatory planning deficits in cerebral palsy arise mainly due to an impaired process of action selection. © 2010 Elsevier B.V. All rights reserved.

1.

Introduction

Individuals with cerebral palsy (CP) are characterized by nonprogressive disorders of movement and posture that are attributed to disturbances in the fetal or infant brain (Bax et al., 2005). Clinical studies have shown large individual variability in terms of the brain areas affected, ranging from lesions in both gray and white matter, brain malformations to no detectable brain abnormalities at all (Korzeniewski et al., 2008; Wu et al., 2006). About 20–33% of the individuals with CP are categorized with hemiparetic CP (HCP), a form of CP affecting the left or right lateral side of the body (Koman et al., 2004; Wuet al., 2006).

In addition to low-level problems with motor execution, one recurring finding is that individuals with HCP are characterized by deficits in anticipatory action planning as well (for review, see Steenbergen & Gordon, 2006). These action planning deficits are occurring in both the affected and the (relatively) unaffected arm, and as such these problems have a major impact on activities in daily life. Previous studies have indicated that action planning deficits are especially apparent when the right body side is affected (Craje et al., 2009; Mutsaarts et al., 2007), in line with the proposed role of the left hemisphere in action planning (Haaland & Harrington, 1996; Vingerhoets, 2008). Support for the notion that action planning deficits are a

⁎ Corresponding author. Donders Institute for Brain, Cognition and Behaviour, P.O. Box 9104, 6500 HE Nijmegen, The Netherlands. Fax: + 31 24 3616066. E-mail address: [email protected] (M. van Elk). 0006-8993/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.brainres.2010.06.055

BR A IN RE S E A RCH 1 3 49 ( 20 1 0 ) 5 6 –6 7

characteristic feature of HCP comes mainly from behavioral studies. Whereas healthy participants typically grasped objects with a grip that allows a comfortable posture at the end of a movement (Rosenbaum Vaughan et al., 1992), individuals with HCP often grasped objects with an initial comfortable grip, even if that resulted in an awkward end posture or task failures (Mutsaarts et al., 2005, 2006; Steenbergen et al., 2004). In addition, it has been found that HCP participants failed to anticipate the fingertip forces required for smoothly grasping an object (Duff & Gordon, 2003). Other studies indicate that people with HCP show less efficient grasping kinematics that – in contrast to healthy controls – are not influenced by later task demands (Chen & Yang, 2007; Steenbergen & van der Kamp, 2004). Although these studies provide tentative support for the notion that participants with HCP are characterized by anticipatory planning deficits, the neural and functional mechanisms underlying these impairments remain poorly understood. An important aspect of action planning involves the selection of the correct motor program (Andersen & Cui, 2009). If you are grasping a pen, for instance, depending on your action intention you need to select a specific grip that allows you to use the object in a proper way (e.g. writing with a pen requires a different grip than moving a pen; cf. Daprati & Sirigu, 2006). Accordingly, in the present study we hypothesized that action planning problems in individuals with HCP may be related to an impaired process of action selection. To investigate this hypothesis we used an action planning task in which subjects were required to make a rotating movement with their unaffected hand (cf. Mutsaarts et al., 2006). We measured subjects’ EEG while they were preparing actions of varying difficulty (i.e. preparing to rotate a disk over 60°, 120° or 180°) and effects of task difficulty were explored by measuring event-related potentials (ERPs). Due to their high temporal resolution and the limited restrictions on subjects’ hand and arm movements, ERPs provide the opportunity to capture the time-course of visuo-motor processing. Based on our interest in early action planning, ERP analysis focused on the action preparation interval and more specifically on the anterior P2 (also labeled P2a or P3f; Makeig et al., 1999; Potts, 2004), which is a positive deflection over frontocentral sites with a peak latency of about 200 ms after the onset of a stimulus. Typically a larger P2 amplitude is observed for stimuli with a to-be-attended feature (Kenemans et al., 1993; Potts, 2004; Smid et al., 1999) and accordingly the P2 has been associated with the evaluation of task-relevant stimuli. In addition the P2 amplitude is larger for trials that require an overt response (Gajewski et al., 2008; Makeig et al., 1999; Potts et al., 1996) and the P2 has been associated with the anticipation of action consequences as well (Nikolaev et al., 2008). Interestingly, in a recent study we found a stronger P2 component (as reflected in a frontal selection positivity; FSP) when subjects were required to grasp compared to when they had to point towards a 3D target object (van Elk et al., in press). This task-specific modulation of the P2 was only found when subjects were required to actually perform the movement, but not when they withheld from a response. In sum, these studies suggest that the P2 reflects an action selection mechanism, enabling the coupling of relevant visual information to specific responses (Kuhn et al., 2009; Smid et al., 1999).

57

In the present study, it was hypothesized that motor planning deficits in participants with HCP should become apparent in slower reaction and movement times, less accurate rotations and more awkward grips compared to control subjects. Based on previous studies (Smid et al., 1999; van Elk et al., in press), we expected that the planning of more complex actions (i.e. rotating a disc over a larger angle) might be accompanied by a stronger anterior P2 component. In addition, differences in action planning between individuals with HCP and control participants may be reflected in a smaller amplitude of the anterior P2 for HCP compared to control participants.

2.

Results

2.1.

Behavioral results

The RT analyses revealed a main effect of rotation, F(2, 17) = 6.5, p <.01, η2 =.43, reflecting that RTs increased with increased rotation angles (see Fig. 2). There was a marginal trend for direction, F(1, 18) = 3.7, p =.07, η2 =.17, suggesting slower RTs for counter-clockwise rotations (777 ms, SE = 119 ms) than for clockwise rotations (738 ms, SE = 104 ms; see Fig. 1). No effect of group was found (F< 1). The analyses of grasping times showed a main effect of rotation, F(2,17)= 9.1, p <.005, η2 =.52, reflecting slower grasping times with increased rotation angles (see Fig. 1). A main effect of direction, F(1,18) = 4.7, p <.05, η2 =.21, reflected slower grasping times for counter-clockwise (2077 ms, SE = 190 ms) compared to clockwise rotations (1925 ms, SE = 188 ms; see Fig. 1). A marginally significant effect of group, F(1,18) = 4.2, p =.056, η2 =.19, indicated slower grasping times for HCP subjects (2381 ms, SE = 263 ms) than for control subjects (1621 ms, SE = 263 ms; see Fig. 1). As expected, the analyses of rotation times showed a main effect of rotation, F(2, 17)= 9.8, p <.001, η2 =.54, reflecting longer rotation times with increased rotations (see Fig. 1). A main effect of direction, F(1,18) = 12.2, p <.005, η2 =.40, reflected slower rotation times for counter-clockwise (3471 ms, SE = 196) compared to clockwise rotations (3198 ms, SE= 176 ms; see Fig. 1). A main effect of group, F(1,18)= 6.6, p <.05, η2 =.27, reflected slower rotation times for HCP subjects (3801 ms, SE = 258 ms) than for control subjects (2869 ms, SE = 257 ms; see Fig. 1). With respect to rotation errors (difference between instructed and realized rotation angle), a main effect of rotation, F(2,17) = 4.4, p <.05, η2 =.34, reflected larger rotation errors with increased rotations (see Fig. 1). No effect of group was found, F(1,18) = 2.2, p =.15. In the analysis of the selection of initial grip types for grasping the hexagon it was found that HCP subjects more often grasped the hexagon with an initial comfortable hand grip (average number of selection of Grip 3 per category = 6.1) compared to control subjects (average number of selection of Grip 3 per category = 2.5), F(1,18) = 4.1, p =.059. In an additional analysis based on the coding of anticipatory grips, a marginally significant interaction was found between direction and rotation, F(2,17) = 2.9, p =.08. This interaction reflected that – overall – subjects showed anticipatory grip selection for 180° rotations. Importantly, a significant interaction between

58

BR A IN RE S EA RCH 1 3 49 ( 20 1 0 ) 5 6 –67

Fig. 1 – Behavioral results. Graphs representing reaction times (upper left graph), grasping times (upper right graph), rotation times (middle left graph) and rotation errors (middle right graph) for control subjects (red lines) and HCP subjects (blue lines).

Group, direction and rotation, F(2,17) = 6.3, p <.01, reflected that control subjects more often showed anticipatory grip planning than hemiplegic subjects. Together these findings suggest that HCP subjects often persisted in grasping the hexagon with the same initial comfortable grip, thereby failing to anticipate the upcoming action.

2.2.

Event-related potentials: Action blocks

The ERPs for control and HCP subjects during action preparation are depicted in Fig. 2. A main effect of group, F(1,18) = 20.8, p <.001, η2 =.54, indicated that control subjects showed a stronger P2 amplitude (average amplitude = 11.7 μV, SE = 1.2 μV) than HCP subjects (average amplitude = 4.1 μV, SE = 1.2 μV). A main effect of rotation, F(2,17) = 4.2, p <.05, η2 =.33, indicated that the P2 amplitude increased with increased rotation angle. No interaction was found between rotation and group, F(2,17) = 2.2, p =.14.

2.3.

Peak correlation analysis

To investigate the functional relation between the P2 amplitude and the behavioral data a peak correlation analysis was conducted (see Fig. 3). Significant negative correlations were observed between the P2 amplitude and grasping time for 60° rotations (Cz: r = −.602, p =.005; FCz: r = −.592, p =.006), for 120° rotations (Cz: r = −.574, p =.008; FCz: r = −.522, p =.018) and marginally significant correlations for 180° rotations (Cz: r = −.352, p =.128; FCz: r = −.435, p =.055). In addition significant negative correlations were observed between the P2 amplitude and rotation time for 60° rotations (Cz: r = −.708, p <.001; FCz: r =

−.671, p =.001), for 120° rotations (Cz: r = −.627, p =.003; FCz: r = −.568, p =.009) and for 180° rotations (Cz: r = −.479, p =.032; FCz: r = −.514, p =.021).1 In sum, significant negative correlations were observed between the P2 amplitude and respectively grasping times and rotation times, reflecting that subjects with a larger P2 amplitude were faster in grasping and rotating the object. No significant correlations were observed between reaction times and P2 amplitude.

2.4.

Source analysis

One regional dipole which was located to the dorsal posterior cingulate cortex (dPCC; Brodmann area 23; x = 4, y = −26, z = 27; see Fig. 4), accounted for more than 95% of variance in the grand averaged data in the P2 interval (150–250 ms) of the control subjects. When this source solution was applied to the grand averaged data of the HCP subjects, a residual variance (RV) of 13% was observed. First, to investigate whether the identified source locations fitted the data for both groups, a dipole analysis was performed on each individual subject's P2 using the source

1 As can be seen in Figure 3, the three HCP participants that were characterized by relatively slow grasping times (> 3000 ms) also showed a relatively small P2 amplitude. To control for the possible confound that the correlation between the P2 amplitude and grasping times was caused by these outliers, an additional analysis was conducted. However, exclusion of the three HCP participants with the slowest grasping and rotation times did not affect the significance of the correlations observed.

BR A IN RE S E A RCH 1 3 49 ( 20 1 0 ) 5 6 –6 7

59

Fig. 2 – ERPs during action blocks. ERPs relative to stimulus onset during action blocks for control subjects (upper left graph) and HCP subjects (upper right graph). Scalp topography of the P2 component for control subjects (middle left graph) and HCP subjects (middle right graph). Scalp distribution of the difference in P2 amplitude between control and HCP subjects for the different rotations (lower graph).

solution from the respective grand average as the starting point. The coordinates of the resulting dipoles were entered into a repeated measures ANOVA with Coordinate (x, y and z) as within-subjects factor and Group (control, HCP subjects) as between-subjects factor. Importantly, no interaction was observed between Group and Coordinate (F(2, 17) = 1.4, p =.27), indicating that the location of the individual source solutions did not differ between groups.

Second, to investigate the relative contribution of this source to the individual data, the source waveforms were computed for each individual subject's P2 using the source solution from the grand average data. A main effect of vector was found significant from 168 to 250 ms, F(2,17) > 7.7, p <.005, reflecting that the regional source projected most strongly in tangential direction. A main effect of group was found significant from 162 to 250 ms, F(1, 18) > 4.5, p <.05, reflecting stronger source

60

BR A IN RE S EA RCH 1 3 49 ( 20 1 0 ) 5 6 –67

Fig. 3 – Correlations between P2 amplitude and grasping/rotation times. Correlations between P2 peak amplitude and grasping times for different stimulus rotations (upper rows). Correlations between P2 peak amplitude and rotation times for different rotations (lower rows).

activations for control compared to HCP subjects (see Fig. 4). The interaction between Group and Vector was found significant from 170 to 234 ms, F(2,17)> 3.7, p <.05, reflecting a stronger tangential source activation for control compared to HCP subjects.

2.5.

Event-related potentials: Verbal blocks

The ERPs for control and HCP subjects during verbal blocks are depicted in Fig. 5.2 A main effect of group, F(1,17) = 10.1, p <.01, η2 =.372, indicated that control subjects showed a stronger P2 amplitude (average amplitude = 10.1 μV, SE = 1.3 μV) than HCP subjects (average amplitude = 4.4 μV, SE = 1.2 μV). A marginally significant effect of rotation, F(2,16) = 3.3, p =.063, η2 =.29, indicated that overall the P2 amplitude increased with increased rotation angle. A significant interaction was found between group and rotation, F(2,16) = 4.3, p <.05, η2 =.35, reflecting that for HCP subjects the P2 amplitude increased with increased rotation angle, whereas for control subjects no such relation was observed (see Fig. 5). Finally, a marginally significant interaction was found between group, orientation and electrode, F(2,16) = 3.3, p =.065, η2 =.29. This three-way interaction reflected that the difference in P2 amplitude 2

Due to a procedural error EEG data from 1 control subject was not recorded during verbal blocks. The analysis for verbal blocks includes data from the remaining 19 subjects.

between control and HCP subjects was located slightly more to posterior sites for 180° rotations (see Fig. 5).

3.

Discussion

The present study investigated the functional and neural dynamics of anticipatory action planning in hemiparetic cerebral palsy (HCP). At a behavioral level, participants with HCP were slower in their movements and often selected an inappropriate grip when grasping the object. At a neural level, individuals with HCP showed a strong reduction in the amplitude of the P2 component and overall a strong correlation was observed between the P2 amplitude and grasping and rotation times. The sources of the P2 were localized to the dorsal part of the posterior cingulate cortex (dPCC), an area that is known to be involved in visuo-spatial processing and that has massive connections to both motor and parietal areas (see Vogt et al., 2006). Together these findings suggest that action planning deficits in hemiplegic subjects arise due to an impaired process of action selection. At a behavioral level, besides the overall slowness, individuals with HCP more often failed to anticipate the consequences of their action and grasped the object with a grip that resulted in awkward and uncomfortable body postures or even in task failures. These findings are line with previous studies, indicating that individuals with HCP show anticipatory action planning

BR A IN RE S E A RCH 1 3 49 ( 20 1 0 ) 5 6 –6 7

61

Fig. 4 – Dipole source analysis on the P2 component. The P2 component was localized to the dorsal posterior cingulate cortex (dPPC; Brodmann area 23; x = 4, y = −26, z = 27). Averaged source activation for the regional dipole is represented separately for control subjects (red line) and HCP subjects (blue line).

deficits (Mutsaarts et al., 2005, 2006; Steenbergen & van der Kamp, 2004; te Velde et al., 2005). At a neural level, both participants with HCP and control participants showed an enhanced P2 amplitude for the planning of actions with increased rotation angle. Previous studies have shown that the P2 amplitude modulation is related to both stimulus evaluation and the organization of the upcoming motor response (Kuhn et al., 2009; Makeig et al., 1999; Potts, 2004). For instance, in a previous study we observed a stronger P2 component when subjects prepared a grasping compared to a pointing movement towards an object and this modulation was only observed in case an overt action was required (van Elk et al., in press). Furthermore, recent studies suggest that the P2 may reflect both stimulus–response coupling (Gajewski et al., 2008) and the coupling between a response and an anticipated action effect (Nikolaev et al., 2008). On the basis of these studies, the P2 has been suggested to reflect an action selection process, whereby a response is selected based on relevant visual information (Kuhn et al., 2009; Smid et al., 1999). Accordingly, in the present study the stronger P2 amplitude with increased rotation angle likely reflects an increased action selection process in case a more difficult action is required. The suggestion that the P2 amplitude enhancement is related to action planning is further supported by our finding that the P2 amplitude was highly correlated with movement times and rotation times. The correlation reflected that a stronger P2 amplitude was associated with successful action planning, as reflected in more efficient grasping and rotation of the object.

Interestingly, the overall P2 amplitude of participants with HCP was about half the size of the P2 amplitude of control participants. Similar to control subjects, participants with HCP also showed an amplitude modulation of the P2 component with increased rotations. In addition, participants with HCP that showed a relatively strong P2 amplitude were also faster in grasping and rotating the object. As the present study employed an anticipatory planning paradigm, faster grasping and rotation times may be indicative of a more efficient planning process, as the selection of an incorrect grip would result in more effort to acquire the desired end posture. Together these findings suggest that individuals with HCP are specifically characterized by an impaired – though still functional – process of action selection. In addition, the present study suggests that the action selection process in HCP is impaired already at an early stage, within the first few hundred milliseconds after the instruction to move. This finding is in line with the action planning–control framework, according to which the planning phase of the action – which involves the processing of visual information and the selection of an appropriate action – occurs in the first few hundred milliseconds (Glover, 2004). The P2 component of control subjects was estimated to originate from the dorsal posterior cingulate cortex (dPCC; BA23) and stronger dPCC sources were observed for control compared to HCP subjects in this region. The dPCC is considered part of the dorsal visual pathway that is involved in visual processing for

62

BR A IN RE S EA RCH 1 3 49 ( 20 1 0 ) 5 6 –67

Fig. 5 – ERPs during verbal blocks. ERPs relative to stimulus onset during verbal blocks for control subjects (upper left graph) and HCP subjects (upper right graph). Scalp distribution of the difference in P2 amplitude between control and HCP subjects for the different rotations (lower graph).

action and the control of action (Goodale & Westwood, 2004). More specifically, the dPCC has been shown to be involved in making predictions about the consequences of one's actions (Blakemore et al., 1998), in eye-hand coordination (Inoue et al., 1998) and in spatial navigation (Maguire, 1997). The dPCC is strongly connected with both the anterior cingulate cortex (ACC) and posterior parietal areas (Kobayashi & Amaral, 2003) and projects to rostral and caudal cingulate motor areas as well (Vogt & Pandya, 1987). Therefore, it has been suggested that a key function of the dPCC is to orient body parts in visual space (for review, see Vogt et al., 2006). The integrative function of the dPCC fits well with the functional characteristics of the P2 component and the weaker dPCC source activation for participants with HCP is in line with the recurrent finding that individuals with HCP show impaired motor and postural control (Bax et al., 2005). The finding that anticipatory planning problems in participants with right-sided HCP are related to an impaired process of action selection is in line with previous studies, showing that damage to the left hemisphere results in impairments in response selection (Haaland & Harrington, 1994; Haaland et al., 1987; Rushworth et al., 1997; Rushworth et al., 1998). In addition, several studies have shown that response selection and action anticipation are associated with activation in left premotor and parietal cortex (Blakemore et al., 1998; Kalaska & Crammond, 1995; Majdandzic et al., 2007; Schluter et al., 2001; Schluter et al., 1998; van Schie & Bekkering, 2007). An intriguing

question is why in the present study effects of action planning were localized to the dPCC, rather than the more lateral motor structures reported in earlier studies. The apparent discrepancy may be related to both the methodology and the paradigm employed. That is, most previous studies on action planning have used fMRI, whereas the present study employed ERPs to capture the early stages of visuo-motor processing. The early and transient activations in dPCC, as measured in the present study, may actually precede the more prolonged activation in parietal and premotor areas as measured with fMRI. In addition, most studies on response selection and action planning have typically used a paradigm that involved the selection of relatively simple movements in response to visual cues. In contrast, in the present study the coupling between visual information and a motor program was more complex and involved the anticipation of the end state of an action involving a specific body posture. Although relatively little is known about the neural mechanisms underlying anticipatory grip planning, the functional properties of the dPCC fit well with its proposed role for mediating the coupling of visual information to an appropriate motor program (Vogt et al., 2006). Importantly, the modulation of P2 amplitude by task difficulty could not be attributed to perceptual differences between conditions (i.e. a different number of LEDs implied a different rotation instruction). When control subjects were required to only verbally respond to the number of LEDs that

63

BR A IN RE S E A RCH 1 3 49 ( 20 1 0 ) 5 6 –6 7

was lighted, no modulation of the P2 amplitude was observed. This finding further supports the interpretation that the P2effect reflects a selection-for-action mechanism, related to response selection on the basis of visual information (Smid et al., 1999; van Elk et al., in press). Although for participants with HCP a modulation of the P2 component was observed in the verbal task, the effect appeared to be weaker and did not show the same consistent pattern as observed in the action planning task. It could well be that the effects observed in the visual task for individuals with HCP reflected the persistent activation of the stimulus–response coupling required for the action planning task. The notion that individuals with HCP may have particular difficulty with controlling and flexibly switching between different stimulus–response couplings opens interesting avenues for future research. An important issue in research with clinical populations concerns the question whether left-handed control participants comprise a valid comparison for participants with rightsided HCP. It could be that most HCP participants had a genetic predisposition to become right-handed prior to their prenatal brain injuries. As the relation between handedness and the structural and functional organization of the brain is well established (Kloppel et al., 2007; Knecht et al., 2000; Willems & Hagoort, 2009; Willems et al., 2009a; Willems et al., 2009b), the comparison between HCP and left-handed control participants may have been confounded. However, although handedness has a strong genetic component, hand preference is determined by environmental factors as well (for review, see Llaurens et al., 2009). From their birth onwards participants with HCP predominantly used their unaffected left hand, thereby providing a good match with left-handed control participants in terms of action experience. In addition, in a recent study it was found that adult ‘converted’ left-handers – who had been forced as children to write with their right hand – showed a comparable left-hemispheric lateralization of the central sulcus as right-handers, thereby underlining the plasticity of the motor system caused by forced use of the nondominant hand (Kloppel et al., 2010). In sum, given the equivalence in action experience and the supposed effect of both forced and spontaneous left-hand use on hemispheric specialization, the comparison between left-handed control participants and subjects with right HCP seems warranted.

4.

Conclusion

The main finding of the present study is that anticipatory planning deficits in subjects with right hemiparetic cerebral palsy (HCP) arise due to impairments in action selection, occurring at an early stage during action preparation, as evidenced by a reduced P2 amplitude and a weaker source activation of the dorsal posterior cingulate cortex.

5. 5.1.

Experimental procedures Subjects

In total 20 subjects participated in the study. The group consisted of 10 participants diagnosed with right spastic

hemiparetic cerebral palsy (HCP; 3 females, mean age = 18.3 years, SD = 1.2 years) and 10 neurologically healthy control participants (2 males, mean age = 19.7 years, SD = 2.2 years). Participants with HCP were recruited via their school (a school for special education Mariëndael in Arnhem, the Netherlands), or via the Dutch society of parents of physically disabled children (‘BOSK’). Hand function was tested using the Box and Blocks test (gross dexterity; Mathiowetz et al., 1985) and the Purdue Pegboard test (fine dexterity; Tiffin, 1985) for both the impaired and unimpaired hand. The severity of the paresis was estimated by calculating the ratio between the score of the impaired and the unimpaired hand. Accordingly, a score near 1 indicates that hand function among both hands was comparable (i.e. mild paresis), whereas a score near 0 indicates a strong difference between the impaired and unimpaired hand (i.e. severe paresis). Participant information is provided in Table 1. Control subjects were students from the Radboud University Nijmegen, who participated for course credits or an experimental fee. All control participants were left-handed, as assessed by an online inventory for handedness. All participants gave informed consent prior to the experiment. The study was approved by the local ethics committee, in accordance with the declaration of Helsinki.

5.2.

Experimental setup

The experiment was conducted in an electrically and soundshielded room. The experimental setup is schematically presented in Fig. 6. Subjects were seated comfortably behind a table on which a custom-made rotatable disk (width 40 cm) was placed. A hexagonal knob (width 11 cm and depth 6 cm) was placed at the center of the disk to allow and detect grasping actions of the subject. At each of the six sides of the hexagon an arrow was inserted (length 15 cm and width 0.5 cm). At 0.5 cm from the edge of the disk six LEDs were placed at 0°, 60°, 120°, 180°, 240° and 300°. In front of the disk a response box was placed from which the subject started the grasping movements. Both the response box and the rotatable disk were controlled by a PC running Presentation software (Neurobehavioral Systems Inc., Albany, CA) to switch on the

Table 1 – Participant information for participants with HCP. Gen = gender; IH = impaired hand; UH = unimpaired hand; Ratio = score (impaired hand)/score (unimpaired hand). Part

1 2 3 4 5 6 7 8 9 10

Gen

M F M M M M F M M F

Age

18.8 19.3 15.7 17.5 18.1 20.1 18.4 21.1 17.8 19.3

Box and Blocks

Purdue Pegboard

IH

UH

Ratio

IH

UH

69 76 47 63 49 49 47 57 56 49

20 11 56 9 33 26 18 60 60 16

.29 .15 1.19 .14 .67 .53 .38 1.05 1.07 .33

28 31 22 20 23 30 32 22 27 28

4 0 21 0 2 0 0 23 20 0

Ratio .14 0 .96 .0 .09 0 .0 1.05 .74 .0

64

BR A IN RE S EA RCH 1 3 49 ( 20 1 0 ) 5 6 –67

Fig. 6 – Experimental setup. Top: Subjects were seated behind a table on which a custom-made disk was placed that could be grasped at the middle hexagon. LEDs on the side of the disk instructed subjects to either rotate the disk in a particular orientation (action blocks) or to report the number of LEDs (verbal blocks). Bottom: Subjects were allowed to freely select their initial handgrip for grasping the hexagon (Grip 1–5; grip 6 was biomechanically impossible).

LEDs, to detect release of the button box (reaction time), the grasping of the hexagon (grasping time), the release of the hexagon (rotation time) and to measure the rotation angle. Markers for the different events were sent to the EEG computer and stored for offline analysis.

5.3.

Experimental procedure

At the beginning of each trial a number of LEDs turned on and depending on the task instructions subjects responded by rotating the disk (action blocks) or by verbally reporting the number of LEDs (verbal blocks). Verbal blocks were included to control for perceptual differences between conditions (i.e. more visual information projected onto the retina when a large rotation is required). During action blocks a combination of LEDs instructed the subject to rotate the disk with a specific angle in a specific direction (see Fig. 6). For instance, if during an action block LEDs 1, 2 and 3 were lighted, this indicated that the subject was required to rotate the disk 120° in a clockwise direction. During verbal blocks a combination of LEDs instructed the subject to report the number of LEDs that were lighted, after the LEDs switched off. For instance, if during a verbal block LEDs 1, 2 and 3 were lighted, the subject was required to verbally report the number of LEDs (i.e. ‘three’) after the LEDs had turned off. In line with previous studies using participants with unilateral brain damage (Kimura & Archibald, 1974; Mutsaarts et al., 2005; Rushworth et al., 1998; Steenbergen et al., 2004; Steenbergen & van der Kamp, 2004), during action blocks participants always performed the movements with their non-

affected/left hand (i.e. the hand ipsilateral to the affected hemisphere). The rationale for having participants perform the action with the left hand was that most hemiplegic participants could correctly perform the grasping and rotation actions only with their ipsilateral hand. This manipulation allowed us to directly assess effects of action planning, without the possible confound of physical limitations in motor abilities between participants. Subjects were instructed to grasp the disk with the thumb and fingers placed on opposite sides of the hexagon. At the beginning of the experiment it was explained that the object could be grasped with 5 different grip types (see Grips 1–5 in Fig. 6; Grip 6 was biomechanically impossible). During the experiment subjects were free to choose by which grip they grasped the object in order to rotate it. After the LEDs switched on, subjects released the starting position (i.e., they released the response button on the button box), grasped the hexagon and rotated the disk according to the task instructions provided by the LEDs. The initial grip by which subjects grasped the object was coded online by an experimenter. After rotation, subjects returned to the starting position upon which the next trial was initiated. During verbal blocks, the LEDs remained on for 1000– 1500 ms after which the subjects verbally reported the number of lighted LEDs to the experimenter. After verbally responding, subjects pressed the response button upon which the next trial was initiated. Each block consisted of 30 trials (2 Directions × 3 Rotation angles × 5 Replications) which were presented in random order. Each subject performed three action blocks and three verbal blocks and block order was

BR A IN RE S E A RCH 1 3 49 ( 20 1 0 ) 5 6 –6 7

counterbalanced between subjects (block order was AVAVAV or VAVAVA).

5.4.

EEG measurements

The electroencephalogram (EEG) was recorded using 61 active electrodes that were placed in an actiCAP (BrainProducts, Munich, Germany). Electrode positions were based on the M-10 Equidistant 61-Channel-Arrangement, with an inter-electrode distance of 37 ± 3 mm (given a head circumference of 58 cm). All electrodes were referenced to the left mastoid online and re-referenced offline to the linked mastoids. The impedance of the electrodes was kept below 10 kOhm. EEG and EOG signals were amplified using two 32channel BrainAmp DC EEG amplifiers. The signal was sampled at 500 Hz and filtered online with an 80 Hz high cut-off filter and a 10 s time-constant.

5.5.

Data analysis

Analysis of behavioral responses focused on reaction times, grasping times (time between release of the starting button and detection of grasping the hexagon) and rotation times (time between detection of grasping the hexagon and release of the hexagon). Response latencies exceeding the subject's mean by more than 3 standard deviations were excluded from analysis. In addition the rotation error was calculated by subtracting the actually rotated angle from the instructed rotation. Behavioral data were analyzed using a 2 × 3 repeated measures general linear model (GLM) with Direction (counterclockwise, clockwise) and Rotation (60°, 120°, 180°) as withinsubject variables and Group (control subjects, HCP subjects) as between-subjects factor. For the analysis of the selection of initial hand grip, the number of initial comfortable handgrips was analyzed, as this is indicative of a deficit in anticipatory planning. In an additional analysis, first each grip type was assigned a score (Grip 1 = 1; Grip 2 = 2 etc.). Based on the number of grips selected, for each subject an average score was calculated per stimulus category. Accordingly, a low score is indicative of anticipatory planning for clockwise movements (CW) and a high score is indicative of anticipatory planning for counterclockwise movements. The individual scores were analyzed using a 2 × 3 repeated measures general linear model (GLM) with Direction (counter-clockwise, clockwise) and Rotation (60°, 120°, 180°) as within-subject variables and Group (control subjects, hemiparetic subjects) as between-subjects factor. Detailed analysis of the selection of the initial grip type is reported elsewhere (Crajé et al., submitted). Analysis of event-related potentials (ERPs) focused on the movement preparation interval and ERPs were calculated relative to the onset of the LEDs from −200 to 500 ms using a 100 ms pre-stimulus baseline. Trials with movement artifacts were excluded from analysis on the basis of careful visual inspection of the raw data. Ocular artifacts were corrected using a semi-automatic correction procedure based on the algorithm of Gratton and Coles (1983). The analyses were conducted on the averaged P2 amplitude at Cz and FCz from 180 to 220 ms after stimulus onset. ERPs were tested for statistical significance using a 3 × 2 repeated measures

65

general linear model (GLM) with Rotation (60°, 120°, 180°) and Electrode (Cz, FCz) as within-subject variables and Group (control subjects, HCP subjects) as between-subjects factor. In a subsequent correlation analysis the functional relation between the ERPs and the behavioral measures was investigated. First, for each individual subject the peak amplitude of the P2 component was identified, by selecting the most positive peak between 150 ms and 250 ms at electrodes Cz and FCz. Next Pearson's R was calculated between the individual peak amplitudes of the P2 component and grasping times and rotation times. Correlations were calculated separately for different rotations (60°, 120° and 180°).

5.6.

Source analysis

Brain electromagnetic source analysis (BESA 5.0, MEGIS Software) was used for EEG dipole source analysis, by using a fourshell ellipsoid head model. For the source analysis of the averaged P2 component in the action condition a single regional dipole was used, in line with previous studies that have modeled sources of fronto-central components (van Schie et al., 2004). The source model was computed from 150 to 250 ms after stimulus onset on the grand average waveform, averaged across different stimulus conditions to increase the signal-to-noise ratio. For the control subjects, the best fitting source model on the grand average potential distribution was computed (residual variance (RV) was below 5%). The source solution for the control subjects was applied to the grand average potential distribution of the hemiparetic subjects. First, to investigate whether the identified source location differed between groups, a dipole analysis was performed on each individual subject's P2 using the source solution from the respective grand average as the starting point. The x, y and z location coordinates for the individual dipole solutions were entered in a repeated measures ANOVA with Coordinate (x, y, z) as within-subjects factor and Group (control, hemiparetic subjects) as between-subjects factor. Source locations were specified in Talaraich coordinates and were projected on an individual MRI. Subsequently, to investigate whether the identified source differed in strength between both groups, the source waveforms were computed for each individual subject's P2, using the source solution from the grand average. To investigate group differences between the source waveforms a sample-wise repeated measures ANOVA was conducted on the 150–250 ms interval, with Vector field (x, y and z) as within-subject factor and Group (control, HCP subjects) as between-subjects factor. The significance criterion for each individual time-bin was set at 0.05. To control for multiple comparisons, a criterion of three consecutive significant intervals was used, thereby reducing p to 50 × 0.053 =.00625.

Acknowledgments This work was supported by the Netherlands Organization for Scientific Research (grants 453-05-001 awarded to H.B. and grant 400-04-046 awarded to C.C.).

66

BR A IN RE S EA RCH 1 3 49 ( 20 1 0 ) 5 6 –67

REFERENCES

Andersen, R.A., Cui, H., 2009. Intention, action planning, and decision making in parietal-frontal circuits. Neuron 63 (5), 568–583. Bax, M., Goldstein, M., Rosenbaum, P., Leviton, A., Paneth, N., Dan, B., et al., 2005. Proposed definition and classification of cerebral palsy, April 2005. Dev. Med. Child Neurol. 47 (8), 571–576. Blakemore, S.J., Rees, G., Frith, C.D., 1998. How do we predict the consequences of our actions? A functional imaging study. Neuropsychologia 36 (6), 521–529. Chen, Y.P., Yang, T.F., 2007. Effect of task goals on the reaching patterns of children with cerebral palsy. J. Mot Behav. 39 (4), 317–324. Craje, C., van der Kamp, J., Steenbergen, B., 2009. Visual information for action planning in left and right congenital hemiparesis. Brain Res. 1261, 54–64. Daprati, E., Sirigu, A., 2006. How we interact with objects: learning from brain lesions. Trends Cogn. Sci. 10 (6), 265–270. Duff, S.V., Gordon, A.M., 2003. Learning of grasp control in children with hemiplegic cerebral palsy. Dev. Med. Child Neurol. 45 (11), 746–757. Gajewski, P.D., Stoerig, P., Falkenstein, M., 2008. ERP–correlates of response selection in a response conflict paradigm. Brain Res. 1189, 127–134. Glover, S., 2004. Separate visual representations in the planning and control of action. Behav. Brain Sci. 27 (1), 3–24 discussion 24-78. Goodale, M.A., Westwood, D.A., 2004. An evolving view of duplex vision: separate but interacting cortical pathways for perception and action. Curr. Opin. Neurobiol. 14 (2), 203–211. Gratton, G., Coles, M.G., Donchin, E., 1983. A new method for off-line removal of ocular artifact. Electroen Clin. Neuro 55 (4), 468–484. Haaland, K.Y., Harrington, D.L., 1994. Limb-sequencing deficits after left but not right hemisphere damage. Brain Cogn. 24 (1), 104–122. Haaland, K.Y., Harrington, D.L., 1996. Hemispheric asymmetry of movement. Curr. Opin. Neurobiol. 6 (6), 796–800. Haaland, K.Y., Harrington, D.L., Yeo, R., 1987. The effects of task complexity on motor performance in left and right CVA patients. Neuropsychologia 25 (5), 783–794. Inoue, K., Kawashima, R., Satoh, K., Kinomura, S., Goto, R., Koyama, M., et al., 1998. PET study of pointing with visual feedback of moving hands. J. Neurophysiol. 79 (1), 117–125. Kalaska, J.F., Crammond, D.J., 1995. Deciding not to GO: neuronal correlates of response selection in a GO/NOGO task in primate premotor and parietal cortex. Cereb. Cortex 5 (5), 410–428. Kenemans, J.L., Kok, A., Smulders, F.T., 1993. Event-related potentials to conjunctions of spatial frequency and orientation as a function of stimulus parameters and response requirements. Electroencephalogr. Clin. Neurophysiol. 88 (1), 51–63. Kimura, D., Archibald, Y., 1974. Motor functions of the left hemisphere. Brain 97 (2), 337–350. Kloppel, S., van Eimeren, T., Glauche, V., Vongerichten, A., Munchau, A., Frackowiak, R.S., et al., 2007. The effect of handedness on cortical motor activation during simple bilateral movements. Neuroimage 34 (1), 274–280. Kloppel, S., Mangin, J.F., Vongerichten, A., Frackowiak, R.S., Siebner, H.R., 2010. Nurture versus nature: long-term impact of forced right-handedness on structure of pericentral cortex and basal ganglia. J. Neurosci. 30 (9), 3271–3275. Knecht, S., Drager, B., Deppe, M., Bobe, L., Lohmann, H., Floel, A., et al., 2000. Handedness and hemispheric language dominance in healthy humans. Brain 123 (Pt 12), 2512–2518. Kobayashi, Y., Amaral, D.G., 2003. Macaque monkey retrosplenial cortex. II. Cortical afferents. J. Comp. Neurol. 466 (1), 48–79.

Koman, L.A., Smith, B.P., Shilt, J.S., 2004. Cerebral palsy. Lancet 363 (9421), 1619–1631. Korzeniewski, S.J., Birbeck, G., DeLano, M.C., Potchen, M.J., Paneth, N., 2008. A systematic review of neuroimaging for cerebral palsy. J. Child Neurol. 23 (2), 216–227. Kuhn, S., Gevers, W., Brass, M., 2009. The neural correlates of intending not to do something. J. Neurophysiol. 101 (4), 1913–1920. Llaurens, V., Raymond, M., Faurie, C., 2009. Why are some people left-handed? An evolutionary perspective. Philos. Trans. R. Soc. Lond. B Biol. Sci. 364 (1519), 881–894. Maguire, E.A., 1997. Hippocampal involvement in human topographical memory: evidence from functional imaging. Philos. Trans. R. Soc. Lond. B Biol. Sci. 352 (1360), 1475–1480. Majdandzic, J., Grol, M.J., van Schie, H.T., Verhagen, L., Toni, I., Bekkering, H., 2007. The role of immediate and final goals in action planning: an fMRI study. Neuroimage 37 (2), 589–598. Makeig, S., Westerfield, M., Jung, T.P., Covington, J., Townsend, J., Sejnowski, T.J., et al., 1999. Functionally independent components of the late positive event-related potential during visual spatial attention. J. Neurosci. 19 (7), 2665–2680. Mathiowetz, V., Volland, G., Kashman, N., Weber, K., 1985. Adult norms for the box and block test for manual dexterity. Amer. J. Occup. Ther. 157, 162–173. Mutsaarts, M., Steenbergen, B., Bekkering, H., 2005. Anticipatory planning of movement sequences in hemiparetic cerebral palsy. Mot. Control 9 (4), 439–458. Mutsaarts, M., Steenbergen, B., Bekkering, H., 2006. Anticipatory planning deficits and task context effects in hemiparetic cerebral palsy. Exp. Brain Res. 172 (2), 151–162. Mutsaarts, M., Steenbergen, B., Bekkering, H., 2007. Impaired motor imagery in right hemiparetic cerebral palsy. Neuropsychologia 45 (4), 853–859. Nikolaev, A.R., Ziessler, M., Dimova, K., van Leeuwen, C., 2008. Anticipated action consequences as a nexus between action and perception: evidence from event-related potentials. Biol. Psychol. 78 (1), 53–65. Potts, G.F., 2004. An ERP index of task relevance evaluation of visual stimuli. Brain Cogn. 56 (1), 5–13. Potts, G.F., Liotti, M., Tucker, D.M., Posner, M.I., 1996. Frontal and inferior temporal activity in visual target detection: evidence from high spatially sampled event-related potentials. Brain Topogr. 9 (1), 3–14. Rosenbaum Vaughan, J., Barnes, H.J., Jorgensen, M.J., 1992. Time course of movement planning: selection of handgrips for object manipulation. J. Exp. Psychol LMC 18 (5), 1058–1073. Rushworth, M.F., Nixon, P.D., Renowden, S., Wade, D.T., Passingham, R.E., 1997. The left parietal cortex and motor attention. Neuropsychologia 35 (9), 1261–1273. Rushworth, M.F., Nixon, P.D., Wade, D.T., Renowden, S., Passingham, R.E., 1998. The left hemisphere and the selection of learned actions. Neuropsychologia 36 (1), 11–24. Schluter, N.D., Rushworth, M.F., Passingham, R.E., Mills, K.R., 1998. Temporary interference in human lateral premotor cortex suggests dominance for the selection of movements A study using transcranial magnetic stimulation. Brain 121 (Pt 5), 785–799. Schluter, N.D., Krams, M., Rushworth, M.F., Passingham, R.E., 2001. Cerebral dominance for action in the human brain: the selection of actions. Neuropsychologia 39 (2), 105–113. Smid, H.G., Jakob, A., Heinze, H.J., 1999. An event-related brain potential study of visual selective attention to conjunctions of color and shape. Psychophysiology 36 (2), 264–279. Steenbergen, B., Gordon, A.M., 2006. Activity limitation in hemiplegic cerebral palsy: evidence for disorders in motor planning. Dev. Med. Child Neurol. 48 (9), 780–783. Steenbergen, B., van der Kamp, J., 2004. Control of prehension in hemiparetic cerebral palsy: similarities and differences between the ipsi- and contra-lesional sides of the body. Dev. Med. Child Neurol. 46 (5), 325–332.

BR A IN RE S E A RCH 1 3 49 ( 20 1 0 ) 5 6 –6 7

Steenbergen, B., Meulenbroek, R.G., Rosenbaum, D.A., 2004. Constraints on grip selection in hemiparetic cerebral palsy: effects of lesional side, end-point accuracy, and context. Brain Res. Cogn. Brain Res. 19 (2), 145–159. te Velde, A.F., van der Kamp, J., Becher, J.G., van Bennekom, C., Savelsbergh, G.J., 2005. Planning and control in a manual collision avoidance task by children with hemiparesis. Mot. Control 9 (4), 417–438. Tiffin, J., 1985. Purdue-Pegboard Examiner Manual. Science Research Associates, Chicago. van Elk, M., van Schie, H. T., Neggers, S. F., & Bekkering, H. (in press). Neural and temporal dynamics underlying visual selection for action. J Neurophysiol. doi:10.1152/jn.01079.2009. van Schie, H.T., Bekkering, H., 2007. Neural mechanisms underlying immediate and final action goals in object use reflected by slow wave brain potentials. Brain Res. 1148, 183–197. van Schie, H.T., Mars, R.B., Coles, M.G., Bekkering, H., 2004. Modulation of activity in medial frontal and motor cortices during error observation. Nat. Neurosci. 7 (5), 549–554.

67

Vingerhoets, G., 2008. Knowing about tools: neural correlates of tool familiarity and experience. Neuroimage 40 (3), 1380–1391. Vogt, B.A., Pandya, D.N., 1987. Cingulate cortex of the rhesus monkey. II. Cortical afferents. J Comp Neurol 262 (2), 271–289. Vogt, B.A., Vogt, L., Laureys, S., 2006. Cytology and functionally correlated circuits of human posterior cingulate areas. Neuroimage 29 (2), 452–466. Willems, R.M., Hagoort, P., 2009. Hand preference influences neural correlates of action observation. Brain Res. 1269, 90–104. Willems, R.M., Peelen, M.V., Hagoort, P., 2009a. Cerebral lateralization of face-selective and body-selective visual areas depends on handedness. Cereb. Cortex. Willems, R.M., Toni, I., Hagoort, P., Casasanto, D., 2009b. Body-specific motor imagery of hand actions: neural evidence from right- and left-handers. Front. Hum. Neurosci. 3, 39. Wu, Y.W., Lindan, C.E., Henning, L.H., Yoshida, C.K., Fullerton, H.J., Ferriero, D.M., et al., 2006. Neuroimaging abnormalities in infants with congenital hemiparesis. Pediatr. Neurol. 35 (3), 191–196.