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The motor system shows adaptive changes in complex regional pain syndrome

Christian Maihöfner, Ralf Baron, Roberto DeCol, Andreas Binder, Frank Birklein, Günther Deuschl, Hermann O. Handwerker, Jörn Schattschneider
DOI: http://dx.doi.org/10.1093/brain/awm131 2671-2687 First published online: 16 June 2007

Summary

The complex regional pain syndrome (CRPS) is a disabling neuropathic pain condition that may develop following injuries of the extremities. In the present study we sought to characterize motor dysfunction in CRPS patients using kinematic analysis and functional imaging investigations on the cerebral representation of finger movements. Firstly, 10 patients and 12 healthy control subjects were investigated in a kinematic analysis assessing possible changes of movement patterns during target reaching and grasping. Compared to controls, CRPS patients particularly showed a significant prolongation of the target phase in this paradigm. The pattern of motor impairment was consistent with a disturbed integration of visual and proprioceptive inputs in the posterior parietal cortex. Secondly, we used functional MRI (fMRI) and investigated cortical activations during tapping movements of the CRPS-affected hand in 12 patients compared to healthy controls (n = 12). During finger tapping of the affected extremity, CRPS patients showed a significant reorganization of central motor circuits, with an increased activation of primary motor and supplementary motor cortices (SMA). Furthermore, the ipsilateral motor cortex showed a markedly increased activation. When the individual amount of motor impairment was introduced as regressor in the fMRI analysis, we were able to demonstrate that activations of the posterior parietal cortices (i.e. areas within the intraparietal sulcus), SMA and primary motor cortex were correlated with the extent of motor dysfunction. In summary, the results of this study suggest that substantial adaptive changes within the central nervous system may contribute to motor symptoms in CRPS.

  • complex regional pain syndrome
  • reorganization
  • neuropathic pain
  • motor system
  • plasticity
  • posterior parietal cortex

Introduction

Complex regional pain syndromes (CRPS) may develop following limb trauma or nerve lesions in up to 5% of all cases (Veldman et al., 1993; Stanton-Hicks et al., 1995; Birklein et al., 2000). CRPS is characterized by autonomic, sensory and motor symptoms. The sensory symptoms may comprise not only spontaneous and stimulus-evoked pain (hyperalgesia or allodynia), but sometimes also sensory impairment, i.e. hypalgesia and hypoesthesia (Veldman et al., 1993; Birklein et al., 2000; Baron, 2004). Autonomic dysfunctions mainly include temperature changes, sweating abnormalities and changes in skin colour. The motor symptoms are weakness, tremor, dystonia and myoclonia, which usually start in the affected extremity but may spread to the other side (Schwartzman and Kerrigan, 1990). In particular, the majority of CRPS patients complain about difficulties in the performance of complex movement patterns and a reduced range of motion (Schwartzman and Kerrigan, 1990; Veldman et al., 1993). It is an interesting observation that movement tasks which cannot be performed actively by the patient can be executed when the affected extremity is passively moved by a second person. Therefore, it is unlikely that the observed alterations of motor function are only compensatory for impairment like oedema, pain or disuse to prevent pain exacerbation, because these factors should affect active and passive movements to nearly the same degree. It is more likely that the observed motor deficits are due to specific alterations of the central motor system induced by the disease (Janig and Baron, 2002; van Hilten et al., 2005). Changes of central motor processing would also explain the occurrence of other motor symptoms in CRPS, e.g. dystonia or tremor (Deuschl et al., 1991; van Hilten et al., 2005). Additional to facilitated neurogenic inflammation (Birklein et al., 2001; Weber et al., 2001), endothelial dysfunction (Schattschneider et al., 2006b) and pathological sympatho-afferent coupling (Baron et al., 2002; Schattschneider et al., 2006a), there is accumulating evidence that central nervous system changes may be involved in the pathogenesis of CRPS (Janig and Baron, 2002, 2003; van Hilten et al., 2005). Using functional imaging techniques, we and others recently provided evidence for a substantial reorganization of the somatotopic map within the primary somatosensory cortex (S1) of CRPS patients (Juottonen et al., 2002; Maihofner et al., 2003; Pleger et al., 2004; Maihofner et al., 2004a, 2005; Pleger et al., 2005; Maihofner et al., 2006a). Using magnetoencephalography (MEG), we found a significant shrinkage of the cortical hand representation contralateral to the CRPS-affected painful arm (Maihofner et al., 2003, 2004a). In addition, the hand position was shifted towards the lip. Predictors for this cortical reorganization were spontaneous CRPS pain and the extent of mechanical hyperalgesia. Interestingly, when treatment was efficacious and CRPS pain reduced, this S1 cortical reorganization in CRPS was reversed (Maihofner et al., 2004a).

Cortical reorganization may be able to explain some of the often puzzling clinical signs of CRPS, e.g. the spatial distribution of sensory disturbances in a glove or stocking-like distribution (Veldman et al., 1993; Birklein et al., 2000) the occurrence of tactile-induced referred sensations (McCabe et al., 2003; Maihofner et al., 2006c) and hemisensory deficits (Rommel et al., 1999, 2001). However, the underlying pathophysiology of motor symptoms remains only poorly understood.

Therefore, in the present study we hypothesized that adaptive cortical changes within the motor system may occur in CRPS. To test our hypothesis, we firstly tried to characterize motor pathology of CRPS using kinematic analysis. Furthermore, in a second set of experiments we used functional magnetic resonance imaging (fMRI) and investigated cerebral activations during motor performance in CRPS patients compared to a control group.

Material and Methods

Subjects and psychophysical examination

The results of the present manuscript represent a collaboration between the two Neurological Departments of the University Hospitals of Kiel and Erlangen within the German Research Network on Neuropathic Pain (GNNP; http://www.neuropathischer-schmerz.de). Two groups of patients were investigated: the kinematic analysis was done in Kiel and the functional imaging studies were performed in Erlangen. At both sites, the patients had to meet the current IASP diagnostic criteria for CRPS (Stanton-Hicks et al., 1995). These criteria were extended so that symptoms must be present at time of investigation. Informed written consent was obtained from all subjects and the study was approved by the local ethics committees.

Kinematic analysis (Kiel site) was performed in 10 patients diagnosed with CRPS Type I of the upper extremity (seven women, three men) with a mean age of 43.0 ± 5.5 years and a mean duration of the disease of 83 ± 16 weeks. Further 12 healthy controls (nine women, three men) with a mean age of 47.5 ± 6.6 years were examined before and after the induction of experimental pain. At the Erlangen site (fMRI study), 12 CRPS patients (10 women, 2 men) with a mean age of 41.2 ± 2.5 years were included. All patients were diagnosed with CRPS I. In order to avoid potential side differences of brain activations, we only included patients with CRPS at the right upper limb. The mean duration of CRPS symptoms was 52.2 ± 32 weeks. The control group consisted of 12 healthy age and sex-matched volunteers (mean age 43.2 ± 2.5 years). All subjects were right-handed according to the Edinburgh handedness inventory (Oldfield, 1971). The clinical and epidemiological data of all patients are given in detail in Table 1.

View this table:
Table 1

Demographic data, diagnoses, symptoms and treatment of patients (patients #1–10 were included in the kinematic study, patients #11–22 in the fMRI study)

Patient No.Age (yrs)GenderDiagnosisAffected limbInciting eventSpontaneous pain rating (NRS)OedemaSkin temp.Hair/nail growthMotor signsTime from onset (weeks)therapyComorbidity and comedication
131FemaleCRPS IRight handDistal radius fracture5paresis1041,3,5none
239MaleCRPS IRight handDistal radius fracture2+paresis261,2,4none
351FemaleCRPS IRight handWrist fracture5paresis1041,3hypertension, diuretic medicationf
420FemaleCRPS IRight handMinor trauma3paresis781,5none
575FemaleCRPS IRight handSprain right wrist3paresis524,5diabetes, insulin
668MaleCRPS IRight handDistal radius fracture5paresis7814,5none
736FemaleCRPS IRight handSprain right wrist5paresis521,3none
845FemaleCRPS IRight handSprain right wrist4+paresis2081,3,4none
925FemaleCRPS IRight handSprain right wrist5paresis262,3none
1040MaleCRPS IRight handDistal radius fracture6paresis1041,3none
1175FemaleCRPS IRight handDistal radius fracture5+paresis101, 3, 5low back pain
1222FemaleCRPS IRight handhand fracture3+paresis121, 2diabetes; glibenclamide
1334MaleCRPS IRight handDistal radius fracture3+paresis91, 2none
1457FemaleCRPS IRight handDistal radius fracture5+paresis261, 2, 4none
1557FemaleCRPS IRight handSprain right wrist4paresis121, 2low back pain
1632FemaleCRPS IRight handRadius fracture4+paresis151, 2hypertension, metoprolol
1744MaleCRPS IRight handDistal radius fracture4+paresis491, 2, 5low back pain
1841FemaleCRPS IRight handRadius fracture4+paresis241, 2none
1927FemaleCRPS IRight handSprain right wrist3+paresis, tremor501none
2060FemaleCRPS IRight handDistal radius fracture3+paresis4011, 2, 5none
2156FemaleCRPS IRight handDistal radius fracture5paresis121, 2, 3none
2260FemaleCRPS IRight handSpontaneous4paresis61, 3none
  • NRS, numeric rating scale; temp., temperature; CTS, carpal tunnel syndrome; n.a., not available; +/− indicates presence or absence of symptoms; therapy: 0 = none; 1 = physical therapy; 2 = non-steroidal anti-inflammatory drugs; 3 = opioid; 4 = amitriptyline; 5 = gabapentin.

Clinical assessment

The same standardized neurological examination was performed in all subjects at both study sites. Sensory function was examined by stroking with a cotton wisp and gently brushing the skin. The examination was performed on the affected and unaffected side in patients and on both sides in healthy controls. All subjects were instructed to report side differences indicating hypo- or hyperaesthesia. Spontaneous pain was rated on a numeric rating scale (NRS), ranging from 0 (no pain) to 10 (worst imaginable pain). Regarding motor function, presence of paresis, tremor and dystonia was assessed in a neurological examination. Finally, presence of trophic changes, oedema, abnormalities in skin colour and sweating were recorded.

Kinematic analysis

Subjects were seated in an adjustable chair facing a table where the target object was fixed on a rack at 32 cm height and 45 cm distance from the body. The object was a black upright cylinder of 1 cm in diameter. At the beginning of each trial the hand rested in a semiprone manner at the starting position. The patients were instructed to reach out and grasp the object only with thumb and index finger at a normal speed as if grasping any object in daily life. The movement started after an acoustic signal. After holding the object for a short period of time the hand returned to the starting position. There were no instructions concerning the duration of the grasping and the resting periods. All subjects performed at least five training trails until they were familiar with the task followed by ten trials each performed on the affected and the contralateral side for off-line analysis. For the recording of the kinematic data we used an optoelectronic motion analysis system (MacReflex version 3.2, Qualisys, Sweden), consisting of four cameras equipped with infrared light emitting diodes and video processors. During the ongoing movement the light was reflected by three passive markers which were attached to the skin at the styloid processus of the radius and the nails of thumb and index finger. The reflected light was recorded by the video processors with a sampling rate of 50Hz and then transferred to a PC for calculation of the kinematic data. Movement paths of the reflective markers were sampled as Cartesian coordinates. Movement speed was calculated as the change of position over time (Wenzelburger et al., 2000).

The target reaching- and grasp-movement is divided into different periods (Fig. 1) (von Hofsten, 1991). The acceleration period starts when the velocity of the wrist exceeds 0.05 m/s and ends when the maximum wrist velocity is reached. The following phase is the deceleration period, which lasts until the velocity falls below 0.05 m/s. The ballistic period consists of the acceleration and deceleration period. The final period of the movement is the target period which terminates when the grasping movement of thumb and index finger is completed. This kinematic fragmentation of the movement is important, because different time periods of movements are probably controlled by different areas of the sensorimotor cortex. Therefore, we were interested to analyse the duration of each period to see whether the motor deficits are pronounced in one of these time periods. Next to the temporal component we recorded the movement trajectories. Special attention was paid to the occurrence of submovements, as an indicator for the occurrence of tremor or correction movements. This was done by calculating the difference between the length of straight lines, connecting successive landmarks of the hand's trajectory (start of the movement and end of acceleration, deceleration and target period), and the real movement path of the hand during each of these periods (curvature index; Fig. 1) (Atkeson and Hollerbach, 1985). Further we analysed the overshoot of the wrist when approaching the target by computing the difference between the highest vertical position of the wrist marker and the vertical marker position at the end of target period. In order to correlate kinematic parameters with motor dysfunction, the functional disability of the upper extremity was assessed by a German translation of the Capabilities of the Upper Extremity Instrument (CUE) (Marino et al., 1998). In the present study we used the sum of four items related to dexterous hand function: picking up a paper clip (item 13), using a key (item 14), turning a coin with thumb and fingers (item 16) and dialing a touch-tone telephone (item 17). In a second experiment, the potential influence of ongoing pain on motor performance was investigated in our control subjects by performing the same kinematic analysis, however, following topical capsaicin application. After cleaning the application side with an alcohol swab, a gauze (12.5 cm2) containing 400 μl of a solution of capsaicin 0.6% in ethanol was placed on the dorsal aspect of the forearm 5 cm proximal to the wrist. The gauze was covered with a plastic tape. The kinematic analysis was started when subjects rated their current ongoing pain with an intensity of 4 [numeric rating scale (NRS) 0–10].

Fig. 1

Kinematic variables of the reach to grasp movement. (A) The trajectory of the wrist with the corresponding velocity profile is shown. The total movement time is divided into an acceleration and deceleration phase followed by the target period. The duration of the different segments is defined by the velocity profile (see ‘Methods’ section). Further the curvature index was calculated. As shown for the target period a straight line distance was determined between the successive landmarks of the movement (1, 2). The distance was subtracted from the real hand path to characterize the hand path curvature. The calculation was also done for the acceleration and deceleration phase. (B) Superimposed traces from successive grasping-to-reach trials are shown. Movement paths of the wrist are less constant in the patient. The peak velocity is decreased in comparison to the control. In the velocity profile the prolongation of the target period is obvious. In this single case grip aperture is reduced.

fMRI experiments and tapping paradigm

Upper limb function was measured using the maximum tapping frequency. The maximum finger tapping frequency was observed for three 30-s trial periods using a tapping counter (Lee et al., 2000). The mean of three trials was calculated for right and left index fingers, both for patients and controls. The maximum tapping rate was observed for three 30-s trial periods outside the magnet, and the mean frequency is reported. The mean maximum tapping frequency of the control group served as a normative data set to assess the patient's individual motor impairment compared to a healthy group by calculating the z-transform: Z = (valuepatient − meancontrols)/SDcontrols (Rolke et al., 2006). The motor task performed during fMRI involved a visually cued finger tapping procedure. This motor paradigm consisted of a block design (see later) with sequential finger tapping, starting with the index finger and ascending to the little finger, whereupon the sequence was reversed until the index finger was reached again, and the process was recommenced. Each of the five stimulation blocks lasted 21 s interrupted by a baseline of 21 s. Previously, patients were trained to execute finger tapping with a frequency of 1 Hz.

Functional MRI and data analysis

Image acquisition

Echoplanar images were collected on a 1.5 Tesla MRI scanner (Sonata, Siemens, Erlangen, Germany) using the standard head coil and the Siemens Magnetom gradient overdrive. For each subject, two time series (unaffected and affected side) of 93 whole-brain images were obtained in a randomized order with a gradient-echo, echo-planar scanning sequence (EPI; repetition time 3 s, time to echo 40 ms, flip angle 90°; field of view 220 mm2, acquisition matrix 64 × 64, 16 axial slices, slice thickness 4 mm, gap 1 mm). The first three images were discarded to account for spin saturation effects. A T1-weighted 3D magnetization prepared rapid acquisition gradient echo sequence (MP RAGE) scan (voxel size = 1.0 × 1.0 × 1.0 mm3) lasting 8 min and 21 s was recorded in the same session as the functional measurements for the recording of the subject's individual brain anatomy. MRI sequences were assessed in the following order: anatomical scout, MP RAGE, 2 × EPI (tapping on the unaffected and affected side in a randomized order). During fMRI experiments, we used a block design for the tapping paradigm with two conditions (‘tapping’ and ‘baseline’) with each block lasting 21 s (see above). The tapping was visually cued. A green square projected onto a screen provided a visual cue for each finger tap. During each rest period the projection screen was black. Subjects were monitored visually at all times during scanning to ensure accurate task performance and to assess for additional involuntary movements.

fMRI data analysis

Data analysis, registration and visualization were performed with the fMRI software package BrainVoyager 2000 (version 4.9; www.brainvoyager.com) as described previously (Maihofner et al., 2004b, 2005; Maihofner and Handwerker, 2005; Maihofner et al., 2006a, b). Briefly, data were motion corrected using sinc interpolation. Preprocessing furthermore included Gaussian spatial (FWHM = 4 mm) and temporal (FWHM = 3 volumes) smoothing of the functional data. Afterwards, the functional data were transformed into a standard stereotactic space (Talairach and Tournoux, 1988), and linear-interpolated to 3 × 3 × 3 mm3 resolution. Individual subjects’ data were averaged for group analysis. We employed a block design with two conditions (‘tapping’ and ‘baseline’) with each block lasting 21 s in which seven images (TR = 3 s) were acquired. This stimulation protocol served to obtain appropriate reference functions reflecting experimental and baseline conditions which were used as predictors in a design matrix, i.e. ‘tapping’= 1, ‘baseline condition’= 0. The resulting design matrices were convoluted with a hemodynamic response function (Boynton et al., 1996) to account for the expected delay and devolution of the BOLD signal. The reference functions served as independent predictors for a general linear model (GLM). As implemented in the BrainVoyager software package, a z-transformation of the functional volume time courses for each subject was applied to take account for different baseline signal levels. All statistical maps were thresholded at P < 0.0001 (uncorrected, two-tailed) and a minimum cluster size of 150 mm3. The cluster size criterion was used as a conservative measure to minimize false positive activations due to type 1 errors (Downar et al., 2002; Mailis-Gagnon et al., 2003; Maihofner et al., 2004b). Corresponding P-values were corrected for multiple comparisons using Bonferroni correction over all voxels.

Statistical analysis

Demographic and kinematic data were analysed by basic descriptive statistics. For psychophysical measures, the Wilcoxon signed ranked test was used to assess statistically significant differences. One way ANOVA was used for comparison of kinematic data between the different groups (group × kinematic parameter). In case of a significant influence of the group factor on the dependent variables post hoc comparisons were computed. Correlation between NRS and CUE scores and kinematic data were calculated using Spearman's rank correlation. Values of P < 0.05 were considered to be statistically significant. All data are expressed as mean ± SEM.

Results

Neurological symptoms and quantitative sensory testing

Patients included for kinematic analysis

All Patients reported spontaneous pain at rest on the affected limb (NRS = 4.3 ± 0.3). There was no significant pain increase by performing the motor task (NRS = 4.3 ± 0.3 versus NRS = 4.7 ± 0.8; P > 0.05). During sensory testing hypoaesthesia was not reported by any of the subjects. Nine patients reported dynamic-mechanical allodyina (NRS = 2.2 ± 0.6) in a glove-like distribution on the affected extremity. Oedema was present in two patients, trophic changes were observed in eight subjects. The CUE score indicated a moderate impairment of upper limb function (15.1 ± 1.2 out of 28 possible points). In control subjects no pathology was detected during neurological examination. After application of the capsaicin it took about 20 min before subjects reported a pain intensity of 4 on the NRS. Spontaneous pain was not significantly changed after finishing the kinematic analysis (NRS = 4.1 ± 0.2).

Patients included for fMRI study

All patients reported pain at rest on the affected limb (NRS = 3.9 ± 0.2). Skin sensory testing revealed no symptoms indicative of segmental or peripheral nerve lesions. On the affected extremity, five patients had dynamic-mechanical allodynia. The allodynic skin area was distributed in a glove-like manner. Oedema was present in nine patients, trophic changes were observed in seven subjects. On the CRPS-affected right side, patients showed a significant decrease of the maximum finger tapping frequency compared to both the non-affected left side (1.2 ± 0.2 versus 3.1 ± 0.1 Hz; P < 0.05), and to the right side of control subjects (1.2 ± 0.2 versus 3.4 ± 0.1 Hz; P < 0.05). No difference was found for the left hand between patients and controls (3.1 ± 0.1 versus 3.1 ± 0.1 Hz; P > 0.05).

Clinical symptoms for both patient groups are listed in detail in Table 1.

Kinematic analysis

One-way ANOVA demonstrated significant differences in total movement time between the groups [F(3,40) = 5.8]. A significant prolongation was observed in patients on the affected side compared to the unaffected side and both control groups (Fig. 2A). Further analysis of the different phases of the movement revealed a distinct pattern. The time needed for acceleration and the maximal movement speed was not significantly changed in any of the groups (Fig. 2B, Table 2). The movement during deceleration was slowed on the affected side [F(3,40) = 5.4] but significance was only reached in comparison to the unaffected side and not in comparison to control subjects (Fig. 2C). The most prominent impairment was observed during the target reaching phase [F(3,40) = 11.2] which was significantly prolonged (Fig. 2D). The movement path of the wrist showed a higher variability in patients compared to controls (Fig. 1). The curvature index was increased during deceleration but not acceleration. A significant increase was found during the target period [F(3,40) = 3.3; Fig. 2E]. No significant differences between the groups could be observed in peak velocity and overshoot (Table 2). Finally no significant differences were observed between the unaffected extremity and the controls in any of the measured parameters.

Fig. 2

Kinematic analysis in patients and controls. Movement time was significantly prolonged on the affected side in CRPS patients compared to the unaffected side and controls with and without pain (A). No significant changes in duration were found during the acceleration phase (B). The increase in movement time was caused by an extensive prolongation of the reaching phase (deceleration) (C) and grip formation (target period) (D). The curvature index was significantly increased on the affected side in CRPS patients (E). This finding indicates an irregularity of movement paths in patients which is restricted to the target period and deceleration phase.

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Table 2

Comparison of kinematic variables between controls and patients

ControlsControls with painPatient unaffected sidePatient-affected side
Overshoot (mm)2.3 ± 0.42.5 ± 0.83.0 ± 0.83.8 ± 0.9
Max. movement speed (m/s)0.85 ± 0.061.0 ± 0.030.98 ± 0.050.69 ± 0.08
  • Note: Values are displayed as means ± SEM.

Correlation between clinical and kinematic measures

A strong correlation was observed between the scores obtained in the CUE score and total movement time (r = –0.76, P = 0.003). No correlation could be demonstrated between the CUE score and other kinematic variables. Further no correlation could be established between spontaneous pain ratings (before and after the kinematic analysis) and the measured parameters.

fMRI study

Figure 3 shows group activation maps during motor performance on the CRPS-affected extremity (i.e. the right hand; Fig. 3A), the right hand of controls (Fig. 3B), the non-affected extremity of CRPS patients (i.e. the left hand; Fig. 3C) and the left hand of controls (Fig. 3D). The corresponding Talairach-coordinates, Z-scores, Bonferroni-corrected P-values, cluster sizes and Brodmann areas are depicted in Table 3. Axial brain slices are referred to by their superior–inferior position relative to the AC–PC line. During finger tapping of the right hand in controls (Fig. 3B and Table 3), significant activations were seen in the contralateral primary sensory and motor cortices (S1 and MC), parietal association cortex (PA), middle frontal cortex (MFC) and bilateral secondary somatosensory cortices (S2), inferior parietal lobule (IPL), insula, supplementary motor cortices (pre-SMA and SMA-proper), bilateral superior frontal cortices (SFC) and ipsilateral inferior frontal cortex (IFC) and MC. Furthermore, the contralateral thalamus, bilateral nuclei lentiformis (ncl) and areas within the intraparietal sulcus (IPS) were activated [bilateral medial intraparietal area (MIP) and contralateral anterior intraparietal area (AIP); see Fig. 3B and Table 3]. The same structures were also activated during finger tapping on the unaffected side in patients and the left side in controls (Fig. 3C and D and Table 3). In contrast, markedly larger brain activations were detected during finger tapping on the CRPS-affected side (Fig. 3A). In this condition, significant activations were found in bilateral MC, S1, PA, IPL, S2, insula, pre-SMA and SMA-proper, SFC, MFC, IFC, IPS (AIP and MIP), thalamus and ncl. To further differentiate cortical activations during tapping on the CRPS-affected side and right hand of controls in more detail, a contrast map in the GLM model was calculated by subtracting the tapping condition of controls from the tapping condition in patients. As shown in Fig. 4A brain regions showing significantly greater response during finger tapping in CRPS patients were the classical motor areas MC, pre-SMA and SMA-proper and intraparietal sulci (AIP and MIP). Furthermore, bilateral S1, S2, IPL, SFC and ipsilateral MFC and IFC were activated. The corresponding coordinates and statistical parameters of the GLM model are given in detail in Table 4. Furthermore, we compared brain activations during finger tapping on the CRPS-affected side with tapping on the non-affected side by calculating a contrast map in the GLM, where brain activations during these two conditions were subtracted. Figure 4B shows that within the motor system the left MC, the right IPS (AIP and MIP) and bilateral pre-SMA and SMA-proper were more activated during finger tapping on the CRPS-affected side. Significant stronger activations were also found in S1, IPL, insula and IFC. In contrast, the right MC was more activated during finger tapping on the left side (coded in blue). Furthermore, we introduced the individual degrees of motor impairment (Z-values of tapping frequencies, i.e. values of the individual maximum tapping frequencies normalized to the mean maximum tapping frequencies of controls, see ‘Methods’ section) as regressors in the GLM model for the condition ‘tapping on the CRPS-affected side’. In this approach, we sought to isolate brain areas correlating with the degree of motor impairment. As seen in Fig. 4C, brain activations correlating with the individual Z-values of the motor impairment were detected in contralateral MC and bilateral pre-SMA and SMA-proper. Within the IPS, we observed bilateral activations in the medial area (area MIP) and the anterior area of IPS (area AIP) on the left side (Fig. 4C). Finally, activity within the contralateral IFC correlated with the motor impairment.

Fig. 3

Regions of cerebral activations related to the following experimental conditions: (A) finger tapping of CRPS-patients on the affected side (i.e. right hand); (B) finger tapping of control subjects with the right hand; (C) finger tapping of CRPS-patients on the unaffected side (i.e. left hand); (D) finger tapping of control subjects with the left hand. Brain slices are referred to by the superior–inferior level in millimetres relative to a line through the anterior and posterior comissure (AC–PC line). Statistical maps were thresholded at P < 0.0001 (uncorrected for multiple comparisons; two-tailed) and a minimum cluster size of 150 mm3. Key areas of activations are indicated according to the following abbreviations: S1, primary somatosensory cortex; S2, secondary somatosensory cortex; MC, motor cortex; PA, parietal association cortex; IPL inferior parietal lobule; SFC, superior frontal cortex; MFC, middle frontal cortex; IFC, inferior frontal cortex; sup, superior; IPS, intraparietal sulcus; AIP, anterior intraparietal area; MIP, medial intraparietal area; SMA, supplementary motor cortex; ncl, nucleus lentiformis.

Fig. 4

(A) Contrast map of the GLM model calculated by subtracting the tapping condition of controls (right hand) from the tapping condition in patients (CRPS-affected side, i.e. right hand). Brain slices are referred to by the superior–inferior level in millimetres relative to a line through the anterior and posterior comissure (AC–PC line). Key areas of activations are presented using the same abbreviations as described in Fig. 3. Z-score indicates level of significance. (B) Contrast map of the GLM model calculated by subtracting the tapping condition on the unaffected side (i.e. left hand) from the affected side (i.e. right hand) in CRPS-patients. Brain slices are referred to by the superior–inferior level in millimetres relative to a line through the anterior and posterior comissure (AC–PC line). Key areas of activations are presented using the same abbreviations as described in Fig. 3. Z-score indicates level of significance. (C) Implementation of the individual degrees of motor impairment (Z-values of tapping frequencies, i.e. values of the individual maximum tapping frequencies normalized to the mean maximum tapping frequencies of controls, see ‘Methods’ section) as regressors in the GLM model for the condition ‘tapping on the CRPS-affected side’. In this approach, we sought to isolate brain areas correlating with the degree of motor impairment. The statistical map was thresholded at P < 0.0001. Key areas of activations are presented using the same abbreviations as described in Fig. 3.

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Table 3

Regions of cerebral activations depicted in Fig. 3

RegionSideXYZCluster sizeZ-scoreP-valueBrodmann area
A: Finger tapping CRPS patients (affected/right hand)
MCcontra381550106336.8<0.00014
MCipsi4595245325.8<0.00014/6
S1contra−37−304735306.7<0.00013
S1ipsi36−294819276.4<0.00013
S2contra−55−252142735.7<0.0001/
S2ipsi53−262237365.5<0.0001/
PAcontra−34−535542525.7<0.00015/7
PAipsi33−525328536.3<0.00015/7
IPLcontra−42−303041236.1<0.000140
IPLipsi46−292845235.8<0.000140
insulacontra−38−31325414.8<0.000113
insulaipsi3471217235.2<0.000113
SFCcontra−595238126.7<0.00016
SFCipsi595237146.8<0.00016
MFCcontra−35243331015.0<0.00019
MFCipsi36283328334.6<0.00019
IFCcontra−3953231394.8<0.00019
IFCipsi3843025875.2<0.00019
aACCcontra−418299786.1<0.000124
aACCipsi218309885.2<0.000124
pACCcontra−3−63212125.4<0.000124/32
pACCipsi2−63314156.1<0.000124/32
SMA propercontra314982936.4<0.00016
SMA properipsi324975135.4<0.00016
pre- SMAcontra3204353676.3<0.00016/8
pre- SMAipsi5164352385.2<0.00016/8
IPS/AIPcontra42423513126.4<0.0001/
IPS/AIPipsi40423512456.3<0.0001/
IPS/MIPcontra27494211236.6<0.0001/
IPS/MIPipsi31474010586.1<0.0001/
thalamuscontra−13−1893564.9<0.0001/
thalamusipsi13−1683124.8<0.0001/
ncl.contra−215115555.0<0.0001/
ncl.ipsi224125384.9<0.0001/
B: Finger tapping controls (right hand)
MCcontra34204957305.5<0.00014
MCipsi36204914345.2<0.00014
S1contra−34−234554386.2<0.00013
S1ipsi42−27539385.2<0.00013
S2contra−52−222519535.3<0.0001/
S2ipsi53−252312454.6<0.0001/
PAcontra−27−594628394.7<0.00015/7
PAipsi33−444523454.6<0.00015/7
IPLcontra−42−552525884.8<0.000140
IPLipsi41−513920314.7<0.000140
insulacontra−362128164.4<0.000113
insulaipsi372127774.7<0.000113
SFCcontra−11145411125.1<0.00016
SFCipsi12125312295.5<0.00016
MFCcontra−30214418274.4<0.00019
IFCcontra−45232414334.5<0.00019
IFCipsi48192612344.6<0.00019
pACCcontra−2−1354355.8<0.000124/32
pACCipsi56314255.2<0.000124/32
SMA propercontra345022125.1<0.00016
SMA properipsi785221115.1<0.00016
pre- SMAcontra418417774.6<0.00016/8
pre- SMAipsi519415394.6<0.00016/8
IPS/AIPcontra4142375125.1<0.0001/
IPS/MIPcontra3047405554.3<0.0001/
IPS/MIPipsi3145405434.6<0.0001/
thalamuscontra−14−15113334.6<0.0001/
ncl.contra−205116554.6<0.0001/
ncl.ipsi218115974.6<0.0001/
C: Finger tapping CRPS patients (unaffected/left hand)
MCcontra37195063225.9<0.00014
MCipsi4044318594.7<0.00014/6
S1contra38−285255336.1<0.00013
S1ipsi−35−305018724.9<0.00013
S2contra51−202719835.8<0.0001/
S2ipsi−51−212418325.7<0.0001/
PAcontra29−574734245.7<0.00015/7
PAipsi−30−474625674.6<0.00015/7
IPLcontra38−403425675.8<0.000140
IPLipsi−36−393921454.8<0.000140
insulacontra34−3167204.10.000113
insulaipsi−35−2167774.00.000113
SFCcontra11225319295.0<0.00016
SFCipsi−19234817564.9<0.00016
MFCipsi−3441287184.6<0.00019
IFCipsi−46122812004.4<0.00019
pACCcontra2−3425484.2<0.000124/32
pACCipsi−63424124.5<0.000124/32
SMA propercontra685224035.6<0.00016
SMA properipsi785022524.30.00026
pre- SMAcontra519395674.40.00016/8
pre- SMAipsi520405324.40.00016/8
IPS/AIPcontra4241384985.9<0.0001/
IPS/MIPcontra3245425144.8<0.0001/
IPS/MIPipsi3248435384.8<0.0001/
thalamuscontra16−20103124.9<0.0001/
ncl.contra224115384.8<0.0001/
ncl.ipsi−215105374.8<0.0001/
D: Finger tapping controls (left hand)
MCcontra36174963305.2<0.00014
MCipsi4064416704.6<0.00014/6
S1contra36−304855405.8<0.00013
S1ipsi−42−24528304.7<0.00013
S2contra52−232218435.7<0.0002/
S2ipsi−53−242117355.3<0.0007/
PAcontra29−485232305.6<0.00015/7
PAipsi−29−455124804.7<0.00015/7
IPLcontra31−393526306.4<0.000140
IPLipsi−30−473519744.8<0.000140
insulacontra3114136124.2<0.000113
insulaipsi−3016147144.3<0.000113
SFCcontra4234414324.6<0.00016
SFCipsi−5194512304.7<0.00016
MFCipsi−2915435124.9<0.00016/8
IFCipsi−39221311324.6<0.000145
pACCcontra2−3405504.9<0.000124/32
pACCipsi−33414994.7<0.000124/32
SMA propercontra655023155.5<0.00016
SMA properipsi355121124.4<0.00016
pre- SMAcontra519376125.0<0.00016/8
pre- SMAipsi121355455.1<0.00016/8
IPS/AIPcontra4141394926.5<0.0001/
IPS/MIPcontra3147425124.4<0.0001/
IPS/MIPipsi3049415424.4<0.0001/
thalamuscontra13−18133156.6<0.0001/
ncl.contra24096134.7<0.0001/
ncl.ipsi−23085374.8<0.0001/
  • S1, primary somatosensory cortex; S2, secondary somatosensory cortex; MC, motor cortex; PA, parietal association cortex; IPL inferior parietal lobule; SFC, superior frontal cortex; MFC, middle frontal cortex; IFC, inferior frontal cortex; IPS, intraparietal sulcus; AIP, anterior intraparietal area; MIP, medial intraparietal area; SMA, supplementary motor cortex; aACC, anterior part of the anterior cingulate cortex; pACC, posterior part of the anterior cingulate cortex; ncl., nucleus lentiformis. P-value, corresponding probability following Bonferroni-correction for multiple comparisons; cluster size, cluster sizes of cortical activations in mm3. Classical areas of the motor system are indicated in bold.

View this table:
Table 4

Regions of cerebral activations depicted in Fig. 4

RegionSideXYZCluster sizeZ-scoreP-valueBrodmann area
A: Finger tapping CRPS (affected hand) versus controls (right hand)
MCcontra29284517694.20.00024
MCipsi4214832504.20.00034/6
S1contra−31−304523734.10.00033
S1ipsi31−304517374.20.00023
S2contra−56−242022344.20.0002/
S2ipsi−55−232025653.90.0007/
PAcontra−30−504421824.10.00035/7
PAipsi30−524025384.20.00025/7
insulaipsi3431832384.20.000313
SFCcontra−595214244.20.00036
SFCipsi575213454.10.00036
MFCipsi3533334524.10.00039
IFCipsi4511154614.8<0.000145
pACCcontra−56315654.30.000224/32
pACCipsi56364334.30.000124/32
SMA propercontra315036004.20.00026
SMA properipsi465035414.20.00026
pre- SMAcontra4194322004.30.00018
pre- SMAipsi4184321004.20.00038
IPS/AIPcontra42393812304.10.0003/
IPS/AIPipsi44413811204.20.0002/
IPS/MIPcontra27504311504.20.0003/
IPS/MIPipsi3047429784.20.0003/
B: Finger tapping CRPS (affected hand) versus CRPS (unaffected hand)
MCleft30284931424.9<0.00014
MCright3423485544.60.00014
S1left−31−304612324.9<0.00013
PAleft−30−49434354.130.00015/7
IPLleft−47−29337084.40.000140
IPLright45−28338344.6<0.000140
insulaleft−353134154.60.000113
insularight3731316154.30.000113
SFCleft−7245715024.20.00016
SFCright6−45917604.30.00016
MFCleft−3624302324.00.00019
MFCright3522332864.50.00019
IFCright353329864.50.00019
pACCleft−25325664.4<0.000124/32
pACCright59332223.60.000224/32
SMA properleft364918154.4<0.00016
SMA properright5154817874.4<0.00018
pre- SMAleft5174522174.40.00018
pre- SMAright5184319794.40.00018
IPS/AIPleft4239392324.10.0001/
IPS/MIPleft2647443544.8<0.0001/
IPS/MIPright2845412434.140.0001/
C: Brain areas correlating with motor impairment
MCcontra332849180017.8<0.00014
IFCcontra46112997914.5<0.00019
SMA propercontra3649250015.0<0.00016
SMA properipsi3652267816.3<0.00016
pre- SMAcontra31438125316.2<0.00016/8
pre- SMAipsi21540112014.5<0.00016/8
IPS/AIPcontra404137187919.0<0.0001/
IPS/MIPcontra304743177717.5<0.0001/
IPS/MIPipsi314842160719.5<0.0001/
  • S1, primary somatosensory cortex; S2, secondary somatosensory cortex; MC, motor cortex; PA parietal association cortex; IPL inferior parietal lobule; SFC, superior frontal cortex; MFC, middle frontal cortex; IFC, inferior frontal cortex; IPS, intraparietal sulcus; AIP, anterior intraparietal area; MIP, medial intraparietal area; SMA, supplementary motor cortex; aACC, anterior part of the anterior cingulate cortex; pACC, posterior part of the anterior cingulate cortex; ncl., nucleus lentiformis. P-value, corresponding probability following Bonferroni-correction for multiple comparisons; cluster size, cluster sizes of cortical activations in mm3. Classical areas of the motor system are indicated in bold.

Discussion

In the present study we sought to characterize motor dysfunction in CRPS patients using kinematic analysis of a standardized reach to grasp paradigm and fMRI investigations on the cerebral representation of finger movements. We demonstrated that the grasping (deceleration and target phase) is altered in a characteristic way, whereas the reaching (acceleration phase) is not significantly changed pinpointing to a disturbed integration of visual and proprioceptive inputs in the region of posterior parietal cortex. This fits well with our functional imaging data, where we found a significant reorganization of motor circuits in CRPS patients. Activations of posterior parietal and motor cortices were correlated with the amount of motor impairment.

Impairment of reach to grasp movements in CRPS

CRPS patients showed a characteristic alteration of their reach to grasp ability compared to our control group. Basically, reaching and grasp movements are two distinct phases. During the reaching phase the hand is positioned in front of the object. From animal experiments it seems that positioning of the hand is predominantly preprogrammed in the premotor cortex on the basis of visual input (Ghez and Gordon, 1987; Jeannerod et al., 1995). The preshaping of the hand and grasping of the object is performed by the distal muscles of the hand (Jeannerod, 1984). The precise grasping depends on the integrity of the contralateral primary motor cortex and the pyramidal tract (Brinkman and Kuypers, 1973). Further the precision of the movement during approaching the object and during grasping movements largely depends on the integration of visual and somatosensory afferent inputs (Jeannerod, 1986; Gentilucci et al., 1994). The most striking finding in the kinematic data is the prolongation of the target phase. Furthermore, the curvature index indicates that patients do not use the optimal path during this phase. An increased curvature index can be observed in tremor or in ataxic patients (Deuschl et al., 2000). However, we observed no rhythmic oscillations in the kinematic data, therefore tremor is not a sufficient explanation. The occurrence of correction movements due to misreaching and failure in the spatial orientation during the target period are more likely. In contrast to the reaching phase, not only the visual input but also the proprioceptive and cutaneous sensory inputs are important for terminal movement regulation. In patients with large fibre neuropathy especially the target phase is prolonged and a number of correction movements are needed to reach the object (Gentilucci et al., 1994). Removing cutaneous afferent feedback by local anaesthesia of the fingers without affecting proprioception impairs object manipulation (Gentilucci et al., 1997). However, none of the patients reported hypoesthesia during clinical examination. Hand reaching requires a coordination of visual and proprioceptive maps (Grefkes and Fink, 2005). Lesions or inactivation in the posterior parietal cortex produce spatial disorientation and misreaching (Desmurget et al., 1999). In such a situation target reaching is inaccurate and the movement is altered in terms of a lower peak velocity and a prolonged deceleration phase. There are increasing numbers of clinical observations pointing to an impaired function of the posterior parietal cortex in CRPS patients. Galer and colleagues described a motor neglect like syndrome in CRPS (Galer et al., 1995; Galer and Jensen, 1999), a symptom which is often found in patients with lesions of the parietal cortex (Triggs et al., 1994). Others described motor impairment not only on the affected but also on unaffected extremity in CRPS patients performing a manipulation task (Ribbers et al., 2002). Furthermore, it was described that patients with CRPS take longer to recognize their affected hand in a laterality recognition task (Moseley, 2004). This task is thought to primarily involve the dorsolateral frontal and posterior parietal cortex (Parsons, 2001). It can be suggested that this disturbed integration of visual and proprioceptive inputs is caused by a change in central representation of spatial maps due to alterations of the afferent input. There are several studies which indicate that cortical reorganization in the primary sensory areas develops in a response to experimentally induced acute and chronic pain (Flor et al., 1995; Soros et al., 2001; Maihofner et al., 2003). In the present study, deficits in motor performance were not correlated with pain intensity in patients. Further controls with experimental pain in healthy controls did not show any abnormalities in kinematic analysis. It could not be excluded that if pain were located more distally in the experimental condition and distributed in a glove-shape pattern that it would influence motor performance in the control subjects. Furthermore, the topical application of capsaicin did not allow assessing the effect of pain in deep structures like muscles which may influence, for example, stretch reflexes (Matre et al., 1998). Nevertheless, our kinematic data imply a potential dysfunction of posterior parietal and supplementary motor cortices in CRPS. This hypothesis was further supported by the fMRI part of our study.

Brain areas correlating with CRPS-associated motor impairment

Activations in MC, intraparietal sulci and supplementary motor cortices were correlated with the amount of motor impairment.

The posterior parietal cortex is concerned with the integration of multimodal information for constructing a spatial representation of the personal and extrapersonal space (Grefkes and Fink, 2005). Furthermore, it plays a pivotal role in planning and executing coordinative movements (Grefkes and Fink, 2005). Particularly regions of the IPS serve as an important interface between perceptive and motor systems for controlling hand and eye movements (Grefkes and Fink, 2005). In the present study, areas within the IPS correlating with motor impairment were bilateral medial intraparietal areas (area MIP) and on the left side the anterior intraparietal area (area AIP). Based on previous studies, area MIP is crucially involved in coordination and execution of hand movements (Grefkes et al., 2004; Grefkes and Fink, 2005), whereas electrophysiological recordings show that area AIP is mainly active during finger movements involved in manipulation, fixation and recognition of objects (Sakata et al., 1995). Furthermore, area AIP is connected to the mirror neuron system of the frontal cortex (Matelli et al., 1986), implying that this network may play a role for the transformation of haptic object properties into appropriate movements. Interestingly, in addition to areas MIP and AIP, we indeed observed activations of the left IFC (Fig. 4C), known to contain the putative human correlate of the mirror neuron system (Iacoboni et al., 1999; Binkofski et al., 2000).

Furthermore, areas of supplementary motor cortices were correlated with motor impairment. Basically, the SMA is divided into two functionally and neuroanatomically distinct regions (Luppino et al., 1993; Rizzolatti et al., 1996; Picard and Strick, 2001). The anterior part, i.e. pre-SMA, lies anterior to the coronal plane through the anterior commissure, whereas the caudal part, i.e. the SMA proper, lies posterior to the coronal plane through the anterior commissure (Luppino et al., 1993; Rizzolatti et al., 1996; Picard and Strick, 2001). Both areas significantly differ with respect to their functions, as pre-SMA is thought to be more involved in planning a spatiotemporal pattern of movement when a subject has to accomplish a motor task which comprises complex coordinative tasks (Luppino et al., 1993; Rizzolatti et al., 1996; Picard and Strick, 2001). Interestingly (Fig. 4C), the pre-SMA showed a greater covariation with motor impairment in CRPS compared to the SMA proper. Comparable to increased activations of IPS areas, this underpins a higher level of coordinative motor planning for the CRPS-affected hand.

Reorganization of motor circuits in CRPS

Compared to activations of MC during finger tapping of the unaffected side and MC activations in control subjects, fMRI signals of the primary motor cortex contralateral to the CRPS-affected side were found to be markedly enlarged. The corresponding volumes for unaffected and affected sides were 554 and 3142 mm3 in the GLM contrast map ‘tapping on the CRPS affected hand versus tapping on the unaffected hand’ (Fig. 4B and Table 4) and 6322 versus 10633 mm3 in the respective single contrasts (Fig. 3A and C and Table 3). This enlargement is strikingly different to functional imaging studies investigating S1 somatotopy in CRPS. Previously, hand representations were consistently found to be reduced in CRPS and the hand position was switched to a more lateral and inferior position towards the lip (Juottonen et al., 2002; Maihofner et al., 2003; Pleger et al., 2004; Maihofner et al., 2004a). Cortical reorganization within S1 correlated with pain experience and mechanical hyperalgesia (Maihofner et al., 2003; Pleger et al., 2004). This incongruence of the sensorimotor system may contribute to an abnormal self perception and disrupted body scheme in CRPS. Furthermore, an incongruence of cortical motor and sensory representations distinguishes CRPS from other neurological conditions accompanied by plastic brain changes. For instance, in patients with hand dystonia, shrinkage of both motor and sensory hand representations were found (Meunier et al., 2001; Candia et al., 2003). To achieve a homogeneous patient group, we intentionally did not include CRPS patients with hand dystonia. Therefore, it would be also interesting to investigate cortical representations of CRPS patients with dystonic features (van Hilten et al., 2000, 2001).

How does cortical reorganization of the motor cortex in CRPS occur? One mechanism, known to mediate short-term changes of map plasticity may be the unmasking of previously ‘latent’ synaptic connections by disinhibition (Sanes et al., 1988). Previous experiments suggests that the inhibitory neurotransmitter GABA plays a major role in establishing cortical maps, as inhibition of GABAergic activity leads to rapid expansions of cortical receptive fields (Jacobs and Donoghue, 1991) and unmasking of previously silent polysynaptic pathways (Pluto et al., 2004). There are indeed several lines of evidence that intracortical inhibition is decreased in the motor cortex in CRPS. Intracortical inhibition as measured by a paired pulse transcranial magnetic stimulation (TMS) paradigm was reported to be decreased (Schwenkreis et al., 2003). Furthermore, evidence for a pathological sensorimotor connectivity between S1 and the motor cortex comes from a previous MEG study (Juottonen et al., 2002). Basically, following tactile stimulations, the motor cortex shows a biphasic characteristic modulation of its 20 Hz rhythm, consisting of a brief suppression and a subsequent enhancement. There is accumulating evidence that this later rebound reflects increased motor cortex inhibition (Salmelin and Hari, 1994; Juottonen et al., 2002). Juottonen and colleagues demonstrated that CRPS patients show an attenuation of the 20 Hz rebound response, consistent with a decreased inhibition of the motor cortex (Juottonen et al., 2002). This also supports previous TMS findings that noxious input can modify motor cortex excitability (Valeriani et al., 1999). Whereas TMS studies in CRPS allow insights in the extension of excitable neuronal structures (Krause et al., 2006), our fMRI data reflect the recruitment of neuronal structures necessary for adequate active finger tapping rather than the direct excitability of the motor cortex. Finally, longer-term adaptive cortical changes may come from axonal sprouting and synaptic rearrangements (Flor, 2003).

Furthermore, compared to activations of the control group and those on the unaffected side, we observed significant increased activations of the ipsilateral (i.e. right) motor cortex during finger tapping at the affected side. The corresponding Talairach coordinates of ipsilateral motor cortex activations agree with the reported position of the premotor area in the literature (Weiller et al., 1992; Chollet and Weiller, 1994). There is converging evidence that increased ipsilateral motor cortex activation may play a general role in adaptation to dysfunction or neuronal damage within the motor system (Weiller et al., 1992; Chollet and Weiller, 1994). Increased ipsilateral motor cortex activation during motor performance can reflect dysfunction of interhemispheric connections, as transcallosal connections between motor cortices are known to mediate predominantly inhibitory responses (Schnitzler et al., 1996). Therefore, ipsilateral motor cortex activation in CRPS may reflect an adaptive response to generate and maintain adequate motor patterns. Finally, compared to controls, parts of the frontal cortex (mainly BAs 8, 9, 10, 46) showed higher activations during finger tapping on the CRPS side. This may reflect higher cognitive processing, as respective brain areas are known to be involved in planning processes, executive aspects of selective attention and complex processes which operate on information of the working memory, like monitoring, manipulation and higher level planning (MacDonald III et al., 2000; Bunge et al., 2001; Sakai et al., 2002; van den Heuvel et al., 2003; Maihofner and Handwerker, 2005).

In summary, in the present study we characterized motor dysfunction in CRPS. We were able to demonstrate impaired reach to grasp movements and significant adaptive changes of the central motor system. Future studies will have to demonstrate how these changes recover under therapy.

Acknowledgements

This study was supported by the German Research Network ‘Neuropathic Pain Syndromes’ (German Federal Ministry of Education and Research, BMBF), the ELAN- fund of the University of Erlangen (37 NL-06.02.10.1), the Deutsche Forschungsgemeinschaft (DFG Ba 1921/1-4) and an unrestricted educational grant from Pfizer, Germany. The authors thank Cornelia Hofmann for excellent technical assistance and care of patients.

Footnotes

  • Abbreviations:
    Abbreviations:
    CRPS
    complex regional pain syndrome

References

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