Research Report
Altered sensorimotor representations after
recovery from peripheral nerve damage in
neuralgic amyotrophy
Renee Lustenhouwer
a,b,*, Ian G.M. Cameron
b, Nens van Alfen
c,
Talitha D. Oorsprong
a,b, Ivan Toni
b, Baziel G.M. van Engelen
c,
Jan T. Groothuis
aand Rick C. Helmich
b,caRadboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Center for Medical Neuroscience, Department of Rehabilitation, Nijmegen, the Netherlands
b
Radboud University, Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Nijmegen, the Netherlands
cRadboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Center for Medical Neuroscience, Department of Neurology, Nijmegen, the Netherlands
a r t i c l e i n f o
Article history: Received 1 August 2019 Reviewed 18 September 2019 Revised 15 November 2019 Accepted 6 February 2020 Action editor Branch Coslett Published online 28 February 2020 Keywords: Neuralgic amyotrophy Motor imagery Peripheral nerve Sensorimotor representations (mal)Adaptive neuroplasticitya b s t r a c t
Neuralgic amyotrophy is a common peripheral nerve disorder caused by acute autoim-mune inflammation of the brachial plexus. Subsequent weakness of the stabilizing shoulder muscles leads to compensatory strategies and abnormal motor control of the shoulder. Despite recovery of peripheral nerves and muscle strength over time, motor dysfunction often persists. Suboptimal motor recovery has been linked to maladaptive changes in the central motor system in several nervous system disorders. We therefore hypothesized that neuralgic amyotrophy patients with persistent motor dysfunction may have altered cerebral sensorimotor representations of the affected upper limb. To test this hypothesis, 21 neuralgic amyotrophy patients (mean age 45± 12 years, 5 female) with persistent lateralized symptoms in the right upper limb and 20 age- and sex-matched healthy controls, all right-handed, performed a hand laterality judgement task in a cross-sectional comparison. Previous evidence has shown that to solve this task, subjects rely on sensorimotor representations of their own upper limb, using a first-person imagery perspective without actual motor execution. This enabled us to investigate altered central sensorimotor representations while controlling for altered motor output and altered so-matosensory afference. We found that neuralgic amyotrophy patients were specifically less accurate for laterality judgments of their affected right limb, as compared to healthy
Abbreviations: DASH, Disabilities of the Arm Shoulder and Hand; ER, error rate; NA, Neuralgic amyotrophy; RT, Reaction time; SRQ-DLV, Shoulder Rating Questionnairee Dutch Language Version.
* Corresponding author. Radboud University Medical Center, Department of Rehabilitation, P.O. Box 9101, 6500 HB, Nijmegen, the Netherlands.
E-mail addresses: Renee.Lustenhouwer@radboudumc.nl (R. Lustenhouwer), I.Cameron@donders.ru.nl (I.G.M. Cameron), Nens. vanAlfen@radboudumc.nl(N. van Alfen),talithaoorsprong@gmail.com(T.D. Oorsprong),I.Toni@donders.ru.nl(I. Toni), Baziel.vanEn-gelen@radboudumc.nl(B.G.M. van Engelen),Jan.Groothuis@radboudumc.nl(J.T. Groothuis),Rick.Helmich@donders.ru.nl(R.C. Helmich).
Available online at
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https://doi.org/10.1016/j.cortex.2020.02.011
0010-9452/© 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/).
controls. There were no significant group differences in reaction times. Both groups used a first-person imagery perspective, as evidenced by changes in reaction times as a function of participants’ own arm posture. We conclude that cerebral sensorimotor representations of the affected upper limb are altered in neuralgic amyotrophy patients. This suggests that maladaptive central neuroplasticity may occur in response to peripheral nerve damage, thereby contributing to motor dysfunction. Therapies focused on altering cerebral senso-rimotor representations may help to treat peripheral nerve disorders such as neuralgic amyotrophy.
© 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
1.
Introduction
Plasticity is a key feature of our nervous system, allowing humans to recover from injury (Navarro, Vivo, & Valero-Cabre, 2007; Palop, Chin,& Mucke, 2006). When parts of the motor system are damaged, motor function can be regained by recruiting compensatory brain circuits (Li, Li, Zhu,& Chen, 2014; van Nuenen et al., 2012; Zeller& Classen, 2014). How-ever, plastic reorganization of the motor system is not always advantageous: it may actually worsen motor dysfunction, in which case it is referred to as“maladaptive neuroplasticity” (Navarro et al., 2007; Oouchida et al., 2016). The occurrence of maladaptive plasticity has been described in several central nervous system disorders (Kishore, Meunier, & Popa, 2014; Takeuchi& Izumi, 2012). There are also clinical examples of maladaptive plasticity occurring after damage to the periph-eral nervous system. One example is obstetric brachial plexus palsy, where developmental apraxia e i.e., clinical motor dysfunction despite peripheral reinnervatione is thought to result from maladaptive central motor programming after birth-related brachial plexus damage (Simon, Franz, Gupta, Alden,& Kliot, 2016). Accordingly, adults with this disorder have altered motor-related brain activity compared to healthy controls (Anguelova, Rombouts, van Dijk, Buur,& Malessy, 2017).
Here we focus on changes in sensorimotor processes occurring in neuralgic amyotrophy (NA), which is a common and disabling peripheral nervous disorder characterized by auto-immune inflammation of the brachial plexus (van Alfen et al., 2015; van Eijk, Groothuis,& van Alfen, 2016). NA is typically asymmetric and most often affects one upper limb (van Alfen& van Engelen, 2006). Paresis of muscles that are innervated by the damaged nerves leads to motor dysfunc-tion. Many patients subsequently develop compensatory, but atypical movement patterns of the affected limb. Several clinical clues link these abnormal patterns to changes in central sensorimotor processes. First, many NA patients show a lack of functional recovery, even after reinnervation of the affected muscles and return of muscle strength (Cup et al., 2013; van Alfen, van der Werf,& van Engelen, 2009; van Eijk et al., 2016). Second, motor dysfunction of the affected upper limb is more severe when patients perform well-trained movements that rely on existing motor programs, as compared to the situation where they perform novel move-ments requiring ad hoc formation of a new motor plan (van
Eijk et al., 2016). Third, some NA patients develop abnormal and involuntary movements that phenotypically resemble
dystonia e a symptom commonly associated with central
changes (Abdo et al., 2009). Finally, patients can regain normal motor function by relearning correct movement patterns through rehabilitation, even years after onset (Ijspeert et al., 2013). This latter finding indicates the clinical importance of distinguishing between peripheral and central causes for motor dysfunction in peripheral nervous system disorders, since they require different treatments.
However, the hypothesis that central sensorimotor pro-cesses become deficient in NA has never been tested. Here we tested this hypothesis by using a hand laterality judgment task, which involves mental rotation of one's upper limb, without overt motor expression. Laterality judgment relies on the same sensorimotor representations and similar brain re-gions as motor planning and execution (Hetu et al., 2013; Parsons, 2001), and controls for possible disease-related pe-ripheral changes in motor execution or associated afferent feedback (Helmich, Aarts, de Lange, Bloem, & Toni, 2009; Parsons, 1987). Some posit that these sensorimotor repre-sentations reflect“motor imagery”, the mental simulation of movement without motor expression (Parsons, 1987; Parsons, 1994). We used a validated task in which subjects are pre-sented with pictures of hands and are asked to indicate their laterality (left or right). Behavioral responses during this hand laterality judgment task follow the same biomechanical and motor constraints as the execution of movements bringing a participant's hand into the same orientation of the hand pic-tures (Parsons, 1987; Parsons, 1994). Responses are also influenced by the position of the subjects' own arms, which indicates that subjects rely on sensorimotor representations of their own upper limb and a first-person imagery perspec-tive is used to solve the task (de Lange, Helmich,& Toni, 2006; Ionta, Fourkas, Fiorio,& Aglioti, 2007; Qu, Wang, Zhong, & Ye, 2018). This task has been shown to be sensitive to changes in sensorimotor representations in several asymmetric central and peripheral disorders (Breckenridge, Ginn, Wallwork, & McAuley, 2018; de Lange, Roelofs, & Toni, 2008; Fiorio, Tinazzi,& Aglioti, 2006; Helmich, de Lange, Bloem, & Toni, 2007; Schmid& Coppieters, 2012; van Elk et al., 2010). Impor-tantly, manipulations of the peripheral nervous system (local anesthesia and immobilization) also influence performance on this task in healthy individuals (Meugnot, Agbangla, & Toussaint, 2016; Silva et al., 2011). Here we compared
behavioral performance on the hand laterality judgment task between right-lateralized NA patients and matched healthy controls. We predicted behavioral impairments for right - but not left - hand stimuli in patients.
2.
Materials and methods
We made a cross-sectional comparison of patients with NA to healthy controls. The study was approved by the local medical
ethical committee (Medical Ethical Committee region
Arnhem-Nijmegen, CMO 2014-1435). No part of the study procedures or analyses was pre-registered prior to the research being conducted. We report how we determined our sample size, all data exclusion, all inclusion/exclusion criteria, whether inclusion/exclusion criteria were established prior to data analysis, all manipulations, and all measures in the study.
2.1. Participants
Twenty-one patients with a clinical diagnosis of NA and twenty-one age and sex-matched healthy control subjects participated in the study. All participants were right-handed and 18 years or older, and all participants gave written informed consent according to the Declaration of Helsinki before they participated in the study. Patients were enrolled through the specialized outpatient plexus clinic at the Rad-boud university medical center in Nijmegen, the Netherlands. All NA patients had clearly lateralized symptoms in the right upper limb and presented with scapular dyskinesia (i.e., abnormal motor control of the shoulder) on the affected, right side. Patients in the acute phase (i.e.,< 2 months since attack onset) of the disorder were excluded. Additional exclusion criteria were the presence of passive shoulder movement limitations, the presence of other disorders that affect the ability to move the upper limb, lumbosacral plexus involve-ment, and the inability to give informed consent. Healthy subjects were recruited through the university's healthy par-ticipants' databases. They were excluded if they had a history of or current complaints in the shoulder region, a neuro-muscular or a neurological disorder. These in- and exclusion criteria were established prior to the start of the study. See Table 1for an overview of the participant characteristics.
We used objective and subjective measures to quantify NA-related symptoms. Since the serratus anterior muscle is often affected in NA patients with abnormal scapular move-ment patterns (van Alfen& van Engelen, 2006), we estimated a maximal force exerted by this muscle using a manual digital dynamometer (MicroFET2®), on both the left and the right side, in both patients and controls. This was done while the arm was extended at shoulder level in the scapular plane (Ijspeert et al., 2020). Furthermore, patients filled out two common questionnaires to assess functional capability of the affected upper limb. First, the Shoulder Rating Questionnaire, Dutch Language Version (SRQ-DLV) assesses functional capability of the shoulder, arm and hand. It is a reliable and validated questionnaire (Vermeulen et al., 2005) that has been shown to be sensitive in this patient population (Ijspeert et al., 2013). The SRQ-DLV consists of a visual analogue scale and 19
multiple choice items that cover seven subscales. Sum scores range from 14 to 100 with higher scores reflecting higher functional capability. Second, the Disability of the Arm, Shoulder and Hand (DASH) assesses shoulder, arm and hand capability. The DASH has been used in multiple disorders of the upper limb (Bot et al., 2004). It consists of 30 multiple choice items about movements and movement-related com-plaints during daily activities, and contains two optional modules on work and sports/performing arts. Scores for the main test range from 1 to 100, with higher scores reflecting more impairment.
2.2. Sample size calculation
As there were no available previous data to conduct a power analysis on, the sample size of the current study was based on comparable studies, using the same task, in different pop-ulations (Fiorio et al., 2006; Schmid& Coppieters, 2012; van Elk et al., 2010).
2.3. Experimental design
We used the hand laterality judgment task (Parsons, 1987) to compare sensorimotor representations of the upper limb be-tween NA patients and healthy controls. Participants were seated in front of a computer screen and were presented with white line drawings of hands on a black background. Their task was to judge whether the stimulus on display repre-sented a left or a right hand. Participants were told that they could use their own hands as reference (i.e., they could ima-gine moving their own limb to match the hand on display), but they were asked not to actually move their own upper limb (confirmed using electromyography, see below). A cover obscured participants' hands from view, to prevent the use of visual information. Participants responded by pressing a Table 1e Participant characteristics the information in the table includes only the participants that were included in the final analyses (21 neuralgic amyotrophy patients, 20 healthy controls). The mean± standard deviation are displayed for all measures, except for the serratus anterior strength, where the mean± standard error of the mean are displayed. SRQ-DLV scores were missing for four patients.
NA patients Healthy controls Age (years) 45± 12 45± 11 Sex (male/female) 16/5 15/5 SRQ-DLV score 51± 17 e DASH score 36± 17 e
Time since last attack (months) median, range
61± 124 16, 5e540
e Serratus anterior strength (Newton)
Left, unaffected/non-dominant side 230.2± 15.1* 265.0 ± 18.3 Right, affected/dominant side 189.0± 16.1* 265.4 ± 16.0* NA¼ neuralgic amyotrophy; SRQ-DLV ¼ Shoulder Rating Ques-tionnairee Dutch Language Version; DASH ¼ Disability of the Arm, Shoulder and Hand.* significant difference (p < .01) between NA patients' right/affected and left/unaffected serratus anterior strength, as well as between NA patients' right/affected and healthy controls' right/dominant serratus anterior strength.
button with the corresponding left or right foot. Participants performed 24e32 practice trials to get familiar with the task. The task consisted of 30e32 blocks of 12 trials each (the first 11 participants only performed 30 blocks). The stimuli varied in laterality (left or right), degree of rotation (rotated 135,
105,75,45, 45, 75, 105, or 135from upright position),
and view (palmar or dorsal); totaling 32 different stimuli types (seeFig. 1A). The inclusion of several rotations along multiple rotational axes is important as the engagement of sensori-motor representations, through first person sensori-motor imagery or other cognitive embodied processes, critically depends on these factors (Parsons, 1987; ter Horst, van Lier, & Steenbergen, 2010). We manipulated the participant's own hand position in a block-wise manner during the experiment. Before each block, participants were instructed to place their own hands in one of four possible positions: both palms facing up, both palms facing down, one palm facing up (left/right) and the contralateral palm facing down (right/left). Thus, for each stimulus, the subject's own hand position was either congruent (e.g., posture: palm up; stimulus: palmar view) or incongruent (e.g., posture: palm up; stimulus: dorsal view) with respect to the stimulus on the screen (seeFig. 1B). This allowed us to test whether participants used a first-person imagery perspective to perform the task. It additionally en-ables the assessment of the influence of disease-related so-matosensory changes. We were interested in soso-matosensory changes, as sensory involvement is common in NA (van Alfen & van Engelen, 2006). The stimulus order was pseudo-randomized, ensuring that the different stimuli types were spread evenly across blocks. The inter-trial interval varied randomly between 500 and 1500 msec. In this inter-trial
interval, participants were presented with a fixation cross. Stimuli were presented until a button was pressed, with a maximum of 5s. We used reaction times and error rates to evaluate behavioral performance. In addition, we monitored muscle activity using electromyography over both thumbs (i.e., thenar eminence) to rule out that subjects made hand movements during the task.
2.4. Statistical analyses
All statistical analyses were performed using IBM SPSS Sta-tistics 25, statistical tests were two-tailed and alpha-level was set at p¼ .05, unless otherwise specified.
The age of the two groups (NA patients and healthy con-trols) was compared with an independent samples t-test. Serratus anterior strength of both arms was compared with a 2-factor mixed analysis of variance (ANOVA) with between-group factor GROUP (NA patients, healthy controls), and repeated factor SIDE (left/unaffected/non-dominant, right/ affected/dominant).
For the motor imagery task, we analyzed the influence of between-group factor GROUP (NA patients, healthy controls), and the repeated factors LATERALITY (left, right), and ROTA-TION (135, 105, 75, 45, 45, 75, 105, 135) on
normalized error rate (ER) and median reaction time (RT) on correct trials with two separate 3-factor mixed ANOVAs. ER was normalized with an arcsine transformation (Sheskin, 2003). We additionally tested for the effects of
between-group factor GROUP and repeated factors POSTURE
(congruent, incongruent) and LATERALITY on normalized ER and median RT with two separate 3-factor mixed ANOVAs. To
Fig. 1e Experimental design. A. Stimulus set Overview of all stimuli. Stimuli differed in LATERALITY (left, right), ROTATION (¡135,¡105,¡75,¡45, 45, 75, 105, or 135), and view (dorsal, palmar). LATERALITY and ROTATION are entered as
factors in the statistical analyses for error rate and reaction time. The two different views (i.e., dorsal, upper row and palmar, bottom row) allow for assessing the effect of the manipulation of posture (see also B.). B. Postural manipulation Participants are seated in front of a computer screen with their hands on a table in front of them. A cover obscures the participants' hands from view. At the start of each task block, participants are asked to place their hands in one of four possible positions: both hands with the palms facing down, both hands with palms facing up, one palm facing up (left/right) and the contralateral palm facing down (right/left). The view (dorsal, or palmar) of the stimulus on the screen can either be congruent with their current hand position (see Congruent example on the left), or it can be incongruent (see Incongruent example on the right).
further verify that participants incorporated their own body posture, we also examined the effect of the symmetry of the
posture of the participants’ own two hands (see
Supplementary materials). If Mauchly testing revealed that the assumption of sphericity of variances was violated, we applied Greenhouse-Geisser (if ε .75) or Huynh-Feldt (if ε > .75) corrections to the degrees of freedom (Girden, 1992). We corrected for multiple testing (4 ANOVAs) by setting alpha at p¼ .0125. To control for any potential group differences in speed-accuracy trade-off during the task, we additionally calculated the efficiency scores for each condition (i.e., divided the normalized ERs by the median RTs) and performed the same ANOVAs on these ratio scores (Machizawa & Driver, 2011; Nixon, Lawton-Craddock, Tivis, & Ceballos, 2007; Townsend& Ashby, 1983; Woltz & Was, 2006).
To evaluate the relationship between performance on the hand laterality judgment task and clinical (patient) charac-teristics, correlational analyses were performed for measures that showed significant effects involving group. For the nor-mally distributed measures of functional capability (the SRQ-DLV and DASH scores) we calculated Pearson correlation co-efficients. As the time since last attack (Table 1) did not follow a normal distribution, we used Spearman correlation to explore possible associations between disease duration and task performance.
2.5. Data availability
De-identified data, task materials, analyses scripts, and questionnaires are available in a data repository through the following URL: http://hdl.handle.net/11633/aacwcmem. The conditions of our ethical approval do no permit public archiving of individual data on age and time since last attack as these are indirect identifiers. Readers seeking access to this data should contact the lead author RL. Access will be granted to named individuals in accordance with ethical procedures governing the reuse of sensitive data. Specifically, requestors must meet the following conditions to obtain the data: they must adhere to the RU-DI-HD-1.0 data use agreement.
3.
Results
One healthy control was excluded from further analyses, as his overall ER of 25% was more than three standard deviations higher than the mean ER. Data of 21 NA patients and 20 healthy controls were used in the final analyses. For four NA patients, we did not have the SRQ-DLV scores. There were no significant group differences in age or sex (Table 1). The groups did differ significantly in force exerted by the serratus
anterior muscles, as evidenced by the significant
GROUP SIDE interaction effect [F (1,39) ¼ 9,3, p ¼ .004, part. h2
¼ .19]. Post-hoc comparisons showed that NA patients exerted significantly less force with the serratus anterior on the affected, right side compared to the contralateral unaf-fected left side [F (1,20)¼ 14,8, p ¼ .001, part. h2¼ .43] and compared to healthy controls on the right side [F (1,39)¼ 11,3, p¼ .002, part. h2¼ .23]. This confirms that NA patients had lateralized symptoms of the right upper limb. Group means and standard error of the means are displayed inTable 1.
3.1. Hand laterality judgment task 3.1.1. Error rates (ER)
Participants performed the task accurately, reflected by low overall ER across both groups [NA patients: 3.2± 2.8%; healthy controls: 2.4± 2.3%; no effect of GROUP: F (1, 39) ¼ .6, p ¼ .46, part.h2¼ .01]. In both groups, subjects made more errors for more extreme rotations [main effect of ROTATION: F (7, 273) ¼ 11.9, p < .001, part. h2 ¼ .23; no interaction effects involving ROTATION and GROUP: F 1.6, p .17, part. h2¼ .04; Fig. 2]. However, NA patients made relatively more errors with
their affected right limb than healthy controls
[GROUP LATERALITY interaction: F (1,39) ¼ 13.1, p ¼ .001, part.h2¼ .25]. Specifically, post-hoc comparisons showed that NA patients had a higher ER for the affected, right limb than healthy controls [F (1,39)¼ 8.9), p ¼ .005, part. h2¼ .19] (see Fig. 2C). Furthermore, in healthy controls the ER was signifi-cantly lower on their dominant right side than on their non-dominant left side [F (1,19) ¼ 19.4, p < .001, part. h2¼ .51], whereas for NA patients ER tended to be higher on their affected, dominant right side than on their non-dominant left side [F (1,20)¼ 4.0, p ¼ .06, part. h2¼ .17]. (The interaction between GROUP and LATERALITY remained significant when correcting ERs for RTs by running the same analysis on effi-ciency scores [F (1,39)¼ 5.4, p ¼ .03, part. h2¼ .12], confirming that group differences in speed-accuracy trade-off did not influence our results (see Supplementary materials). Across groups, participants’ own hand posture did not significantly influence ER [no main effect of POSTURE: F (1, 39)¼ 2.2, p ¼ . 14, part.h2¼ .05; no interaction effects involving POSTURE and GROUP: F (1, 39) 1.1, p .30, part. h2 .03].
3.1.2. Reaction times (RT)
Overall, NA patients and healthy controls performed the task equally fast [no main effect of GROUP: F (1,39)¼ .04, p ¼ .84, part. h2
¼ .001;Fig. 3]. All participants were faster on their dominant, right side than on their non-dominant, left side [significant main effect of LATERALITY: F (1,39)¼ 20.6, p < .001, part. h2 ¼ .35; no significant interaction effects involving LATERALITY and GROUP: F .5, p .50, part. h2 .01]. Par-ticipants were slower for stimuli that were rotated at more extreme angles main effect of ROTATION [F (3.1, 119.5)¼ 67.8, p< .001, part. h2¼ .64]. Importantly, in both groups RTs were modulated by the biomechanical complexity of the imagined movement. More specifically, participants responded faster for stimuli where the hand was rotated to a medial versus a lateral orientation, with respect to the body axis. This became apparent in a significant LATERALITY ROTATION interac-tion [F (2.8, 109.4)¼ 30.9, p < .001, part. h2¼ .44], where stimuli that were rotated clockwise (i.e., 45, 75, 105, 135) were easier (medial orientation) for left hands, but more difficult (lateral orientation) for right hands, and vice versa for stimuli that were rotated counter-clockwise (i.e.,45,75,105,
135). Post-hoc testing indeed revealed that participants
were significantly slower for laterally oriented stimuli than for medially orientated stimuli [F (1,39) ¼ 55.2, p < .001, part.
h2 ¼ .59]. This previously documented biomechanical
complexity effect shows that participants were sensitive to biomechanical constraints associated with task-related upper limb movements. This confirms that participants did not
employ a purely visual imagery strategy to solve the task. Finally, across both groups, participants responded faster to congruent stimuli that matched the current position of their own hand, as compared to incongruent stimuli [significant main effect of POSTURE: F (1, 39)¼ 18.0, p < .001, part. h2¼ .32; no significant interaction effects involving GROUP: F (1, 39) .2, p .25, part. h2 .04]. Moreover, participants responded faster when the posture of their own two hands
was symmetric, as compared to trials were the posture of their own two hands was asymmetric, and this result did not in-fluence the main findings reported in this paper (see Supplementary materials). The significant effect of POSTURE is an important piece of evidence to indicate that subjects incorporated their own body posture and thus relied on sensorimotor representations, using a first-person rather than a third-person perspective.
Fig. 2e Error rates These graphs show the unnormalized error rates in percentage for the different rotations for unaffected non-dominant left (A.) and affected dominant right (B.) hands for factors LATERALITY, ROTATION and GROUP. In panel (C.)
the data have been collapsed across ROTATION, to illustrate the LATERALITY£ GROUP interaction and the between- and
within-group differences. Individual data points are provided. NA¼ neuralgic amyotrophy patients; HC ¼ healthy controls. Error bars± 1 standard error. * significant difference at p < .01. SeeSupplementary Fig. 1for graphs depicting the normalized error rates, on which the statistical analyses were performed.
Fig. 3e Median reaction times These graphs show the median reaction times (RT) for the different rotations for unaffected non-dominant left (A.) and affected dominant right (B.) hands for factors LATERALITY, ROTATION and GROUP. Overall, participants were faster for stimuli on their dominant, right side than on their non-dominant, left side. RTs increased with degree of rotation, and were higher for laterally orientated stimuli than for medially orientated stimuli. RT did not differ between groups. NA¼ neuralgic amyotrophy patients; HC ¼ healthy controls; Error bars ± 1 standard error.
3.2. Correlation with clinical measures
The normalized ER for right hands did not correlate with functional capability [SRQ-DLV scores (r¼ - .01, p ¼ .96), gen-eral DASH or DASH modules (r ± .14, p .56)] in NA patients. The time since the last attack in NA patients was also not correlated with the right normalized ER (r ¼ .09, p ¼ .69).
4.
Discussion
We tested whether patients with a strictly lateralized pe-ripheral nervous system disorder (neuralgic amyotrophy of the right upper limb) showed altered central sensorimotor representations of their affected right limb. Thus, we compared behavioral performance during the validated hand laterality judgment task, between 21 NA patients and 20 healthy controls. In line with our hypothesis, we found that NA patients showed a specific and significant deficit (increased error rate) when recognizing their affected right limb, as compared to healthy controls.
Importantly, our results confirm that both groups used a first-person perspective, i.e., that they used their own body as a reference during imagery: RTs were sensitive to limb-specific biomechanical constraints (lateral or medial rota-tion with respect to the body axis) and to the posirota-tion of the subjects' own arm posture (congruent or incongruent with respect to the stimulus on the screen), in line with previous studies (de Lange et al., 2006; Ionta et al., 2007; Jongsma et al., 2013; Qu et al., 2018). These findings, especially the posture congruency effect, provide empirical evidence that NA patients did not employ alternative (visual) strategies to solve this task (Vannuscorps & Caramazza, 2015, 2016). There is some debate as to which processes underly the hand laterality judgment task. Since its introduction, it has been widely assumed that a hand's laterality is determined by implicitly imagining moving the own hand to match the hand on the screen (i.e., implicit“motor imagery”) (Parsons, 1987; Parsons, 1994; Parsons & Fox, 1998). Recently, it has been proposed that instead of through motor imagery, lat-erality is determined through the multisensory binding of the proprioceptive representation of the own hand and the visual representation of the hand on the screen (i.e., multi-sensory integration) (Viswanathan, Fritz, & Grafton, 2012). Both motor imagery and multisensory integration involve sensorimotor representations and central sensorimotor processes. Previous neuroimaging studies (Hetu et al., 2013; Parsons, 2001) show that the hand laterality judgment task evokes brain activity in regions that are involved in prepa-ration, planning, selection, and execution of movement (Gardini et al., 2016; Hardwick, Caspers, Eickhoff, & Swinnen, 2018; Pedersen et al., 1998; Randerath, Valyear, Philip, & Frey, 2017). Furthermore, in previous work the posture congruency effect was specifically associated with brain activity in the posterior parietal cortex (de Lange et al., 2006; Hetu et al., 2013), a region that is essential for body schema encoding (Whitlock, 2017). Body schema is the in-tegrated neural representation of the body based on so-matosensory feedback (Head& Holmes, 1911e1912; Medina & Coslett, 2010).
In the current study, the posture congruency effect was similar between NA patients and controls, indicating that patients are able to incorporate postural information of their affected upper limb during imagery. We thus propose that the patients’ impaired performance for laterality judgment of their right upper limb is associated with deficits in central sensorimotor processes. Whether this deficit stems from deficient motor, sensory, or integrational processes, remains to be investigated. In line with this idea, we also found that whereas healthy controls were significantly more accurate with their dominant than with their non-dominant limb, pa-tients showed a trend towards the opposite (i.e., lower accu-racy for the dominant, affected, limb than for the non-dominant, unaffected, limb). Patients often report reduced use of their affected, dominant limb, and increased use of their unaffected, non-dominant limb. Hence, it could be argued that patients may develop a bias towards the non-affected, non-dominant, limb, and that our results may therefore reflect a shift in limb preference rather than an impairment of the affected limb. However, it has been shown in healthy individuals that while hand-immobilization nega-tively affects recognition of the immobilized hand in this task, it does not improve performance for the over-used non-immobilized hand (Debarnot, Huber, Guillot, & Schwartz, 2018; Meugnot, Almecija, & Toussaint, 2014; Meugnot & Toussaint, 2015). The effect of long-term limb disuse on task performance has been studied in a small sample of in-dividuals with traumatic brachial plexus injury. Although patients performed worst with their injured, disused limb, performance was also decreased for their uninjured, over-used limb compared to healthy controls (Date et al., 2019). If a bias towards the over-used hand would underly the decrease in performance for the disused hand, a concurrent increase in performance for the over-used hand would be expected. At this time, we cannot determine whether a direct impairment of the affected limb or a bias towards the unaf-fected limb underlies the altered central sensorimotor repre-sentations we found in NA patients in the current study.
4.1. Changes in central sensorimotor processes after peripheral nerve damage
Our findings, and those of others, indicate that patients with peripheral nerve damage are susceptible to changes in the central sensorimotor system, which in turn may influence their clinical symptoms. A growing body of evidence de-scribes how the central nervous system adapts to peripheral nerve injury, and that the adaptations are not always bene-ficial. Examples include long-lasting reorganization of so-matosensory representations and primary motor cortex despite peripheral regeneration after peripheral nerve injury in monkeys (Florence, Garraghty, Wall, & Kaas, 1994; Merzenich et al., 1983; Wall et al., 1986; Wall, Felleman, & Kaas, 1983; Wall & Kaas, 1986) and rats (Donoghue, Suner, & Sanes, 1990; Sanes, Suner, & Donoghue, 1990; Sanes, Suner, Lando, & Donoghue, 1988), respectively. In humans, examples include phantom pain and phantom movements after upper limb amputation (Andoh, Milde, Tsao, & Flor, 2018; Lotze, Flor, Grodd, Larbig,& Birbaumer, 2001; Mercier, Reilly, Vargas, Aballea,& Sirigu, 2006), paresthesia, pain and
functional deficits in carpal tunnel syndrome (Maeda et al., 2013, 2014, 2016) and focal hand dystonia in response to (over)use (Furuya& Hanakawa, 2016; Quartarone, Siebner, & Rothwell, 2006). Maladaptive motor representations have also been linked to developmental apraxia and muscle weakness in individuals with birth-related brachial plexus injury (Anguelova et al., 2017; Simon et al., 2016). The main finding of this study, i.e., abnormal sensorimotor represen-tations in NA patients, confirms our clinical impression that many NA patients have persistent motor deficits despite clinical signs of peripheral nerve recovery. It is therefore possible that cerebral (mal)adaptations also play a role in persistent motor dysfunction in NA. This notion may have important implications for treatment. Behavioral therapies that target cerebral plasticity, such as sensory and motor re-education, show promising results in other peripheral dis-orders with documented cerebral (mal)adaptations (Navarro et al., 2007; Novak& von der Heyde, 2015). In our outpatient clinic, NA patients are able to regain normal motor function through relearning correct movement patterns (Ijspeert et al., 2013). It remains to be investigated whether markers of central dysfunction can predict the response of NA patients to these therapies.
4.2. Strengths and interpretational issues
Mechanical factors related to the disorder did not underlie the selectivity of the reported deficit, as participants responded with their feet, instead of with their finger(s), which is the typical method of response in this task. The lower extremities were not affected in the NA patients that participated in this study (van Alfen& van Engelen, 2006; van Eijk et al., 2016), ensuring that the physical button press was not influenced by peripheral factors related to the disorder, which may have been the case if finger button presses were used. As performance was only decreased for the affected limb, our findings cannot be explained by general group dif-ferences in cognitive factors such as working memory, attention or motivation, which may also affect performance on this task (Amesz, Tessari, Ottoboni,& Marsden, 2016; de Lange et al., 2004; Mazhari & Moghadas Tabrizi, 2014; Tabrizi et al., 2013). Our findings are also not explained by group differences in speed-accuracy trade-off, as evidenced by the analysis on efficiency scores. Thus, we conclude that the deficit we found is task-induced and likely to be caused by NA itself.
We did not find a significant correlation between perfor-mance on the hand laterality judgment task and any of our clinical outcome measures. Although some studies have found that clinical measures such as pain duration, predicted pain, pain medication intake and general activities are asso-ciated with performance on this task in other upper-limb disorders (Coslett, Medina, Kliot, & Burkey, 2010; Moseley, 2004; Pelletier, Bourbonnais, et al., 2018), others have not found such associations (Pelletier, Higgins, & Bourbonnais, 2018; Schmid& Coppieters, 2012). The lack of significant cor-relations in our study could mean that clinical measures are only indirectly related to, or are not sensitive enough to the sensorimotor representations deficit we found evidence for in NA. There may also be lasting peripheral changes that could
contribute to persistent motor problems in NA (van Eijk et al., 2016). However, peripheral changes cannot explain the cur-rent findings: our experimental design eliminates the influ-ence of peripheral factors (such as nerve damage and altered motor execution), and instead relies on central sensorimotor processes.
5.
Conclusion
We conclude that peripheral nerve damage can lead to impaired central sensorimotor representations, as evidenced by altered behavioral performance during the hand laterality judgment task in patients with neuralgic amyotrophy. In as-sociation with our clinical experience, these changes are compatible with maladaptive central neuroplasticity, and they may be susceptible to interventions aimed at restoring these deficits (such as specific rehabilitation techniques). Our findings form the foundation for further (neuroimaging) research into the cerebral mechanisms that are associated with persistent motor dysfunction and recovery in NA. Our findings may also be relevant for other peripheral motor dis-orders, where similar mechanisms may apply, although this remains to be investigated.
Credit author statement
Renee Lustenhouwer: Conceptualization, Software, Formal Analysis, Investigation, Data Curation, Writing e Original Draft, Visualization, Project Administration Ian Cameron: Conceptualization, Methodology, Software, Investigation, Re-sources, Data Curation, Writing e Original Draft, Writing e Review& Editing, Supervision, Funding Acquisition Nens Van Alfen: Conceptualization, Methodology, Resources, Writing e Review & Editing, Supervision, Funding Acquisition Talitha Oorsprong: Software, Formal Analysis, Investigation, Project Administration Ivan Toni: Conceptualization, Methodology, Resources, Writinge Review & Editing, Supervision, Funding Acquisition Baziel van Engelen: Conceptualization, Writinge Review & Editing, Supervision, Funding Acquisition Jan
Groothuis: Conceptualization, Methodology, Resources,
Writinge Review & Editing, Supervision, Funding Acquisition Rick Helmich: Conceptualization, Methodology, Software, Resources, Writing e Original Draft, Writing e Review & Editing, Supervision, Funding Acquisition.
Funding
This work was supported by the Prinses Beatrix Spierfonds [W.OR16-05]. The funder has had no role in development, execution of, or reporting on this study and its outcomes.
Open practices
The study in this article earned Open Materials badges for transparent practices. Materials for the study are available at http://hdl.handle.net/11633/aacwcmem.
Declaration of Competing Interest
None.Acknowledgements
We thank our participants for their time and commitment to the study. We also thank Lisa Nieland for her contribution to data collection.
Supplementary data
Supplementary data to this article can be found online at https://doi.org/10.1016/j.cortex.2020.02.011.
r e f e r e n c e s
Abdo, W. F., Bloem, B. R., Eijk, J. J., Geurts, A. C., van Alfen, N., & van de Warrenburg, B. P. (2009). Atypical dystonic shoulder movements following neuralgic amyotrophy. Movement Disorders, 24(2), 293e296.https://doi.org/10.1002/mds.22398. Amesz, S., Tessari, A., Ottoboni, G., & Marsden, J. (2016). An
observational study of implicit motor imagery using laterality recognition of the hand after stroke. Brain Injury, 30(8), 999e1004.https://doi.org/10.3109/02699052.2016.1147600. Andoh, J., Milde, C., Tsao, J. W., & Flor, H. (2018). Cortical plasticity
as a basis of phantom limb pain: Fact or fiction? Neuroscience, 387, 85e91.https://doi.org/10.1016/j.neuroscience.2017.11.015. Anguelova, G. V., Rombouts, S., van Dijk, J. G., Buur, P. F., &
Malessy, M. J. A. (2017). Increased brain activation during motor imagery suggests central abnormality in neonatal brachial plexus palsy. Neuroscience Research, 123, 19e26. https://doi.org/10.1016/j.neures.2017.05.001.
Bot, S. D., Terwee, C. B., van der Windt, D. A., Bouter, L. M., Dekker, J., & de Vet, H. C. (2004). Clinimetric evaluation of shoulder disability questionnaires: A systematic review of the literature. Annals of the Rheumatic Diseases, 63(4), 335e341. Breckenridge, J. D., Ginn, K. A., Wallwork, S. B., & McAuley, J. H.
(2018). Do people with chronic musculoskeletal pain have impaired motor imagery? A meta-analytical systematic review of the left/right judgement task. The Journal of Pain.https:// doi.org/10.1016/j.jpain.2018.07.004.
Coslett, H. B., Medina, J., Kliot, D., & Burkey, A. R. (2010). Mental motor imagery indexes pain: The hand laterality task. European Journal of Pain, 14(10), 1007e1013.https://doi.org/ 10.1016/j.ejpain.2010.04.001.
Cup, E. H., Ijspeert, J., Janssen, R. J., Bussemaker-Beumer, C., Jacobs, J., Pieterse, A. J., & van Alfen, N. (2013). Residual complaints after neuralgic amyotrophy. Archives of Physical Medicine and Rehabilitation, 94(1), 67e73.https://doi.org/ 10.1016/j.apmr.2012.07.014.
Date, S., Kurumadani, H., Yoshimura, M., Fukae, A., Onishi, K., Hayashi, J., & Sunagawa, T. (2019). Long-term disuse of the hand affects motor imagery ability in patients with complete brachial plexus palsy. Neuroreport, 30(6), 452e456.https:// doi.org/10.1097/WNR.0000000000001229.
Debarnot, U., Huber, C., Guillot, A., & Schwartz, S. (2018). Sensorimotor representation and functional motor changes following short-term arm immobilization. Behavioral Neuroscience.https://doi.org/10.1037/bne0000274.
de Lange, F. P., Helmich, R. C., & Toni, I. (2006). Posture influences motor imagery: An fMRI study. Neuroimage, 33(2), 609e617. https://doi.org/10.1016/j.neuroimage.2006.07.017.
de Lange, F. P., Kalkman, J. S., Bleijenberg, G., Hagoort, P., van der Werf, S. P., van der Meer, J. W., et al. (2004). Neural correlates of the chronic fatigue syndrome–an fMRI study. Brain, 127(Pt 9), 1948e1957.https://doi.org/10.1093/brain/awh225. de Lange, F. P., Roelofs, K., & Toni, I. (2008). Motor imagery: A
window into the mechanisms and alterations of the motor system. Cortex, 44(5), 494e506.https://doi.org/10.1016/ j.cortex.2007.09.002.
Donoghue, J. P., Suner, S., & Sanes, J. N. (1990). Dynamic organization of primary motor cortex output to target muscles in adult rats. II. Rapid reorganization following motor nerve lesions. Experimental Brain Research, 79(3), 492e503.
Fiorio, M., Tinazzi, M., & Aglioti, S. M. (2006). Selective impairment of hand mental rotation in patients with focal hand dystonia. Brain, 129(Pt 1), 47e54.https://doi.org/10.1093/brain/awh630. Florence, S. L., Garraghty, P. E., Wall, J. T., & Kaas, J. H. (1994).
Sensory afferent projections and area 3b somatotopy following median nerve cut and repair in macaque monkeys. Cerebral Cortex, 4(4), 391e407.
Furuya, S., & Hanakawa, T. (2016). The curse of motor expertise: Use-dependent focal dystonia as a manifestation of
maladaptive changes in body representation. Neuroscience Research, 104, 112e119.https://doi.org/10.1016/
j.neures.2015.12.001.
Gardini, S., Venneri, A., McGeown, W. J., Toraci, C., Nocetti, L., Porro, C. A., et al. (2016). Brain activation patterns
characterizing different phases of motor action: Execution, choice and ideation. Brain Topography, 29(5), 679e692.https:// doi.org/10.1007/s10548-016-0491-5.
Girden, E. (1992). ANOVA: Repeated measures. Newbury park, CA: Sage.
Hardwick, R. M., Caspers, S., Eickhoff, S. B., & Swinnen, S. P. (2018). Neural correlates of action: Comparing meta-analyses of imagery, observation, and execution. Neuroscience and Biobehavioral Reviews, 94, 31e44.https://doi.org/10.1016/ j.neubiorev.2018.08.003.
Head, H., & Holmes, G. (1911e1912). Sensory disturbances from cerebral lesions. Brain, 34, 102e254.
Helmich, R. C., Aarts, E., de Lange, F. P., Bloem, B. R., & Toni, I. (2009). Increased dependence of action selection on recent motor history in Parkinson's disease. The Journal of Neuroscience, 29(19), 6105e6113.https://doi.org/10.1523/ JNEUROSCI.0704-09.2009.
Helmich, R. C., de Lange, F. P., Bloem, B. R., & Toni, I. (2007). Cerebral compensation during motor imagery in Parkinson's disease. Neuropsychologia, 45(10), 2201e2215.https://doi.org/ 10.1016/j.neuropsychologia.2007.02.024.
Hetu, S., Gregoire, M., Saimpont, A., Coll, M. P., Eugene, F., Michon, P. E., et al. (2013). The neural network of motor imagery: An ALE meta-analysis. Neuroscience and Biobehavioral Reviews, 37(5), 930e949.https://doi.org/10.1016/
j.neubiorev.2013.03.017.
Ijspeert, J., Janssen, R. M., Murgia, A., Pisters, M. F., Cup, E. H., Groothuis, J. T., et al. (2013). Efficacy of a combined physical and occupational therapy intervention in patients with subacute neuralgic amyotrophy: A pilot study.
Neurorehabilitation, 33(4), 657e665. https://doi.org/10.3233/NRE-130993.
Ijspeert, J., Kerstens, H. C. J. W., Janssen, R. M. J., Geurts, A. C. H., van Alfen, N., & Groothuis, J. T. (2020). Validity and reliability of serratus anterior hand held dynamometry. BMC
Musculoskeletal Disorders.
Ionta, S., Fourkas, A. D., Fiorio, M., & Aglioti, S. M. (2007). The influence of hands posture on mental rotation of hands and
feet. Experimental Brain Research, 183(1), 1e7.https://doi.org/ 10.1007/s00221-007-1020-2.
Jongsma, M. L., Meulenbroek, R. G., Okely, J., Baas, C. M., van der Lubbe, R. H., & Steenbergen, B. (2013). Effects of hand orientation on motor imagery–event related potentials suggest kinesthetic motor imagery to solve the hand laterality judgment task. PLoS One, 8(9), e76515.https://doi.org/10.1371/ journal.pone.0076515.
Kishore, A., Meunier, S., & Popa, T. (2014). Cerebellar influence on motor cortex plasticity: Behavioral implications for
Parkinson's disease. Frontiers in Neurology, 5, 68.https:// doi.org/10.3389/fneur.2014.00068.
Li, W., Li, Y., Zhu, W., & Chen, X. (2014). Changes in brain functional network connectivity after stroke. Neural
Regeneration Research, 9(1), 51e60. https://doi.org/10.4103/1673-5374.125330.
Lotze, M., Flor, H., Grodd, W., Larbig, W., & Birbaumer, N. (2001). Phantom movements and pain. An fMRI study in upper limb amputees. Brain, 124(Pt 11), 2268e2277.
Machizawa, M. G., & Driver, J. (2011). Principal component analysis of behavioural individual differences suggests that particular aspects of visual working memory may relate to specific aspects of attention. Neuropsychologia, 49(6), 1518e1526.https://doi.org/10.1016/
j.neuropsychologia.2010.11.032.
Maeda, Y., Kettner, N., Holden, J., Lee, J., Kim, J., Cina, S., & Napadow, V. (2014). Functional deficits in carpal tunnel syndrome reflect reorganization of primary somatosensory cortex. Brain, 137(Pt 6), 1741e1752.https://doi.org/10.1093/ brain/awu096.
Maeda, Y., Kettner, N., Kim, J., Kim, H., Cina, S., Malatesta, C., & Napadow, V. (2016). Primary somatosensory/motor cortical thickness distinguishes paresthesia-dominant from pain-dominant carpal tunnel syndrome. Pain, 157(5), 1085e1093. https://doi.org/10.1097/j.pain.0000000000000486.
Maeda, Y., Kettner, N., Sheehan, J., Kim, J., Cina, S., Malatesta, C., & Napadow, V. (2013). Altered brain morphometry in carpal tunnel syndrome is associated with median nerve pathology. Neuroimage Clinics, 2, 313e319.https://doi.org/10.1016/ j.nicl.2013.02.001.
Mazhari, S., & Moghadas Tabrizi, Y. (2014). Abnormalities of mental rotation of hands associated with speed of information processing and executive function in chronic schizophrenic patients. Psychiatry and Clinical Neurosciences, 68(6), 410e417.https://doi.org/10.1111/pcn.12148.
Medina, J., & Coslett, H. B. (2010). From maps to form to space: touch and the body schema. Neuropsychologia, 48(3), 645e654. https://doi.org/10.1016/j.neuropsychologia.2009.08.017. Mercier, C., Reilly, K. T., Vargas, C. D., Aballea, A., & Sirigu, A.
(2006). Mapping phantom movement representations in the motor cortex of amputees. Brain, 129(Pt 8), 2202e2210.https:// doi.org/10.1093/brain/awl180.
Merzenich, M. M., Kaas, J. H., Wall, J. T., Sur, M., Nelson, R. J., & Felleman, D. J. (1983). Progression of change following median nerve section in the cortical representation of the hand in areas 3b and 1 in adult owl and squirrel monkeys. Neuroscience, 10(3), 639e665.
Meugnot, A., Agbangla, N. F., & Toussaint, L. (2016). Selective impairment of sensorimotor representations following short-term upper-limb immobilization. The Quarterly Journal of Experimental Psychology (Hove), 69(9), 1842e1850.https:// doi.org/10.1080/17470218.2015.1125376.
Meugnot, A., Almecija, Y., & Toussaint, L. (2014). The embodied nature of motor imagery processes highlighted by short-term limb immobilization. Experimental Psychology, 61(3), 180e186. https://doi.org/10.1027/1618-3169/a000237.
Meugnot, A., & Toussaint, L. (2015). Functional plasticity of sensorimotor representations following short-term
immobilization of the dominant versus non-dominant hands. Acta Psychologica (Amst), 155, 51e56.https://doi.org/10.1016/ j.actpsy.2014.11.013.
Moseley, G. L. (2004). Why do people with complex regional pain syndrome take longer to recognize their affected hand? Neurology, 62(12), 2182e2186.
Navarro, X., Vivo, M., & Valero-Cabre, A. (2007). Neural plasticity after peripheral nerve injury and regeneration. Progress in Neurobiology, 82(4), 163e201.https://doi.org/10.1016/ j.pneurobio.2007.06.005.
Nixon, S. J., Lawton-Craddock, A., Tivis, R., & Ceballos, N. (2007). Nicotine's effects on attentional efficiency in alcoholics. Alcoholism Clinical and Experimental Research, 31(12), 2083e2091. https://doi.org/10.1111/j.1530-0277.2007.00526.x.
Novak, C. B., & von der Heyde, R. L. (2015). Rehabilitation of the upper extremity following nerve and tendon reconstruction: When and how. Seminars Plastic Surgery, 29(1), 73e80.https:// doi.org/10.1055/s-0035-1544172.
Oouchida, Y., Sudo, T., Inamura, T., Tanaka, N., Ohki, Y., & Izumi, S. (2016). Maladaptive change of body representation in the brain after damage to central or peripheral nervous system. Neuroscience Research, 104, 38e43.https://doi.org/ 10.1016/j.neures.2015.12.015.
Palop, J. J., Chin, J., & Mucke, L. (2006). A network dysfunction perspective on neurodegenerative diseases. Nature, 443(7113), 768e773.https://doi.org/10.1038/nature05289.
Parsons, L. M. (1987). Imagined spatial transformations of one's hands and feet. Cognitive Psychology, 19, 178e241.
Parsons, L. M. (1994). Temporal and kinematic properties of motor behavior reflected in mentally simulated action. Journal of Experimental Psychology Human Perception and Performance, 20(4), 709e730.
Parsons, L. M. (2001). Integrating cognitive psychology, neurology and neuroimaging. Acta Psychologica (Amst), 107(1e3), 155e181. Parsons, L. M., & Fox, P. T. (1998). The neural basis of implicit
movements used in recognising hand shape. Cognitive Neuropsychology, 15(6e8), 583e615.
Pedersen, J. R., Johannsen, P., Bak, C. K., Kofoed, B., Saermark, K., & Gjedde, A. (1998). Origin of human motor readiness field linked to left middle frontal gyrus by MEG and PET. Neuroimage, 8(2), 214e220.https://doi.org/10.1006/ nimg.1998.0362.
Pelletier, R., Bourbonnais, D., Higgins, J., Mireault, M.,
Danino, M. A., & Harris, P. G. (2018). Left right judgement task and sensory, motor, and cognitive assessment in participants with wrist/hand pain. Rehabilitation Research Practice, 2018, 1530245.https://doi.org/10.1155/2018/1530245.
Pelletier, R., Higgins, J., & Bourbonnais, D. (2018). Laterality recognition of images, motor performance, and aspects related to pain in participants with and without wrist/hand disorders: An observational cross-sectional study.
Musculoskeletal Science Practice, 35, 18e24.https://doi.org/ 10.1016/j.msksp.2018.01.010.
Quartarone, A., Siebner, H. R., & Rothwell, J. C. (2006). Task-specific hand dystonia: Can too much plasticity be bad for you? Trends in Neurosciences, 29(4), 192e199.https://doi.org/ 10.1016/j.tins.2006.02.007.
Qu, F., Wang, J., Zhong, Y., & Ye, H. (2018). Postural effects on the mental rotation of body-related pictures: An fMRI study. Frontiers in Psychology, 9, 720.https://doi.org/10.3389/ fpsyg.2018.00720.
Randerath, J., Valyear, K. F., Philip, B. A., & Frey, S. H. (2017). Contributions of the parietal cortex to increased efficiency of planning-based action selection. Neuropsychologia, 105, 135e143.https://doi.org/10.1016/
j.neuropsychologia.2017.04.024.
Sanes, J. N., Suner, S., & Donoghue, J. P. (1990). Dynamic organization of primary motor cortex output to target muscles
in adult rats. I. Long-term patterns of reorganization following motor or mixed peripheral nerve lesions. Experimental Brain Research, 79(3), 479e491.
Sanes, J. N., Suner, S., Lando, J. F., & Donoghue, J. P. (1988). Rapid reorganization of adult rat motor cortex somatic representation patterns after motor nerve injury. Proceeding of National Academy Science in United States of America, 85(6), 2003e2007.
Schmid, A. B., & Coppieters, M. W. (2012). Left/right judgment of body parts is selectively impaired in patients with unilateral carpal tunnel syndrome. The Clinical Journal of Pain, 28(7), 615e622.https://doi.org/10.1097/AJP.0b013e31823e16b9. Sheskin, D. J. (2003). The handbook of parametric and nonparametric
statistical procedures. Boca Raton, FL: Chapman& Hall/CRC. Silva, S., Loubinoux, I., Olivier, M., Bataille, B., Fourcade, O.,
Samii, K., & Demonet, J. F. (2011). Impaired visual hand recognition in preoperative patients during brachial plexus anesthesia: Importance of peripheral neural input for mental representation of the hand. Anesthesiology, 114(1), 126e134. https://doi.org/10.1097/ALN.0b013e31820164f1.
Simon, N. G., Franz, C. K., Gupta, N., Alden, T., & Kliot, M. (2016). Central adaptation following brachial plexus injury. World Neurosurgery, 85, 325e332.https://doi.org/10.1016/ j.wneu.2015.09.027.
Tabrizi, Y. M., Mazhari, S., Nazari, M. A., Zangiabadi, N., Sheibani, V., & Azarang, S. (2013). Compromised motor imagery ability in individuals with multiple sclerosis and mild physical disability: An ERP study. Clinical Neurology and Neurosurgery, 115(9), 1738e1744.https://doi.org/10.1016/ j.clineuro.2013.04.002.
Takeuchi, N., & Izumi, S. (2012). Maladaptive plasticity for motor recovery after stroke: Mechanisms and approaches. Neural Plasticity, 2012, 359728.https://doi.org/10.1155/2012/359728. ter Horst, A. C., van Lier, R., & Steenbergen, B. (2010). Mental
rotation task of hands: Differential influence number of rotational axes. Experimental Brain Research, 203(2), 347e354. https://doi.org/10.1007/s00221-010-2235-1.
Townsend, J. T., & Ashby, F. G. (1983). The stochastic modeling of elementary psychological processes. Cambridge, Cambridgeshire: New York, NY: Cambridge University Press.
van Alfen, N., van Eijk, J. J., Ennik, T., Flynn, S. O., Nobacht, I. E., Groothuis, J. T., & van de Laar, F. A. (2015). Incidence of neuralgic amyotrophy (Parsonage Turner syndrome) in a primary care setting–a prospective cohort study. PLoS One, 10(5), e0128361.https://doi.org/10.1371/journal.pone.0128361. van Alfen, N., & van Engelen, B. G. (2006). The clinical spectrum of
neuralgic amyotrophy in 246 cases. Brain, 129(Pt 2), 438e450. https://doi.org/10.1093/brain/awh722.
van Alfen, N., van der Werf, S. P., & van Engelen, B. G. (2009). Long-term pain, fatigue, and impairment in neuralgic amyotrophy. Archives of Physical Medicine and Rehabilitation, 90(3), 435e439.https://doi.org/10.1016/j.apmr.2008.08.216.
van Eijk, J. J., Groothuis, J. T., & van Alfen, N. (2016). Neuralgic amyotrophy: An update on diagnosis, pathophysiology, and treatment. Muscle andNerve, 53(3), 337e350.https://doi.org/ 10.1002/mus.25008.
van Elk, M., Craje, C., Beeren, M. E., Steenbergen, B., van Schie, H. T., & Bekkering, H. (2010). Neural evidence for compromised motor imagery in right hemiparetic cerebral palsy. Frontiers in Neurology, 1, 150.https://doi.org/10.3389/ fneur.2010.00150.
van Nuenen, B. F., Helmich, R. C., Buenen, N., van de
Warrenburg, B. P., Bloem, B. R., & Toni, I. (2012). Compensatory activity in the extrastriate body area of Parkinson's disease patients. The Journal of Neuroscience, 32(28), 9546e9553.https:// doi.org/10.1523/JNEUROSCI.0335-12.2012.
Vannuscorps, G., & Caramazza, A. (2015). Typical biomechanical bias in the perception of congenitally absent hands. Cortex, 67, 147e150.https://doi.org/10.1016/j.cortex.2015.02.015.
Vannuscorps, G., & Caramazza, A. (2016). The origin of the biomechanical bias in apparent body movement perception. Neuropsychologia, 89, 281e286.https://doi.org/10.1016/ j.neuropsychologia.2016.05.029.
Vermeulen, H. M., Boonman, D. C., Schuller, H. M.,
Obermann, W. R., van Houwelingen, H. C., Rozing, P. M., et al. (2005). Translation, adaptation and validation of the shoulder rating questionnaire (SRQ) into the Dutch language. Clinical Rehabilitation, 19(3), 300e311.https://doi.org/10.1191/ 0269215505cr811oa.
Viswanathan, S., Fritz, C., & Grafton, S. T. (2012). Telling the right hand from the left hand: Multisensory integration, not motor imagery, solves the problem. Psychological Science, 23(6), 598e607.https://doi.org/10.1177/0956797611429802. Wall, J. T., Felleman, D. J., & Kaas, J. H. (1983). Recovery of
normal topography in the somatosensory cortex of monkeys after nerve crush and regeneration. Science, 221(4612), 771e773.
Wall, J. T., & Kaas, J. H. (1986). Long-term cortical consequences of reinnervation errors after nerve regeneration in monkeys. Brain Research, 372(2), 400e404.
Wall, J. T., Kaas, J. H., Sur, M., Nelson, R. J., Felleman, D. J., & Merzenich, M. M. (1986). Functional reorganization in somatosensory cortical areas 3b and 1 of adult monkeys after median nerve repair: Possible relationships to sensory recovery in humans. The Journal of Neuroscience, 6(1), 218e233. Whitlock, J. R. (2017). Posterior parietal cortex. Current Biology,
27(14), R691eR695.https://doi.org/10.1016/j.cub.2017.06.007. Woltz, D. J., & Was, C. A. (2006). Availability of related long-term
memory during and after attention focus in working memory. Memory and Cognition, 34(3), 668e684.
Zeller, D., & Classen, J. (2014). Plasticity of the motor system in multiple sclerosis. Neuroscience, 283, 222e230.https://doi.org/ 10.1016/j.neuroscience.2014.05.043.
