Object-centered sensorimotor bias of torque control in the chronic stage following stroke

Object-centered sensorimotor bias of torque control in the chronic stage following stroke | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Object-centered sensorimotor bias of torque control in the chronic stage following stroke Thomas Rudolf Schneider, Joachim Hermsdörfer This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1466052/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background When lifting objects whose center of mass (CoM) are not centered below the handle one must compensate for arising external torques already at lift-off to avoid object tilt. Previous studies showed that finger force scaling during object lifting may be impaired at both hands following stroke. However, torque control in object manipulation has not yet been studied in patients with stroke. In this study, thirteen patients with chronic stage left hemispheric stroke (SL), nine patients with right hemispheric stroke (SR) and hand-matched controls had to grasp and lift an object with the fingertips of their ipsilesional hand at a handle while preventing object tilt. Object CoM and therewith the external torque was varied by either relocating a covert weight or the handle. The compensatory torque at lift-off (Tcom) is the sum of the torque resulting from 1) grip force being produced at different vertical finger positions (∆CoP x GF) and 2) different vertical load forces on both sides of the handle (∆Fy x w/2). Results When having to rely on sensorimotor memories, ∆CoP x GF was elevated when the object CoM was on the ipislesional-, but decreased when CoM was on the contralesional side in SL, whereas ∆Fy x w/2 was biased in the opposite direction, resulting in normal Tcom. SR patients applied a smaller ∆CoP x GF when the CoM was on the contralesional side. Torques were not altered when geometric cues were available. The sensorimotor spatial bias of ∆CoP x GF was more pronounced and translated to a bias of overall Tcom in SL patients with signs of apraxia (n = 3). Conclusion Our findings provide evidence for an object-centered spatial bias of manual sensorimotor torque control with the ipsilesional hand following stroke. While both intact finger force-to-position coordination and visuomotor control may compensate for the spatial sensorimotor bias in most stroke patients, it may result in a hampered manual torque control in patients with apraxia. grasping sensorimotor learning visuomotor transformation torque compensation stroke spatial bias Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Background Many stroke survivors suffer from impairments of dexterous upper-limb function affecting their functional independence as well as quality of life ( 1 – 3 ). Weakness, spasticity and a loss of selective finger movements of the contralesional upper extremity consequent to lesions of the primary cortex or the corticospinal tract as well as impaired manual dexterity due to somatosensory deficits linked to thalamic or parietal cortical lesions are clinically well recognized consequences of stroke and have been the focus of physical rehabilitation research as they contribute most to functional impairments (for review see ( 2 )). Consequently, stroke survivors with contralateral hemiparesis must rely on their ipsilesional, i.e. non-paretic, hand to a great extent to perform activities of daily living. However, a growing number of studies demonstrates that fine motor performance of the ipsilesional upper limb is also substantially deprived following stroke ( 4 , 5 ). Impaired fine motor control of the ipsilesional hand is evident in clinical motor function tests like the Jebsen Hand Function Test ( 5 – 10 ), in finger-tapping ( 11 , 12 ), and tests of fine motor dexterity, e.g. the 9-hole-peg test ( 8 , 9 , 13 – 15 ). Subtle losses in dexterity of the ipsilesional hand are relevant for performance in activities of daily living and thus threaten the regaining of functional independence following stroke. Accordingly, poorer performance with the ipsilesional hand was confirmed in activities of daily living like the one-handed binding of shoes ( 16 ) and the preparation of meals ( 17 ). Recent research highlights that ipsilesional hand performance is highly relevant for the functional independence following left hemisphere stroke ( 18 ). Therefore, identifying the factors underlying impaired, ipsilesional upper limb control and developing targeted rehabilitation regimes is of paramount importance. Kinematic analyses of reaching tasks revealed that ipsilesional motor deficits are hemisphere dependent and reflect lateralization of motor function. Movements of the ipsilesional arm are slower and more variable following left hemisphere damage while final position accuracy is decreased after right hemisphere damage ( 18 – 24 ). These observations led to the proposal of a “dynamic dominance” hypothesis of motor lateralization stating that the dominant hemisphere is specialized for the coordination of limb and task dynamics, i.e. movement trajectories, while the nondominant hemisphere is responsible for achieving the final, i.e. steady-state, end-effector positions and stabilizing external loads ( 22 , 25 – 27 ). Ipsilesional motor deficits in reaching tasks scale with the severity of contralesional arm impairment, i.e. the more severe the contralesional arm paresis, the larger the ispilesional motor deficits ( 14 ), and correlate with apraxia scores in patients with left-hemispheric stroke ( 7 , 8 ) although the relationship may be complex( 21 ). One elegant way to study complementary pathophysiologic aspects of manual dexterity following stroke is to examine kinetics, i.e. forces and torques, when patients execute elementary grasp-to-lift tasks. In healthy adults grip forces (GF), i.e. the force acting orthogonal to the grip surface, and load forces (LF), i.e. the forces directed tangentially upwards, rise in parallel and are precisely scaled to the anticipated characteristics of both the object (weight, frictional characteristics) according to previous experience, i.e. sensorimotor memories ( 28 , 29 ), and visual object characteristics, e.g. size, material, arbitrary cues, object identity ( 30 – 35 ), and the dynamics of the task (for review see: ( 36 )). Hemiparetic patients with stroke typically exert increased grip forces when lifting objects with their more affected, contralesional, hand which can be partially attributed to disturbed sensorimotor integration ( 37 – 43 ). Moreover, studies investigating the ipsilesional, non paretic, hand of stroke survivors also found elevated grip force levels ( 44 – 46 ) as well as an increased grip force variability ( 45 ) and disturbed anticipatory grip-to-load force coupling ( 46 ). In contrast, gross grip strength is not reduced in the ipsilesional hand following stroke ( 5 , 9 , 10 ). Adding to these problems in the task execution, the anticipatory planning of forces is also impaired following stroke. While the anticipatory scaling of grip forces according to object size is intact in stroke patients (Li et al., 2011), patients with left hemisphere damage failed to scale grip forces to the actual weight of objects of daily life when grasping and lifting them with their ipsilesional hand ( 47 ). This GF scaling deficit was associated with scores of apraxia. Similarly, patients with left-sided middle-cerebral artery (MCA) stroke could not use color-cues associated with object weight to scale grip forces with either hand, whereas patients with right MCA stroke only showed impaired force scaling with their contralesional hand ( 48 ). The control of torques when lifting an object with an eccentric center of mass (CoM) relative to the hand is another essential aspect of dexterous object handling in daily life which has been extensively studied in healthy adults over the last two decades. To prevent object tilt, e.g. when lifting a cup of tea at the handle, arising torques must be already compensated at the moment of object lift-off, i.e. before full sensory feedback of object toque is available. Two torque components add up to the total torque applied by the fingers in the direction of interest. These are a) the product of the load force difference between grasp-sides (∆Fy) and half the grasp-width (w/2) and b) the product of the distance between the finger centers of pressure on the grasp surfaces (∆CoP) and the grip force (GF). Therefore, the digit placements and grip- and load forces must be coordinated to apply adequate counteracting torques at lift-off (for review see ( 49 )). Healthy adults learn to modulate both their digit centers of pressure and digit forces by placing the digit(s) on the side of the center of mass higher and applying more load force at the digit on that side according to previous experience ( 50 – 52 ), even when object dynamics change unpredictably ( 53 , 54 ). Furthermore, subjects can visually process salient object shape/geometry cues to infer the weight distribution of the object and plan torques accordingly ( 51 , 55 – 57 ). To generate adequate compensatory torques, digit -forces and -placements are covaried by a high-, respectively task-level control. This principle of force-to position covariation is grasp-type independent ( 58 ) and was shown for grasps with a precision grip ( 50 ), tripod grip ( 59 ), whole hand grasps ( 60 ) as well as for bimanual grasps ( 61 ). Although torques can be applied by any combination of digit center of pressure differences between the grasp sides (∆CoP) and load force partitioning between sides (∆Fy) as long as the resulting torque components add up to the required total torques, we recently demonstrated that an adequate finger-tip positioning and a predominant torque exertion by the product of ∆CoP and GF is essential for a force efficient task execution ( 62 ). Whether these aspects of high-level torque control are impaired at the ipsilesional hand of patients with unilateral stroke has not been investigated, yet. In the present study, we examined whether the anticipatory torque control with the ipsilesional hand when lifting an object with a varying asymmetric weight distribution is impaired in the chronic stage following unilateral stroke. We tested two cue conditions. The first was a ‘no-cues’ condition in which the position of a covert weight was changed while object shape (inverted T) was not informative of the CoM. In this condition, subjects had to rely on sensorimotor memories from the last lift or lifts. In the second condition the visually salient object geometry was congruent with weight distribution (L-shape) allowing visual inference of CoM. Moreover, two sequence conditions, one in which the mass distribution was constant over a block of trials and one in which it could change from trial to trial were employed for both cue conditions. Since the right-hemisphere is proposed to be responsible for end-effector positions according to the “dynamic dominance” model ( 25 ) we expected that patients with right hemisphere damage would fail to learn to position their fingers for an adequate torque component ∆CoPxGF, but would correct for this by compensatory ∆Fy (x w/2) resulting in successful total torque compensation. Based on the hypothesized role of the left hemisphere in the dynamic phase of an action, we hypothesized a less accurate coordination of fingertip load forces (∆Fy) to the present ∆CoP and consequently less successful predictive torque compensation in patients with left-hemispheric-, but not right hemispheric stroke, irrespective of the side of the object center of mass (CoM). Moreover, we presumed that patients with signs of apraxia would present an accentuated impairment of force-to position coordination and consequently torque compensation. However, as stroke patients previously exhibited mostly intact visuomotor processing of size and weight cues to scale finger-tip forces ( 63 , 64 ) we expected that most stroke patient can improve torque anticipation when salient-geometric cues are provided. As an exception, we presumed that patients with hemispatial neglect might fail to utilize a lateralized geometric cue indicating a CoM on the contralesional side. Concerning grip force levels, we expected to observe elevated and more variable GF levels in both stroke groups based on previous studies ( 44 , 45 ). Materials And Methods 3.1 Participants Overall, 13 patients with chronic-stage left hemispheric stroke (SL group: 6 female, mean age 63.3 ± 16.3 years, mean years since onset of stroke (YOS): 6.06 ± 4.10 years) and 9 patients with chronic-stage right hemispheric stroke (SR group: 5 female, mean age 63.9 ± 6.7 years, mean YOS 7.5 ± 5.7 years) were tested with their ipsilesional hand. 15 healthy adults who conducted the experiment with their left hand (CL group: 6 female, mean age 63.0 ± 13.1 years) and 9 healthy adults who conducted the experiment with their right hand (CR group: 4 female, mean age 69.8 ± 3.8years) served as control groups. Patients with a single unilateral cerebrovascular event older than 6 months and no evidence of bilateral lesions in their medical reports were recruited from the community with the help of physiotherapists, occupational therapists, speech therapists and neuropsychologist in the greater Munich area (see Acknowledgements). All participants reported to be right handed. Table 1 provides group summaries of the demographic and clinical characteristics as well as the results of the performed neglect and apraxia tests together with the statistical results of between group tests (ANOVA, respectively t- tests for numerical data, chi-square tests for categorical data). Individual patient’s data are outlined in Supplementary Table S1 . The experimental procedures were approved by the Institutional Review Board of the School of Medicine at the Technical University of Munich and were in accordance with the Declaration of Helsinki. All subjects were naïve to the purpose of the study and gave informed consent to participate in the study and have us collect relevant medical reports from their family doctor. Measurements took place at our lab as well as in patients’ homes between September 2016 and April 2017. All participants received 20 € for their participation in the study which lasted ~ 2 hours. Table 1 Group summary of the demographics, clinical data, the coefficients of fraction, maximum voluntary GF, the results of the pantomime and imitation tests of G. Goldenberg (see also ( 65 – 67 ) as well as the results of the line bisection test, letter cancellation test ( 68 ), and a Posner type reaction time test ( 69 ). The p-values of between groups differences were based on ANOVA tests for numerical data (respectively t-tests if data were only obtained for the stroke groups) and on chi-square tests for categorical data. Abbreviations: Stroke type: i = ischemic; h = hemorrhagic; i, h = ischemic stroke followed by hemorrhage; h, i: hemorrhage with subsequent ischemic infarction. CL (N = 15) CR (N = 9) SL (N = 13) SR (N = 9) p value Age 0.561 1 Mean (SD) 63.0 (13.1) 69.8 (3.8) 63.3 (16.7) 63.9 (6.7) Range 24.9–80.5 65.3–76.3 24.5–79.8 50.4–72.2 Gender 0.907 2 m 9 (60.0%) 5 (55.6%) 7 (53.8%) 4 (44.4%) f 6 (40.0%) 4 (44.4%) 6 (46.2%) 5 (55.6%) Stroke Type 0.042 2 i 0 0 10 (76.9%) 5 (55.6%) h 0 0 0 (0.0%) 4 (44.4%) i, h 0 0 1 (7.7%) 0 (0.0%) h, i 0 0 2 (15.4%) 0 (0.0%) mRS 0.702 1 Mean (SD) NA NA 2.4 (0.8) 2.2 (1.2) Range NA NA 1.0–4.0 1.0–4.0 Years since stroke onset 0.505 1 Mean (SD) NA NA 6.1 (4.1) 7.5 (5.7) Range NA NA 1.1–15.0 2.2–19.9 Coefficient of friction \({}_{\mathbf{s}}\) 0.292 1 Mean (SD) 0.9 (0.2) 1.0 (0.2) 0.9 (0.1) 0.9 (0.1) Range 0.6–1.2 0.7–1.2 0.7–1.1 0.7–1.0 Peak voluntary GF [N] 0.609 1 Mean (SD) 68.7 (24.1) 57.5 (17.7) 67.6 (20.7) 66.0 (16.0) Range 34.1–111.1 35.4–93.1 34.7–98.5 37.8–93.3 Imitation Hand 0.070 1 N 0 0 13 8 Mean (SD) NA NA 18.7 (1.7) 19.9 (0.4) Range NA NA 15.0–20.0 19.0–20.0 Imitation Finger 0.616 1 Mean (SD) NA NA 18.6 (2.7) 19.1 (1.0) Range NA NA 11.0–20.0 17.0–20.0 Pantomime correct items [/20] 0.224 1 N 0 0 13 9 Mean (SD) NA NA 17.2 (4.9) 19.3 (1.0) Range NA NA 3.0–20.0 18.0–20.0 Pantomime Score [/55] 0.241 1 Mean (SD) NA NA 50.2 (10.1) 54.3 (1.0) Range NA NA 19.0–55.0 53.0–55.0 Bisection Test: mean horizontal deviation [mm] 0.432 1 N 0 0 10 6 Mean (SD) NA NA -0.3 (2.7) 1.0 (3.8) Range NA NA -4.9–4.5 -3.8–6.6 Letter cancellation test: center of cancellation 0.201 1 N 0 0 11 5 Mean (SD) NA NA 0.0 (0.0) 0.0 (0.0) Range NA NA -0.0–0.0 -0.0–0.1 Letter cancellation test: overall letters found [/60] 0.051 1 Mean (SD) NA NA 59.1 (1.4) 57.2 (2.2) Range NA NA 57.0–60.0 54.0–60.0 Posner test: median reaction time [ms] 0.346 1 N 0 0 12 5 Mean (SD) NA NA 557.3 (179.4) 474.4 (87.1) Range NA NA 324.0–960.5 403.5–617.0 Posner test: relative L-R reaction time difference [%] 0.001 1 Mean (SD) NA NA -9.1 (8.3) 14.6 (16.5) Range NA NA -20.4–9.6 0.3–39.7 1 Linear Model ANOVA, 2 Pearson’s Chi-squared test 3.2 Modified Rankin Scale (mRS) The modified Rankin Scale (mRS) was assessed as measure of the degree of disability or dependence in the daily activities using the simplified questionnaire proposed by Bruno et al. ( 70 ). 3.3 Apraxia Tests We administered two established tests of apraxia and video-recorded them for later analysis. Firstly, we examined the imitation of meaningless gestures of hand- and finger postures with the ipsilesional hand. Imitation scores below 18 of 20 for hand- and 17 of 20 for finger-postures were considered as suggestive of apraxia (( 65 , 71 – 73 ). In addition to imitation, we examined pantomime of tool-use. Here, we showed patients pictures of one of 20 tools or objects of the daily life and asked them to mime specific action as if they were holding the object in their ipsilesional hand. We scored whether hand positions and movements were correct. Scores below 45/55 were considered as suggestive of apraxia ( 67 , 72 , 74 ). 3.4 Tests of hemispatial Neglect The presence of hemispatial neglect was assessed by the a) line bisection-test in which a deviation of more than 6 mm from the midpoint indicates hemispatial neglect ( 75 ), b) the letter cancellation test with performance quantified by the center of calculation (CoC) score introduced by Rorden and Karnath ( 68 ) – i.e. an absolute CoC score above 0.083 indicates presence of hemispatial neglect - and c) a Posner type spatial cueing test ( 76 ) implemented in the free computer test battery PEBL (version 0.14, ( 77 )). In the latter, patients sat in front of a 15.6-inch Lenovo laptop. After a cue to the left, right or both sides (neutral) was provided, indicating where the response is likely to be, patients had to press a key when they detected a stimulus either to the left or right of fixation. As measure of a hemispatial visual bias we calculated the standardized median reaction time difference between trials with stimuli to the left and to the right of fixation (overall 200 trials, 100 trials per stimulus side, cues were valid in 120 trials, neutral in 40 trials, and invalid in 40 trials). Reaction time differences between stimuli on the left and right side in Posner-type reaction time tests were shown to be more sensitive than paper and pencil based tests in detecting hemispatial neglect ( 69 ). However, there is no established cut-off defining hemispatial neglect. 3.5 Experimental Design and Statistical Analyses 3.5.1 Apparatus Subjects were instructed to reach, grasp, lift and replace a custom made, grip device with the thumb opposing the index and the middle finger ( 53 ) (see Fig. 1 A). The grasp surfaces (120x40 mm) were covered with fine-grained sand paper (2000 grit). Two 6-axis force/torque-sensors (ATI Nano-17 SI-50-0.5, ATI Industrial Automation; force range: 50,50, and 70 N for x-, y-, and z-axes, respectively; force resolution: 0.012 N; torque range 0.5 Nm; torque resolution: 0.063 Nmm, sampling rate 200 Hz) recorded the forces and torques applied on both grasp sides. Position and orientation data of the device were measured by a lightweight magnetic position/orientation-tracker (TrakSTAR, Ascension Technology Corporation, accuracy: 1.4 mm RMS, 0.5 degrees RMS, sampling rate 200 Hz) fixed on top of the horizontal base. Data collection was synchronized using custom software written in Matlab 2016a (MATLAB, RRID:SCR_001622). Both the position of the handle device on top of the base as well as the location of a 250 g aluminum weight which was put into cavities of the base hidden by a lid could be altered to vary the object’s center of mass (CoM) relative to the hand (see Experimental Protocol). 3.5.2 Determining the static coefficient of friction, µ s , at slip onset Prior to the main experiment, subjects were asked to lift and hold the grip device in a three-finger precision grip with the thumb, index and middle fingers of the hand used for the upcoming lifting taks and slowly release it until the object slipped. We estimated the average static friction coefficient, µ s , at the digit - surface contacts, by calculating the ratio between the load- and grip force at slip onset which was visually detected by a sudden drop in the load force and height. Overall, µ s could be successfully calculated in 121 slip-trials. The averaged µ s estimates are based on an average of 2.63 slip-trials per subject (SD 0.77, median 3, range 1–4). 3.5.3 Maximum GF Prior to the main experiment we had participants pinch the grasp surfaces as hard as they could in the specified three-finger precision grip twice for five seconds and determined the highest applied GF as maximum GF. 3.5.4 Experimental Task For the main experiment, we instructed participants to start reaching for the grasp-device after a signal tone, grasp the grasp surfaces with the fingertips of the thumb-, index- and middle finger in a precision grip, lift it in a smooth movement to a height of ~ 5–10 cm while minimizing object tilts and hold the object steady thereafter. A second tone 4 seconds after the first signaled subjects to replace the device. Patients were allowed to position and orient the object on the table in a way that allowed for a comfortable wrist position for grasping. 3.5.5 Experimental Protocol First, participants conducted six practice grasp-to-lift trials in which the object’s CoM was below the middle of the handle (zero external torque). Subsequently, the main experimental protocol contained two sequence conditions and two cue conditions (see Fig. 1 C ) . In the ‘no cues condition’, the object handle was attached over the center of the base (symmetric, inverted T-shape) and the center of mass was varied by placing a covert 250 g aluminum weight into either the outer left or outer right hidden cavity of the horizonal base, resulting in external torques of ± 0.21 Nm ( see Fig. 1 C). In the ‘geometric cues condition’, in contrast, the aluminum weight was constantly placed in the center cavity, but the handle was either positioned on top of the left or right object edge creating an asymmetric L-shape and resulting in an external torques of ± 0.46 Nm ( see Fig. 1 C). As convention, negative signs denote a counter-clockwise external torque. The total object weight was 750 g. In both cue-conditions, participants first conducted 37 trials in the ‘pseudorandom’ sequence-condition in which the CoM was changed in a pseudo random fashion which could not be predicted by the participants ( see Fig. 1 C). Participants had to close their eyes while the hidden weight was removed and placed back either into the same or the opposite position after each trial. This was followed by the blocked sequence-condition in which the CoM remained constant for 8 trials per block before the CoM changed side for the next blocks. Participants were informed about the CoM change between blocks but were restricted of watching the configuration change. The blocked-sequence encompassed 4 complete blocks and the first trial of the 5th block, i.e. 33 trials. The succession of the pseudorandom and blocked sequence-condition trials was performed for both the no-cues and geometric-cues conditions, amounting to a total of 140 main trials per participant. We randomly assigned the order of the two cue conditions and the initial CoM side for the first trial for the no-cues- and geometric-cues conditions to the participants. 3.5.6 Data Processing Data were processed and analyzed with custom software written in Matlab 2016a. The collected force/torque data was filtered through a sixth-order Butterworth low-pass filter with a cutoff frequency of 14 Hz. The index and middle finger contacting the same grip side produced net mechanical forces and moments equivalent to the sum of their individual actions and were hence considered as a virtual finger ( 78 ). We analyzed the exerted total torque ( Tcom ) as well as the torque components ΔFy*w/2 and ΔCoP *GF outlined below as well as the grip force ( GF ) at the moment of object lift off , defined as the moment 10ms prior to which the vertical position of the object raised above a threshold of 0.2 mm. We examined the following experimental variables (see Fig. 1 B): 1) Grip force ( GF ) was defined as the mean normal force directed orthogonal towards the grip surfaces. 2) ∆CoP at lift-off was defined as the vertical difference between the center of pressure (CoP) on the right and the left grip sides at the moment of lift-off. 3) Tcom , the compensatory torque exerted at object lift off, is an established indicator of torque anticipation ( 50 , 79 , 80 ). Tcom is the sum of: a) ΔCoP *GF , the product of GF and ΔCoP and b) ΔFy*w/2 , the torque generated by the product of the difference between the right and left load force and half the distance between the grip-surfaces ( \(\frac{\text{w}}{2}\) = 20.4 mm). With the chosen sign conventions, Tcom matches in sign with the external torque when it counterbalances the exerted torque, e.g. is directed in opposing direction to the external torque. Hence, clockwise exerted torques were defined as negative and counter-clockwise torques as positive (see Fig. 1 A and the supplementary material of ( 53 ): https://doi.org/10.6084/m9.figshare.7683707 ). As outcome measures in the statistical analyses, we calculated the respective ratios between the torque variables and the external torque to compensate for, i.e.: \(\frac{\mathbf{T}\mathbf{c}\mathbf{o}\mathbf{m}}{\mathbf{E}\mathbf{x}\mathbf{t}\mathbf{e}\mathbf{r}\mathbf{n}\mathbf{a}\mathbf{l} \mathbf{T}\mathbf{o}\mathbf{r}\mathbf{q}\mathbf{u}\mathbf{e}}\) , and . This allows for direct evaluation of the success of torque anticipation as a ratio of 1 indicates perfect torque compensation and negative ratios indicate torques directed in the wrong direction. \(\frac{\mathbf{T}\mathbf{c}\mathbf{o}\mathbf{m}}{\mathbf{E}\mathbf{x}\mathbf{t}\mathbf{e}\mathbf{r}\mathbf{n}\mathbf{a}\mathbf{l} \mathbf{T}\mathbf{o}\mathbf{r}\mathbf{q}\mathbf{u}\mathbf{e}}\) is the primary outcome variable , \(\frac{{\Delta }\text{F}\text{y}\text{*}\text{w}/2}{\text{E}\text{x}\text{t}\text{e}\text{r}\text{n}\text{a}\text{l} \text{T}\text{o}\text{r}\text{q}\text{u}\text{e}}\) , \(\frac{{\Delta }\text{C}\text{o}\text{P} \text{*}\text{G}\text{F}}{\text{E}\text{x}\text{t}\text{e}\text{r}\text{n}\text{a}\text{l} \text{T}\text{o}\text{r}\text{q}\text{u}\text{e}}\) are the secondary outcome variables, and ∆CoP and GF represent exploratory tertiary outcome variables. 4) Additionally, we estimated the average static coefficients of friction, μ s , of each participant by averaging the ratios between the load force and grip force at the moment at which slips occurred in the slip-task to control for possible friction differences between groups. 3.5.7 Data Management Due to technical errors 1.58% (106/6716) of the measurements had to be discarded. We obtained 121 μ s estimates employing the slip-method. 3.5.8 Statistical Analysis Statistical analyses were performed in the R environment for statistical computing (version 4.0.3, ( 81 ), R Project for Statistical Computing, (RRID):SCR_001905). To compare the demographic and clinical characteristic of the control- and stroke groups exploratory analyses of variance (ANOVA) tests for numerical data (respectively t-tests if data were only obtained for the stroke groups) and chi-square tests for categorical data were conducted as implemented in the ‘arsenal’ package ( 82 ). Concerning the main outcome measures, we fit linear mixed effects regression models (LMM) for the dependent experimental variables with the restricted maximum likelihood criterion using the ‘lme4’- ( 83 ) package. P-values of the predictor-estimates of all LMMs were calculated based on Wald-type t-Tests using the Kenward-Roger approximation of the degrees of freedom. Post-hoc t-tests of pairwise comparisons between stroke patient- and hand-matched control groups were based on the marginal means of the LMMs ( 84 ) with Holm-Bonferroni correction for multiple testing applied ( 85 ). Separate models for the torque variables, ∆CoP- and GF at lift off were fitted for every experimental condition. In the models for the blocked condition, the model predictors were the participant group, the external torque and the two-way interaction between these factors. We conducted both analyses of the trials 4–8 of each block to assess the extent of motor learning as well as of the respective first trials of blocks 2–4 after the CoM changed to investigate the transfer of motor plans to a new situation. In the models for the pseudorandom sequence condition, we included the additional predictor ‘CoM-retained/inverted’ as well as all resulting two- and three-way interactions with the predictors group and external torque into the model specifications. Three patients with left hemispheric stroke showed signs of apraxia (see below and Supplementary Figure S1 ). Therefore, we performed additional exploratory statistical analyses for the variables in the blocked conditions with post-hoc comparisons between the groups CL (n = 15), SL apraxia negative (n = 10), and SL apraxia positive (n = 3) but otherwise identical model specifications as outlined above. Due to the small sample size of apraxia positive patients, both unadjusted and Holm- adjusted p-values of the between group comparisons are presented for these additional analyses. Results 4.1 Demographic characteristics, clinical measures and static coefficients of friction We found no statistically significant differences between groups regarding age (p = 0.56), years since stroke onset (p = 0.51), gender distribution (p = 0.91), mRS (p = 0.70), mean coefficient of friction (p = 0.29, see also Supplementary Figure S2 ), nor the voluntary maximum GF in the tripod grip (p = 0.609) ( see Table 1 ). 4.2 Apraxia and Neglect The vast majority of patients scored within the normal range in the administered apraxia and neglect tests: Only three patients with left MCA strokes scored below the cutoff in the hand imitation test (< 18), two of these patients (ID24, ID27) also failed the finger imitation (< 17) - and pantomime tests (< 45, Supplementary Figure S1 ). Regarding the paper-based tests of hemispatial-neglect, only one patient with right MCA stroke (ID9) showed a line bisection deviation suggestive of hemispatial neglect to the left. However, results of the letter cancellation test were within the normal range in all patients. The results of the hand- (p = 0.070), and finger imitation tests (p = 0.616), the pantomime score (p = 0.241) as well as the line bisection (p = 0.43) and the CoC on the letter cancellation test (p = 0.201) did not differ between patient groups. The only significant difference between the SL and SR group was found for the percentual left-right reaction time difference in the Posner test (p = 0.001). Whereas SL patients were about 9.1% (SD 8.3%) slower in reacting to a stimulus on the right side, SR patients were 14.6% (SD 16.5%) slower when the stimulus was on the left side. In contrast, the mean reaction time in the Posner test (p = 0.35) was similar between patient groups. Table 1 summarizes the demographic, clinical and grip related measures of the participant groups. 4.3 Torque compensation at lift off 4.3.1 No cues, blocked condition trials 4–8: Sensorimotor learning of the anticipatory coordination of centers of pressure and grip force is spatially biased following stroke. Participants of all groups only needed some 2–3 lift trials to learn to compensate for torques at the moment of lift-off. After that, Tcom remained stable for the rest of the block (see Supplementary Figure S3 for the individual and group-averaged Tcom trajectories across trials in the ‘no cues’ condition). All groups generated similar compensatory torques at lift-off in trials 4–8 with no significant differences between stroke and control groups. However, there was a trend towards a decreased Tcom for the SR-group when the weight was on the left side which was not significant after Holm-correction (t = 2.15, df = 55.3, p = 0.071, see Fig. 2 A and Supplementary Table S3 ). In contrast, the torque components at lift-off were spatially biased following a specific directional pattern in both stroke groups. The torque generated by grip force being produced at different vertical finger positions ( \(\frac{{\Delta }\mathbf{C}\mathbf{o}\mathbf{P} \mathbf{*}\mathbf{G}\mathbf{F}}{\mathbf{E}\mathbf{x}\mathbf{t}\mathbf{e}\mathbf{r}\mathbf{n}\mathbf{a}\mathbf{l} \mathbf{T}\mathbf{o}\mathbf{r}\mathbf{q}\mathbf{u}\mathbf{e}}\) ) was lower in the SL group than the CL group when the CoM was on the right, i.e. contralesional, side (t = 4.59, df = 65.5, p < 0.001, see Fig. 2 B and Supplementary Table S5 ) but higher than in the CL group when the weight was on the left, i.e. ipsilesional, side (t = -4.10, df = 65.5, p < 0.001). The torque produced by different load forces at the handle sides was biased in the opposite direction, i.e. \(\frac{{\Delta }\mathbf{F}\mathbf{y}\mathbf{*}\mathbf{w}/2}{\mathbf{E}\mathbf{x}\mathbf{t}\mathbf{e}\mathbf{r}\mathbf{n}\mathbf{a}\mathbf{l} \mathbf{T}\mathbf{o}\mathbf{r}\mathbf{q}\mathbf{u}\mathbf{e}}\) was higher than in CL for a CoM on the contralesional, right side (t = -5.03, df = 98.2, p < 0.001, see Fig. 2 C and Supplementary Table S7 ) and lower for a CoM on the ipsilesional, left side (t = 5.33, df = 98.2, p < 0.001). As the patterns of the object-centered spatial bias are diametrically opposed for \(\frac{{\Delta }\mathbf{C}\mathbf{o}\mathbf{P} \mathbf{*}\mathbf{G}\mathbf{F}}{\mathbf{E}\mathbf{x}\mathbf{t}\mathbf{e}\mathbf{r}\mathbf{n}\mathbf{a}\mathbf{l} \mathbf{T}\mathbf{o}\mathbf{r}\mathbf{q}\mathbf{u}\mathbf{e}}\) and \(\frac{{\Delta }\mathbf{F}\mathbf{y}\mathbf{*}\mathbf{w}/2}{\mathbf{E}\mathbf{x}\mathbf{t}\mathbf{e}\mathbf{r}\mathbf{n}\mathbf{a}\mathbf{l} \mathbf{T}\mathbf{o}\mathbf{r}\mathbf{q}\mathbf{u}\mathbf{e}}\) the effects seem to cancel each other out resulting in normal total torques (Tcom) as outlined above. SR patients equally exerted less torque by grip force being produced at different vertical finger positions ( \(\frac{{\Delta }\text{C}\text{o}\text{P} \text{*}\text{G}\text{F}}{\text{E}\text{x}\text{t}\text{e}\text{r}\text{n}\text{a}\text{l} \text{T}\text{o}\text{r}\text{q}\text{u}\text{e}}\) ) than CR controls when the CoM was on the contralesional, left side (t = 2.16, df = 67.4, p = 0.035 see Fig. 2 B and Supplementary Table 5 ), however \(\frac{{\Delta }\mathbf{C}\mathbf{o}\mathbf{P} \mathbf{*}\mathbf{G}\mathbf{F}}{\mathbf{E}\mathbf{x}\mathbf{t}\mathbf{e}\mathbf{r}\mathbf{n}\mathbf{a}\mathbf{l} \mathbf{T}\mathbf{o}\mathbf{r}\mathbf{q}\mathbf{u}\mathbf{e}}\) was not increased for the ispilesional CoM side and we found no differences of the torque produced by differential load forces ( \(\frac{{\Delta }\mathbf{F}\mathbf{y}\mathbf{*}\mathbf{w}/2}{\mathbf{E}\mathbf{x}\mathbf{t}\mathbf{e}\mathbf{r}\mathbf{n}\mathbf{a}\mathbf{l} \mathbf{T}\mathbf{o}\mathbf{r}\mathbf{q}\mathbf{u}\mathbf{e}}\) ) at lift off in the SR group. 4.3.2 No cues, blocked condition, trials after CoM change: Failed transfer of sensorimotor memories to explicit CoM changes. Despite being explicitly told that the CoM would be changed to the opposing side at the end of each block of eight trials, subjects of all groups subsequently failed to adapt to the new CoM situation and could not inverse the direction of the previously learned Tcom, i.e. transfer sensorimotor memories. This stands in line with previous studies (e.g. ( 52 , 79 )). Tcom was mostly near zero but clearly generated in the wrong, i.e. the previously learned, direction as indicated by a negative ratio of \(\frac{\mathbf{T}\mathbf{c}\mathbf{o}\mathbf{m}}{\mathbf{E}\mathbf{x}\mathbf{t}\mathbf{e}\mathbf{r}\mathbf{n}\mathbf{a}\mathbf{l} \mathbf{T}\mathbf{o}\mathbf{r}\mathbf{q}\mathbf{u}\mathbf{e}}\) . We observed no significant Tcom differences between stroke and control groups ( see Fig. 3 A and Supplementary Table 9 ). Concerning the torque components, the SL group applied a higher torque by grip force being exerted at different vertical finger positions ( \(\frac{{\Delta }\mathbf{C}\mathbf{o}\mathbf{P} \mathbf{*}\mathbf{G}\mathbf{F}}{\mathbf{E}\mathbf{x}\mathbf{t}\mathbf{e}\mathbf{r}\mathbf{n}\mathbf{a}\mathbf{l} \mathbf{T}\mathbf{o}\mathbf{r}\mathbf{q}\mathbf{u}\mathbf{e}}\) ) than controls when the hidden weight was transferred to the ipsilesional, left side (t = -2.81, df = 126.196, p = 0.012, see Fig. 3 B and Supplementary Table S11 ). Apart from this, there were no further differences between stroke- and control groups ( see also Fig. 3 C and Supplementary Table S13 ). 4.3.3 No cues, pseudorandom condition: Torque planning according to sensorimotor memories despite uncertainty In this condition the position of the hidden weight was either retained or inverted between trials in a pseudorandom fashion. After each trial the hidden weight was removed and placed back either into the same or the opposite position. Although a rational torque planning was not possible in this condition, we observed that all groups planned according to the previous lifts resulting in clearly positive Tcom ratios when the CoM was not inverted ( see Fig. 4 A). Remarkably, we did not observe the generation of Tcom of similar magnitudes directed in the wrong direction following CoM inversals. Rather, Tcom was close to zero in trials after a CoM inversion suggesting that participants must have partially corrected the exerted torque already until lift-off. We found two just significant group differences. First, the SL group exerted a Tcom closer to zero when the CoM was switched to the left (t = -2.28, df = 236.9, p = 0.046, see Fig. 4 A and Supplementary Table S15 ). Secondly, the SR group produced a smaller Tcom when the CoM remained on the right (t = 2.33, df = 246.7, p = 0.041). Concerning the torque components, we again found contrasting object-centered spatial biases of the torque anticipation strategies in the SL group when compared with the CL group and this was irrespective of whether the weight position was changed or not: While the torque generated by grip force being exerted at different vertical positions ( \(\frac{{\Delta }\mathbf{C}\mathbf{o}\mathbf{P} \mathbf{*}\mathbf{G}\mathbf{F}}{\mathbf{E}\mathbf{x}\mathbf{t}\mathbf{e}\mathbf{r}\mathbf{n}\mathbf{a}\mathbf{l} \mathbf{T}\mathbf{o}\mathbf{r}\mathbf{q}\mathbf{u}\mathbf{e}}\) ) was less adequate (smaller ratio) when the weight was on the right, i.e. contralesional, side (CoM inverted: t = 4.79, df = 536.5, p < 0.001, CoM retained: t = 3.72, df = 531.4, p < 0.001, see Fig. 4 B and Supplementary Table S17 ) but more adequate (higher ratio) than in the CL group when the weight was on the left, i.e. ipsilesional side (CoM inverted: t = -4.22, df = 529.0, p < 0.001, CoM retained: t = -4.28, df = 529.0, p < 0.001). Again, the torque generated by differential load forces between sides was biased in the opposite direction, i.e. \(\frac{{\Delta }\mathbf{F}\mathbf{y}\mathbf{*}\mathbf{w}/2}{\mathbf{E}\mathbf{x}\mathbf{t}\mathbf{e}\mathbf{r}\mathbf{n}\mathbf{a}\mathbf{l} \mathbf{T}\mathbf{o}\mathbf{r}\mathbf{q}\mathbf{u}\mathbf{e}}\) was higher in the SL than in the CL group for a CoM on the contralesional, right side (CoM inverted: t = -4.47, df = 536.5, p < 0.001, CoM retained: t = -3.25, df = 531.4, p = 0.0025, see Fig. 4 C and Supplementary Table S19 ) and lower for a CoM on the ipsilesional, left side (CoM inverted: t = 2.72, df = 528.961, p = 0.0136, CoM retained: t = 3.35, df = 528.961, p = 0.0017). No significant differences were detected between the right-hand groups SR and CR. 4.3.4 Geometric cues: Successful torque anticipation in all experimental conditions In the geometric cue condition in which the CoM was altered by attaching the handle either on the left or right edge of the base participants of all groups successfully compensated for the arising external torque at lift off both in the blocked as well as in the pseudorandom condition and even in trials following a change of the handle position in the blocked condition. Supplementary Figure S4 depicts the Tcom trajectories of all participants in the geometric-cue conditions. Tcom was mostly generated by GF being produced at different vertical centers of pressure and only to a lesser degree by differential load force sharing. We found no differences of Tcom success between the stroke and control groups in neither the blocked- nor the pseudorandom condition ( see Figs. 5 – 7 and Supplementary Tables S20-36) . This lack of group differences was also observed when analyzing the torque components, with the exception of the finding of less successful torque generation by \(\frac{{\Delta }\mathbf{C}\mathbf{o}\mathbf{P} \mathbf{*}\mathbf{G}\mathbf{F}}{\mathbf{E}\mathbf{x}\mathbf{t}\mathbf{e}\mathbf{r}\mathbf{n}\mathbf{a}\mathbf{l} \mathbf{T}\mathbf{o}\mathbf{r}\mathbf{q}\mathbf{u}\mathbf{e}}\) in the SL group than the CL group in the first trials in the blocked condition following a change of the handle to the left, i.e. the CoM to the right side (t = 2.60, df = 95.9, p = 0.021, see Fig. 6 B and Supplementary Table S28 ). 4.3.5 ∆CoP and GF at lift-off The total compensatory torque and its components at lift-off were the task-level variables participants had to control to prevent object tilt. While the load force sharing between grasp-sides, ∆Fy, is directly proportional to the resulting torque component as the grip width is constant, both the center of pressures and the GF must be actively controlled to achieve the desired torque product ∆CoP*GF. Therefore, we were interested to evaluate whether the found spatial biases of the torque produced by vertical center of pressure modulation, ∆CoP*GF, can be traced back to distinct alterations in the control of either ∆CoP, GF or both at lift-off. Regarding ∆CoP, we found a non-significant trend toward a better modulation in the SL than the CL group when the weight CoM was on the left side (t = 2.1, df = 46.0, p = 0.083) and a significantly worse modulation when the CoM was on the right side (t = 2.38, df = 46.0, p = 0.043, see Fig. 8 A). These findings are consistent with the reported results for ∆CoP*GF, although less robust. Apart from that, there were no other significant differences between groups ( see Fig. 8 and Supplementary Tables 37–44 ). Concerning GF, we did not detect any significant differences between stroke and control groups ( see Fig. 9 and Supplementary Tables 45–52 ). 4.3.6 Object-centered spatial bias also affects Tcom in patients with apraxia Our exploratory comparisons between patients with left hemispheric stroke with- and without signs of apraxia (Apr. pos., n = 3; Apr. neg., n = 10) and controls (CL, n = 15) in the blocked conditions suggest that the found object-centered spatial torque bias in the no-cues blocked condition is more pronounced in patients with evidence of apraxia and does not only affect the torque strategy but, in contrast to the SL group as a whole, also the total torque at lift-off, Tcom. Before applying Holm-adjustments for multiple comparisons, we found that Tcom was significantly higher in SL-patients with sign of apraxia than both in CL controls (t = -2.17, df = 33.8, p = 0.037, p-adjusted = 0.112, n.s.) and SL-patients without signs of apraxia (t = -2.05, df = 33.8, p = 0.049, p-adjusted = 0.112, n.s.) when the CoM was on the ipsilesional, left side, whereas Tcom was lower in SL- patients with apraxia than in CL controls when the weight was on the contralesional, right side (t = 2.2.5, df = 33.8, p = 0.031, p-adjusted = 0.092, n.s., no significant difference between Apr. neg. and Apr. pos. patients, see Fig. 10 A). The opposed spatial bias patterns for the torque components ∆CoP*GF and ∆Fy*w/2 were confirmed (see Fig. 10 B and C) . The three patients with signs of apraxia had no deficits in the visual processing of geometric cues to guide their torque compensation (see Supplementary Figure S5 ). Although no significant findings emerged for the variables ∆CoP and GF given the small sample size (see Supplementary Figure S6 and S7 ), patients with sign of apraxia seemed to exert a higher GF when the CoM was on the left side both in the no-cues and geometric cues condition (see Supplementary Figure S7) . Discussion This study was set out to investigate whether manual torque control with the ipsilesional hand is impaired in patients in the chronic stage following unilateral stroke when lifting objects. Using a cross-over design with two cue- and two-sequence conditions, we studied both a cue-condition in which learning had to rely on previous sensorimotor memories of recent lifts as well as a visual cue condition in which the object CoM could be inferred from object geometry. Moreover, participants performed trials both in blocked, i.e. predictable, sequence-condition as well as a pseudorandom sequence condition in which the CoM could change after each trial in an unforeseeable manner. Both our main hypotheses that a) ∆CoP modulation was impaired in the SR group and b) deficient load force sharing (∆Fy) in the SL group would lead to impaired torque compensation at lift-off, were not confirmed. Instead, both stroke groups learned to compensate torques at lift-off to overall similar degrees as controls in both cue conditions and patients presented neither general deficits of force-to finger position coordination, nor elevated GF levels, on a group level. Instead, we observed a specific pattern of an object-centered spatial bias of torque components in patients with stroke when having to rely on sensorimotor memories. While torques resulting from force being produced at different vertical finger positions, ∆CoP x GF, were lower when the object CoM was on the contralesional side and higher when the CoM was on the ipsilesional side in patients with left hemispheric stroke, torques generated by differential load forces between sides (∆Fy x w/2) were biased in the opposite direction. While these biases largely cancelled each other out on the group level of SL-patients, the spatial bias of ∆CoP x GF was more pronounced in SL patients with signs of apraxia and translated to overall Tcom. SR patients also applied a distinctly smaller ∆CoP x GF for a CoM on the contralesional, left side but showed neither a clear compensation by ∆Fy x w/2 nor an increase in ∆CoP x GF for a CoM on the ipsilesional side. Torque control was intact in both stroke groups when a geometric cue on the weight distribution was available. We summarize and discuss our findings in the following sections. 5.1 Preserved sensorimotor force-to position coordination despite a spatial bias of ∆CoP x GF following stroke In line with studies of young and elderly healthy adults ( 52 , 62 , 79 ), participants in all groups quickly learned to exert an adequate Tcom when the CoM was constant across the trials of a block. At the beginning of a new block they failed to transfer the learned torque planning to the new situation even when they were explicitly told that the CoM would be inverted. They also continued to rely on sensorimotor memories of previous lifts when the CoM could change from trial to trial ( 53 , 54 ). Intriguingly, the magnitude of torques directed in the wrong direction when the CoM had unexpectedly changed from one side to the other was smaller than the torque exerted in the right direction when the CoM had stayed the same. This suggests that participants in all groups applied corrective feedback-mechanism to partially correct for erroneous torque anticipation within the short time interval prior to lift-off, although full feedback about object torque only becomes available after lift-off. This finding is consistent with our previous studies in healthy subjects ( 53 , 57 ) and the time course and underlying mechanism of these corrections need to be further explored in future analyses. There were no noteworthy differences of Tcom between the stroke and the control groups, despite the emergence of a distinct pattern of differences between the torque components. The most remarkable finding of this study is that the torque resulting from grip force being produced at different vertical centers of pressure, ∆CoP x GF, and from differential load force sharing between sides, ∆Fy x w/2, were spatially biased in diametrical directions in patients with left hemispheric-stroke when participants had to exclusively rely on sensorimotor memories to guide torque control: Patients with left hemispheric stroke applied a smaller ∆CoPxGF at lift off than controls when the CoM was on the contralesional side but a higher ∆CoPxGF when the CoM was on the ispilesional, i.e. left, side. In contrast, the torque resulting from differential load forces at the handle sides (∆Fy x w/2) was spatially biased in the opposite direction in SL-patients, i.e. ∆Fy x w/2 was higher for a CoM on the right- and lower for a CoM on the left side. As a consequence, the overall Tcom did not significantly differ between left hemispheric stroke patients and controls on the group level. Patients with right hemispheric stroke also exhibited a markedly smaller torque resulting from grip force being produced at different vertical finger positions, ∆CoP x GF, but showed no signs of a compensatory load force distribution (∆Fy x w/2). However, this only translated to a not significant trend towards a lower Tcom. This was not significant after Holm correction as the variability was high and the sample size low. No significant differences or even visually discernible trends were found for Tcom or the torque components when the covert weight was on the ipsilesional right side. As the center of pressure in the employed three-finger precision grip mostly depended upon the finger positioning when grasping the handle and to a lesser degree on the normal force distribution between the index and middle finger ( 80 ), the torque component ∆CoP x GF arguably better represents explicit context-dependent motor planning in unconstrained grasping; whereas the load force distribution contributing to the total torque (∆Fy x w/2) is modulated as a function of finger-positioning after the formation of the grasp to achieve a targeted total torque ( 50 , 58 , 86 – 88 ). Consequently, the observed spatial bias of laod force sharing in left hemispheric stroke patients might represent a compensatory mechanism to counteract the spatial bias of grip force exerted at different vertical positions. This supports the concept of a task-level, i.e. high-level, neural representation of the task goal, namely the compensatory total torque, which is used to orchestrate both the feedforward as well as feedback control of the positions and forces of the low-level effectors, e.g. fingertips ( 49 , 54 , 89 ). However, the same pattern of spatial bias was evident in patients with left hemispheric stroke in the pseudorandom, no cues-condition with more successful ∆CoP x GF for a CoM on the left and a less successful ∆CoP x GF for a CoM on the right as well as opposing findings for the torque component ∆Fy x w/2, both for trials in which the CoM was inverted and trials in which the CoM was retained. Therefore, the object-centered spatial torque bias solely depended upon the current side of the CoM but not the CoM of the previous trial on which sensorimotor memories for torque planning are based on. This casts doubt on whether the torque component ∆CoP x GF can really be regarded as measure of exclusively anticipatory planning. Instead, it is more likely that the bias observed in the pseudorandom condition affected the corrections of the torque components ∆CoP x GF and ∆Fy x w/2 just prior to lift-off according to sensory feedback. In this case, it is more justified to speak of a bias of torque control instead of torque anticipation, which implies exclusive feedforward control. Irrespective of the relative contribution of feedforward- and feedback-mechanisms on torque generation at lift off, the opposingly directed object-centered spatial bias for ∆CoP x GF and ∆Fy x w/2 in left hemispheric stroke patients and the isolated bias for ∆CoP x GF in right hemispheric stroke patients corroborates the notion that different neural networks control these task level variables. This notion has previously been based on behavioral studies which could show that finger positioning represents context dependent, explicit, learning, whereas load force distribution is more influenced by effector- and use-dependent, implicit, learning processes ( 52 , 90 ). 5.2 Visuomotor processing of geometric cues for torque control is intact in chronic stroke patients When the mass distribution could be inferred from the geometric shape of the object (L-Shape) all participant groups successfully compensated for torques arising at lift off mainly by adequately modulating the centers of pressure on both grip sides (∆CoP x GF) both when learning successful manipulation over a course trials with constant object properties but also when object geometry and weight distribution changed randomly. Given a geometric cue, torques by load force partitioning (∆Fy x w/2) only contributed a small part of the total Tcom. Changing the object geometry after a sequence of 8 trials led to an interference of sensorimotor memories of previous lifts on lift planning resulting in a slightly smaller Tcom. The successful processing of geometric cues to guide torques and sensorimotor inference on geometric processing confirm previous studies examining young- and elderly healthy subjects ( 56 , 57 , 80 ). The compensatory torque and torque components did not differ in the stroke groups suggesting intact visuomotor processing of object shape to infer mass distribution. This stands in line with previous studies which showed that grip force scaling according to object size was not affected by unilateral MCI stroke on a group level ( 63 , 64 , 66 ). Most notably, we found no evidence of a spatial bias of the torque components ∆CoP x GF or ∆Fy x w/2 in the stroke groups suggesting that these biases following stroke are specific to sensorimotor control and can be corrected by visual control. 5.3 Spatial bias of ∆CoP x GF is pronounced in patients with apraxia cannot be fully compensated for by ∆Fy x w/2 Three patients with a left-hemispheric stroke showed signs of apraxia in the finger-imitation test. These patients showed a more pronounced spatial bias of the torque components which also translated to the overall torque Tcom, i.e. Tcom was lower than in controls for a CoM on the contralesional, right side, and higher than in controls for a CoM on the ipsilesional, left side. The fact that Tcom was biased in the same directions as ∆CoP x GF, supports the notion that stroke primarily causes a shift of ∆CoP x GF which can only be compensated to a certain degree by a diametrical shift of ∆Fy x w/2, and not vice versa. Due to the small sample size and the lack of brain imaging data from our patients, we cannot infer whether damages to cortical regions specific to apraxia are related to a stronger spatial bias. Possibly, larger cortical lesion volumes in patients with signs of apraxia might account for the pronounced bias, especially since also patients with solely subcortical stroke lesions were included as SL patients without signs of apraxia. 5.4 Evidence for an allocentric premotor neglect? The finding of an object-centric spatial bias of the sensorimotor torque control with a higher than normal ∆CoP x GF for a CoM on the ipsilesional side (only SL group) and a lower ∆CoP x GF for a CoM on the contralesional side (both stroke groups) could be taken as evidence for a shift of spatial attention towards eccentric loads on the ipsilesional side and away from loads on the contralesional side following unilateral stroke. This may represent a novel subtype of allocentric premotor attention bias, i.e. neglect. Concerning the association between neglect and motor control, the phenomenon of premotor neglect (PMN), i.e. an intentional, voluntary, and directional action motor bias concerning objects in the contralesional hemispace, was described for object directed hand movements (for review see: ( 91 , 92 ). Previous studies found that patients with PMN exhibit, inter alia, abnormally slowed initiation and execution of reaching movements towards targets on the contralesional side when using their ispilesional hand ( 93 – 96 ). It is important to note that participants in our study were allowed to adjust the exact position and orientation of the object on the table in a way that allowed for comfortable grasping. Usually, the object was positioned in the hemispace of the involved, ipsilesional hand. Therefore, in contrast to previous studies on premotor neglect the reference frame of torque control in the current study was rather object- or hand specific, i.e. allocentric, than egocentric. To the best of our knowledge, a premotor-allocentric neglect has not yet been reported for an everyday object manipulation task. As the found bias concerns the control of object tilts due to a directed allocentric eccentric load, studies investigating the perception of the subjective vertical and -horizontal might also be relevant to the interpretation of our findings. These studies revealed that patients with left-sided as well as right-sided neglect systematically tilted the spatial orientation of the subjective vertical- and horizontal in the direction of the neglected, contraversive, side both in a visual and tactile modality- suggesting multisensory spatial orientation deficits in neglect patients ( 97 – 100 ). Applied to our studied task, a shift of the targeted subjective vertical of the object handle towards the contralesional side might have led to the tendency of an under compensation of torques towards the contraversive side and to an over compensation of torques towards the ipsiversive side, as a small tilt to the contralestional side might have been perceived as ideal. However, we found this only to be true for the anticipatory torque component ∆CoP x GF, but not for the torque resulting from asymmetric load force sharing (∆Fy x w/2). Moreover, we only found evidence for a bidirectional spatial bias in patients with left hemispheric stroke while patients with right hemispheric stroke only showed a decreased ∆CoP x GF for a CoM on the contralesional side but no ∆CoP x GF elevation when the CoM was on the ipsilesional side. None of the chronic stroke patients exhibited clear signs of perceptual hemispatial neglect in the conducted pen-and-paper based tests. As we did not expect to find an object centered bias of torque control we unfortunately did not test for the presence of an allocentric neglect. Nevertheless, our finding could be viewed a subtle form of an object centered premotor attention bias regarding torques. However, this inattention might not be of relevance in daily living in the majority of stroke patients as both intact load-force coordination and visuomotor processing of object geometry can compensate for the bias. 5.5 Neural correlates of torque control in object manipulation Only recently, TMS and neuroimaging studies have begun to explore the neural mechanism of the coordination finger-positions and forces in unconstrained grasping, whereas previous studies had focused on the correlates of force control when digit positions were predetermined. A recent TMS revealed that virtual lesions of the contralateral primary motor cortex (M1) inhibit the planning of digit positions as well as the covariation of the load force distribution, whereas virtual lesions of the primary sensory cortex (S1) only reduced the asymmetric load force sharing but not the retrieval of learned finger positions ( 101 ). Consequently, contralateral M1 is probably directly involved in using trial-by trial sensory feedback of digit position to adapt forces in unconstrained, natural, grasping, whereas the role of S1 could be the sensing and comparison of expected and actual finger placement to allow for control of load forces in collaboration with M1 ( 101 ). In an fMRI study a widespread network comprising the cerebellum, BA44 and PMv was found to be differently activated when participants were allowed to freely choose their finger positioning instead of having to place them on predefined positions ( 102 ). The same research group ( 103 ) also reported that a set of regions (PMv AIPn SPL7, somatosensory PSC, ventral LOC and cerebellum) are involved in finger-positioning and force control when lifting an object with an off centered center of mass, although at different time points. Recent studies using Bayesian variational representational similarity analyses of deconvolution-modeled fMRI data showed that planning the lift of objects with an asymmetric weight distribution in the absence of congruent visual cues led to an early emergence of CoM-specific pattern distances, most distinctly in ventral visual stream regions as well as in cerebellar and selected dorsal stream regions ( 104 ). A follow up study suggested that there might be only minor differences in the way that the brain encodes anticipatory control of load force sharing between the presence and absence of salient visual shape cues with early ventral stream input being of particular importance for lift force planning in more uncertain situations in the absence of congruent visual cues ( 105 ). 5.6 Study limitations Finally, a number of limitations of this study must be considered. The main limitation is that the studied stroke groups were small and heterogenous regarding stroke type, localization, the time from stroke onset and the stroke related functional impairments. As only chronic stroke patients referred by outpatient therapists participated in this study we could only obtain the medical reports but failed to collect the CT or MRI imaging studies. Therefore, we cannot make claims on the role of specific neuroanatomical regions or networks in the studied tasks. Since our study is confined to highly chronic stroke patients, we cannot exclude that the pattern of torque control deficits differs in earlier phases of stroke. Moreover, we did not perform a comprehensive neurological exam. Since only few of the chronic stroke patients of the sample revealed clear signs of apraxia we were only able to make a first tentative inference about the possible role of apraxia in torque control of our task. As we did not expect to find the object centered spatial bias of torque control a priori, we did not perform tests of allocentric neglect. Moreover, as no patient had convincing signs of chronic neglect, we could not further examine the impact of neglect on torque control. Finally, it must be noted that we conducted numerous statistical tests of the primary and secondary variables of interest and experimental conditions rendering the analyses exploratory. However, despite the small samples size, patient heterogeneity and an exploratory statistical analysis plan a clear pattern of highly significant results emerged which reveal a novel aspect of impaired motor control of the ipsilesional hand following stroke and will guide the design of future studies on object manipulation following stroke. Conclusions In summary, we found that patients with left-hemispheric stroke show a spatial bias of the torque resulting from grip force being applied at different vertical finger position depending on the mass object mass distribution when relying on sensorimotor memories with the torque component being increased for a CoM on the ipsilesional but decreased for a CoM on the contralesional side. This bias was compensated for by a load-force sharing biased in the opposite direction as evidence of intact force-to-position coordination. The found bias was more severe and could not be fully compensated in patients with apraxia, resulting in a biased overall torque compensation to the disadvantage of the contralesional side. While patients with right hemispheric stroke also exhibited lower torques due to grip force being applied at different vertical finger position for a CoM on the contralesional side, we found no evidence for an increase of this torque component for a CoM on the ipsilesional side or a compensatory bias of load force distributions. When salient, congruent geometric cues were present, patient performance was not different from controls, suggesting that visuomotor processing ameliorates the noted sensorimotor bias. The sensorimotor object-centered spatial bias of torque strategies could be a subtle sign of a premotor attention bias, respectively a premotor attention bias as a subtype of neglect, which might be even present in the absence of a an evident hemispatial neglect. The found object centered spatial bias of torque controls should be further investigated in patients in the acute stage of stroke. Declarations 7.1 Ethics approval and consent to participate The experimental procedures were approved by the Institutional Review Board of the School of Medicine at the Technical University of Munich and were in accordance with the Declaration of Helsinki. All subjects gave informed consent to participate in the study. 7.2 Consent for publication Not applicable 7.3 Availability of data and materials The data that support the findings of this study are openly available in “figshare” at 10.6084/m9.figshare.17057675. 7.4 Competing interests The authors declare no competing interests. 7.5 Funding The authors received no targeted funding. 7.6 Authors' contributions T.S.: Conceptualization, Methodology, Software, Formal analysis, Investigation, Data Curation, Writing – Original Draft, Visualization; J.H.: Conceptualization, Methodology, Resources, Formal analysis, Writing – Review & Editing, Supervision, Project administration. 7.7 Acknowledgements We thank Manfred Pfaller for support in constructing the grip device, Peter Föhr, Constantin von Deimling, Patrick Wagner for technical assistance, and Hans-Joachim Koch for help in organizing measurements. 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Supplementary Files SupplementaryMaterialBMC.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 09 Jun, 2022 Reviews received at journal 09 May, 2022 Reviewers agreed at journal 04 May, 2022 Reviewers invited by journal 05 Apr, 2022 Editor assigned by journal 05 Apr, 2022 Editor invited by journal 02 Apr, 2022 Submission checks completed at journal 02 Apr, 2022 First submitted to journal 18 Mar, 2022 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1466052","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":95584502,"identity":"7f6c4e1d-f29d-4268-83ff-907e5a3bd359","order_by":0,"name":"Thomas Rudolf Schneider","email":"data:image/png;base64,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","orcid":"","institution":"Technical University of Munich","correspondingAuthor":true,"prefix":"","firstName":"Thomas","middleName":"Rudolf","lastName":"Schneider","suffix":""},{"id":95584503,"identity":"82fdd4f9-7f13-44a8-85ea-6bf36fed0c54","order_by":1,"name":"Joachim Hermsdörfer","email":"","orcid":"","institution":"Technical University of Munich","correspondingAuthor":false,"prefix":"","firstName":"Joachim","middleName":"","lastName":"Hermsdörfer","suffix":""}],"badges":[],"createdAt":"2022-03-18 14:44:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1466052/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1466052/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":19979865,"identity":"ffee0af2-5225-4989-8804-6dad2b722ef9","added_by":"auto","created_at":"2022-04-05 15:19:21","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":580767,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eExperimental apparatus, variables and design. \u003c/em\u003e\u003c/strong\u003e\u003cem\u003e(A) The custom-built grip-device consists of a handle element mounted centrally on a horizontal bar (frontal view). The handle element allowed subjects to freely choose digit placement on the grip surfaces (40 x 120mm) covered with sandpaper. Two 6-axis-force/torque sensors were mounted under the grasp surfaces. In the ‘no cues’ condition a hidden weight was either placed in the left or right cavity resulting in an external torque after lift-off. The exerted total torque is the sum of the torque components ∆CoP x GF and ∆Fy x w/2 and must compensate for the external torque to prevent object tilt. (B) The recorded experimental variables are illustrated for an exemplary trial, the torque variables at lift off were considered to be indicators of anticipatory torque control. (C) The experimental protocol comprised the two cue- conditions ‘no cues’ in which the center of mass (CoM) was changed by placing a hidden weight either on the left or the right (with the handle being positioned above the middle cavity), resulting in external torque of ± 0.21 Nm after liftoff, and the ‘geometric cues’ condition in which\u0026nbsp;the handle was either mounted above the left or right cavity (with the hidden weight inserted in the central cavity) , resulting in external torque of ± 0.46 Nm after liftoff. The order of the conditions and first CoM side was randomly assigned to participants (see Supplementary Table 1). For each cue-conditions participants first completed a pseudorandom sequence of 37 trials in which the CoM could change from trial to trial and 33 trials in which the CoM stayed constant for 8 trials before it was inverted.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-1466052/v1/3f452fcbf8c7edb25f224ef3.png"},{"id":19980402,"identity":"ea2f7016-ed42-498d-be9b-3e3fb1b94a54","added_by":"auto","created_at":"2022-04-05 15:29:21","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":66995,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSensorimotor learning of anticipatory torque compensation\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e. Box and whiskers plots in the style of Tukey (central horizontal line: median, lower, and upper hinges: 25th and 75th percentiles, upper and lower whiskers extend up to 1.5 interquartile ranges) as well as the mean and standard deviation of the ratios of anticipatory torque anticipation success Tcom/external torque\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e \u003c/em\u003e\u003c/strong\u003e\u003cem\u003e(A)\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e, \u003c/em\u003e\u003c/strong\u003e\u003cem\u003eΔCoP * GF / External Torque\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e \u003c/em\u003e\u003c/strong\u003e\u003cem\u003e(B), and\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e \u003c/em\u003e\u003c/strong\u003e\u003cem\u003eΔFy * 0.5*w / External Torque\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e \u003c/em\u003e\u003c/strong\u003e\u003cem\u003e(C) for trials 4 to 8 of blocks in the ‘no cues’ condition are depicted for each group together with Holm-adjusted p-values of post-hoc t-tests of pairwise differences between controls and left- respectively right-hemispheric stroke patients.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-1466052/v1/54109da766ed4cfb6d166d0c.png"},{"id":19979871,"identity":"036f71ad-466b-43c9-9fa2-d6281cb82c24","added_by":"auto","created_at":"2022-04-05 15:19:21","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":64360,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTransfer of sensorimotor learning of anticipatory torque compensation to explicit CoM changes\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e. (A)\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e \u003c/em\u003e\u003c/strong\u003e\u003cem\u003eTcom/external torque\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e, \u003c/em\u003e\u003c/strong\u003e\u003cem\u003e(B) ΔCoP * GF / External Torque\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e, \u003c/em\u003e\u003c/strong\u003e\u003cem\u003eand\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e \u003c/em\u003e\u003c/strong\u003e\u003cem\u003e(C) ΔFy * 0.5*w / External Torque\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e \u003c/em\u003e\u003c/strong\u003e\u003cem\u003eof the first trial of a block after the CoM has changed in the ‘no cues, blocked’ condition (first trial of first block excluded) of all groups.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-1466052/v1/9f2a1500a96920221ca1ecf0.png"},{"id":19980058,"identity":"b3a22094-270d-434c-b49e-8d8d7ec7bebe","added_by":"auto","created_at":"2022-04-05 15:24:21","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":97002,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSensorimotor torque control in uncertainty\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e. (A)\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e \u003c/em\u003e\u003c/strong\u003e\u003cem\u003eTcom/external torque\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e, \u003c/em\u003e\u003c/strong\u003e\u003cem\u003e(B) ΔCoP * GF / External Torque\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e, \u003c/em\u003e\u003c/strong\u003e\u003cem\u003eand\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e \u003c/em\u003e\u003c/strong\u003e\u003cem\u003e(C) ΔFy * 0.5*w / External Torque\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e \u003c/em\u003e\u003c/strong\u003e\u003cem\u003eof all groups \u003c/em\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cem\u003eaveraged for trials in which the CoM has changed and trials in which it remained constant for both possible CoMs in the ‘no cues, pseudorandom’ condition.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-1466052/v1/ff84ee9dcd943623037b50cc.png"},{"id":19980399,"identity":"ded3a267-d8cf-48a4-9b4e-d12a391438cb","added_by":"auto","created_at":"2022-04-05 15:29:21","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":62237,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eLearning of anticipatory torque compensation according to both geometric cues and sensorimotor memories\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e. (A)\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e \u003c/em\u003e\u003c/strong\u003e\u003cem\u003eTcom/external torque\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e, \u003c/em\u003e\u003c/strong\u003e\u003cem\u003e(B) ΔCoP * GF / External Torque\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e, \u003c/em\u003e\u003c/strong\u003e\u003cem\u003eand\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e \u003c/em\u003e\u003c/strong\u003e\u003cem\u003e(C) ΔFy * 0.5*w / External Torque for trials 4 to 8 of blocks in the ‘geometric cues’ condition of all groups.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-1466052/v1/86207d2dcdaf040b0cbfa875.png"},{"id":19980062,"identity":"512656af-0c51-4bc8-ac65-6e5db912764a","added_by":"auto","created_at":"2022-04-05 15:24:21","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":61998,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eInteraction of visuomotor transformations and the transfer of sensorimotor learning of anticipatory torque compensation after CoM change in the blocked condition\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e. (A)\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e \u003c/em\u003e\u003c/strong\u003e\u003cem\u003eTcom/external torque\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e, \u003c/em\u003e\u003c/strong\u003e\u003cem\u003e(B) ΔCoP * GF / External Torque\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e, \u003c/em\u003e\u003c/strong\u003e\u003cem\u003eand\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e \u003c/em\u003e\u003c/strong\u003e\u003cem\u003e(C) ΔFy * 0.5*w / External Torque\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e \u003c/em\u003e\u003c/strong\u003e\u003cem\u003eof the first trial of a block after the CoM has changed in the ‘geometric cues’ condition (first trial of first block excluded) of all groups.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-1466052/v1/44a750df607e1819495def98.png"},{"id":19979867,"identity":"5e61f782-43af-45e6-b0af-041b3e8381f1","added_by":"auto","created_at":"2022-04-05 15:19:21","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":89723,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eInteraction of visuomotor transformations and the transfer of sensorimotor learning of anticipatory torque compensation after CoM change in the pseudorandom condition\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e.\u0026nbsp;(A)\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e \u003c/em\u003e\u003c/strong\u003e\u003cem\u003eTcom/external torque\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e, \u003c/em\u003e\u003c/strong\u003e\u003cem\u003e(B) ΔCoP * GF / External Torque\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e, \u003c/em\u003e\u003c/strong\u003e\u003cem\u003eand\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e \u003c/em\u003e\u003c/strong\u003e\u003cem\u003e(C) ΔFy * 0.5*w / External Torque\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e \u003c/em\u003e\u003c/strong\u003e\u003cem\u003eof all groups \u003c/em\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cem\u003eaveraged for trials in which the CoM has changed and trials in which it remained constant for both possible CoMs in the ‘geometric cues, pseudorandom’ condition.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"fig7.png","url":"https://assets-eu.researchsquare.com/files/rs-1466052/v1/814da64faea8602ee386f07e.png"},{"id":19980644,"identity":"abf350af-67c2-40ff-885f-34edcd4ac8fd","added_by":"auto","created_at":"2022-04-05 15:34:21","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":100218,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003e∆CoP at lift-off\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e. A) the blocked, no-cues condition (trials 4-8), B) the blocked, visual-cues condition (trials 4-8), C) the pseudorandom, no-cues condition and D) the pseudorandom, visual-cues condition.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"fig8.png","url":"https://assets-eu.researchsquare.com/files/rs-1466052/v1/ce6aad60cb545eb24d37e274.png"},{"id":19979874,"identity":"05987f34-ca61-4c98-a3f3-5e7ba55f9a23","added_by":"auto","created_at":"2022-04-05 15:19:21","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":113676,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eGF at lift-off was similar between stroke and control groups in all experimental conditions\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e. A) the blocked, no-cues condition (trials 4-8), B) the blocked, visual-cues condition (trials 4-8), C) the pseudorandom, no-cues condition and D) the pseudorandom, visual-cues condition.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"fig9.png","url":"https://assets-eu.researchsquare.com/files/rs-1466052/v1/624d3c83daaa30799a7c1595.png"},{"id":19980060,"identity":"a79a78fd-91cf-43e8-b000-c912f4d33d99","added_by":"auto","created_at":"2022-04-05 15:24:21","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":95588,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eDifferences of torques at lift-off between CL, and SL patients with and without signs of apraxia in the blocked, no-cues condition.\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e. (A)\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e , \u003c/em\u003e\u003c/strong\u003e\u003cem\u003eΔCoP * GF / External Torque\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e \u003c/em\u003e\u003c/strong\u003e\u003cem\u003e(B), and\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e \u003c/em\u003e\u003c/strong\u003e\u003cem\u003eΔFy * 0.5*w / External Torque\u003c/em\u003e\u003cstrong\u003e\u003cem\u003e \u003c/em\u003e\u003c/strong\u003e\u003cem\u003e(C) for trials 4 to 8 of blocks in the ‘no cues’ condition are depicted for each group together with both unadjusted- and Holm-adjusted p-values of post-hoc t-tests of pairwise differences.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"fig10.png","url":"https://assets-eu.researchsquare.com/files/rs-1466052/v1/3c726cbb615f7d93529c612d.png"},{"id":19980645,"identity":"4a21d3d7-182a-4f3e-9858-975691af7f2b","added_by":"auto","created_at":"2022-04-05 15:34:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1446314,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1466052/v1/d862391c-2dd6-4a1f-9717-28f68e17fd3a.pdf"},{"id":19979875,"identity":"d5ab2e18-4213-4d55-a2b5-bca41556de27","added_by":"auto","created_at":"2022-04-05 15:19:22","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":4650132,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterialBMC.docx","url":"https://assets-eu.researchsquare.com/files/rs-1466052/v1/d24203a294e502e99997cd9f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Object-centered sensorimotor bias of torque control in the chronic stage following stroke","fulltext":[{"header":"Background","content":"\u003cp\u003eMany stroke survivors suffer from impairments of dexterous upper-limb function affecting their functional independence as well as quality of life (\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Weakness, spasticity and a loss of selective finger movements of the contralesional upper extremity consequent to lesions of the primary cortex or the corticospinal tract as well as impaired manual dexterity due to somatosensory deficits linked to thalamic or parietal cortical lesions are clinically well recognized consequences of stroke and have been the focus of physical rehabilitation research as they contribute most to functional impairments (for review see (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)). Consequently, stroke survivors with contralateral hemiparesis must rely on their ipsilesional, i.e. non-paretic, hand to a great extent to perform activities of daily living. However, a growing number of studies demonstrates that fine motor performance of the ipsilesional upper limb is also substantially deprived following stroke (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Impaired fine motor control of the ipsilesional hand is evident in clinical motor function tests like the Jebsen Hand Function Test (\u003cspan additionalcitationids=\"CR6 CR7 CR8 CR9\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e), in finger-tapping (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), and tests of fine motor dexterity, e.g. the 9-hole-peg test (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Subtle losses in dexterity of the ipsilesional hand are relevant for performance in activities of daily living and thus threaten the regaining of functional independence following stroke. Accordingly, poorer performance with the ipsilesional hand was confirmed in activities of daily living like the one-handed binding of shoes (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) and the preparation of meals (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Recent research highlights that ipsilesional hand performance is highly relevant for the functional independence following left hemisphere stroke (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Therefore, identifying the factors underlying impaired, ipsilesional upper limb control and developing targeted rehabilitation regimes is of paramount importance.\u003c/p\u003e \u003cp\u003eKinematic analyses of reaching tasks revealed that ipsilesional motor deficits are hemisphere dependent and reflect lateralization of motor function. Movements of the ipsilesional arm are slower and more variable following left hemisphere damage while final position accuracy is decreased after right hemisphere damage (\u003cspan additionalcitationids=\"CR19 CR20 CR21 CR22 CR23\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). These observations led to the proposal of a \u0026ldquo;dynamic dominance\u0026rdquo; hypothesis of motor lateralization stating that the dominant hemisphere is specialized for the coordination of limb and task dynamics, i.e. movement trajectories, while the nondominant hemisphere is responsible for achieving the final, i.e. steady-state, end-effector positions and stabilizing external loads (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Ipsilesional motor deficits in reaching tasks scale with the severity of contralesional arm impairment, i.e. the more severe the contralesional arm paresis, the larger the ispilesional motor deficits (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), and correlate with apraxia scores in patients with left-hemispheric stroke (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) although the relationship may be complex(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOne elegant way to study complementary pathophysiologic aspects of manual dexterity following stroke is to examine kinetics, i.e. forces and torques, when patients execute elementary grasp-to-lift tasks. In healthy adults grip forces (GF), i.e. the force acting orthogonal to the grip surface, and load forces (LF), i.e. the forces directed tangentially upwards, rise in parallel and are precisely scaled to the anticipated characteristics of both the object (weight, frictional characteristics) according to previous experience, i.e. sensorimotor memories (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e), and visual object characteristics, e.g. size, material, arbitrary cues, object identity (\u003cspan additionalcitationids=\"CR31 CR32 CR33 CR34\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e), and the dynamics of the task (for review see: (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e)).\u003c/p\u003e \u003cp\u003eHemiparetic patients with stroke typically exert increased grip forces when lifting objects with their more affected, contralesional, hand which can be partially attributed to disturbed sensorimotor integration (\u003cspan additionalcitationids=\"CR38 CR39 CR40 CR41 CR42\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). Moreover, studies investigating the ipsilesional, non paretic, hand of stroke survivors also found elevated grip force levels (\u003cspan additionalcitationids=\"CR45\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e) as well as an increased grip force variability (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e) and disturbed anticipatory grip-to-load force coupling (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). In contrast, gross grip strength is not reduced in the ipsilesional hand following stroke (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Adding to these problems in the task execution, the anticipatory planning of forces is also impaired following stroke. While the anticipatory scaling of grip forces according to object size is intact in stroke patients (Li et al., 2011), patients with left hemisphere damage failed to scale grip forces to the actual weight of objects of daily life when grasping and lifting them with their ipsilesional hand (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). This GF scaling deficit was associated with scores of apraxia. Similarly, patients with left-sided middle-cerebral artery (MCA) stroke could not use color-cues associated with object weight to scale grip forces with either hand, whereas patients with right MCA stroke only showed impaired force scaling with their contralesional hand (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe control of torques when lifting an object with an eccentric center of mass (CoM) relative to the hand is another essential aspect of dexterous object handling in daily life which has been extensively studied in healthy adults over the last two decades. To prevent object tilt, e.g. when lifting a cup of tea at the handle, arising torques must be already compensated at the moment of object lift-off, i.e. before full sensory feedback of object toque is available. Two torque components add up to the total torque applied by the fingers in the direction of interest. These are a) the product of the load force difference between grasp-sides (∆Fy) and half the grasp-width (w/2) and b) the product of the distance between the finger centers of pressure on the grasp surfaces (∆CoP) and the grip force (GF). Therefore, the digit placements and grip- and load forces must be coordinated to apply adequate counteracting torques at lift-off (for review see (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e)). Healthy adults learn to modulate both their digit centers of pressure and digit forces by placing the digit(s) on the side of the center of mass higher and applying more load force at the digit on that side according to previous experience (\u003cspan additionalcitationids=\"CR51\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e), even when object dynamics change unpredictably (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e). Furthermore, subjects can visually process salient object shape/geometry cues to infer the weight distribution of the object and plan torques accordingly (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan additionalcitationids=\"CR56\" citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). To generate adequate compensatory torques, digit -forces and -placements are covaried by a high-, respectively task-level control. This principle of force-to position covariation is grasp-type independent (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e) and was shown for grasps with a precision grip (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e), tripod grip (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e), whole hand grasps (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e) as well as for bimanual grasps (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e). Although torques can be applied by any combination of digit center of pressure differences between the grasp sides (∆CoP) and load force partitioning between sides (∆Fy) as long as the resulting torque components add up to the required total torques, we recently demonstrated that an adequate finger-tip positioning and a predominant torque exertion by the product of ∆CoP and GF is essential for a force efficient task execution (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e). Whether these aspects of high-level torque control are impaired at the ipsilesional hand of patients with unilateral stroke has not been investigated, yet.\u003c/p\u003e \u003cp\u003eIn the present study, we examined whether the anticipatory torque control with the ipsilesional hand when lifting an object with a varying asymmetric weight distribution is impaired in the chronic stage following unilateral stroke. We tested two cue conditions. The first was a \u0026lsquo;no-cues\u0026rsquo; condition in which the position of a covert weight was changed while object shape (inverted T) was not informative of the CoM. In this condition, subjects had to rely on sensorimotor memories from the last lift or lifts. In the second condition the visually salient object geometry was congruent with weight distribution (L-shape) allowing visual inference of CoM. Moreover, two sequence conditions, one in which the mass distribution was constant over a block of trials and one in which it could change from trial to trial were employed for both cue conditions.\u003c/p\u003e \u003cp\u003eSince the right-hemisphere is proposed to be responsible for end-effector positions according to the \u0026ldquo;dynamic dominance\u0026rdquo; model (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) we expected that patients with right hemisphere damage would fail to learn to position their fingers for an adequate torque component ∆CoPxGF, but would correct for this by compensatory ∆Fy (x w/2) resulting in successful total torque compensation.\u003c/p\u003e \u003cp\u003eBased on the hypothesized role of the left hemisphere in the dynamic phase of an action, we hypothesized a less accurate coordination of fingertip load forces (∆Fy) to the present ∆CoP and consequently less successful predictive torque compensation in patients with left-hemispheric-, but not right hemispheric stroke, irrespective of the side of the object center of mass (CoM). Moreover, we presumed that patients with signs of apraxia would present an accentuated impairment of force-to position coordination and consequently torque compensation.\u003c/p\u003e \u003cp\u003eHowever, as stroke patients previously exhibited mostly intact visuomotor processing of size and weight cues to scale finger-tip forces (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e) we expected that most stroke patient can improve torque anticipation when salient-geometric cues are provided. As an exception, we presumed that patients with hemispatial neglect might fail to utilize a lateralized geometric cue indicating a CoM on the contralesional side.\u003c/p\u003e \u003cp\u003eConcerning grip force levels, we expected to observe elevated and more variable GF levels in both stroke groups based on previous studies (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e).\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cp\u003e3.1 Participants\u003c/p\u003e\n\u003cp\u003eOverall, 13 patients with chronic-stage left hemispheric stroke (SL group: 6 female, mean age 63.3\u0026thinsp;\u0026plusmn;\u0026thinsp;16.3 years, mean years since onset of stroke (YOS): 6.06\u0026thinsp;\u0026plusmn;\u0026thinsp;4.10 years) and 9 patients with chronic-stage right hemispheric stroke (SR group: 5 female, mean age 63.9\u0026thinsp;\u0026plusmn;\u0026thinsp;6.7 years, mean YOS 7.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.7 years) were tested with their ipsilesional hand. 15 healthy adults who conducted the experiment with their left hand (CL group: 6 female, mean age 63.0\u0026thinsp;\u0026plusmn;\u0026thinsp;13.1 years) and 9 healthy adults who conducted the experiment with their right hand (CR group: 4 female, mean age 69.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8years) served as control groups. Patients with a single unilateral cerebrovascular event older than 6 months and no evidence of bilateral lesions in their medical reports were recruited from the community with the help of physiotherapists, occupational therapists, speech therapists and neuropsychologist in the greater Munich area (see Acknowledgements). All participants reported to be right handed.\u003c/p\u003e\n\u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e provides group summaries of the demographic and clinical characteristics as well as the results of the performed neglect and apraxia tests together with the statistical results of between group tests (ANOVA, respectively t- tests for numerical data, chi-square tests for categorical data). Individual patient\u0026rsquo;s data are outlined in \u003cstrong\u003eSupplementary Table S1\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eThe experimental procedures were approved by the Institutional Review Board of the School of Medicine at the Technical University of Munich and were in accordance with the Declaration of Helsinki. All subjects were na\u0026iuml;ve to the purpose of the study and gave informed consent to participate in the study and have us collect relevant medical reports from their family doctor. Measurements took place at our lab as well as in patients\u0026rsquo; homes between September 2016 and April 2017. All participants received 20 \u0026euro; for their participation in the study which lasted\u0026thinsp;~\u0026thinsp;2 hours.\u003c/p\u003e\n\u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup summary\u003c/strong\u003e of the demographics, clinical data, the coefficients of fraction, maximum voluntary GF, the results of the pantomime and imitation tests of G. Goldenberg (see also (\u003cspan class=\"CitationRef\"\u003e65\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e67\u003c/span\u003e) as well as the results of the line bisection test, letter cancellation test (\u003cspan class=\"CitationRef\"\u003e68\u003c/span\u003e), and a Posner type reaction time test (\u003cspan class=\"CitationRef\"\u003e69\u003c/span\u003e). The p-values of between groups differences were based on ANOVA tests for numerical data (respectively t-tests if data were only obtained for the stroke groups) and on chi-square tests for categorical data. Abbreviations: Stroke type: i\u0026thinsp;=\u0026thinsp;ischemic; h\u0026thinsp;=\u0026thinsp;hemorrhagic; i, h\u0026thinsp;=\u0026thinsp;ischemic stroke followed by hemorrhage; h, i: hemorrhage with subsequent ischemic infarction.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCL (N\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCR (N\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSL (N\u0026thinsp;=\u0026thinsp;13)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSR (N\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.561\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63.0 (13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69.8 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63.3 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63.9 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.9\u0026ndash;80.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65.3\u0026ndash;76.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.5\u0026ndash;79.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.4\u0026ndash;72.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.907\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003em\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (60.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (55.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (53.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (44.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (40.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (44.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (46.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (55.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eStroke Type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.042\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ei\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (76.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (55.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (44.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ei, h\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eh, i\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (15.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003emRS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.702\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.4 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.2 (1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0\u0026ndash;4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0\u0026ndash;4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eYears since stroke onset\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.505\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.1 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.5 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.1\u0026ndash;15.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.2\u0026ndash;19.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoefficient of friction\u003c/strong\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({}_{\\mathbf{s}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.292\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9 (0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0 (0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9 (0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9 (0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6\u0026ndash;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7\u0026ndash;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7\u0026ndash;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7\u0026ndash;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePeak voluntary GF [N]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.609\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68.7 (24.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57.5 (17.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67.6 (20.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66.0 (16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.1\u0026ndash;111.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.4\u0026ndash;93.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.7\u0026ndash;98.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37.8\u0026ndash;93.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eImitation Hand\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.070\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.7 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.9 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.0\u0026ndash;20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.0\u0026ndash;20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eImitation Finger\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.616\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.6 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.1 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.0\u0026ndash;20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.0\u0026ndash;20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePantomime correct items [/20]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.224\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.2 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.3 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.0\u0026ndash;20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.0\u0026ndash;20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePantomime Score [/55]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.241\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.2 (10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54.3 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.0\u0026ndash;55.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53.0\u0026ndash;55.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBisection Test: mean horizontal deviation [mm]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.432\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.3 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4.9\u0026ndash;4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.8\u0026ndash;6.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLetter cancellation test: center of cancellation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.201\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0\u0026ndash;0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.0\u0026ndash;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLetter cancellation test: overall letters found [/60]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.051\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59.1 (1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57.2 (2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57.0\u0026ndash;60.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54.0\u0026ndash;60.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePosner test: median reaction time [ms]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.346\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e557.3 (179.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e474.4 (87.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e324.0\u0026ndash;960.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e403.5\u0026ndash;617.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePosner test: relative L-R reaction time difference [%]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-9.1 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.6 (16.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-20.4\u0026ndash;9.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3\u0026ndash;39.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003e\u003csup\u003e1\u003c/sup\u003e Linear Model ANOVA, \u003csup\u003e2\u003c/sup\u003e Pearson\u0026rsquo;s Chi-squared test\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n\u003c/table\u003e\n\u003cp\u003e3.2 Modified Rankin Scale (mRS)\u003c/p\u003e\n\u003cp\u003eThe modified Rankin Scale (mRS) was assessed as measure of the degree of disability or dependence in the daily activities using the simplified questionnaire proposed by Bruno et al. (\u003cspan class=\"CitationRef\"\u003e70\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e3.3 Apraxia Tests\u003c/p\u003e\n\u003cp\u003eWe administered two established tests of apraxia and video-recorded them for later analysis. Firstly, we examined the imitation of meaningless gestures of hand- and finger postures with the ipsilesional hand. Imitation scores below 18 of 20 for hand- and 17 of 20 for finger-postures were considered as suggestive of apraxia ((\u003cspan class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e71\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e73\u003c/span\u003e). In addition to imitation, we examined pantomime of tool-use. Here, we showed patients pictures of one of 20 tools or objects of the daily life and asked them to mime specific action as if they were holding the object in their ipsilesional hand. We scored whether hand positions and movements were correct. Scores below 45/55 were considered as suggestive of apraxia (\u003cspan class=\"CitationRef\"\u003e67\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e74\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e3.4 Tests of hemispatial Neglect\u003c/p\u003e\n\u003cp\u003eThe presence of hemispatial neglect was assessed by the a) line bisection-test in which a deviation of more than 6 mm from the midpoint indicates hemispatial neglect (\u003cspan class=\"CitationRef\"\u003e75\u003c/span\u003e), b) the letter cancellation test with performance quantified by the center of calculation (CoC) score introduced by Rorden and Karnath (\u003cspan class=\"CitationRef\"\u003e68\u003c/span\u003e) \u0026ndash; i.e. an absolute CoC score above 0.083 indicates presence of hemispatial neglect - and c) a Posner type spatial cueing test (\u003cspan class=\"CitationRef\"\u003e76\u003c/span\u003e) implemented in the free computer test battery PEBL (version 0.14, (\u003cspan class=\"CitationRef\"\u003e77\u003c/span\u003e)). In the latter, patients sat in front of a 15.6-inch Lenovo laptop. After a cue to the left, right or both sides (neutral) was provided, indicating where the response is likely to be, patients had to press a key when they detected a stimulus either to the left or right of fixation. As measure of a hemispatial visual bias we calculated the standardized median reaction time difference between trials with stimuli to the left and to the right of fixation (overall 200 trials, 100 trials per stimulus side, cues were valid in 120 trials, neutral in 40 trials, and invalid in 40 trials). Reaction time differences between stimuli on the left and right side in Posner-type reaction time tests were shown to be more sensitive than paper and pencil based tests in detecting hemispatial neglect (\u003cspan class=\"CitationRef\"\u003e69\u003c/span\u003e). However, there is no established cut-off defining hemispatial neglect.\u003c/p\u003e\n\u003cp\u003e3.5 Experimental Design and Statistical Analyses\u003c/p\u003e\n\u003cdiv class=\"Section2\" id=\"Sec5\"\u003e\n \u003cp\u003e3.5.1 Apparatus\u003c/p\u003e\n \u003cp\u003eSubjects were instructed to reach, grasp, lift and replace a custom made, grip device with the thumb opposing the index and the middle finger (\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e) (see Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA). The grasp surfaces (120x40 mm) were covered with fine-grained sand paper (2000 grit). Two 6-axis force/torque-sensors (ATI Nano-17 SI-50-0.5, ATI Industrial Automation; force range: 50,50, and 70 N for x-, y-, and z-axes, respectively; force resolution: 0.012 N; torque range 0.5 Nm; torque resolution: 0.063 Nmm, sampling rate 200 Hz) recorded the forces and torques applied on both grasp sides. Position and orientation data of the device were measured by a lightweight magnetic position/orientation-tracker (TrakSTAR, Ascension Technology Corporation, accuracy: 1.4 mm RMS, 0.5 degrees RMS, sampling rate 200 Hz) fixed on top of the horizontal base. Data collection was synchronized using custom software written in Matlab 2016a (MATLAB, RRID:SCR_001622). Both the position of the handle device on top of the base as well as the location of a 250 g aluminum weight which was put into cavities of the base hidden by a lid could be altered to vary the object\u0026rsquo;s center of mass (CoM) relative to the hand (see Experimental Protocol).\u003c/p\u003e\n \u003cp\u003e3.5.2 Determining the static coefficient of friction, \u0026micro;\u003csub\u003es\u003c/sub\u003e, at slip onset\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec6\"\u003e\n \u003cp\u003ePrior to the main experiment, subjects were asked to lift and hold the grip device in a three-finger precision grip with the thumb, index and middle fingers of the hand used for the upcoming lifting taks and slowly release it until the object slipped. We estimated the average static friction coefficient, \u0026micro;\u003csub\u003es\u003c/sub\u003e, at the digit - surface contacts, by calculating the ratio between the load- and grip force at slip onset which was visually detected by a sudden drop in the load force and height. Overall, \u0026micro;\u003csub\u003es\u003c/sub\u003e could be successfully calculated in 121 slip-trials. The averaged \u0026micro;\u003csub\u003es\u003c/sub\u003e estimates are based on an average of 2.63 slip-trials per subject (SD 0.77, median 3, range 1\u0026ndash;4).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec7\"\u003e\n \u003cp\u003e3.5.3 Maximum GF\u003c/p\u003e\n \u003cp\u003ePrior to the main experiment we had participants pinch the grasp surfaces as hard as they could in the specified three-finger precision grip twice for five seconds and determined the highest applied GF as maximum GF.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec8\"\u003e\n \u003cp\u003e3.5.4 Experimental Task\u003c/p\u003e\n \u003cp\u003eFor the main experiment, we instructed participants to start reaching for the grasp-device after a signal tone, grasp the grasp surfaces with the fingertips of the thumb-, index- and middle finger in a precision grip, lift it in a smooth movement to a height of ~\u0026thinsp;5\u0026ndash;10 cm while minimizing object tilts and hold the object steady thereafter. A second tone 4 seconds after the first signaled subjects to replace the device. Patients were allowed to position and orient the object on the table in a way that allowed for a comfortable wrist position for grasping.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec9\"\u003e\n \u003cp\u003e3.5.5 Experimental Protocol\u003c/p\u003e\n \u003cp\u003eFirst, participants conducted six practice grasp-to-lift trials in which the object\u0026rsquo;s CoM was below the middle of the handle (zero external torque).\u003c/p\u003e\n \u003cp\u003eSubsequently, the main experimental protocol contained two sequence conditions and two cue conditions \u003cstrong\u003e(see\u003c/strong\u003e Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eC\u003cstrong\u003e)\u003c/strong\u003e. In the \u0026lsquo;no cues condition\u0026rsquo;, the object handle was attached over the center of the base (symmetric, inverted T-shape) and the center of mass was varied by placing a covert 250 g aluminum weight into either the outer left or outer right hidden cavity of the horizonal base, resulting in external torques of \u0026plusmn;\u0026thinsp;0.21 Nm (\u003cstrong\u003esee\u003c/strong\u003e Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eC). In the \u0026lsquo;geometric cues condition\u0026rsquo;, in contrast, the aluminum weight was constantly placed in the center cavity, but the handle was either positioned on top of the left or right object edge creating an asymmetric L-shape and resulting in an external torques of \u0026plusmn;\u0026thinsp;0.46 Nm (\u003cstrong\u003esee\u003c/strong\u003e Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eC). As convention, negative signs denote a counter-clockwise external torque. The total object weight was 750 g.\u003c/p\u003e\n \u003cp\u003eIn both cue-conditions, participants first conducted 37 trials in the \u0026lsquo;pseudorandom\u0026rsquo; sequence-condition in which the CoM was changed in a pseudo random fashion which could not be predicted by the participants (\u003cstrong\u003esee\u003c/strong\u003e Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eC). Participants had to close their eyes while the hidden weight was removed and placed back either into the same or the opposite position after each trial.\u003c/p\u003e\n \u003cp\u003eThis was followed by the blocked sequence-condition in which the CoM remained constant for 8 trials per block before the CoM changed side for the next blocks. Participants were informed about the CoM change between blocks but were restricted of watching the configuration change. The blocked-sequence encompassed 4 complete blocks and the first trial of the 5th block, i.e. 33 trials. The succession of the pseudorandom and blocked sequence-condition trials was performed for both the no-cues and geometric-cues conditions, amounting to a total of 140 main trials per participant. We randomly assigned the order of the two cue conditions and the initial CoM side for the first trial for the no-cues- and geometric-cues conditions to the participants.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec10\"\u003e\n \u003cp\u003e3.5.6 Data Processing\u003c/p\u003e\n \u003cp\u003eData were processed and analyzed with custom software written in Matlab 2016a. The collected force/torque data was filtered through a sixth-order Butterworth low-pass filter with a cutoff frequency of 14 Hz. The index and middle finger contacting the same grip side produced net mechanical forces and moments equivalent to the sum of their individual actions and were hence considered as a virtual finger (\u003cspan class=\"CitationRef\"\u003e78\u003c/span\u003e). We analyzed the exerted total torque (\u003cstrong\u003eTcom\u003c/strong\u003e) as well as the torque components \u003cstrong\u003e\u0026Delta;Fy*w/2\u003c/strong\u003e and \u003cstrong\u003e\u0026Delta;CoP *GF\u003c/strong\u003e outlined below as well as the grip force (\u003cstrong\u003eGF\u003c/strong\u003e) at the moment of object \u003cstrong\u003elift off\u003c/strong\u003e, defined as the moment 10ms prior to which the vertical position of the object raised above a threshold of 0.2 mm.\u003c/p\u003e\n \u003cp\u003eWe examined the following experimental variables (see Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eB):\u003c/p\u003e\n \u003cp\u003e1) Grip force (\u003cstrong\u003eGF\u003c/strong\u003e) was defined as the mean normal force directed orthogonal towards the grip surfaces.\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e2) ∆CoP\u003c/strong\u003e at lift-off was defined as the vertical difference between the center of pressure (CoP) on the right and the left grip sides at the moment of lift-off.\u003c/p\u003e\n \u003c/span\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3) Tcom\u003c/strong\u003e, the compensatory torque exerted at object lift off, is an established indicator of torque anticipation (\u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e80\u003c/span\u003e). \u003cstrong\u003eTcom\u003c/strong\u003e is the sum of: a) \u003cstrong\u003e\u0026Delta;CoP *GF\u003c/strong\u003e, the product of GF and \u0026Delta;CoP and b) \u003cstrong\u003e\u0026Delta;Fy*w/2\u003c/strong\u003e, the torque generated by the product of the difference between the right and left load force and half the distance between the grip-surfaces (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{\\text{w}}{2}\\)\u003c/span\u003e\u003c/span\u003e= 20.4 mm). With the chosen sign conventions, Tcom matches in sign with the external torque when it counterbalances the exerted torque, e.g. is directed in opposing direction to the external torque. Hence, clockwise exerted torques were defined as negative and counter-clockwise torques as positive (see Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA and the supplementary material of (\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e): \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.6084/m9.figshare.7683707\u003c/span\u003e\u003c/span\u003e). As outcome measures in the statistical analyses, we calculated the respective \u003cstrong\u003eratios\u003c/strong\u003e between the torque variables and the external torque to compensate for, i.e.: \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{\\mathbf{T}\\mathbf{c}\\mathbf{o}\\mathbf{m}}{\\mathbf{E}\\mathbf{x}\\mathbf{t}\\mathbf{e}\\mathbf{r}\\mathbf{n}\\mathbf{a}\\mathbf{l} \\mathbf{T}\\mathbf{o}\\mathbf{r}\\mathbf{q}\\mathbf{u}\\mathbf{e}}\\)\u003c/span\u003e\u003c/span\u003e, \u003cimg src=\"data:image/png;base64,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\"\u003e\u0026nbsp;and \u003cimg src=\"data:image/png;base64,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\"\u003e. This allows for direct evaluation of the success of torque anticipation as a ratio of 1 indicates perfect torque compensation and negative ratios indicate torques directed in the wrong direction. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{\\mathbf{T}\\mathbf{c}\\mathbf{o}\\mathbf{m}}{\\mathbf{E}\\mathbf{x}\\mathbf{t}\\mathbf{e}\\mathbf{r}\\mathbf{n}\\mathbf{a}\\mathbf{l} \\mathbf{T}\\mathbf{o}\\mathbf{r}\\mathbf{q}\\mathbf{u}\\mathbf{e}}\\)\u003c/span\u003e\u003c/span\u003e is the \u003cstrong\u003eprimary outcome variable\u003c/strong\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{{\\Delta }\\text{F}\\text{y}\\text{*}\\text{w}/2}{\\text{E}\\text{x}\\text{t}\\text{e}\\text{r}\\text{n}\\text{a}\\text{l} \\text{T}\\text{o}\\text{r}\\text{q}\\text{u}\\text{e}}\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{{\\Delta }\\text{C}\\text{o}\\text{P} \\text{*}\\text{G}\\text{F}}{\\text{E}\\text{x}\\text{t}\\text{e}\\text{r}\\text{n}\\text{a}\\text{l} \\text{T}\\text{o}\\text{r}\\text{q}\\text{u}\\text{e}}\\)\u003c/span\u003e\u003c/span\u003e are the secondary outcome variables, and ∆CoP and GF represent exploratory tertiary outcome variables.\u003c/p\u003e\n \u003c/span\u003e\u003cspan\u003e\n \u003cp\u003e4) Additionally, we estimated the average static coefficients of friction, \u0026mu;\u003csub\u003es\u003c/sub\u003e, of each participant by averaging the ratios between the load force and grip force at the moment at which slips occurred in the slip-task to control for possible friction differences between groups.\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003e3.5.7 Data Management\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec11\"\u003e\n \u003cp\u003eDue to technical errors 1.58% (106/6716) of the measurements had to be discarded. We obtained 121 \u0026mu;\u003csub\u003es\u003c/sub\u003e estimates employing the slip-method.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec12\"\u003e\n \u003cp\u003e3.5.8 Statistical Analysis\u003c/p\u003e\n \u003cp\u003eStatistical analyses were performed in the R environment for statistical computing (version 4.0.3, (\u003cspan class=\"CitationRef\"\u003e81\u003c/span\u003e), R Project for Statistical Computing, (RRID):SCR_001905). To compare the demographic and clinical characteristic of the control- and stroke groups exploratory analyses of variance (ANOVA) tests for numerical data (respectively t-tests if data were only obtained for the stroke groups) and chi-square tests for categorical data were conducted as implemented in the \u0026lsquo;arsenal\u0026rsquo; package (\u003cspan class=\"CitationRef\"\u003e82\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eConcerning the main outcome measures, we fit linear mixed effects regression models (LMM) for the dependent experimental variables with the restricted maximum likelihood criterion using the \u0026lsquo;lme4\u0026rsquo;- (\u003cspan class=\"CitationRef\"\u003e83\u003c/span\u003e) package. P-values of the predictor-estimates of all LMMs were calculated based on Wald-type t-Tests using the Kenward-Roger approximation of the degrees of freedom. Post-hoc t-tests of pairwise comparisons between stroke patient- and hand-matched control groups were based on the marginal means of the LMMs (\u003cspan class=\"CitationRef\"\u003e84\u003c/span\u003e) with Holm-Bonferroni correction for multiple testing applied (\u003cspan class=\"CitationRef\"\u003e85\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eSeparate models for the torque variables, ∆CoP- and GF at lift off were fitted for every experimental condition. In the models for the blocked condition, the model predictors were the participant group, the external torque and the two-way interaction between these factors. We conducted both analyses of the trials 4\u0026ndash;8 of each block to assess the extent of motor learning as well as of the respective first trials of blocks 2\u0026ndash;4 after the CoM changed to investigate the transfer of motor plans to a new situation. In the models for the pseudorandom sequence condition, we included the additional predictor \u0026lsquo;CoM-retained/inverted\u0026rsquo; as well as all resulting two- and three-way interactions with the predictors group and external torque into the model specifications.\u003c/p\u003e\n \u003cp\u003eThree patients with left hemispheric stroke showed signs of apraxia (see below and \u003cstrong\u003eSupplementary Figure S1\u003c/strong\u003e). Therefore, we performed additional exploratory statistical analyses for the variables in the blocked conditions with post-hoc comparisons between the groups CL (n\u0026thinsp;=\u0026thinsp;15), SL apraxia negative (n\u0026thinsp;=\u0026thinsp;10), and SL apraxia positive (n\u0026thinsp;=\u0026thinsp;3) but otherwise identical model specifications as outlined above. Due to the small sample size of apraxia positive patients, both unadjusted and Holm- adjusted p-values of the between group comparisons are presented for these additional analyses.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e4.1 Demographic characteristics, clinical measures and static coefficients of friction\u003c/p\u003e\n\u003cp\u003eWe found no statistically significant differences between groups regarding age (p\u0026thinsp;=\u0026thinsp;0.56), years since stroke onset (p\u0026thinsp;=\u0026thinsp;0.51), gender distribution (p\u0026thinsp;=\u0026thinsp;0.91), mRS (p\u0026thinsp;=\u0026thinsp;0.70), mean coefficient of friction (p\u0026thinsp;=\u0026thinsp;0.29, see also \u003cstrong\u003eSupplementary Figure S2\u003c/strong\u003e), nor the voluntary maximum GF in the tripod grip (p\u0026thinsp;=\u0026thinsp;0.609) (\u003cstrong\u003esee\u003c/strong\u003e Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e4.2 Apraxia and Neglect\u003c/p\u003e\n\u003cp\u003eThe vast majority of patients scored within the normal range in the administered apraxia and neglect tests: Only three patients with left MCA strokes scored below the cutoff in the hand imitation test (\u0026lt;\u0026thinsp;18), two of these patients (ID24, ID27) also failed the finger imitation (\u0026lt;\u0026thinsp;17) - and pantomime tests (\u0026lt;\u0026thinsp;45, \u003cstrong\u003eSupplementary Figure S1\u003c/strong\u003e). Regarding the paper-based tests of hemispatial-neglect, only one patient with right MCA stroke (ID9) showed a line bisection deviation suggestive of hemispatial neglect to the left. However, results of the letter cancellation test were within the normal range in all patients. The results of the hand- (p\u0026thinsp;=\u0026thinsp;0.070), and finger imitation tests (p\u0026thinsp;=\u0026thinsp;0.616), the pantomime score (p\u0026thinsp;=\u0026thinsp;0.241) as well as the line bisection (p\u0026thinsp;=\u0026thinsp;0.43) and the CoC on the letter cancellation test (p\u0026thinsp;=\u0026thinsp;0.201) did not differ between patient groups. The only significant difference between the SL and SR group was found for the percentual left-right reaction time difference in the Posner test (p\u0026thinsp;=\u0026thinsp;0.001). Whereas SL patients were about 9.1% (SD 8.3%) slower in reacting to a stimulus on the right side, SR patients were 14.6% (SD 16.5%) slower when the stimulus was on the left side. In contrast, the mean reaction time in the Posner test (p\u0026thinsp;=\u0026thinsp;0.35) was similar between patient groups. Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the demographic, clinical and grip related measures of the participant groups.\u003c/p\u003e\n\u003cp\u003e4.3 Torque compensation at lift off\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.3.1 No cues, blocked condition trials 4\u0026ndash;8: Sensorimotor learning of the anticipatory coordination of centers of pressure and grip force is spatially biased following stroke.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants of all groups only needed some 2\u0026ndash;3 lift trials to learn to compensate for torques at the moment of lift-off. After that, Tcom remained stable for the rest of the block (see \u003cstrong\u003eSupplementary Figure S3\u003c/strong\u003e for the individual and group-averaged Tcom trajectories across trials in the \u0026lsquo;no cues\u0026rsquo; condition).\u003c/p\u003e\n\u003cp\u003eAll groups generated similar compensatory torques at lift-off in trials 4\u0026ndash;8 with no significant differences between stroke and control groups. However, there was a trend towards a decreased Tcom for the SR-group when the weight was on the left side which was not significant after Holm-correction (t\u0026thinsp;=\u0026thinsp;2.15, df\u0026thinsp;=\u0026thinsp;55.3, p\u0026thinsp;=\u0026thinsp;0.071, \u003cstrong\u003esee\u003c/strong\u003e Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA \u003cstrong\u003eand Supplementary Table S3\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eIn contrast, the torque components at lift-off were spatially biased following a specific directional pattern in both stroke groups. The torque generated by grip force being produced at different vertical finger positions (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{{\\Delta }\\mathbf{C}\\mathbf{o}\\mathbf{P} \\mathbf{*}\\mathbf{G}\\mathbf{F}}{\\mathbf{E}\\mathbf{x}\\mathbf{t}\\mathbf{e}\\mathbf{r}\\mathbf{n}\\mathbf{a}\\mathbf{l} \\mathbf{T}\\mathbf{o}\\mathbf{r}\\mathbf{q}\\mathbf{u}\\mathbf{e}}\\)\u003c/span\u003e\u003c/span\u003e) was lower in the SL group than the CL group when the CoM was on the right, i.e. contralesional, side (t\u0026thinsp;=\u0026thinsp;4.59, df\u0026thinsp;=\u0026thinsp;65.5, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cstrong\u003esee\u003c/strong\u003e Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eB \u003cstrong\u003eand Supplementary Table S5\u003c/strong\u003e) but higher than in the CL group when the weight was on the left, i.e. ipsilesional, side (t = -4.10, df\u0026thinsp;=\u0026thinsp;65.5, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The torque produced by different load forces at the handle sides was biased in the opposite direction, i.e. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{{\\Delta }\\mathbf{F}\\mathbf{y}\\mathbf{*}\\mathbf{w}/2}{\\mathbf{E}\\mathbf{x}\\mathbf{t}\\mathbf{e}\\mathbf{r}\\mathbf{n}\\mathbf{a}\\mathbf{l} \\mathbf{T}\\mathbf{o}\\mathbf{r}\\mathbf{q}\\mathbf{u}\\mathbf{e}}\\)\u003c/span\u003e\u003c/span\u003e was higher than in CL for a CoM on the contralesional, right side (t = -5.03, df\u0026thinsp;=\u0026thinsp;98.2, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cstrong\u003esee\u003c/strong\u003e Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eC \u003cstrong\u003eand Supplementary Table S7\u003c/strong\u003e) and lower for a CoM on the ipsilesional, left side (t\u0026thinsp;=\u0026thinsp;5.33, df\u0026thinsp;=\u0026thinsp;98.2, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). As the patterns of the object-centered spatial bias are diametrically opposed for \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{{\\Delta }\\mathbf{C}\\mathbf{o}\\mathbf{P} \\mathbf{*}\\mathbf{G}\\mathbf{F}}{\\mathbf{E}\\mathbf{x}\\mathbf{t}\\mathbf{e}\\mathbf{r}\\mathbf{n}\\mathbf{a}\\mathbf{l} \\mathbf{T}\\mathbf{o}\\mathbf{r}\\mathbf{q}\\mathbf{u}\\mathbf{e}}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{{\\Delta }\\mathbf{F}\\mathbf{y}\\mathbf{*}\\mathbf{w}/2}{\\mathbf{E}\\mathbf{x}\\mathbf{t}\\mathbf{e}\\mathbf{r}\\mathbf{n}\\mathbf{a}\\mathbf{l} \\mathbf{T}\\mathbf{o}\\mathbf{r}\\mathbf{q}\\mathbf{u}\\mathbf{e}}\\)\u003c/span\u003e\u003c/span\u003e the effects seem to cancel each other out resulting in normal total torques (Tcom) as outlined above.\u003c/p\u003e\n\u003cp\u003eSR patients equally exerted less torque by grip force being produced at different vertical finger positions (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{{\\Delta }\\text{C}\\text{o}\\text{P} \\text{*}\\text{G}\\text{F}}{\\text{E}\\text{x}\\text{t}\\text{e}\\text{r}\\text{n}\\text{a}\\text{l} \\text{T}\\text{o}\\text{r}\\text{q}\\text{u}\\text{e}}\\)\u003c/span\u003e\u003c/span\u003e) than CR controls when the CoM was on the contralesional, left side (t\u0026thinsp;=\u0026thinsp;2.16, df\u0026thinsp;=\u0026thinsp;67.4, p\u0026thinsp;=\u0026thinsp;0.035 \u003cstrong\u003esee\u003c/strong\u003e Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eB \u003cstrong\u003eand Supplementary Table\u0026nbsp;5\u003c/strong\u003e), however \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{{\\Delta }\\mathbf{C}\\mathbf{o}\\mathbf{P} \\mathbf{*}\\mathbf{G}\\mathbf{F}}{\\mathbf{E}\\mathbf{x}\\mathbf{t}\\mathbf{e}\\mathbf{r}\\mathbf{n}\\mathbf{a}\\mathbf{l} \\mathbf{T}\\mathbf{o}\\mathbf{r}\\mathbf{q}\\mathbf{u}\\mathbf{e}}\\)\u003c/span\u003e\u003c/span\u003e was not increased for the ispilesional CoM side and we found no differences of the torque produced by differential load forces (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{{\\Delta }\\mathbf{F}\\mathbf{y}\\mathbf{*}\\mathbf{w}/2}{\\mathbf{E}\\mathbf{x}\\mathbf{t}\\mathbf{e}\\mathbf{r}\\mathbf{n}\\mathbf{a}\\mathbf{l} \\mathbf{T}\\mathbf{o}\\mathbf{r}\\mathbf{q}\\mathbf{u}\\mathbf{e}}\\)\u003c/span\u003e\u003c/span\u003e) at lift off in the SR group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.3.2 No cues, blocked condition, trials after CoM change: Failed transfer of sensorimotor memories to explicit CoM changes.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDespite being explicitly told that the CoM would be changed to the opposing side at the end of each block of eight trials, subjects of all groups subsequently failed to adapt to the new CoM situation and could not inverse the direction of the previously learned Tcom, i.e. transfer sensorimotor memories. This stands in line with previous studies (e.g. (\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e79\u003c/span\u003e)). Tcom was mostly near zero but clearly generated in the wrong, i.e. the previously learned, direction as indicated by a negative ratio of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{\\mathbf{T}\\mathbf{c}\\mathbf{o}\\mathbf{m}}{\\mathbf{E}\\mathbf{x}\\mathbf{t}\\mathbf{e}\\mathbf{r}\\mathbf{n}\\mathbf{a}\\mathbf{l} \\mathbf{T}\\mathbf{o}\\mathbf{r}\\mathbf{q}\\mathbf{u}\\mathbf{e}}\\)\u003c/span\u003e\u003c/span\u003e. We observed no significant Tcom differences between stroke and control groups (\u003cstrong\u003esee\u003c/strong\u003e Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA \u003cstrong\u003eand Supplementary Table\u0026nbsp;9\u003c/strong\u003e). Concerning the torque components, the SL group applied a higher torque by grip force being exerted at different vertical finger positions (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{{\\Delta }\\mathbf{C}\\mathbf{o}\\mathbf{P} \\mathbf{*}\\mathbf{G}\\mathbf{F}}{\\mathbf{E}\\mathbf{x}\\mathbf{t}\\mathbf{e}\\mathbf{r}\\mathbf{n}\\mathbf{a}\\mathbf{l} \\mathbf{T}\\mathbf{o}\\mathbf{r}\\mathbf{q}\\mathbf{u}\\mathbf{e}}\\)\u003c/span\u003e\u003c/span\u003e) than controls when the hidden weight was transferred to the ipsilesional, left side (t = -2.81, df\u0026thinsp;=\u0026thinsp;126.196, p\u0026thinsp;=\u0026thinsp;0.012, \u003cstrong\u003esee\u003c/strong\u003e Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eB \u003cstrong\u003eand Supplementary Table S11\u003c/strong\u003e). Apart from this, there were no further differences between stroke- and control groups (\u003cstrong\u003esee also\u003c/strong\u003e Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eC \u003cstrong\u003eand Supplementary Table S13\u003c/strong\u003e).\u003c/p\u003e\n\u003cdiv class=\"Section2\" id=\"Sec14\"\u003e\n \u003cp\u003e4.3.3 No cues, pseudorandom condition: Torque planning according to sensorimotor memories despite uncertainty\u003c/p\u003e\n \u003cp\u003eIn this condition the position of the hidden weight was either retained or inverted between trials in a pseudorandom fashion. After each trial the hidden weight was removed and placed back either into the same or the opposite position. Although a rational torque planning was not possible in this condition, we observed that all groups planned according to the previous lifts resulting in clearly positive Tcom ratios when the CoM was not inverted (\u003cstrong\u003esee\u003c/strong\u003e Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eA). Remarkably, we did not observe the generation of Tcom of similar magnitudes directed in the wrong direction following CoM inversals. Rather, Tcom was close to zero in trials after a CoM inversion suggesting that participants must have partially corrected the exerted torque already until lift-off. We found two just significant group differences. First, the SL group exerted a Tcom closer to zero when the CoM was switched to the left (t = -2.28, df\u0026thinsp;=\u0026thinsp;236.9, p\u0026thinsp;=\u0026thinsp;0.046, \u003cstrong\u003esee\u003c/strong\u003e Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eA \u003cstrong\u003eand Supplementary Table S15\u003c/strong\u003e). Secondly, the SR group produced a smaller Tcom when the CoM remained on the right (t\u0026thinsp;=\u0026thinsp;2.33, df\u0026thinsp;=\u0026thinsp;246.7, p\u0026thinsp;=\u0026thinsp;0.041).\u003c/p\u003e\n \u003cp\u003eConcerning the torque components, we again found contrasting object-centered spatial biases of the torque anticipation strategies in the SL group when compared with the CL group and this was irrespective of whether the weight position was changed or not: While the torque generated by grip force being exerted at different vertical positions (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{{\\Delta }\\mathbf{C}\\mathbf{o}\\mathbf{P} \\mathbf{*}\\mathbf{G}\\mathbf{F}}{\\mathbf{E}\\mathbf{x}\\mathbf{t}\\mathbf{e}\\mathbf{r}\\mathbf{n}\\mathbf{a}\\mathbf{l} \\mathbf{T}\\mathbf{o}\\mathbf{r}\\mathbf{q}\\mathbf{u}\\mathbf{e}}\\)\u003c/span\u003e\u003c/span\u003e) was less adequate (smaller ratio) when the weight was on the right, i.e. contralesional, side (CoM inverted: t\u0026thinsp;=\u0026thinsp;4.79, df\u0026thinsp;=\u0026thinsp;536.5, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, CoM retained: t\u0026thinsp;=\u0026thinsp;3.72, df\u0026thinsp;=\u0026thinsp;531.4, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cstrong\u003esee\u003c/strong\u003e Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eB \u003cstrong\u003eand Supplementary Table S17\u003c/strong\u003e) but more adequate (higher ratio) than in the CL group when the weight was on the left, i.e. ipsilesional side (CoM inverted: t = -4.22, df\u0026thinsp;=\u0026thinsp;529.0, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, CoM retained: t = -4.28, df\u0026thinsp;=\u0026thinsp;529.0, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Again, the torque generated by differential load forces between sides was biased in the opposite direction, i.e. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{{\\Delta }\\mathbf{F}\\mathbf{y}\\mathbf{*}\\mathbf{w}/2}{\\mathbf{E}\\mathbf{x}\\mathbf{t}\\mathbf{e}\\mathbf{r}\\mathbf{n}\\mathbf{a}\\mathbf{l} \\mathbf{T}\\mathbf{o}\\mathbf{r}\\mathbf{q}\\mathbf{u}\\mathbf{e}}\\)\u003c/span\u003e\u003c/span\u003e was higher in the SL than in the CL group for a CoM on the contralesional, right side (CoM inverted: t = -4.47, df\u0026thinsp;=\u0026thinsp;536.5, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, CoM retained: t = -3.25, df\u0026thinsp;=\u0026thinsp;531.4, p\u0026thinsp;=\u0026thinsp;0.0025, \u003cstrong\u003esee\u003c/strong\u003e Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eC \u003cstrong\u003eand Supplementary Table S19\u003c/strong\u003e) and lower for a CoM on the ipsilesional, left side (CoM inverted: t\u0026thinsp;=\u0026thinsp;2.72, df\u0026thinsp;=\u0026thinsp;528.961, p\u0026thinsp;=\u0026thinsp;0.0136, CoM retained: t\u0026thinsp;=\u0026thinsp;3.35, df\u0026thinsp;=\u0026thinsp;528.961, p\u0026thinsp;=\u0026thinsp;0.0017). No significant differences were detected between the right-hand groups SR and CR.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec15\"\u003e\n \u003cp\u003e4.3.4 Geometric cues: Successful torque anticipation in all experimental conditions\u003c/p\u003e\n \u003cp\u003eIn the geometric cue condition in which the CoM was altered by attaching the handle either on the left or right edge of the base participants of all groups successfully compensated for the arising external torque at lift off both in the blocked as well as in the pseudorandom condition and even in trials following a change of the handle position in the blocked condition. \u003cstrong\u003eSupplementary Figure S4\u003c/strong\u003e depicts the Tcom trajectories of all participants in the geometric-cue conditions. Tcom was mostly generated by GF being produced at different vertical centers of pressure and only to a lesser degree by differential load force sharing. We found no differences of Tcom success between the stroke and control groups in neither the blocked- nor the pseudorandom condition (\u003cstrong\u003esee\u003c/strong\u003e Figs. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e \u003cstrong\u003eand Supplementary Tables S20-36)\u003c/strong\u003e. This lack of group differences was also observed when analyzing the torque components, with the exception of the finding of less successful torque generation by \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{{\\Delta }\\mathbf{C}\\mathbf{o}\\mathbf{P} \\mathbf{*}\\mathbf{G}\\mathbf{F}}{\\mathbf{E}\\mathbf{x}\\mathbf{t}\\mathbf{e}\\mathbf{r}\\mathbf{n}\\mathbf{a}\\mathbf{l} \\mathbf{T}\\mathbf{o}\\mathbf{r}\\mathbf{q}\\mathbf{u}\\mathbf{e}}\\)\u003c/span\u003e\u003c/span\u003e in the SL group than the CL group in the first trials in the blocked condition following a change of the handle to the left, i.e. the CoM to the right side (t\u0026thinsp;=\u0026thinsp;2.60, df\u0026thinsp;=\u0026thinsp;95.9, p\u0026thinsp;=\u0026thinsp;0.021, \u003cstrong\u003esee\u003c/strong\u003e Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eB \u003cstrong\u003eand Supplementary Table S28\u003c/strong\u003e).\u003c/p\u003e\n \u003cp\u003e4.3.5 ∆CoP and GF at lift-off\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec16\"\u003e\n \u003cp\u003eThe total compensatory torque and its components at lift-off were the task-level variables participants had to control to prevent object tilt. While the load force sharing between grasp-sides, ∆Fy, is directly proportional to the resulting torque component as the grip width is constant, both the center of pressures and the GF must be actively controlled to achieve the desired torque product ∆CoP*GF. Therefore, we were interested to evaluate whether the found spatial biases of the torque produced by vertical center of pressure modulation, ∆CoP*GF, can be traced back to distinct alterations in the control of either ∆CoP, GF or both at lift-off. Regarding ∆CoP, we found a non-significant trend toward a better modulation in the SL than the CL group when the weight CoM was on the left side (t\u0026thinsp;=\u0026thinsp;2.1, df\u0026thinsp;=\u0026thinsp;46.0, p\u0026thinsp;=\u0026thinsp;0.083) and a significantly worse modulation when the CoM was on the right side (t\u0026thinsp;=\u0026thinsp;2.38, df\u0026thinsp;=\u0026thinsp;46.0, p\u0026thinsp;=\u0026thinsp;0.043, \u003cstrong\u003esee\u003c/strong\u003e Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003eA). These findings are consistent with the reported results for ∆CoP*GF, although less robust. Apart from that, there were no other significant differences between groups (\u003cstrong\u003esee\u003c/strong\u003e Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e \u003cstrong\u003eand Supplementary Tables\u0026nbsp;37\u0026ndash;44\u003c/strong\u003e). Concerning GF, we did not detect any significant differences between stroke and control groups (\u003cstrong\u003esee\u003c/strong\u003e Fig. \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003e \u003cstrong\u003eand Supplementary Tables\u0026nbsp;45\u0026ndash;52\u003c/strong\u003e).\u003c/p\u003e\n \u003cp\u003e4.3.6 Object-centered spatial bias also affects Tcom in patients with apraxia\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec17\"\u003e\n \u003cp\u003eOur exploratory comparisons between patients with left hemispheric stroke with- and without signs of apraxia (Apr. pos., n\u0026thinsp;=\u0026thinsp;3; Apr. neg., n\u0026thinsp;=\u0026thinsp;10) and controls (CL, n\u0026thinsp;=\u0026thinsp;15) in the blocked conditions suggest that the found object-centered spatial torque bias in the no-cues blocked condition is more pronounced in patients with evidence of apraxia and does not only affect the torque strategy but, in contrast to the SL group as a whole, also the total torque at lift-off, Tcom. Before applying Holm-adjustments for multiple comparisons, we found that Tcom was significantly higher in SL-patients with sign of apraxia than both in CL controls (t = -2.17, df\u0026thinsp;=\u0026thinsp;33.8, p\u0026thinsp;=\u0026thinsp;0.037, p-adjusted\u0026thinsp;=\u0026thinsp;0.112, n.s.) and SL-patients without signs of apraxia (t = -2.05, df\u0026thinsp;=\u0026thinsp;33.8, p\u0026thinsp;=\u0026thinsp;0.049, p-adjusted\u0026thinsp;=\u0026thinsp;0.112, n.s.) when the CoM was on the ipsilesional, left side, whereas Tcom was lower in SL- patients with apraxia than in CL controls when the weight was on the contralesional, right side (t\u0026thinsp;=\u0026thinsp;2.2.5, df\u0026thinsp;=\u0026thinsp;33.8, p\u0026thinsp;=\u0026thinsp;0.031, p-adjusted\u0026thinsp;=\u0026thinsp;0.092, n.s., no significant difference between Apr. neg. and Apr. pos. patients, see Fig. \u003cspan class=\"InternalRef\"\u003e10\u003c/span\u003eA). The opposed spatial bias patterns for the torque components ∆CoP*GF and ∆Fy*w/2 were confirmed (see Fig. \u003cspan class=\"InternalRef\"\u003e10\u003c/span\u003eB \u003cstrong\u003eand C)\u003c/strong\u003e. The three patients with signs of apraxia had no deficits in the visual processing of geometric cues to guide their torque compensation (see \u003cstrong\u003eSupplementary Figure S5\u003c/strong\u003e). Although no significant findings emerged for the variables ∆CoP and GF given the small sample size (see \u003cstrong\u003eSupplementary Figure S6 and S7\u003c/strong\u003e), patients with sign of apraxia seemed to exert a higher GF when the CoM was on the left side both in the no-cues and geometric cues condition (see \u003cstrong\u003eSupplementary Figure S7)\u003c/strong\u003e.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study was set out to investigate whether manual torque control with the ipsilesional hand is impaired in patients in the chronic stage following unilateral stroke when lifting objects. Using a cross-over design with two cue- and two-sequence conditions, we studied both a cue-condition in which learning had to rely on previous sensorimotor memories of recent lifts as well as a visual cue condition in which the object CoM could be inferred from object geometry. Moreover, participants performed trials both in blocked, i.e. predictable, sequence-condition as well as a pseudorandom sequence condition in which the CoM could change after each trial in an unforeseeable manner. Both our main hypotheses that a) ∆CoP modulation was impaired in the SR group and b) deficient load force sharing (∆Fy) in the SL group would lead to impaired torque compensation at lift-off, were not confirmed. Instead, both stroke groups learned to compensate torques at lift-off to overall similar degrees as controls in both cue conditions and patients presented neither general deficits of force-to finger position coordination, nor elevated GF levels, on a group level.\u003c/p\u003e\n\u003cp\u003eInstead, we observed a specific pattern of an object-centered spatial bias of torque components in patients with stroke when having to rely on sensorimotor memories. While torques resulting from force being produced at different vertical finger positions, ∆CoP x GF, were lower when the object CoM was on the contralesional side and higher when the CoM was on the ipsilesional side in patients with left hemispheric stroke, torques generated by differential load forces between sides (∆Fy x w/2) were biased in the opposite direction. While these biases largely cancelled each other out on the group level of SL-patients, the spatial bias of ∆CoP x GF was more pronounced in SL patients with signs of apraxia and translated to overall Tcom. SR patients also applied a distinctly smaller ∆CoP x GF for a CoM on the contralesional, left side but showed neither a clear compensation by ∆Fy x w/2 nor an increase in ∆CoP x GF for a CoM on the ipsilesional side. Torque control was intact in both stroke groups when a geometric cue on the weight distribution was available.\u003c/p\u003e\n\u003cp\u003eWe summarize and discuss our findings in the following sections.\u003c/p\u003e\n\u003cp\u003e5.1 Preserved sensorimotor force-to position coordination despite a spatial bias of ∆CoP x GF following stroke\u003c/p\u003e\n\u003cp\u003eIn line with studies of young and elderly healthy adults (\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e79\u003c/span\u003e), participants in all groups quickly learned to exert an adequate Tcom when the CoM was constant across the trials of a block. At the beginning of a new block they failed to transfer the learned torque planning to the new situation even when they were explicitly told that the CoM would be inverted. They also continued to rely on sensorimotor memories of previous lifts when the CoM could change from trial to trial (\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e54\u003c/span\u003e). Intriguingly, the magnitude of torques directed in the wrong direction when the CoM had unexpectedly changed from one side to the other was smaller than the torque exerted in the right direction when the CoM had stayed the same. This suggests that participants in all groups applied corrective feedback-mechanism to partially correct for erroneous torque anticipation within the short time interval prior to lift-off, although full feedback about object torque only becomes available after lift-off. This finding is consistent with our previous studies in healthy subjects (\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e57\u003c/span\u003e) and the time course and underlying mechanism of these corrections need to be further explored in future analyses. There were no noteworthy differences of Tcom between the stroke and the control groups, despite the emergence of a distinct pattern of differences between the torque components.\u003c/p\u003e\n\u003cp\u003eThe most remarkable finding of this study is that the torque resulting from grip force being produced at different vertical centers of pressure, ∆CoP x GF, and from differential load force sharing between sides, ∆Fy x w/2, were spatially biased in diametrical directions in patients with left hemispheric-stroke when participants had to exclusively rely on sensorimotor memories to guide torque control: Patients with left hemispheric stroke applied a smaller ∆CoPxGF at lift off than controls when the CoM was on the contralesional side but a higher ∆CoPxGF when the CoM was on the ispilesional, i.e. left, side. In contrast, the torque resulting from differential load forces at the handle sides (∆Fy x w/2) was spatially biased in the opposite direction in SL-patients, i.e. ∆Fy x w/2 was higher for a CoM on the right- and lower for a CoM on the left side. As a consequence, the overall Tcom did not significantly differ between left hemispheric stroke patients and controls on the group level.\u003c/p\u003e\n\u003cp\u003ePatients with right hemispheric stroke also exhibited a markedly smaller torque resulting from grip force being produced at different vertical finger positions, ∆CoP x GF, but showed no signs of a compensatory load force distribution (∆Fy x w/2). However, this only translated to a not significant trend towards a lower Tcom. This was not significant after Holm correction as the variability was high and the sample size low. No significant differences or even visually discernible trends were found for Tcom or the torque components when the covert weight was on the ipsilesional right side.\u003c/p\u003e\n\u003cp\u003eAs the center of pressure in the employed three-finger precision grip mostly depended upon the finger positioning when grasping the handle and to a lesser degree on the normal force distribution between the index and middle finger (\u003cspan class=\"CitationRef\"\u003e80\u003c/span\u003e), the torque component ∆CoP x GF arguably better represents explicit context-dependent motor planning in unconstrained grasping; whereas the load force distribution contributing to the total torque (∆Fy x w/2) is modulated as a function of finger-positioning after the formation of the grasp to achieve a targeted total torque (\u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e86\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e88\u003c/span\u003e). Consequently, the observed spatial bias of laod force sharing in left hemispheric stroke patients might represent a compensatory mechanism to counteract the spatial bias of grip force exerted at different vertical positions. This supports the concept of a task-level, i.e. high-level, neural representation of the task goal, namely the compensatory total torque, which is used to orchestrate both the feedforward as well as feedback control of the positions and forces of the low-level effectors, e.g. fingertips (\u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e89\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eHowever, the same pattern of spatial bias was evident in patients with left hemispheric stroke in the pseudorandom, no cues-condition with more successful ∆CoP x GF for a CoM on the left and a less successful ∆CoP x GF for a CoM on the right as well as opposing findings for the torque component ∆Fy x w/2, both for trials in which the CoM was inverted and trials in which the CoM was retained. Therefore, the object-centered spatial torque bias solely depended upon the current side of the CoM but not the CoM of the previous trial on which sensorimotor memories for torque planning are based on. This casts doubt on whether the torque component ∆CoP x GF can really be regarded as measure of exclusively anticipatory planning. Instead, it is more likely that the bias observed in the pseudorandom condition affected the corrections of the torque components ∆CoP x GF and ∆Fy x w/2 just prior to lift-off according to sensory feedback. In this case, it is more justified to speak of a bias of torque control instead of torque anticipation, which implies exclusive feedforward control.\u003c/p\u003e\n\u003cp\u003eIrrespective of the relative contribution of feedforward- and feedback-mechanisms on torque generation at lift off, the opposingly directed object-centered spatial bias for ∆CoP x GF and ∆Fy x w/2 in left hemispheric stroke patients and the isolated bias for ∆CoP x GF in right hemispheric stroke patients corroborates the notion that different neural networks control these task level variables. This notion has previously been based on behavioral studies which could show that finger positioning represents context dependent, explicit, learning, whereas load force distribution is more influenced by effector- and use-dependent, implicit, learning processes (\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e90\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e5.2 Visuomotor processing of geometric cues for torque control is intact in chronic stroke patients\u003c/p\u003e\n\u003cp\u003eWhen the mass distribution could be inferred from the geometric shape of the object (L-Shape) all participant groups successfully compensated for torques arising at lift off mainly by adequately modulating the centers of pressure on both grip sides (∆CoP x GF) both when learning successful manipulation over a course trials with constant object properties but also when object geometry and weight distribution changed randomly. Given a geometric cue, torques by load force partitioning (∆Fy x w/2) only contributed a small part of the total Tcom. Changing the object geometry after a sequence of 8 trials led to an interference of sensorimotor memories of previous lifts on lift planning resulting in a slightly smaller Tcom. The successful processing of geometric cues to guide torques and sensorimotor inference on geometric processing confirm previous studies examining young- and elderly healthy subjects (\u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e80\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eThe compensatory torque and torque components did not differ in the stroke groups suggesting intact visuomotor processing of object shape to infer mass distribution. This stands in line with previous studies which showed that grip force scaling according to object size was not affected by unilateral MCI stroke on a group level (\u003cspan class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e66\u003c/span\u003e). Most notably, we found no evidence of a spatial bias of the torque components ∆CoP x GF or ∆Fy x w/2 in the stroke groups suggesting that these biases following stroke are specific to sensorimotor control and can be corrected by visual control.\u003c/p\u003e\n\u003cp\u003e5.3 Spatial bias of ∆CoP x GF is pronounced in patients with apraxia cannot be fully compensated for by ∆Fy x w/2\u003c/p\u003e\n\u003cp\u003eThree patients with a left-hemispheric stroke showed signs of apraxia in the finger-imitation test. These patients showed a more pronounced spatial bias of the torque components which also translated to the overall torque Tcom, i.e. Tcom was lower than in controls for a CoM on the contralesional, right side, and higher than in controls for a CoM on the ipsilesional, left side. The fact that Tcom was biased in the same directions as ∆CoP x GF, supports the notion that stroke primarily causes a shift of ∆CoP x GF which can only be compensated to a certain degree by a diametrical shift of ∆Fy x w/2, and not vice versa.\u003c/p\u003e\n\u003cp\u003eDue to the small sample size and the lack of brain imaging data from our patients, we cannot infer whether damages to cortical regions specific to apraxia are related to a stronger spatial bias. Possibly, larger cortical lesion volumes in patients with signs of apraxia might account for the pronounced bias, especially since also patients with solely subcortical stroke lesions were included as SL patients without signs of apraxia.\u003c/p\u003e\n\u003cp\u003e5.4 Evidence for an allocentric premotor neglect?\u003c/p\u003e\n\u003cp\u003eThe finding of an object-centric spatial bias of the sensorimotor torque control with a higher than normal ∆CoP x GF for a CoM on the ipsilesional side (only SL group) and a lower ∆CoP x GF for a CoM on the contralesional side (both stroke groups) could be taken as evidence for a shift of spatial attention towards eccentric loads on the ipsilesional side and away from loads on the contralesional side following unilateral stroke. This may represent a novel subtype of allocentric premotor attention bias, i.e. neglect. Concerning the association between neglect and motor control, the phenomenon of premotor neglect (PMN), i.e. an intentional, voluntary, and directional action motor bias concerning objects in the contralesional hemispace, was described for object directed hand movements (for review see: (\u003cspan class=\"CitationRef\"\u003e91\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e92\u003c/span\u003e). Previous studies found that patients with PMN exhibit, inter alia, abnormally slowed initiation and execution of reaching movements towards targets on the contralesional side when using their ispilesional hand (\u003cspan class=\"CitationRef\"\u003e93\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e96\u003c/span\u003e). It is important to note that participants in our study were allowed to adjust the exact position and orientation of the object on the table in a way that allowed for comfortable grasping. Usually, the object was positioned in the hemispace of the involved, ipsilesional hand. Therefore, in contrast to previous studies on premotor neglect the reference frame of torque control in the current study was rather object- or hand specific, i.e. allocentric, than egocentric. To the best of our knowledge, a premotor-allocentric neglect has not yet been reported for an everyday object manipulation task.\u003c/p\u003e\n\u003cp\u003eAs the found bias concerns the control of object tilts due to a directed allocentric eccentric load, studies investigating the perception of the subjective vertical and -horizontal might also be relevant to the interpretation of our findings. These studies revealed that patients with left-sided as well as right-sided neglect systematically tilted the spatial orientation of the subjective vertical- and horizontal in the direction of the neglected, contraversive, side both in a visual and tactile modality- suggesting multisensory spatial orientation deficits in neglect patients (\u003cspan class=\"CitationRef\"\u003e97\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e100\u003c/span\u003e). Applied to our studied task, a shift of the targeted subjective vertical of the object handle towards the contralesional side might have led to the tendency of an under compensation of torques towards the contraversive side and to an over compensation of torques towards the ipsiversive side, as a small tilt to the contralestional side might have been perceived as ideal.\u003c/p\u003e\n\u003cp\u003eHowever, we found this only to be true for the anticipatory torque component ∆CoP x GF, but not for the torque resulting from asymmetric load force sharing (∆Fy x w/2). Moreover, we only found evidence for a bidirectional spatial bias in patients with left hemispheric stroke while patients with right hemispheric stroke only showed a decreased ∆CoP x GF for a CoM on the contralesional side but no ∆CoP x GF elevation when the CoM was on the ipsilesional side.\u003c/p\u003e\n\u003cp\u003eNone of the chronic stroke patients exhibited clear signs of perceptual hemispatial neglect in the conducted pen-and-paper based tests. As we did not expect to find an object centered bias of torque control we unfortunately did not test for the presence of an allocentric neglect.\u003c/p\u003e\n\u003cp\u003eNevertheless, our finding could be viewed a subtle form of an object centered premotor attention bias regarding torques. However, this inattention might not be of relevance in daily living in the majority of stroke patients as both intact load-force coordination and visuomotor processing of object geometry can compensate for the bias.\u003c/p\u003e\n\u003cp\u003e5.5 Neural correlates of torque control in object manipulation\u003c/p\u003e\n\u003cp\u003eOnly recently, TMS and neuroimaging studies have begun to explore the neural mechanism of the coordination finger-positions and forces in unconstrained grasping, whereas previous studies had focused on the correlates of force control when digit positions were predetermined.\u003c/p\u003e\n\u003cp\u003eA recent TMS revealed that virtual lesions of the contralateral primary motor cortex (M1) inhibit the planning of digit positions as well as the covariation of the load force distribution, whereas virtual lesions of the primary sensory cortex (S1) only reduced the asymmetric load force sharing but not the retrieval of learned finger positions (\u003cspan class=\"CitationRef\"\u003e101\u003c/span\u003e). Consequently, contralateral M1 is probably directly involved in using trial-by trial sensory feedback of digit position to adapt forces in unconstrained, natural, grasping, whereas the role of S1 could be the sensing and comparison of expected and actual finger placement to allow for control of load forces in collaboration with M1 (\u003cspan class=\"CitationRef\"\u003e101\u003c/span\u003e). In an fMRI study a widespread network comprising the cerebellum, BA44 and PMv was found to be differently activated when participants were allowed to freely choose their finger positioning instead of having to place them on predefined positions (\u003cspan class=\"CitationRef\"\u003e102\u003c/span\u003e). The same research group (\u003cspan class=\"CitationRef\"\u003e103\u003c/span\u003e) also reported that a set of regions (PMv AIPn SPL7, somatosensory PSC, ventral LOC and cerebellum) are involved in finger-positioning and force control when lifting an object with an off centered center of mass, although at different time points.\u003c/p\u003e\n\u003cp\u003eRecent studies using Bayesian variational representational similarity analyses of deconvolution-modeled fMRI data showed that planning the lift of objects with an asymmetric weight distribution in the absence of congruent visual cues led to an early emergence of CoM-specific pattern distances, most distinctly in ventral visual stream regions as well as in cerebellar and selected dorsal stream regions (\u003cspan class=\"CitationRef\"\u003e104\u003c/span\u003e). A follow up study suggested that there might be only minor differences in the way that the brain encodes anticipatory control of load force sharing between the presence and absence of salient visual shape cues with early ventral stream input being of particular importance for lift force planning in more uncertain situations in the absence of congruent visual cues (\u003cspan class=\"CitationRef\"\u003e105\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e5.6 Study limitations\u003c/p\u003e\n\u003cp\u003eFinally, a number of limitations of this study must be considered. The main limitation is that the studied stroke groups were small and heterogenous regarding stroke type, localization, the time from stroke onset and the stroke related functional impairments. As only chronic stroke patients referred by outpatient therapists participated in this study we could only obtain the medical reports but failed to collect the CT or MRI imaging studies. Therefore, we cannot make claims on the role of specific neuroanatomical regions or networks in the studied tasks. Since our study is confined to highly chronic stroke patients, we cannot exclude that the pattern of torque control deficits differs in earlier phases of stroke. Moreover, we did not perform a comprehensive neurological exam. Since only few of the chronic stroke patients of the sample revealed clear signs of apraxia we were only able to make a first tentative inference about the possible role of apraxia in torque control of our task. As we did not expect to find the object centered spatial bias of torque control a priori, we did not perform tests of allocentric neglect. Moreover, as no patient had convincing signs of chronic neglect, we could not further examine the impact of neglect on torque control. Finally, it must be noted that we conducted numerous statistical tests of the primary and secondary variables of interest and experimental conditions rendering the analyses exploratory.\u003c/p\u003e\n\u003cp\u003eHowever, despite the small samples size, patient heterogeneity and an exploratory statistical analysis plan a clear pattern of highly significant results emerged which reveal a novel aspect of impaired motor control of the ipsilesional hand following stroke and will guide the design of future studies on object manipulation following stroke.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, we found that patients with left-hemispheric stroke show a spatial bias of the torque resulting from grip force being applied at different vertical finger position depending on the mass object mass distribution when relying on sensorimotor memories with the torque component being increased for a CoM on the ipsilesional but decreased for a CoM on the contralesional side. This bias was compensated for by a load-force sharing biased in the opposite direction as evidence of intact force-to-position coordination. The found bias was more severe and could not be fully compensated in patients with apraxia, resulting in a biased overall torque compensation to the disadvantage of the contralesional side. While patients with right hemispheric stroke also exhibited lower torques due to grip force being applied at different vertical finger position for a CoM on the contralesional side, we found no evidence for an increase of this torque component for a CoM on the ipsilesional side or a compensatory bias of load force distributions. When salient, congruent geometric cues were present, patient performance was not different from controls, suggesting that visuomotor processing ameliorates the noted sensorimotor bias. The sensorimotor object-centered spatial bias of torque strategies could be a subtle sign of a premotor attention bias, respectively a premotor attention bias as a subtype of neglect, which might be even present in the absence of a an evident hemispatial neglect. The found object centered spatial bias of torque controls should be further investigated in patients in the acute stage of stroke.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003e7.1 Ethics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eThe experimental procedures were approved by the Institutional Review Board of the School of Medicine at the Technical University of Munich and were in accordance with the Declaration of Helsinki. All subjects gave informed consent to participate in the study.\u003c/p\u003e\n\u003ch2\u003e7.2 Consent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003ch2\u003e7.3 Availability of data and materials\u003c/h2\u003e\n\u003cp\u003eThe data that support the findings of this study are openly available in \u0026ldquo;figshare\u0026rdquo; at 10.6084/m9.figshare.17057675.\u003c/p\u003e\n\u003ch2\u003e7.4 Competing interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003ch2\u003e7.5 Funding\u003c/h2\u003e\n\u003cp\u003eThe authors received no targeted funding.\u003c/p\u003e\n\u003ch2\u003e7.6 Authors\u0026apos; contributions\u003c/h2\u003e\n\u003cp\u003eT.S.: Conceptualization, Methodology, Software, Formal analysis, Investigation, Data Curation, Writing \u0026ndash; Original Draft, Visualization; J.H.: Conceptualization, Methodology, Resources, Formal analysis, Writing \u0026ndash; Review \u0026amp; Editing, Supervision, Project administration.\u003c/p\u003e\n\u003ch2\u003e7.7 Acknowledgements\u003c/h2\u003e\n\u003cp\u003eWe thank Manfred Pfaller for support in constructing the grip device, Peter F\u0026ouml;hr, Constantin von Deimling, Patrick Wagner for technical assistance, and Hans-Joachim Koch for help in organizing measurements. Moreover, we thank the therapists Bernd Weiss, Dr. Susanne J\u0026uuml;rgensmeyer, Anne Schellhorn, Barbara Amberg-Haubenreiser, Christine Serio and Beate Jung for help in recruiting the participating stroke patients.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eJ\u0026oslash;rgensen HS, Nakayama H, Raaschou HO, Vive-Larsen J, St\u0026oslash;ier M, Olsen TS. Outcome and time course of recovery in stroke. Part I: Outcome. The Copenhagen Stroke Study. Arch Phys Med Rehabil. 1995;76(5):399\u0026ndash;405.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoby-Brami A, Jarrass\u0026eacute; N, Parry R. Impairment and Compensation in Dexterous Upper-Limb Function After Stroke. From the Direct Consequences of Pyramidal Tract Lesions to Behavioral Involvement of Both Upper-Limbs in Daily Activities. 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Cerebral Cortex Communications. 2020;1(1).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"grasping, sensorimotor learning, visuomotor transformation, torque compensation, stroke, spatial bias","lastPublishedDoi":"10.21203/rs.3.rs-1466052/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1466052/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eWhen lifting objects whose center of mass (CoM) are not centered below the handle one must compensate for arising external torques already at lift-off to avoid object tilt. Previous studies showed that finger force scaling during object lifting may be impaired at both hands following stroke. However, torque control in object manipulation has not yet been studied in patients with stroke.\u003c/p\u003e\u003cp\u003eIn this study, thirteen patients with chronic stage left hemispheric stroke (SL), nine patients with right hemispheric stroke (SR) and hand-matched controls had to grasp and lift an object with the fingertips of their ipsilesional hand at a handle while preventing object tilt. Object CoM and therewith the external torque was varied by either relocating a covert weight or the handle. The compensatory torque at lift-off (Tcom) is the sum of the torque resulting from 1) grip force being produced at different vertical finger positions (∆CoP x GF) and 2) different vertical load forces on both sides of the handle (∆Fy x w/2).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eWhen having to rely on sensorimotor memories, ∆CoP x GF was elevated when the object CoM was on the ipislesional-, but decreased when CoM was on the contralesional side in SL, whereas ∆Fy x w/2 was biased in the opposite direction, resulting in normal Tcom. SR patients applied a smaller ∆CoP x GF when the CoM was on the contralesional side. Torques were not altered when geometric cues were available. The sensorimotor spatial bias of ∆CoP x GF was more pronounced and translated to a bias of overall Tcom in SL patients with signs of apraxia (n = 3). \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eOur findings provide evidence for an object-centered spatial bias of manual sensorimotor torque control with the ipsilesional hand following stroke. While both intact finger force-to-position coordination and visuomotor control may compensate for the spatial sensorimotor bias in most stroke patients, it may result in a hampered manual torque control in patients with apraxia.\u003c/p\u003e","manuscriptTitle":"Object-centered sensorimotor bias of torque control in the chronic stage following stroke","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-04-05 15:19:19","doi":"10.21203/rs.3.rs-1466052/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2022-06-09T09:09:10+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-05-09T04:07:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"3a84c6b2-fa86-496c-b8fe-0801520725c7","date":"2022-05-05T03:15:17+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-04-06T03:54:23+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-04-06T03:46:04+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2022-04-02T13:16:33+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2022-04-02T13:11:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2022-03-18T14:40:58+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"eefd3532-2dc9-4927-b8c9-243d9ab8294a","owner":[],"postedDate":"April 5th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2022-08-18T09:14:21+00:00","versionOfRecord":[],"versionCreatedAt":"2022-04-05 15:19:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1466052","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1466052","identity":"rs-1466052","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}