Brain Response To A Knee Proprioception Task Among Persons With Anterior Cruciate Ligament Reconstruction And Controls

Brain Response To A Knee Proprioception Task Among Persons With Anterior Cruciate Ligament Reconstruction And Controls | 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 Research Article Brain Response To A Knee Proprioception Task Among Persons With Anterior Cruciate Ligament Reconstruction And Controls Andrew Strong, Helena Grip, Carl-Johan Boraxbekk, Jonas Selling, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-955159/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 22 Mar, 2022 Read the published version in Frontiers in Human Neuroscience → Version 1 posted You are reading this latest preprint version Abstract Knee proprioception deficits and neuroplasticity have been indicated following injury to the anterior cruciate ligament (ACL). Evidence is however scarce regarding brain response to knee proprioception tasks and the impact of ACL injury. Twenty-one persons with unilateral ACL reconstruction (mean 23 months post-surgery) of either the right (n = 10) or left (n = 11) knee, as well as 19 controls (CTRL) matched for sex, age, height, weight and current activity level, performed a knee joint position sense (JPS) test during simultaneous functional magnetic resonance imaging (fMRI). Integrated motion capture recorded knee kinematics. Recruited brain regions included somatosensory cortices, prefrontal cortex and insula. Neither brain response nor JPS errors differed between groups, but across groups significant correlations revealed that greater errors were associated with greater ipsilateral response in the anterior cingulate (r = 0.476, P = 0.009), supramarginal gyrus (r = 0.395, P = 0.034) and insula (r = 0.474, P = 0.008). This is the first study to capture brain response using fMRI in relation to quantifiable knee JPS. Activated brain regions have previously been associated with sensorimotor processes, body schema and interoception. Our innovative paradigm can help to guide future research investigating brain response to lower limb proprioception. Neurology Health Policy Anterior Cruciate Ligament Anterior Cruciate Ligament Reconstruction Knee Rehabilitation Position Sense Magnetic Resonance Imaging Neuronal Plasticity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Rupture of the anterior cruciate ligament (ACL) is a common knee injury among athletic populations 1 , with a reported 30% rate of secondary ACL injury up to 15 years post-reconstruction 2 and a four times higher risk for knee osteoarthritis 3 . Evidence further indicates that individuals with ACL reconstruction (ACLR) have lesser bilateral corticospinal excitability than those without injury, which may have a detrimental effect on muscle recovery. 4 The initial trauma and potential surgical reconstruction causes loss of neural elements such as Golgi tendon organ-like receptors 5 . These receptors contribute with afferent information to the central nervous system (CNS) regarding proprioceptive sensations such as movement and position 6 . Of the proprioceptive senses, joint position sense (JPS) is one of the most commonly tested, typically involving the passive or active reproduction of joint angles with occluded vision. Outcomes are based on the difference in degrees between the target and reproduced angles, thus reflecting the kinematic errors. Meta-analyses have found significantly greater knee JPS errors for ACL-injured knees compared to both the contralateral non-injured knees of the same individuals 7 – 9 and to those of asymptomatic persons 8 , 9 . The clinical significance of these findings is however unclear given the small absolute differences of < 1° knee flexion angle. Existing JPS tests have also been criticized for lacking reliability and validity 10 . Therefore, despite the belief that neurosensory information and knee proprioception may be impaired following ACL injury 11 , simply comparing knee JPS errors may be insufficient in detecting intricate alterations to the CNS 12 . Brain response associated with lower limb proprioceptive acuity is unclear. Callaghan and colleagues 13 implemented a single-joint knee JPS task during functional magnetic resonance imaging (fMRI) among asymptomatic controls and found greater blood-oxygen-level-dependent (BOLD) response in the supplementary motor area, ventral tegmental area, primary sensory cortex, cerebellum and precentral gyrus compared to a similar movement without angle reproduction. However, no outcomes of the JPS test were recorded, the sample size was small (n = 8) and the authors recommended a multi-joint movement to better represent normal functional tasks. In the same study, patellar taping, hypothesized to increase proprioceptive input, decreased response in the anterior cingulate and cerebellum. Based on a similar hypothesis, Thijs et al. 14 applied a knee brace and knee sleeve during lower limb multi-joint movements among asymptomatic individuals and found greater response in the frontal lobe and paracentral lobule, and the parietal lobe and superior parietal lobule, respectively. The combined findings of these studies indicate that changes to afferent information at the knee alters brain response during lower limb movements. Injury to the ACL is believed to cause adaptations to the CNS 15 . A recent scoping review of the topic by Neto and colleagues 16 indeed found evidence for greater brain response compared to controls in mainly cortical areas associated with sensory and motor processes. One electroencephalography (EEG) study by Baumeister and colleagues 12 incorporated a test of knee JPS and found greater frontal Theta-power for individuals with ACLR compared to controls. This response was believed to generate from the anterior cingulate cortex due to attentional demands and task complexity. Correlations for both groups additionally showed a reduction of JPS errors over time together with increased activity linked to the cortex and posterior areas (parietal-temporal-occipital). However, EEG is limited in providing exact locations of the electrical sources from scalp recordings 17 . The only studies which used fMRI were those by Kapreli et al. 18 and Grooms et al. 19 who used similar task designs of single-joint knee flexion and extension. Both studies found less cerebellum activation and greater activation of secondary somatosensory areas for their ACL groups compared to their respective control groups, but also some inconsistent results for other regions. Differences between the ACL populations, such as treatment strategy, i.e., with or without reconstruction, and contrasting activity levels may have contributed to the divergent results. Grooms et al. 19 suggested that multi-joint movements would improve the clinical applicability of future investigations. A more recent study thus included repetitive multi-joint heel slide movements and found that individuals with ACLR had greater response in areas associated with visual-spatial cognition and orientation compared with asymptomatic matched controls 20 . It has however been recommended to improve the clinical applicability of such findings by increasing the motor control demands of such tasks by including, e.g., a proprioceptive goal-oriented element such as position matching 19 , 20 . To summarize, brain response to proprioceptive tasks of the lower extremities remains unclear. Injury to the ACL may cause deficits to knee proprioception and related adaptations of the CNS. We have previously developed a supine knee JPS test which can be adapted for use in an fMRI setting 21 . We therefore aimed to investigate the possibility of characterizing brain response using fMRI during simultaneous performance of a novel quantifiable knee JPS test among asymptomatic controls and individuals with unilateral ACLR. The specific research questions were: 1) Does our knee JPS test evoke a different brain response compared to a similar knee flexion movement without an angle reproduction task? 2) Is brain response different in persons with ACLR compared to asymptomatic persons during our knee JPS test? 3) Does brain response correlate to knee JPS test errors captured by kinematics? We hypothesized that our knee JPS test would recruit somatosensory and motor cortices more than during simple knee flexion and that individuals with ACLR would show greater response in such regions compared to asymptomatic persons. We further hypothesized that knee JPS errors would correlate with BOLD response in associated brain regions. Methods Participant Selection For this cross-sectional study, participants were recruited from April 2017 to May 2019 using convenience sampling via orthopedic clinics, sports clubs, advertisements at the local University, social media and via word of mouth. Screening ensured the following eligibility criteria were met: aged 17-35 years, magnetic resonance imaging compliance, current Tegner activity score 22 of at least 4, ability to understand either Swedish or English language, no known previous or ongoing injuries or diseases (other than ACLR and possible concomitant meniscus injury in the previous 5 years) that could affect the CNS or leg movements. Specific criteria for participants of the ACLR group required unilateral hamstring autograft reconstructive surgery performed 6 months to 5 years prior to testing, limited to only one ACL injury and subsequent surgery. All ACLR participants had to be cleared for full return to activity by their physical therapist. Asymptomatic controls were to be right-side dominant (leg preferred to kick a ball) and matched to ACLR participants with regard to sex, age, height, mass and current Tegner activity score. Our study is the first to incorporate this JPS paradigm during fMRI and thus data was not available to perform power calculations to estimate the required sample sizes. Considering previous similar research, one fMRI study comparing a different knee JPS task to a similar movement without a JPS task included eight healthy males 13 . Previous fMRI studies comparing individuals with ACL injury to controls have included groups of either 15 19,20 or 17/18 18 , whereas a previous EEG study incorporating a knee JPS test included groups of 10/12 12 , respectively. Considering that our task design was calculated to result in fewer brain volumes than the aforementioned studies, we estimated that a pooled group of 40 participants would be required to investigate the brain regions recruited by our JPS test and 20 per group to examine potential differences in brain response between the ACLR and asymptomatic groups. The project was approved by the Regional Ethical Review Board in Umeå, Sweden (Dnr. 2015/67-31) and was performed in accordance with the relevant guidelines and regulations stated in the Declaration of Helsinki. All participants provided their written informed consent prior to participation. Procedures Data collection occurred between June 2017 and May 2019. All participants completed the Marx Activity Scale 23 and the Tegner Activity Scale 22 . The following questionnaires were also completed by the ACLR participants: 2000 International Knee Documentation Committee Subjective Knee Form (IKDC) 24 ; Lysholm Scale 25 ; and the Swedish version of the Tampa Scale of Kinesiophobia (TSK) 26 . Participants then performed a supine knee JPS test in the U-motion laboratory at Umeå University, Sweden to familiarize themselves with the task. Approximately one hour later they performed the knee JPS test in an MRI scanner at the Umeå center for Functional Brain Imaging, University Hospital of Umeå, Sweden. Knee joint position sense test protocol A knee JPS test was specifically designed for fMRI compatibility by using a supine position, slow active movements and additional rest blocks. It was considered important that the test reflect those typically applied in the literature whereby target angle memorisation is performed immediately prior to each attempt to reproduce the angle 27 . It was further considered important that only blocks during which proprioception was of most importance were to be assessed to reflect processing of proprioceptive information. This is in contrast to a previous study in which brain imaging analyses were performed without memorisation prior to each reproduction attempt and during movement to a start position for which proprioception was less relevant and represented half of the brain images assessed 13 . Standardized written test instructions were provided to each participant and any questions were answered. A three-camera motion capture system (Oqus MRI Qualisys AB, Gothenburg, Sweden, 120 Hz) provided real-time kinematic data for the lower limbs. Passive retro-reflective spherical markers were affixed with participants in standing on the skin overlying the greater trochanter and lateral epicondyle of each femur using skin-friendly double-sided adhesive tape. The greater trochanter markers were placed on sticks 56 mm in length (wand markers) to improve their visibility. Participants then lay supine with their feet in foot holders of a custom-made low-friction knee flexion/extension board (see Figure 1 ). Elastic bands with hook-and-loop fasteners secured each foot and lower shank to the foot holders to ensure a 90° ankle joint angle. A strap over the torso and cushions in the head coil limited head movement. Wand markers with 46 mm sticks were affixed on the lateral part of each foot holder in line with the lateral malleolus in the sagittal plane. Kinematic data of the knee were based on the three respective markers for each leg in the sagittal plane. To provide an asymmetrical marker set and thus more stable real-time marker tracking, two markers were additionally affixed on the middle distal edge of the right footplate and one on the left footplate of the sliding board. Participants were positioned to allow a maximum knee flexion angle of approximately 100° when reaching an in-built physical stop at the proximal end of the board. For all movements, a constant knee angular velocity of 10°/s was attempted. This was practiced during familiarization using real-time graphical feedback for three trials per leg. If knee angular velocity fluctuated by more than 5°/s for consecutive trials of the MRI protocol, participants were verbally reminded to move slower or faster accordingly. Automated instructions were provided throughout the tests based on knee angle and angular velocity calculated from the real-time kinematic data as further described henceforth. While supine in the Start position (legs fully extended), participants were instructed to flex a specified leg (randomized order) until a stop sign appeared (randomly activated at 35° or 60° knee flexion, but participants told angles were random). Two seconds after stopping, participants were instructed to maintain the position and memorize the knee (target) angle. Eight seconds later, they were instructed to return to the Start position and then five seconds after returning were instructed to reproduce the same angle. Four seconds after stopping, participants were instructed to return to the Start position. This was performed eight times per angle on each leg, resulting in a total of 16 repetitions for the JPS test on each leg. Additionally, knee flexion to the physical stop at ~100° was performed on eight separate occasions per leg, with the timeframe from 0-65° extracted for brain imaging analysis for a Flex condition. The JPS and Flex conditions were pseudorandomized with a maximum two consecutive repetitions of the same condition and a minimum seven seconds between trials. A Rest condition (Start position for 15 seconds) was also included five times at evenly-spaced intervals throughout testing. Thus, the task had a block design, individualized based on kinematic data. We utilized three different experimental conditions: 1) JPS condition - active knee flexion during angle reproduction (start/end at onset/cessation of flexion, respectively), 2) Flex condition - active knee flexion without angle reproduction (start at onset of flexion and end when reaching 65° knee angle), and 3) Rest condition - Start position (start/end at cessation of extension and onset of flexion, respectively). The protocol lasted approximately 40 minutes, resulting in 1240 whole-brain sets. The current fMRI-adapted knee JPS test was also assessed for test-retest reliability in our movement laboratory among a separate group of 15 (9 males) asymptomatic persons (mean ± SD: age 25.0 ± 3.1 years, height 1.78 ± 0.09 m, mass 74.4 ± 11.2 kg) who performed the test on two occasions 7 days apart. Reliability was estimated with Intraclass Correlation Coefficients (ICC) and 95% confidence intervals (CI) based on a mean rating ( k = 10), two-way mixed effects model with absolute agreement and Standard Error of Measurement (SEM), calculated as the mean square error term from the ANOVA, separately for the non-dominant (ICC 3,10 = 0.64 [CI 0.02-0.87], SEM = 0.67°) and dominant leg (ICC 3,10 = 0.78 [CI 0.34-0.93], SEM = 0.86°). Image acquisition A 3T General Electric MR scanner with a 32-channel head coil was used to acquire the MR images. A T1 structural image was first acquired to create a study-specific template using the following parameters: 180 slices; 1 mm thickness; repetition time 8.2 msec; echo time 3.2 msec; flip angle 12°; field of view 25 x 25 cm. The functional gradient-echo-planar imaging sequence was collected with the following scanning parameters: repetition time = 2000 msec, echo time = 30 msec, flip angle = 80°, field of view = 25 x 25 cm. Thirty-seven transaxial slices with a thickness of 3.4 mm (0.5 mm gap) were acquired in an interleaved order. Ten initial dummy scans were collected and discarded prior to analysis. Test instructions were presented on a computer screen, which were seen via a tilted mirror attached to the head coil. The computer parallel port was used to detect the trigger output signal from the MR scanner to synchronize kinematic data with fMRI data in later analyses. Data processing and analysis Motion capture data were exported to Visual3D software (v.5.02.19, C-Motion Inc. Germantown, MD, USA) and filtered with a 6 Hz fourth-order low-pass zero-lag Butterworth filter. Automated scripts set events based on knee angles and knee angular velocities in the sagittal plane. Target and reproduction angles were extracted 2 seconds after cessation of flexion during the respective phases. All events were checked visually by the lead researcher (AS) and adjusted if deemed incorrect. No data were removed from analyses. Data were exported to IBM SPSS Statistics for Windows, version 25 (IBM Corp., Armonk, N.Y., USA) in which all statistical analyses for knee JPS outcome measures, participant characteristics and patient-reported outcomes were performed. SPM12 software (Wellcome Department of Cognitive Neurology, London, UK) run under MATLAB R 2016 b (MathWorks, Inc., Natick, MA) was used for automated batching, pre-processing and data analysis. SPM was used for visualization of statistical maps and MarsBaR 0.44 28 was used to calculate the percentage of BOLD signal change. Data were pre-processed in the following way: slice timing correction (interleaved order, first image set to reference slice), movement correction by unwarping and realigning all subsequent scans to the first image, co-registration of the mean functional image set and the structural T1 image set, segmentation of the co-registered structural image, normalization to a sample-specific template based on white and grey matter segments from the segmented, co-registered, structural image (using DARTEL 29 ) and affine alignment to Montreal Neurological Institute (MNI) standard space and smoothing with an 8-mm FWHM Gaussian kernel. The final voxel size was 2 × 2 × 2 mm. Statistical analyses The ACLR group was subdivided into those with right-side (R-ACLR) and left-side (L-ACLR) reconstruction. Sex distribution between groups was analysed with a Chi-square test. Age and current activity level (Tegner current and Marx activity) between all groups, as well as pre-injury activity level of the ACLR groups to current activity level of CTRL, were analysed with Kruskal-Wallis tests and Dunn-Bonferroni post-hoc tests for significant results. The questionnaires TSK, IKDC and Lysholm Scale were compared between ACLR groups with Mann-Whitney U tests. A One-way analysis of variance (ANOVA) compared body height and mass between all groups, as well as months since reconstruction between ACLR groups. Between-group comparisons for kinematic data and brain response were made between the injured leg of ACLR and the matched leg of CTRL. Knee JPS error was defined in degrees as the absolute difference (absolute error [AE]) between the target and reproduction angles of the knee for each repetition of the JPS test. Mean AE was calculated for each leg by pooling the 40° and 65° angle conditions for each participant. Outliers in the data set were assessed for eligibility at group level, but none were removed due to a lack of evidence to the contrary. Shapiro-Wilk tests of normality and analysis of distribution graphs confirmed non-normally distributed group-level data. Knee JPS data were thus log transformed and were subsequently normally distributed. Independent samples t-tests were used to compare the log transformed knee JPS AE between groups. Significance levels were set a priori (α = 0.05). Brain imaging data for each angle condition were pooled so that each participant contributed with data from 16 JPS trials per leg. The first-order (single-subject) analyses were set up by including the experimental conditions as regressors of interest in the general linear model, convolved with the hemodynamic response function. Six realignment parameters (head rotations and translations) were included as covariates of no interest to account for movement artefacts. The following contrasts were set up for each participant: 1) [ JPS > Rest ] and 2) [ Flex > Rest ]. Second-order (group) analyses were based on flexible factorial models 30 of the [ JPS > Rest ] and [ Flex > Rest ] contrasts from each participant, including participant, group (two levels, R-ACLR or L-ACLR and CTRL), condition (two levels, JPS and Flex ) and the interaction (group × condition) as factors. Separate analyses of the conditions used in the flexible factorial design [ JPS > Rest ] and [ Flex > Rest ] were also performed to investigate activation patterns in comparison to Rest . These analyses are included as supplementary material. The main effect from condition ([ JPS > Rest ] > [ Flex > Rest ]) and the interaction (group × condition) was analysed (family-wise error [FWE] rate corrected, 0.05; voxel limit 15). Brain regions were defined and labelled according to the MNI coordinates, which relate to the peak activity within the cluster, using automated anatomic labelling in SPM 31 . Brain regions that showed significant activation for any of these analyses were further analysed by calculating the percentage of BOLD signal change during the JPS condition (i.e., the original beta values) in the significant region, compared to the overall mean brain activity of the session. The percentage of BOLD change values were exported to SPSS where Spearman’s rho was used to analyse correlations of participant mean values between percentage of BOLD change and JPS errors. Results Of 77 persons with ACL injury and 61 potential controls who expressed an interest in participating, 55 and 14, respectively, were considered ineligible due to either another existing injury, too low physical activity level, left leg dominance for controls, older age, or a combination of those factors. Thus, 22 individuals with ACLR and 47 asymptomatic controls were considered eligible for the study. To ensure matching of characteristics between groups, controls were invited to participate only after a matching ACLR participant had completed testing. One ACLR participant did not complete the fMRI procedure due to claustrophobic feelings in the MRI scanner. Despite completing testing, one asymptomatic control was not included in the analyses due to the presence of a benign arachnoid cyst, unknown prior to participation, which would have confounded brain imaging analyses. Thus, 10 R-ACLR, 11 L-ACLR and 19 CTRL completed testing and were included in the analyses (see Figure 2 for a flow diagram of the recruitment process and Table 1 for group characteristics). Due to a technical issue, one L-ACLR participant completed a shortened protocol of 12, instead of 16, repetitions per leg. Also, due to slow performance of the test, one participant from each group performed one less repetition on both legs. Current activity level of CTRL was significantly lower than pre-injury level of R-ACLR ( P = 0.010). No groups differed significantly with regard to sex, age, height, weight or the remaining patient-report outcome measures. Months since reconstruction did not differ significantly between the ACLR groups. For the knee JPS test, no statistically significant differences in errors were seen between either the left reconstructed/non-dominant leg of L-ACLR (median [Mdn] 5.10° [Q1 4.04°, Q3 6.82°]) and CTRL (Mdn 4.17° [Q1 2.89°, Q3 4.95°]) respectively, or between the right reconstructed/dominant leg of R-ACLR (Mdn 4.89° [Q1 3.54°, Q3 6.85°]) and CTRL (4.55° [Q1 3.64°, Q3 6.56°]) respectively. Table 1 Participant Characteristics of the Study Groups R-ACLR L-ACLR CTRL Participants, n 10 11 19 Age, y, mean (SD) 24.8 (4.2) 28.2 (4.7) 27.1 (4.6) Male:female, n 4:6 4:7 7:12 Months since reconstruction, mean (SD) 20.0 (9.7) 28.5 (18.6) - Body height, m, mean (SD) 1.72 (0.09) 1.73 (0.09) 1.75 (0.08) Body mass, kg, mean (SD) 72.6 (7.8) 72.1 (11.0) 73.1 (9.9) Patient-reported outcome scales, median (IQR) IKDC 2000, % of maximum 77.6 (14.1) 77.0 (15.0) - Lysholm score 86.0 (12.5) 86.0 (5.0) - Marx activity score 12.0 (6.5) 10.0 (7.0) 11.0 (7.0) Tegner pre-injury score 8.5 (1.2) † , ‡ 8.0 (2.0) - Tegner current score 5.5 (2.2) 7.0 (4.0) 6.0 (4.0) TSK score 36.5 (11.5) 33.0 (5.0) - Injury mechanism, non-contact:contact, n 8:2 11:0 - Injury activity, n Soccer 4 2 Downhill skiing 2 4 Martial arts 0 2 Basketball 0 1 Dancing 1 0 Floorball 1 0 Gymnastics 0 1 Rugby 1 0 Snowboard 1 0 Volleyball 0 1 † Significantly greater than R-ACLR Tegner current score ( P = 0.011). ‡ Significantly greater than CTRL Tegner current score ( P = 0.010). Abbreviations: CTRL, asymptomatic control group; IKDC 2000, International Knee Documentation Committee Subjective Knee Form; IQR, interquartile range; L-ACLR, left-side anterior cruciate ligament-reconstructed group; R-ACLR, right-side anterior cruciate ligament-reconstructed group; TSK, Tampa Scale of Kinesiophobia. Brain response during the knee joint position sense test The JPS condition evoked significantly greater BOLD response ( P = 0.05, FWE corrected; voxel limit 15) in seven brain regions for each leg compared to the Flex condition without a JPS task. These included prefrontal regions, the precentral gyrus, cingulate gyri and insula (see Figure 3 , Figure 4 and Table 2 for all significant regions with voxel extent, exact statistics, and MNI coordinates). Table 2 Brain Regions with Significantly Greater BOLD Response During JPS than Flex ([JPS > Rest)] > [Flex > Rest])† Test side Brain regions Voxel # P Z max MNI coordinate X Y Z Left Contra. Inferior Frontal Gyrus 1608 .000 6.15 51 9 30 Contra. Middle Frontal Gyrus 1049 .000 5.33 36 30 33 Contra. Median Cingulate and Paracingulate Gyri 864 .000 5.29 8 29 36 Ipsi. Insula ‡ 330 .001 5.63 -32 24 2 Contra. Temporal Pole: Superior Temporal Gyrus 97 .008 5.17 54 11 -5 Contra. Supramarginal Gyrus 84 .010 4.60 48 -29 38 Ipsi. Superior Frontal Gyrus 43 .018 4.57 -9 29 47 Right Ipsi. Middle Frontal Gyrus 666 .000 5.51 29 33 26 Ipsi. Precentral Gyrus 596 .000 5.76 51 5 20 Contra. Anterior Cingulate and Paracingulate Gyri 152 .005 4.98 -9 33 21 Ipsi. Anterior Cingulate and Paracingulate Gyri ‡ 135 .006 4.67 8 33 26 Ipsi. Insula 61 .015 4.70 35 20 6 Ipsi. Supramarginal Gyrus ‡ 15 .031 4.70 65 -26 42 Ipsi. Precentral Gyrus 15 .031 4.42 47 0 42 † Seven brain regions for each test side showed significantly greater BOLD response during the JPS condition compared with the Flex condition across groups. ‡ Significant correlation between knee JPS AE and BOLD percentage change. For left test side n = 30 (L-ACLR 11 and CTRL 19), right test side n = 29 (R-ACLR 10 and CTRL 19). Test side: the leg that was active during the JPS test; Voxel #: indicates number of activated voxels in this cluster; P : 0.05 family wise error rate corrected (cluster level); Z max: Z-score of the voxel with the highest activity for main effect from condition; MNI: voxel with the highest activity in MNI-space. Abbreviations: Contra. , contralateral; CTRL, asymptomatic control group; Flex , flex condition; Ipsi. , ipsilateral; JPS , joint position sense condition; L-ACLR, left-side anterior cruciate ligament-reconstructed group; MNI, Montreal Neurological Institute; Rest , rest condition; R-ACLR, right-side anterior cruciate ligament-reconstructed group. Between-group comparisons of brain response during the knee joint position sense test No significant between-group differences were found on the corrected level (FWE 0.05). Correlations between brain response and knee joint position sense errors Correlation analyses were performed for the seven regions per test side that were found to have significantly greater BOLD response during the JPS condition compared to the Flex condition (see Table 2 for a list of the regions). When performing the test with the right leg (R-ACL and CTRL, n = 29), significant positive correlations were found between JPS errors and BOLD signal percentage change (i.e., greater JPS AE correlated with greater BOLD response) in the ipsilateral anterior cingulate (r = 0.476, P = 0.009; Figure 5 A) as well as the ipsilateral supramarginal gyrus (r = 0.395, P = 0.034; Figure 5 B). Close to significance was also the ipsilateral middle frontal gyrus (r = 0.364, P = 0.052). For the left leg (L-ACLR and CTRL, n = 30), a significant positive correlation was found for the ipsilateral insula (r = 0.474, P = 0.008; Figure 5 C). Discussion Our hypothesis that our knee JPS test would evoke greater response in somatosensory and motor cortices compared to simple knee flexion was confirmed by observations of greater response during angle reproduction in, for example, the precentral gyrus, middle frontal gyrus, insula and cingulate gyri. Our hypothesis that individuals with ACL reconstruction would show differences in brain response compared to asymptomatic controls was rejected due to a lack of significant differences between groups. Our hypothesis that knee JPS errors would correlate with response in related regions was on the other hand confirmed by associations between greater errors and BOLD response in the insula, anterior cingulate and supramarginal gyrus. Our knee JPS test evoked response in the ipsilateral precentral gyrus for the right test side and cingulate gyri for both test sides. Response in these regions has also been observed among asymptomatic individuals during active knee flexion tasks of JPS 13 and force matching 32 . Response in the right middle frontal gyrus was seen for both test sides and has been previously associated with switching between exogenous and endogenous attention 33 , relevant for our JPS task where the focus of attention changes from external instructions on a screen to internal sensations related to proprioception. Also common for both test sides was recruitment of the ipsilateral insula, previously associated with sensorimotor processes such as active and passive stepping motions 34 . This finding also aligns with the body image and body schema concepts of body representations 35 , in which current understandings attribute the insula with conscious perceptual representation of the body and memory 36 . The insula and anterior cingulate are further thought to play a key role in interoception, a term originally introduced by Sherrington 37 to describe visceral sensations, but now often used as a broader term encompassing the subjective experience of the body state 38 and even proprioception 10 . In fact damage to the insula due to stroke has been associated with poor position sense of the upper limbs 39 . The same study also found similar associations for the inferior frontal and superior temporal gyri, two areas that were activated during our JPS test in the current study. Thus, our findings add to previous evidence of neural networks involved in proprioceptive tasks and expand these to those associated with the lower limbs. There were no significant between-group differences for brain response nor for knee JPS errors. Previous research investigating knee JPS and somatosensory evoked potentials of individuals 18 months after surgical reconstruction of the ACL also found a lack of difference compared with controls as evidence of sensory neurone regeneration 40 . The original version of the current supine knee JPS test also did not detect any significant differences in errors for a separate ACLR group approximately two years after surgical reconstruction compared with matched athletes 21 . In that study, less-active controls instead showed significantly greater JPS errors compared to the ACLR group, suggesting that activity level is a more important factor in this context. It is therefore possible that deficits in proprioception were not present among the individuals of our ACLR group, who were active and participated on average 23 months after surgical reconstruction. Additionally, a recent meta-analysis found that only knee JPS tests with passive rather than active movements differentiate between ACL-injured knees and those of asymptomatic controls 9 . The active movements of the current test, which also incorporated the hip, may further have contributed to the lack of between-group difference seen here. The target angles of 40° and 65° knee flexion used in our JPS test both lie close to the mid-range of motion for the joint. These angles may not have been optimal for elucidating differences between groups where joint receptors are the focus of investigation, given that they are believed to play a more predominant role towards the limits of joint rotation 41 . It is also possible that small group sizes (due to separating ACLR into right and left leg analyses), as well as the contrast to such a similar movement, may have reduced the sensitivity of our analysis. Our results showed that greater knee JPS errors, i.e., poorer knee proprioceptive acuity, was associated with greater brain response in the ipsilateral insula for the left test side, as well as the ipsilateral anterior, paracingulate and supramarginal gyri for the right test side. These results are line with the Embodied Predictive Interoception Coding (EPIC) model proposed by Barrett and Simons 42 , which describes the process of active inference in interoception. Part of this model describes the role of the mid- and posterior insula in computing and transmitting prediction errors as well as the integration of other agranular visceromotor cortices such as the cingulate cortex in this process. This model may thus be relevant for proprioceptive tasks. The importance of the insula to position sense is further supported by findings previously mentioned here for the upper limbs following stroke, whereby lesions in this region were associated with greater errors when attempting to actively move the unaffected arm to the mirror-matched position of the passively moved contralateral arm 39 . Associated response for the right supramarginal gyrus is supported by previous findings of greater response during a proprioceptive task of force matching at the knee among asymptomatic females 32 . A limitation of our study was the additional task of attempting a constant knee angular velocity, although this was similar for the contrast Flex condition. Further, the active movement of the whole lower limb meant that proprioceptive feedback was not isolated to the knee, but also incorporated the hip. Although this is more similar to everyday activities and thus may enhances the ecological validity of the task compared with a single-joint movement, compensations at the hip joint for potential deficits at the knee are possible. Despite the active task, head movement (range 0.14 - 0.88 mm) did not confound brain imaging analyses. Due to challenges in recruiting participants, we included ACLR individuals who had injured either knee, but a control group with only right-side dominance. Future studies with a greater number of and more homogenous participants are likely required to further elucidate potential group differences. Comparisons were thus made to the non-dominant and dominant legs of CTRL for the L-ACLR and R-ACLR groups respectively. Additionally, both sexes were represented in each of our groups. Two similar fMRI studies have however indicated potentially different functional brain connectivity between males 43 and females 44 who later suffered an ACL injury. Our eligibility criteria required a minimum physical activity level score of four according to the Tegner activity scale. Although we matched current activity level between groups, a sub-analysis using Wilcoxon Signed Ranks tests compared pre-injury and current activity levels within the ACLR groups and found that R-ACLR had significantly reduced their activity level ( P = 0.011), but the level was not significantly changed among L-ACLR. A difference in activity level change from pre- to post-injury was thus a potentially confounding factor in our analyses. To explore this further, a Mann-Whitney U test to compare change in activity level between the groups found no significant between-group difference. A significant reduction in activity level following ACL injury is however considered a useful outcome for defining non-copers 45 . Future studies may thus benefit from analyses that consider coping classification of individuals with ACL injury. In summary, our paradigm found greater BOLD response for a number of brain regions which have previously been associated with processes that can be linked to proprioception. These results thus indicate that the experimental design was successful in recruiting brain regions involved in proprioception. The lack of differences between groups is perhaps not surprising given mixed evidence of proprioceptive deficits among individuals nearly two years post-ACLR. The small sample sizes as a result of splitting the ACLR group into left and right-side injuries may however have been a contributing factor to the lack of significance. The significant correlations between knee JPS error and activation in some brain regions further indicates that demands were placed on the proprioceptive acuity of the participants. The novel integration of kinematics with fMRI thus provided added value to the paradigm by providing behavioural data as well as specific time frames for extraction of brain images to isolate such processes. This is pioneering work that has attempted to capture brain response to a lower limb proprioception task using fMRI and simultaneous kinematics to quantify knee JPS. The identification of brain regions associated with lower limb proprioception tasks, such as knee JPS, provides new and valuable information regarding central processing of such tasks. Our unique paradigm demonstrates a method to expand these findings and provide further insights into brain response to proprioception at the knee and other joints as well as among different populations. Declarations Data availability The datasets generated during and/or analysed during the current study are available from the corresponding author upon reasonable request. Acknowledgements We acknowledge the Umeå center for Functional Brain Imaging (UFBI) for collaboration and assistance, Dr. Ashokan Arumugam and PhD student Adam Grinberg for assistance during data collection, and all of the study participants. The study was funded by the Swedish Scientific Research Council (Grant No. 2017-00892), Region Västerbotten (Grant No. ALF VLL548501, VLL838421 and Strategic funding VLL-358901; Project No. 7002795), the Swedish Scientific Research Council for Sports Science (Grant No. Dnr CIF P2018-0104; P2019-0068), Umeå University School of Sport Science (Grant No. Dnr IH 5.3-13-2017). King Gustaf V and Queen Victoria’s Masonic Foundation, and the Kempe foundation. The funders did not have any role in the study design or outcomes. Author contributions CH obtained the funding for the study. All authors were involved in the design of the paradigm. JS built the sliding board for the task and developed the real-time software. AS and CH recruited the participants. AS and JS performed the data collection. AS processed the motion capture files and performed statistics on the kinematic data. AS and HG processed the brain images. HG and CJB performed statistical analyses of the brain imaging data. AS wrote the first draft of the manuscript. AS prepared figures 1, 2 and 5. AS, HG and JS prepared figures 3 and 4. All authors reviewed subsequent drafts of the manuscript. Competing interests The authors declare no competing interests. References Majewski, M., Susanne, H. & Klaus, S. Epidemiology of athletic knee injuries: A 10-year study. Knee , 13 , 184–188 https://doi.org/10.1016/j.knee.2006.01.005 (2006). Leys, T., Salmon, L., Waller, A., Linklater, J. & Pinczewski, L. Clinical results and risk factors for reinjury 15 years after anterior cruciate ligament reconstruction: a prospective study of hamstring and patellar tendon grafts. Am. J. Sports Med , 40 , 595–605 https://doi.org/10.1177/0363546511430375 (2012). Poulsen, E. et al. 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Central Nervous System Adaptation After Ligamentous Injury: a Summary of Theories, Evidence, and Clinical Interpretation. Sports Med , 47 , 1271–1288 https://doi.org/10.1007/s40279-016-0666-y (2017). Neto, T., Sayer, T., Theisen, D. & Mierau, A. Functional Brain Plasticity Associated with ACL Injury: A Scoping Review of Current Evidence. Neural Plast. 2019, 3480512, doi: 10.1155/2019/3480512 (2019). Ritter, P. & Villringer, A. Simultaneous EEG–fMRI. Neurosci. Biobehav. Rev , 30 , 823–838 https://doi.org/10.1016/j.neubiorev.2006.06.008 (2006). Kapreli, E. et al. Anterior cruciate ligament deficiency causes brain plasticity: a functional MRI study. Am. J. Sports Med , 37 , 2419–2426 https://doi.org/10.1177/0363546509343201 (2009). Grooms, D. R. et al. Neuroplasticity associated with anterior cruciate ligament reconstruction. J. Orthop. Sports Phys. Ther , 47 , 180–189 https://doi.org/10.2519/jospt.2017.7003 (2017). Criss, C. R., Onate, J. A. & Grooms, D. R. 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Sports Med , 29 , 600–613 https://doi.org/10.1177/03635465010290051301 (2001). Lysholm, J. & Gillquist, J. Evaluation of knee ligament surgery results with special emphasis on use of a scoring scale. The American Journal of Sports Medicine , 10 , 150–154 https://doi.org/10.1177/036354658201000306 (1982). Lundberg, M. K. E., Styf, J. & Carlsson, S. G. A psychometric evaluation of the Tampa Scale for Kinesiophobia — from a physiotherapeutic perspective. Physiother. Theory Pract , 20 , 121–133 https://doi.org/10.1080/09593980490453002 (2004). Han, J., Waddington, G., Adams, R., Anson, J. & Liu, Y. Assessing proprioception: A critical review of methods. J Sport Health Sci , 5 , 80–90 https://doi.org/10.1016/j.jshs.2014.10.004 (2016). Brett, M., Anton, J. L., Valabregue, R., Poline, J. B. & Modeling & analysis. Neuroimage 16 , 769-1198, doi: 10.1016/s1053-8119(02)90013-3 (2002). Ashburner, J. A fast diffeomorphic image registration algorithm., 38 , 95–113 https://doi.org/10.1016/j.neuroimage.2007.07.007 (2007). Gläscher, J. & Gitelman, D. Contrast weights in flexible factorial design with multiple groups of subjects. SPM@ JISCMAIL. AC. UK) Sml, editor ,1–12(2008). Tzourio-Mazoyer, N. et al. Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain., 15 , 273–289 https://doi.org/10.1006/nimg.2001.0978 (2002). Grooms, D. R., Criss, C. R., Simon, J. E., Haggerty, A. L. & Wohl, T. R. Neural Correlates of Knee Extension and Flexion Force Control: A Kinetically-Instrumented Neuroimaging Study. Front. Hum. Neurosci , 14 , https://doi.org/10.3389/fnhum.2020.622637 (2021). Japee, S., Holiday, K., Satyshur, M. D., Mukai, I. & Ungerleider, L. G. A role of right middle frontal gyrus in reorienting of attention: a case study. Front. Syst. Neurosci , 9 , https://doi.org/10.3389/fnsys.2015.00023 (2015). Jaeger, L. et al. Brain activation associated with active and passive lower limb stepping. Front. Hum. Neurosci , 8 , 828 https://doi.org/10.3389/fnhum.2014.00828 (2014). Head, H. & Holmes, G. Sensory Disturbances from Cerebral Lesions., 34 , 102–254 https://doi.org/10.1093/brain/34.2-3.102 (1911). Dijkerman, H. C. & de Haan, E. H. Somatosensory processes subserving perception and action. Behav. Brain Sci. 30 , 189-201; discussion 201-139, doi: 10.1017/s0140525x07001392 (2007). Sherrington, C. S. The integrative action of the nervous system (Yale University Press, 1906). Ceunen, E., Vlaeyen, J. W. S. & Van Diest, I. On the Origin of Interoception. Front. Psychol , 7 , 743–743 https://doi.org/10.3389/fpsyg.2016.00743 (2016). Findlater, S. E. et al. Central perception of position sense involves a distributed neural network - Evidence from lesion-behavior analyses. Cortex , 79 , 42–56 https://doi.org/10.1016/j.cortex.2016.03.008 (2016). Ochi, M., Iwasa, J., Uchio, Y., Adachi, N. & Sumen, Y. The regeneration of sensory neurones in the reconstruction of the anterior cruciate ligament. J. Bone Joint Surg. Br , 81 , 902–906 https://doi.org/10.1302/0301-620x.81b5.9202 (1999). Proske, U. & Chen, B. Two senses of human limb position: methods of measurement and roles in proprioception. Exp. Brain Res , https://doi.org/10.1007/s00221-021-06207-4 (2021). Barrett, L. F. & Simmons, W. K. Interoceptive predictions in the brain. Nature Reviews Neuroscience , 16 , 419–429 https://doi.org/10.1038/nrn3950 (2015). Diekfuss, J. A. et al. Alterations in knee sensorimotor brain functional connectivity contributes to ACL injury in male high-school football players: a prospective neuroimaging analysis. Braz J Phys Ther , 24 , 415–423 https://doi.org/10.1016/j.bjpt.2019.07.004 (2020). Diekfuss, J. A. et al. Does brain functional connectivity contribute to musculoskeletal injury? A preliminary prospective analysis of a neural biomarker of ACL injury risk. J Sci Med Sport , 22 , 169–174 https://doi.org/10.1016/j.jsams.2018.07.004 (2019). Button, K., van Deursen, R. & Price, P. Classification of functional recovery of anterior cruciate ligament copers, non-copers, and adapters. Br. J. Sports Med. 40 , 853-859; discussion 859, doi: 10.1136/bjsm.2006.028258 (2006). Additional Declarations No competing interests reported. Supplementary Files Supplementaryinformation.docx Cite Share Download PDF Status: Published Journal Publication published 22 Mar, 2022 Read the published version in Frontiers in Human Neuroscience → Version 1 posted 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. 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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-955159","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":55919663,"identity":"f4158152-11db-4709-b4a6-773e829e1887","order_by":0,"name":"Andrew Strong","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIiWNgGAWjYHACAyR2BSlaeMDkGZK1MLYRoZ5/dvO2Dx/bGOztpQ8fe/h13uFogwPsDx/g0yJx51jxzJltDIk9fGnpxrLbDuduOMBjbIBPC8ONHGNm3m0MCTw8PGbSkhAtbBL4dMiDtPzdxmAP0TIHpIX9+Q98WgxAWhi3MTD2ALVIfmwAaWEww+suwxtpxYy9/yQSe86wpUkzHEvPnXmYxxivw+RuJG9m+HHGxp69h/mY5I8a69y+4+0PP+C1BgIgxjKDI4eZCPVwwIjX26NgFIyCUTBiAQDsS0YtVTZPagAAAABJRU5ErkJggg==","orcid":"","institution":"Umeå University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Andrew","middleName":"","lastName":"Strong","suffix":""},{"id":55919664,"identity":"8176cfbe-d76a-42f7-abff-d205f5f4be31","order_by":1,"name":"Helena Grip","email":"","orcid":"","institution":"Umeå University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Helena","middleName":"","lastName":"Grip","suffix":""},{"id":55919665,"identity":"21ea3e84-5f52-4c80-83f0-2753c5b0a34d","order_by":2,"name":"Carl-Johan Boraxbekk","email":"","orcid":"","institution":"Umeå University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Carl-Johan","middleName":"","lastName":"Boraxbekk","suffix":""},{"id":55919666,"identity":"b4499a8c-e3f7-4e41-b15c-b603030c694e","order_by":3,"name":"Jonas Selling","email":"","orcid":"","institution":"Umeå University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jonas","middleName":"","lastName":"Selling","suffix":""},{"id":55919667,"identity":"f3ee6218-e0c0-44ce-a735-bc6eab6a017c","order_by":4,"name":"Charlotte K. Häger","email":"","orcid":"","institution":"Umeå University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Charlotte","middleName":"K.","lastName":"Häger","suffix":""}],"badges":[],"createdAt":"2021-10-04 10:29:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-955159/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-955159/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.3389/fnhum.2022.841874","type":"published","date":"2022-03-22T17:25:15+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":14422358,"identity":"c8b8e856-2e5d-4373-b0be-12027bd4af70","added_by":"auto","created_at":"2021-10-11 18:30:16","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":199679,"visible":true,"origin":"","legend":"An illustration of the experimental setup. The individual is performing with their right leg A) one repetition of the JPS test with a target angle of 65°, and B) one repetition of the Flex condition. Example instructions shown at the top were displayed on a screen at the rear of the scanner visible to the participant via a tilted mirror attached to the head coil. BOLD response was measured during the highlighted “JPS” (from Start position to reproduction angle) and “Flex” (from Start position to 65° knee flexion) blocks, respectively, as well as for a “Rest” block (Start position for 15 seconds). Abbreviations: TA, target angle.","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-955159/v1/6ddc9aef45c3bee08f2f066d.png"},{"id":14422452,"identity":"42ccb50d-13d4-4955-b4e8-66f2cae0e018","added_by":"auto","created_at":"2021-10-11 18:33:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":78635,"visible":true,"origin":"","legend":"Flow diagram illustrating the recruitment process.","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-955159/v1/3769e09c81a40b485e168785.png"},{"id":14422360,"identity":"f65a0261-b136-48c0-ab22-cda1cf1714f0","added_by":"auto","created_at":"2021-10-11 18:30:16","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":675103,"visible":true,"origin":"","legend":"Brain regions with significant main effect condition in [JPS \u003e Rest] \u003e [Flex \u003e Rest], P = 0.05, family-wise corrected, voxel limit 15. Slices -5:2:38 mm (MNI) in inferior-superior direction are shown. Group mean brains (Dartel) are used for the illustration for A) Left-side analyses - L-ACLR moving their injured left leg and CTRL moving their left non-dominant leg, and B) Right-side analyses - R-ACLR moving their right injured leg and CTRL moving their right non-dominant leg.","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-955159/v1/4a9555c6c86f8ec257f6861d.png"},{"id":14422362,"identity":"fc117520-bd67-458a-8be7-31ec7ef2192e","added_by":"auto","created_at":"2021-10-11 18:30:16","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":207082,"visible":true,"origin":"","legend":"BOLD signal change (%) during angle reproduction of the JPS test for the brain regions with a significant main effect from condition ([JPS \u003e Rest] \u003e [Flex \u003e Rest]). Abbreviations: Ant., Anterior; Contra., contralateral; CTRL, asymptomatic control group; Flex, flex condition; Ipsi., ipsilateral; JPS, joint position sense condition; L-ACLR, left side anterior cruciate ligament-reconstructed group; R-ACL, right-side anterior cruciate ligament-reconstructed group; Temp., Temporal.","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-955159/v1/66ce205036e80e1d0738f566.png"},{"id":14422453,"identity":"b20870fa-300b-4fba-8f6a-f80ea1de1af9","added_by":"auto","created_at":"2021-10-11 18:33:16","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":78979,"visible":true,"origin":"","legend":"Scatter plots illustrating the significant correlations between mean knee joint position sense absolute errors and simultaneous percentage change in BOLD response for the right test side (A and B) and the left test side (C).","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-955159/v1/fdb3a46017a1ee2d1698011c.png"},{"id":19660851,"identity":"d5652e2e-3fab-461a-8c3f-ee4c1674c6ba","added_by":"auto","created_at":"2022-03-27 17:25:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1609032,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-955159/v1/c42e0e3d-b6f0-4ba7-a637-c12d5a4b4297.pdf"},{"id":14422363,"identity":"f6221233-55df-4acb-a844-b81e15f5e07b","added_by":"auto","created_at":"2021-10-11 18:30:17","extension":"docx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":649347,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryinformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-955159/v1/a96ec7b96dcc1f8ad2f5fdc0.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eBrain Response To A Knee Proprioception Task Among Persons With Anterior Cruciate Ligament Reconstruction And Controls\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRupture of the anterior cruciate ligament (ACL) is a common knee injury among athletic populations\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e, with a reported 30% rate of secondary ACL injury up to 15 years post-reconstruction\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e and a four times higher risk for knee osteoarthritis\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Evidence further indicates that individuals with ACL reconstruction (ACLR) have lesser bilateral corticospinal excitability than those without injury, which may have a detrimental effect on muscle recovery.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e The initial trauma and potential surgical reconstruction causes loss of neural elements such as Golgi tendon organ-like receptors\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. These receptors contribute with afferent information to the central nervous system (CNS) regarding proprioceptive sensations such as movement and position\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Of the proprioceptive senses, joint position sense (JPS) is one of the most commonly tested, typically involving the passive or active reproduction of joint angles with occluded vision. Outcomes are based on the difference in degrees between the target and reproduced angles, thus reflecting the kinematic errors. Meta-analyses have found significantly greater knee JPS errors for ACL-injured knees compared to both the contralateral non-injured knees of the same individuals\u003csup\u003e\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e and to those of asymptomatic persons\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. The clinical significance of these findings is however unclear given the small absolute differences of \u0026lt; 1\u0026deg; knee flexion angle. Existing JPS tests have also been criticized for lacking reliability and validity\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Therefore, despite the belief that neurosensory information and knee proprioception may be impaired following ACL injury\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, simply comparing knee JPS errors may be insufficient in detecting intricate alterations to the CNS\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBrain response associated with lower limb proprioceptive acuity is unclear. Callaghan and colleagues\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e implemented a single-joint knee JPS task during functional magnetic resonance imaging (fMRI) among asymptomatic controls and found greater blood-oxygen-level-dependent (BOLD) response in the supplementary motor area, ventral tegmental area, primary sensory cortex, cerebellum and precentral gyrus compared to a similar movement without angle reproduction. However, no outcomes of the JPS test were recorded, the sample size was small (n = 8) and the authors recommended a multi-joint movement to better represent normal functional tasks. In the same study, patellar taping, hypothesized to increase proprioceptive input, decreased response in the anterior cingulate and cerebellum. Based on a similar hypothesis, Thijs et al.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e applied a knee brace and knee sleeve during lower limb multi-joint movements among asymptomatic individuals and found greater response in the frontal lobe and paracentral lobule, and the parietal lobe and superior parietal lobule, respectively. The combined findings of these studies indicate that changes to afferent information at the knee alters brain response during lower limb movements.\u003c/p\u003e \u003cp\u003eInjury to the ACL is believed to cause adaptations to the CNS\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. A recent scoping review of the topic by Neto and colleagues\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e indeed found evidence for greater brain response compared to controls in mainly cortical areas associated with sensory and motor processes. One electroencephalography (EEG) study by Baumeister and colleagues\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e incorporated a test of knee JPS and found greater frontal Theta-power for individuals with ACLR compared to controls. This response was believed to generate from the anterior cingulate cortex due to attentional demands and task complexity. Correlations for both groups additionally showed a reduction of JPS errors over time together with increased activity linked to the cortex and posterior areas (parietal-temporal-occipital). However, EEG is limited in providing exact locations of the electrical sources from scalp recordings\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. The only studies which used fMRI were those by Kapreli et al.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e and Grooms et al.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e who used similar task designs of single-joint knee flexion and extension. Both studies found less cerebellum activation and greater activation of secondary somatosensory areas for their ACL groups compared to their respective control groups, but also some inconsistent results for other regions. Differences between the ACL populations, such as treatment strategy, i.e., with or without reconstruction, and contrasting activity levels may have contributed to the divergent results. Grooms et al.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e suggested that multi-joint movements would improve the clinical applicability of future investigations. A more recent study thus included repetitive multi-joint heel slide movements and found that individuals with ACLR had greater response in areas associated with visual-spatial cognition and orientation compared with asymptomatic matched controls\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. It has however been recommended to improve the clinical applicability of such findings by increasing the motor control demands of such tasks by including, e.g., a proprioceptive goal-oriented element such as position matching\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo summarize, brain response to proprioceptive tasks of the lower extremities remains unclear. Injury to the ACL may cause deficits to knee proprioception and related adaptations of the CNS. We have previously developed a supine knee JPS test which can be adapted for use in an fMRI setting\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. We therefore aimed to investigate the possibility of characterizing brain response using fMRI during simultaneous performance of a novel quantifiable knee JPS test among asymptomatic controls and individuals with unilateral ACLR. The specific research questions were: 1) Does our knee JPS test evoke a different brain response compared to a similar knee flexion movement without an angle reproduction task? 2) Is brain response different in persons with ACLR compared to asymptomatic persons during our knee JPS test? 3) Does brain response correlate to knee JPS test errors captured by kinematics? We hypothesized that our knee JPS test would recruit somatosensory and motor cortices more than during simple knee flexion and that individuals with ACLR would show greater response in such regions compared to asymptomatic persons. We further hypothesized that knee JPS errors would correlate with BOLD response in associated brain regions.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv class=\"Section2\" id=\"Sec3\"\u003e\n \u003ch2\u003eParticipant Selection\u003c/h2\u003e\n \u003cp\u003eFor this cross-sectional study, participants were recruited from April 2017 to May 2019 using convenience sampling via orthopedic clinics, sports clubs, advertisements at the local University, social media and via word of mouth. Screening ensured the following eligibility criteria were met: aged 17-35 years, magnetic resonance imaging compliance, current Tegner activity score\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e of at least 4, ability to understand either Swedish or English language, no known previous or ongoing injuries or diseases (other than ACLR and possible concomitant meniscus injury in the previous 5 years) that could affect the CNS or leg movements. Specific criteria for participants of the ACLR group required unilateral hamstring autograft reconstructive surgery performed 6 months to 5 years prior to testing, limited to only one ACL injury and subsequent surgery. All ACLR participants had to be cleared for full return to activity by their physical therapist. Asymptomatic controls were to be right-side dominant (leg preferred to kick a ball) and matched to ACLR participants with regard to sex, age, height, mass and current Tegner activity score. Our study is the first to incorporate this JPS paradigm during fMRI and thus data was not available to perform power calculations to estimate the required sample sizes. Considering previous similar research, one fMRI study comparing a different knee JPS task to a similar movement without a JPS task included eight healthy males\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Previous fMRI studies comparing individuals with ACL injury to controls have included groups of either 15\u003csup\u003e19,20\u003c/sup\u003e or 17/18\u003csup\u003e18\u003c/sup\u003e, whereas a previous EEG study incorporating a knee JPS test included groups of 10/12\u003csup\u003e12\u003c/sup\u003e, respectively. Considering that our task design was calculated to result in fewer brain volumes than the aforementioned studies, we estimated that a pooled group of 40 participants would be required to investigate the brain regions recruited by our JPS test and 20 per group to examine potential differences in brain response between the ACLR and asymptomatic groups. The project was approved by the Regional Ethical Review Board in Ume\u0026aring;, Sweden (Dnr. 2015/67-31) and was performed in accordance with the relevant guidelines and regulations stated in the Declaration of Helsinki. All participants provided their written informed consent prior to participation.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec4\"\u003e\n \u003ch2\u003eProcedures\u003c/h2\u003e\n \u003cp\u003eData collection occurred between June 2017 and May 2019. All participants completed the Marx Activity Scale\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e and the Tegner Activity Scale\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. The following questionnaires were also completed by the ACLR participants: 2000 International Knee Documentation Committee Subjective Knee Form (IKDC)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e; Lysholm Scale\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e; and the Swedish version of the Tampa Scale of Kinesiophobia (TSK)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Participants then performed a supine knee JPS test in the U-motion laboratory at Ume\u0026aring; University, Sweden to familiarize themselves with the task. Approximately one hour later they performed the knee JPS test in an MRI scanner at the Ume\u0026aring; center for Functional Brain Imaging, University Hospital of Ume\u0026aring;, Sweden.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec5\"\u003e\n \u003ch2\u003eKnee joint position sense test protocol\u003c/h2\u003e\n \u003cp\u003eA knee JPS test was specifically designed for fMRI compatibility by using a supine position, slow active movements and additional rest blocks. It was considered important that the test reflect those typically applied in the literature whereby target angle memorisation is performed immediately prior to each attempt to reproduce the angle\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. It was further considered important that only blocks during which proprioception was of most importance were to be assessed to reflect processing of proprioceptive information. This is in contrast to a previous study in which brain imaging analyses were performed without memorisation prior to each reproduction attempt and during movement to a start position for which proprioception was less relevant and represented half of the brain images assessed\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Standardized written test instructions were provided to each participant and any questions were answered. A three-camera motion capture system (Oqus MRI Qualisys AB, Gothenburg, Sweden, 120 Hz) provided real-time kinematic data for the lower limbs. Passive retro-reflective spherical markers were affixed with participants in standing on the skin overlying the greater trochanter and lateral epicondyle of each femur using skin-friendly double-sided adhesive tape. The greater trochanter markers were placed on sticks 56 mm in length (wand markers) to improve their visibility. Participants then lay supine with their feet in foot holders of a custom-made low-friction knee flexion/extension board (see Figure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Elastic bands with hook-and-loop fasteners secured each foot and lower shank to the foot holders to ensure a 90\u0026deg; ankle joint angle. A strap over the torso and cushions in the head coil limited head movement. Wand markers with 46 mm sticks were affixed on the lateral part of each foot holder in line with the lateral malleolus in the sagittal plane. Kinematic data of the knee were based on the three respective markers for each leg in the sagittal plane. To provide an asymmetrical marker set and thus more stable real-time marker tracking, two markers were additionally affixed on the middle distal edge of the right footplate and one on the left footplate of the sliding board. Participants were positioned to allow a maximum knee flexion angle of approximately 100\u0026deg; when reaching an in-built physical stop at the proximal end of the board. For all movements, a constant knee angular velocity of 10\u0026deg;/s was attempted. This was practiced during familiarization using real-time graphical feedback for three trials per leg. If knee angular velocity fluctuated by more than 5\u0026deg;/s for consecutive trials of the MRI protocol, participants were verbally reminded to move slower or faster accordingly. Automated instructions were provided throughout the tests based on knee angle and angular velocity calculated from the real-time kinematic data as further described henceforth.\u003c/p\u003e\n \u003cp\u003eWhile supine in the Start position (legs fully extended), participants were instructed to flex a specified leg (randomized order) until a stop sign appeared (randomly activated at 35\u0026deg; or 60\u0026deg; knee flexion, but participants told angles were random). Two seconds after stopping, participants were instructed to maintain the position and memorize the knee (target) angle. Eight seconds later, they were instructed to return to the Start position and then five seconds after returning were instructed to reproduce the same angle. Four seconds after stopping, participants were instructed to return to the Start position. This was performed eight times per angle on each leg, resulting in a total of 16 repetitions for the JPS test on each leg. Additionally, knee flexion to the physical stop at ~100\u0026deg; was performed on eight separate occasions per leg, with the timeframe from 0-65\u0026deg; extracted for brain imaging analysis for a \u003cem\u003eFlex\u003c/em\u003e condition. The \u003cem\u003eJPS\u003c/em\u003e and \u003cem\u003eFlex\u003c/em\u003e conditions were pseudorandomized with a maximum two consecutive repetitions of the same condition and a minimum seven seconds between trials. A \u003cem\u003eRest\u003c/em\u003e condition (Start position for 15 seconds) was also included five times at evenly-spaced intervals throughout testing. Thus, the task had a block design, individualized based on kinematic data. We utilized three different experimental conditions: 1) \u003cem\u003eJPS\u003c/em\u003e condition - active knee flexion during angle reproduction (start/end at onset/cessation of flexion, respectively), 2) \u003cem\u003eFlex\u003c/em\u003e condition - active knee flexion without angle reproduction (start at onset of flexion and end when reaching 65\u0026deg; knee angle), and 3) \u003cem\u003eRest\u003c/em\u003e condition - Start position (start/end at cessation of extension and onset of flexion, respectively). The protocol lasted approximately 40 minutes, resulting in 1240 whole-brain sets.\u003c/p\u003e\n \u003cp\u003eThe current fMRI-adapted knee JPS test was also assessed for test-retest reliability in our movement laboratory among a separate group of 15 (9 males) asymptomatic persons (mean \u0026plusmn; SD: age 25.0 \u0026plusmn; 3.1 years, height 1.78 \u0026plusmn; 0.09 m, mass 74.4 \u0026plusmn; 11.2 kg) who performed the test on two occasions 7 days apart. Reliability was estimated with Intraclass Correlation Coefficients (ICC) and 95% confidence intervals (CI) based on a mean rating (\u003cem\u003ek\u003c/em\u003e = 10), two-way mixed effects model with absolute agreement and Standard Error of Measurement (SEM), calculated as the mean square error term from the ANOVA, separately for the non-dominant (ICC 3,10\u0026thinsp;=\u0026thinsp;0.64 [CI 0.02-0.87], SEM = 0.67\u0026deg;) and dominant leg (ICC 3,10\u0026thinsp;=\u0026thinsp;0.78 [CI 0.34-0.93], SEM = 0.86\u0026deg;).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec6\"\u003e\n \u003ch2\u003eImage acquisition\u003c/h2\u003e\n \u003cp\u003eA 3T General Electric MR scanner with a 32-channel head coil was used to acquire the MR images. A T1 structural image was first acquired to create a study-specific template using the following parameters: 180 slices; 1 mm thickness; repetition time 8.2 msec; echo time 3.2 msec; flip angle 12\u0026deg;; field of view 25 x 25 cm. The functional gradient-echo-planar imaging sequence was collected with the following scanning parameters: repetition time = 2000 msec, echo time = 30 msec, flip angle = 80\u0026deg;, field of view = 25 x 25 cm. Thirty-seven transaxial slices with a thickness of 3.4 mm (0.5 mm gap) were acquired in an interleaved order. Ten initial dummy scans were collected and discarded prior to analysis. Test instructions were presented on a computer screen, which were seen via a tilted mirror attached to the head coil. The computer parallel port was used to detect the trigger output signal from the MR scanner to synchronize kinematic data with fMRI data in later analyses.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec7\"\u003e\n \u003ch2\u003eData processing and analysis\u003c/h2\u003e\n \u003cp\u003eMotion capture data were exported to Visual3D software (v.5.02.19, C-Motion Inc. Germantown, MD, USA) and filtered with a 6 Hz fourth-order low-pass zero-lag Butterworth filter. Automated scripts set events based on knee angles and knee angular velocities in the sagittal plane. Target and reproduction angles were extracted 2 seconds after cessation of flexion during the respective phases. All events were checked visually by the lead researcher (AS) and adjusted if deemed incorrect. No data were removed from analyses. Data were exported to IBM SPSS Statistics for Windows, version 25 (IBM Corp., Armonk, N.Y., USA) in which all statistical analyses for knee JPS outcome measures, participant characteristics and patient-reported outcomes were performed.\u003c/p\u003e\n \u003cp\u003eSPM12 software (Wellcome Department of Cognitive Neurology, London, UK) run under MATLAB R 2016 b (MathWorks, Inc., Natick, MA) was used for automated batching, pre-processing and data analysis. SPM was used for visualization of statistical maps and MarsBaR 0.44\u003csup\u003e28\u003c/sup\u003e was used to calculate the percentage of BOLD signal change. Data were pre-processed in the following way: slice timing correction (interleaved order, first image set to reference slice), movement correction by unwarping and realigning all subsequent scans to the first image, co-registration of the mean functional image set and the structural T1 image set, segmentation of the co-registered structural image, normalization to a sample-specific template based on white and grey matter segments from the segmented, co-registered, structural image (using DARTEL\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e) and affine alignment to Montreal Neurological Institute (MNI) standard space and smoothing with an 8-mm FWHM Gaussian kernel. The final voxel size was 2 \u0026times; 2 \u0026times; 2 mm.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec8\"\u003e\n \u003ch2\u003eStatistical analyses\u003c/h2\u003e\n \u003cp\u003eThe ACLR group was subdivided into those with right-side (R-ACLR) and left-side (L-ACLR) reconstruction. Sex distribution between groups was analysed with a Chi-square test. Age and current activity level (Tegner current and Marx activity) between all groups, as well as pre-injury activity level of the ACLR groups to current activity level of CTRL, were analysed with Kruskal-Wallis tests and Dunn-Bonferroni post-hoc tests for significant results. The questionnaires TSK, IKDC and Lysholm Scale were compared between ACLR groups with Mann-Whitney \u003cem\u003eU\u003c/em\u003e tests. A One-way analysis of variance (ANOVA) compared body height and mass between all groups, as well as months since reconstruction between ACLR groups.\u003c/p\u003e\n \u003cp\u003eBetween-group comparisons for kinematic data and brain response were made between the injured leg of ACLR and the matched leg of CTRL. Knee JPS error was defined in degrees as the absolute difference (absolute error [AE]) between the target and reproduction angles of the knee for each repetition of the JPS test. Mean AE was calculated for each leg by pooling the 40\u0026deg; and 65\u0026deg; angle conditions for each participant. Outliers in the data set were assessed for eligibility at group level, but none were removed due to a lack of evidence to the contrary. Shapiro-Wilk tests of normality and analysis of distribution graphs confirmed non-normally distributed group-level data. Knee JPS data were thus log transformed and were subsequently normally distributed. Independent samples t-tests were used to compare the log transformed knee JPS AE between groups. Significance levels were set \u003cem\u003ea priori\u003c/em\u003e (\u0026alpha;\u0026thinsp;=\u0026thinsp;0.05).\u003c/p\u003e\n \u003cp\u003eBrain imaging data for each angle condition were pooled so that each participant contributed with data from 16 \u003cem\u003eJPS\u003c/em\u003e trials per leg. The first-order (single-subject) analyses were set up by including the experimental conditions as regressors of interest in the general linear model, convolved with the hemodynamic response function. Six realignment parameters (head rotations and translations) were included as covariates of no interest to account for movement artefacts. The following contrasts were set up for each participant: 1) [\u003cem\u003eJPS\u003c/em\u003e \u0026gt; \u003cem\u003eRest\u003c/em\u003e] and 2) [\u003cem\u003eFlex\u003c/em\u003e \u0026gt; \u003cem\u003eRest\u003c/em\u003e]. Second-order (group) analyses were based on flexible factorial models\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e of the [\u003cem\u003eJPS\u003c/em\u003e \u0026gt; \u003cem\u003eRest\u003c/em\u003e] and [\u003cem\u003eFlex\u003c/em\u003e \u0026gt; \u003cem\u003eRest\u003c/em\u003e] contrasts from each participant, including participant, group (two levels, R-ACLR or L-ACLR and CTRL), condition (two levels, \u003cem\u003eJPS\u003c/em\u003e and \u003cem\u003eFlex\u003c/em\u003e) and the interaction (group \u0026times; condition) as factors. Separate analyses of the conditions used in the flexible factorial design [\u003cem\u003eJPS\u003c/em\u003e \u0026gt; \u003cem\u003eRest\u003c/em\u003e] and [\u003cem\u003eFlex\u003c/em\u003e \u0026gt; \u003cem\u003eRest\u003c/em\u003e] were also performed to investigate activation patterns in comparison to \u003cem\u003eRest\u003c/em\u003e. These analyses are included as supplementary material. The main effect from condition ([\u003cem\u003eJPS\u003c/em\u003e \u0026gt; \u003cem\u003eRest\u003c/em\u003e] \u0026gt; [\u003cem\u003eFlex\u003c/em\u003e \u0026gt; \u003cem\u003eRest\u003c/em\u003e]) and the interaction (group \u0026times; condition) was analysed (family-wise error [FWE] rate corrected, 0.05; voxel limit 15). Brain regions were defined and labelled according to the MNI coordinates, which relate to the peak activity within the cluster, using automated anatomic labelling in SPM\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Brain regions that showed significant activation for any of these analyses were further analysed by calculating the percentage of BOLD signal change during the \u003cem\u003eJPS\u003c/em\u003e condition (i.e., the original beta values) in the significant region, compared to the overall mean brain activity of the session. The percentage of BOLD change values were exported to SPSS where Spearman\u0026rsquo;s rho was used to analyse correlations of participant mean values between percentage of BOLD change and JPS errors.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOf 77 persons with ACL injury and 61 potential controls who expressed an interest in participating, 55 and 14, respectively, were considered ineligible due to either another existing injury, too low physical activity level, left leg dominance for controls, older age, or a combination of those factors. Thus, 22 individuals with ACLR and 47 asymptomatic controls were considered eligible for the study. To ensure matching of characteristics between groups, controls were invited to participate only after a matching ACLR participant had completed testing. One ACLR participant did not complete the fMRI procedure due to claustrophobic feelings in the MRI scanner. Despite completing testing, one asymptomatic control was not included in the analyses due to the presence of a benign arachnoid cyst, unknown prior to participation, which would have confounded brain imaging analyses. Thus, 10 R-ACLR, 11 L-ACLR and 19 CTRL completed testing and were included in the analyses (see Figure \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e for a flow diagram of the recruitment process and Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e for group characteristics). Due to a technical issue, one L-ACLR participant completed a shortened protocol of 12, instead of 16, repetitions per leg. Also, due to slow performance of the test, one participant from each group performed one less repetition on both legs. Current activity level of CTRL was significantly lower than pre-injury level of R-ACLR (\u003cem\u003eP\u003c/em\u003e = 0.010). No groups differed significantly with regard to sex, age, height, weight or the remaining patient-report outcome measures. Months since reconstruction did not differ significantly between the ACLR groups. For the knee JPS test, no statistically significant differences in errors were seen between either the left reconstructed/non-dominant leg of L-ACLR (median [Mdn] 5.10\u0026deg; [Q1 4.04\u0026deg;, Q3 6.82\u0026deg;]) and CTRL (Mdn 4.17\u0026deg; [Q1 2.89\u0026deg;, Q3 4.95\u0026deg;]) respectively, or between the right reconstructed/dominant leg of R-ACLR (Mdn 4.89\u0026deg; [Q1 3.54\u0026deg;, Q3 6.85\u0026deg;]) and CTRL (4.55\u0026deg; [Q1 3.64\u0026deg;, Q3 6.56\u0026deg;]) respectively.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u0026nbsp;\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\u003eParticipant Characteristics of the Study Groups\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\u003eR-ACLR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eL-ACLR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCTRL\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\u003eParticipants, n\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\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge, y, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.8 (4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.2 (4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.1 (4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale:female, n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4:6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4:7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7:12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMonths since reconstruction, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.0 (9.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.5 (18.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBody height, m, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.72 (0.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.73 (0.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.75 (0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBody mass, kg, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72.6 (7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72.1 (11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73.1 (9.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePatient-reported outcome scales, median (IQR)\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 \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIKDC 2000, % of maximum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e77.6 (14.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e77.0 (15.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLysholm score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86.0 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86.0 (5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarx activity score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.0 (6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.0 (7.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.0 (7.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTegner pre-injury score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.5 (1.2)\u003csup\u003e\u0026dagger;\u003c/sup\u003e,\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.0 (2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTegner current score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.5 (2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.0 (4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.0 (4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTSK score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.5 (11.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.0 (5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInjury mechanism, non-contact:contact, n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8:2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11:0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInjury activity, n\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 \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSoccer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\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\u003eDownhill skiing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\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\u003eMartial arts\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\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\u003eBasketball\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\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\u003eDancing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\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\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFloorball\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\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\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGymnastics\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\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\u003eRugby\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\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\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSnowboard\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\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\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVolleyball\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\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\" colspan=\"4\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003eSignificantly greater than R-ACLR Tegner current score (\u003cem\u003eP\u003c/em\u003e = 0.011). \u003csup\u003e\u0026Dagger;\u003c/sup\u003eSignificantly greater than CTRL Tegner current score (\u003cem\u003eP\u003c/em\u003e = 0.010). Abbreviations: CTRL, asymptomatic control group; IKDC 2000, International Knee Documentation Committee Subjective Knee Form; IQR, interquartile range; L-ACLR, left-side anterior cruciate ligament-reconstructed group; R-ACLR, right-side anterior cruciate ligament-reconstructed group; TSK, Tampa Scale of Kinesiophobia.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec10\"\u003e\n \u003ch2\u003eBrain response during the knee joint position sense test\u003c/h2\u003e\n \u003cp\u003eThe \u003cem\u003eJPS\u003c/em\u003e condition evoked significantly greater BOLD response (\u003cem\u003eP\u003c/em\u003e = 0.05, FWE corrected; voxel limit 15) in seven brain regions for each leg compared to the \u003cem\u003eFlex\u003c/em\u003e condition without a JPS task. These included prefrontal regions, the precentral gyrus, cingulate gyri and insula (see Figure \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, Figure \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e and Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e for all significant regions with voxel extent, exact statistics, and MNI coordinates).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u0026nbsp;\u003ctable border=\"1\" id=\"Tab2\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBrain Regions with Significantly Greater BOLD Response During JPS than Flex ([JPS \u0026gt; Rest)] \u0026gt; [Flex \u0026gt; Rest])\u0026dagger;\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTest side\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBrain regions\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVoxel #\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eZ max\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eMNI coordinate\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\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=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cem\u003eX Y Z\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"7\"\u003e\n \u003cp\u003eLeft\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eContra.\u003c/em\u003e Inferior Frontal Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1608\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\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\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eContra.\u003c/em\u003e Middle Frontal Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eContra.\u003c/em\u003e Median Cingulate and Paracingulate Gyri\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e864\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.29\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\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eIpsi.\u003c/em\u003e Insula\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e330\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eContra.\u003c/em\u003e Temporal Pole: Superior Temporal Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54\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\u003e-5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eContra.\u003c/em\u003e Supramarginal Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eIpsi.\u003c/em\u003e Superior Frontal Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"7\"\u003e\n \u003cp\u003eRight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eIpsi.\u003c/em\u003e Middle Frontal Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e666\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eIpsi.\u003c/em\u003e Precentral Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e596\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\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\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eContra.\u003c/em\u003e Anterior Cingulate and Paracingulate Gyri\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eIpsi.\u003c/em\u003e Anterior Cingulate and Paracingulate Gyri\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.67\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\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eIpsi.\u003c/em\u003e Insula\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eIpsi.\u003c/em\u003e Supramarginal Gyrus\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eIpsi.\u003c/em\u003e Precentral Gyrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47\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\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003eSeven brain regions for each test side showed significantly greater BOLD response during the \u003cem\u003eJPS\u003c/em\u003e condition compared with the \u003cem\u003eFlex\u003c/em\u003e condition across groups. \u003csup\u003e\u0026Dagger;\u003c/sup\u003eSignificant correlation between knee JPS AE and BOLD percentage change. For left test side n = 30 (L-ACLR 11 and CTRL 19), right test side n = 29 (R-ACLR 10 and CTRL 19). Test side: the leg that was active during the JPS test; Voxel #: indicates number of activated voxels in this cluster; \u003cem\u003eP\u003c/em\u003e: 0.05 family wise error rate corrected (cluster level); Z max: Z-score of the voxel with the highest activity for main effect from condition; MNI: voxel with the highest activity in MNI-space. Abbreviations: \u003cem\u003eContra.\u003c/em\u003e, contralateral; CTRL, asymptomatic control group; \u003cem\u003eFlex\u003c/em\u003e, flex condition; \u003cem\u003eIpsi.\u003c/em\u003e, ipsilateral; \u003cem\u003eJPS\u003c/em\u003e, joint position sense condition; L-ACLR, left-side anterior cruciate ligament-reconstructed group; MNI, Montreal Neurological Institute; \u003cem\u003eRest\u003c/em\u003e, rest condition; R-ACLR, right-side anterior cruciate ligament-reconstructed group.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec11\"\u003e\n \u003ch2\u003eBetween-group comparisons of brain response during the knee joint position sense test\u003c/h2\u003e\n \u003cp\u003eNo significant between-group differences were found on the corrected level (FWE 0.05).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec12\"\u003e\n \u003ch2\u003eCorrelations between brain response and knee joint position sense errors\u003c/h2\u003e\n \u003cp\u003eCorrelation analyses were performed for the seven regions per test side that were found to have significantly greater BOLD response during the \u003cem\u003eJPS\u003c/em\u003e condition compared to the \u003cem\u003eFlex\u003c/em\u003e condition (see Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e for a list of the regions). When performing the test with the right leg (R-ACL and CTRL, n = 29), significant positive correlations were found between JPS errors and BOLD signal percentage change (i.e., greater JPS AE correlated with greater BOLD response) in the \u003cem\u003eipsilateral\u003c/em\u003e anterior cingulate (r = 0.476, \u003cem\u003eP\u003c/em\u003e = 0.009; Figure \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eA) as well as the \u003cem\u003eipsilateral\u003c/em\u003e supramarginal gyrus (r = 0.395, \u003cem\u003eP\u003c/em\u003e = 0.034; Figure \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eB). Close to significance was also the \u003cem\u003eipsilateral\u003c/em\u003e middle frontal gyrus (r = 0.364, \u003cem\u003eP\u003c/em\u003e = 0.052). For the left leg (L-ACLR and CTRL, n = 30), a significant positive correlation was found for the \u003cem\u003eipsilateral\u003c/em\u003e insula (r = 0.474, \u003cem\u003eP\u003c/em\u003e = 0.008; Figure \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eC).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur hypothesis that our knee JPS test would evoke greater response in somatosensory and motor cortices compared to simple knee flexion was confirmed by observations of greater response during angle reproduction in, for example, the precentral gyrus, middle frontal gyrus, insula and cingulate gyri. Our hypothesis that individuals with ACL reconstruction would show differences in brain response compared to asymptomatic controls was rejected due to a lack of significant differences between groups. Our hypothesis that knee JPS errors would correlate with response in related regions was on the other hand confirmed by associations between greater errors and BOLD response in the insula, anterior cingulate and supramarginal gyrus.\u003c/p\u003e\n\u003cp\u003eOur knee JPS test evoked response in the \u003cem\u003eipsilateral\u003c/em\u003e precentral gyrus for the right test side and cingulate gyri for both test sides. Response in these regions has also been observed among asymptomatic individuals during active knee flexion tasks of JPS\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e and force matching\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Response in the right middle frontal gyrus was seen for both test sides and has been previously associated with switching between exogenous and endogenous attention\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, relevant for our JPS task where the focus of attention changes from external instructions on a screen to internal sensations related to proprioception. Also common for both test sides was recruitment of the \u003cem\u003eipsilateral\u003c/em\u003e insula, previously associated with sensorimotor processes such as active and passive stepping motions\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. This finding also aligns with the body image and body schema concepts of body representations\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e, in which current understandings attribute the insula with conscious perceptual representation of the body and memory\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. The insula and anterior cingulate are further thought to play a key role in interoception, a term originally introduced by Sherrington\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e to describe visceral sensations, but now often used as a broader term encompassing the subjective experience of the body state\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e and even proprioception\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. In fact damage to the insula due to stroke has been associated with poor position sense of the upper limbs\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. The same study also found similar associations for the inferior frontal and superior temporal gyri, two areas that were activated during our JPS test in the current study. Thus, our findings add to previous evidence of neural networks involved in proprioceptive tasks and expand these to those associated with the lower limbs.\u003c/p\u003e\n\u003cp\u003eThere were no significant between-group differences for brain response nor for knee JPS errors. Previous research investigating knee JPS and somatosensory evoked potentials of individuals 18 months after surgical reconstruction of the ACL also found a lack of difference compared with controls as evidence of sensory neurone regeneration\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. The original version of the current supine knee JPS test also did not detect any significant differences in errors for a separate ACLR group approximately two years after surgical reconstruction compared with matched athletes\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. In that study, less-active controls instead showed significantly greater JPS errors compared to the ACLR group, suggesting that activity level is a more important factor in this context. It is therefore possible that deficits in proprioception were not present among the individuals of our ACLR group, who were active and participated on average 23 months after surgical reconstruction. Additionally, a recent meta-analysis found that only knee JPS tests with passive rather than active movements differentiate between ACL-injured knees and those of asymptomatic controls\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. The active movements of the current test, which also incorporated the hip, may further have contributed to the lack of between-group difference seen here. The target angles of 40\u0026deg; and 65\u0026deg; knee flexion used in our JPS test both lie close to the mid-range of motion for the joint. These angles may not have been optimal for elucidating differences between groups where joint receptors are the focus of investigation, given that they are believed to play a more predominant role towards the limits of joint rotation\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. It is also possible that small group sizes (due to separating ACLR into right and left leg analyses), as well as the contrast to such a similar movement, may have reduced the sensitivity of our analysis.\u003c/p\u003e\n\u003cp\u003eOur results showed that greater knee JPS errors, i.e., poorer knee proprioceptive acuity, was associated with greater brain response in the ipsilateral insula for the left test side, as well as the ipsilateral anterior, paracingulate and supramarginal gyri for the right test side. These results are line with the Embodied Predictive Interoception Coding (EPIC) model proposed by Barrett and Simons\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e, which describes the process of active inference in interoception. Part of this model describes the role of the mid- and posterior insula in computing and transmitting prediction errors as well as the integration of other agranular visceromotor cortices such as the cingulate cortex in this process. This model may thus be relevant for proprioceptive tasks. The importance of the insula to position sense is further supported by findings previously mentioned here for the upper limbs following stroke, whereby lesions in this region were associated with greater errors when attempting to actively move the unaffected arm to the mirror-matched position of the passively moved contralateral arm\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Associated response for the right supramarginal gyrus is supported by previous findings of greater response during a proprioceptive task of force matching at the knee among asymptomatic females\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eA limitation of our study was the additional task of attempting a constant knee angular velocity, although this was similar for the contrast \u003cem\u003eFlex\u003c/em\u003e condition. Further, the active movement of the whole lower limb meant that proprioceptive feedback was not isolated to the knee, but also incorporated the hip. Although this is more similar to everyday activities and thus may enhances the ecological validity of the task compared with a single-joint movement, compensations at the hip joint for potential deficits at the knee are possible. Despite the active task, head movement (range 0.14 - 0.88 mm) did not confound brain imaging analyses. Due to challenges in recruiting participants, we included ACLR individuals who had injured either knee, but a control group with only right-side dominance. Future studies with a greater number of and more homogenous participants are likely required to further elucidate potential group differences. Comparisons were thus made to the non-dominant and dominant legs of CTRL for the L-ACLR and R-ACLR groups respectively. Additionally, both sexes were represented in each of our groups. Two similar fMRI studies have however indicated potentially different functional brain connectivity between males\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e and females\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e who later suffered an ACL injury. Our eligibility criteria required a minimum physical activity level score of four according to the Tegner activity scale. Although we matched current activity level between groups, a sub-analysis using Wilcoxon Signed Ranks tests compared pre-injury and current activity levels within the ACLR groups and found that R-ACLR had significantly reduced their activity level (\u003cem\u003eP\u003c/em\u003e = 0.011), but the level was not significantly changed among L-ACLR. A difference in activity level change from pre- to post-injury was thus a potentially confounding factor in our analyses. To explore this further, a Mann-Whitney U test to compare change in activity level between the groups found no significant between-group difference. A significant reduction in activity level following ACL injury is however considered a useful outcome for defining non-copers\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. Future studies may thus benefit from analyses that consider coping classification of individuals with ACL injury.\u003c/p\u003e\n\u003cp\u003eIn summary, our paradigm found greater BOLD response for a number of brain regions which have previously been associated with processes that can be linked to proprioception. These results thus indicate that the experimental design was successful in recruiting brain regions involved in proprioception. The lack of differences between groups is perhaps not surprising given mixed evidence of proprioceptive deficits among individuals nearly two years post-ACLR. The small sample sizes as a result of splitting the ACLR group into left and right-side injuries may however have been a contributing factor to the lack of significance. The significant correlations between knee JPS error and activation in some brain regions further indicates that demands were placed on the proprioceptive acuity of the participants. The novel integration of kinematics with fMRI thus provided added value to the paradigm by providing behavioural data as well as specific time frames for extraction of brain images to isolate such processes.\u003c/p\u003e\n\u003cp\u003eThis is pioneering work that has attempted to capture brain response to a lower limb proprioception task using fMRI and simultaneous kinematics to quantify knee JPS. The identification of brain regions associated with lower limb proprioception tasks, such as knee JPS, provides new and valuable information regarding central processing of such tasks. Our unique paradigm demonstrates a method to expand these findings and provide further insights into brain response to proprioception at the knee and other joints as well as among different populations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analysed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge the Ume\u0026aring; center for Functional Brain Imaging (UFBI) for collaboration and assistance, Dr. Ashokan Arumugam and PhD student Adam Grinberg for assistance during data collection, and all of the study participants. The study was funded by the Swedish Scientific Research Council (Grant No. 2017-00892), Region V\u0026auml;sterbotten (Grant No. ALF VLL548501, VLL838421 and Strategic funding VLL-358901; Project No. 7002795), the Swedish Scientific Research Council for Sports Science (Grant No. Dnr CIF P2018-0104; P2019-0068), Ume\u0026aring; University School of Sport Science (Grant No. Dnr IH 5.3-13-2017). King Gustaf V and Queen Victoria\u0026rsquo;s Masonic Foundation, and the Kempe foundation. The\u0026nbsp;funders\u0026nbsp;did not have any role\u0026nbsp;in the study design or outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCH obtained the funding for the study. All authors were involved in the design of the paradigm. JS built the sliding board for the task and developed the real-time software. AS and CH recruited the participants. AS and JS performed the data collection. AS processed the motion capture files and performed statistics on the kinematic data. AS and HG processed the brain images. HG and CJB performed statistical analyses of the brain imaging data. AS wrote the first draft of the manuscript. AS prepared figures 1, 2 and 5. AS, HG and JS prepared figures 3 and 4. All authors reviewed subsequent drafts of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMajewski, M., Susanne, H. \u0026amp; Klaus, S. 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Sports Med.\u003c/em\u003e \u003cb\u003e40\u003c/b\u003e, 853-859; discussion 859, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bjsm.2006.028258\u003c/span\u003e\u003c/span\u003e (2006).\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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Anterior Cruciate Ligament, Anterior Cruciate Ligament Reconstruction, Knee, Rehabilitation, Position Sense, Magnetic Resonance Imaging, Neuronal Plasticity","lastPublishedDoi":"10.21203/rs.3.rs-955159/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-955159/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eKnee proprioception deficits and neuroplasticity have been indicated following injury to the anterior cruciate ligament (ACL). Evidence is however scarce regarding brain response to knee proprioception tasks and the impact of ACL injury. Twenty-one persons with unilateral ACL reconstruction (mean 23 months post-surgery) of either the right (n = 10) or left (n = 11) knee, as well as 19 controls (CTRL) matched for sex, age, height, weight and current activity level, performed a knee joint position sense (JPS) test during simultaneous functional magnetic resonance imaging (fMRI). Integrated motion capture recorded knee kinematics. Recruited brain regions included somatosensory cortices, prefrontal cortex and insula. Neither brain response nor JPS errors differed between groups, but across groups significant correlations revealed that greater errors were associated with greater ipsilateral response in the anterior cingulate (r = 0.476, \u003cem\u003eP\u003c/em\u003e = 0.009), supramarginal gyrus (r = 0.395, \u003cem\u003eP\u003c/em\u003e = 0.034) and insula (r = 0.474, \u003cem\u003eP\u003c/em\u003e = 0.008). This is the first study to capture brain response using fMRI in relation to quantifiable knee JPS. Activated brain regions have previously been associated with sensorimotor processes, body schema and interoception. Our innovative paradigm can help to guide future research investigating brain response to lower limb proprioception.\u003c/p\u003e","manuscriptTitle":"Brain Response To A Knee Proprioception Task Among Persons With Anterior Cruciate Ligament Reconstruction And Controls","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-10-11 18:30:14","doi":"10.21203/rs.3.rs-955159/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"726f7cf2-b7bb-46cc-89f2-324fe8be42b6","owner":[],"postedDate":"October 11th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":7774316,"name":"Neurology"},{"id":7774317,"name":"Health Policy"}],"tags":[],"updatedAt":"2022-03-27T17:25:15+00:00","versionOfRecord":{"articleIdentity":"rs-955159","link":"https://doi.org/10.3389/fnhum.2022.841874","journal":{"identity":"frontiers-in-human-neuroscience","isVorOnly":true,"title":"Frontiers in Human Neuroscience"},"publishedOn":"2022-03-22 17:25:15","publishedOnDateReadable":"March 22nd, 2022"},"versionCreatedAt":"2021-10-11 18:30:14","video":"","vorDoi":"10.3389/fnhum.2022.841874","vorDoiUrl":"https://doi.org/10.3389/fnhum.2022.841874","workflowStages":[]},"version":"v1","identity":"rs-955159","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-955159","identity":"rs-955159","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}