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Journal of Neurophysiology logoLink to Journal of Neurophysiology
. 2018 Jul 5;120(4):1591–1601. doi: 10.1152/jn.00207.2018

Motor adaptations to trunk perturbation: effects of experimental back pain and spinal tissue creep

Jacques Abboud 1,✉, Catherine Daneau 2, François Nougarou 3, Claude Dugas 2, Martin Descarreaux 2
PMCID: PMC6230797  PMID: 29975166

Abstract

In complex anatomical systems, such as the trunk, motor control theories suggest that many motor solutions can be implemented to achieve a similar goal. Although reflex mechanisms act as a stabilizer of the spine, how the central nervous system uses trunk redundancy to adapt neuromuscular responses under the influence of external perturbations, such as experimental pain or spinal tissue creep, is still unclear. The aim of this study was to identify and characterize trunk neuromuscular adaptations in response to unexpected trunk perturbations under the influence of spinal tissue creep and experimental back pain. Healthy participants experienced a repetition of sudden external trunk perturbations in two protocols: 1) 15 perturbations before and after a spinal tissue creep protocol and 2) 15 perturbations with and without experimental back pain. Trunk neuromuscular adaptations were measured by using high-density electromyography to record erector spinae muscle activity recruitment patterns and a motion analysis system. Muscle activity reflex attenuation was found across unexpected trunk perturbation trials under the influence of creep and pain. A similar area of muscle activity distribution was observed with or without back pain as well as before and after creep. No change of trunk kinematics was observed. We conclude that although under normal circumstances muscle activity adaptation occurs throughout the same perturbations, a reset of the adaptation process is present when experiencing a new perturbation such as experimental pain or creep. However, participants are still able to attenuate reflex responses under these conditions by using variable recruitment patterns of back muscles.

NEW & NOTEWORTHY The present study characterizes, for the first time, trunk motor adaptations with high-density surface electromyography when the spinal system is challenged by a series of unexpected perturbations. We propose that the central nervous system is able to adapt neuromuscular responses by using a variable recruitment pattern of back muscles to maximize the motor performance, even under the influence of pain or when the passive structures of the spine are altered.

Keywords: creep, HD-EMG, lumbar muscle, pain, spinal stability

INTRODUCTION

Trunk muscles play an important role in postural stability. In everyday life, several neuromuscular adaptations, such as increase of reflex muscle activity and/or postural adjustments, are used when the trunk system is challenged by an external perturbation. The complexity of muscles surrounding the trunk makes it a relevant system to better understand how motor variability could be used to face environmental perturbations. However, few studies have investigated the ability of the trunk system to adapt when it is challenged by repetitions of external unexpected perturbations (Abboud et al. 2016b; Skotte et al. 2004). These studies suggest that the central nervous system (CNS) is able to adapt neuromuscular outcomes based on previous experience of a given external perturbation even when it is unexpected. These neuromuscular adaptations, referring to an attenuation of trunk reflex activity amplitude and/or postural oscillations (Abboud et al. 2016b; Skotte et al. 2004), have been also reported in other muscles, such as those of the neck or lower limbs (Blouin et al. 2003; Nashner 1976; Siegmund et al. 2003). These observations concur with the ability of the CNS to use trunk muscle system redundancy to adapt neuromuscular responses. In light of these findings, it seems reasonable to suggest that these responses occur when trunk muscle control works adequately. This raises the question of the capacity of the CNS to adapt trunk neuromuscular responses to generate proper motor control in the presence of an external condition that has the potential to alter trunk muscle control, such as experimental back pain or spinal tissue creep.

In a recent systematic review, our group explored and synthesized the effects of spinal tissue creep on trunk muscle neuromuscular responses while postural stability was challenged by unexpected trunk perturbations (Abboud et al. 2017). Most studies reviewed were of good quality, but the high heterogeneity and small sample sizes rendered the evidence inconclusive. One of the reasons for such discrepancies among these studies could be the lack of information regarding muscle activity recruitment strategies used to face external trunk perturbations. All of the above-mentioned studies have been limited by the use of bipolar electromyography (EMG). One could argue that high-density EMG (HD-EMG), because of its larger size and high number of recording electrodes, could provide a unique perspective on muscle activity reflex responses, such as the topographical distribution of muscle activity (Zwarts and Stegeman 2003). It was recently observed that the level of motor variability, assessed by muscle activity recruitment pattern with HD-EMG, could be influenced by the presence of spinal tissue creep (Abboud et al. 2016a). Under the influence of creep deformation, spinal passive structures are altered, and a reorganization of muscle activity occurs to compensate for such changes (Abboud et al. 2016a; Solomonow 2012).

As for the effects of experimental back pain on low back neuromuscular responses, no change in muscle reflex amplitude was observed, whereas contradictory results were found for the erector spinae reflex latency following unexpected trunk perturbations (Boudreau et al. 2011; Gregory et al. 2008; Miller et al. 2013). It has also been proposed that the level of motor variability can also be influenced by the presence of pain. For instance, a higher motor variability was observed in the upper limb or in the trunk in the presence of acute pain, whereas it was lower under chronic pain conditions (Madeleine 2010; van Dieën et al. 2017). Moreover, it has been proposed that neuromuscular responses to pain are not stereotypical and that the pattern of muscle activity recruitment varies between individuals submitted to experimental back pain (Hodges et al. 2013). Overall, these observations reflect trunk muscle system redundancy, which enables the CNS to choose from several distinct combinations of muscle activations.

Therefore, the first objective of the present study was to identify and characterize the neuromuscular responses in healthy participants when they are submitted to unexpected trunk perturbations in two different experimental conditions (spinal tissue creep and experimental back pain). The second objective of this study was to determine whether the trunk neuromuscular responses to an unexpected perturbation can be modulated by a previous and similar trunk perturbation (trial-to-trial adaptation) under the influence of spinal tissue creep and experimental back pain. In light of the trunk muscle system’s high redundancy potential and the prediction of Madeleine’s motor variability model (Madeleine 2010), we hypothesized that participants would be able to adapt their neuromuscular responses across trunk perturbation trials even in the presence of creep deformation or experimental back pain.

METHODS

Participants

Two groups of participants were included in this study: an experimental group and a control group. In the experimental group, 20 healthy participants (4 women and 16 men) were recruited from the university community. Participant mean age, height, weight, and body mass index were 28.2 [standard deviation (SD) 5.4] yr, 1.75 (SD 0.07) m, 77.3 (SD 13.8) kg, and 25.1 (SD 3.6) kg/m2, respectively. For the control group, 14 healthy participants (5 women and 9 men) were recruited from the university community. Participant mean age, height, weight, and body mass index were 27.1 (SD 6.9) yr, 1.75 (SD 0.09) m, 71.5 (SD 11.4) kg, and 23.3 (SD 2.3) kg/m2, respectively.

For both groups, the exclusion criteria were history of acute/chronic thoracic or low back pain in the past 6 mo, ankylosing spondylitis, inflammatory arthritis, trunk neuromuscular disease, scoliosis (≥15°), and previous spinal surgery. The project received approval from the university’s ethics committee for research with humans (Comité d’éthique de la recherche avec des êtres humains). Before their participation in this study, all participants gave their written informed consent.

Protocol

Healthy participants from the experimental group participated in two different conditions on separate days. In one condition, participants were asked to sit with a flexion of their trunk to induce spinal tissue creep in the lumbar region (creep condition). In the other condition, participants were submitted to an experimental low back pain protocol (experimental pain condition). To minimize possible order effects, half of the participants were first submitted to the creep protocol, whereas the other half started with the experimental pain protocol. In both experimental conditions, participants responded to two series of 15 unexpected trunk perturbations. During the experimental pain condition, one of the two series was performed without the influence of experimental back pain and the other with the influence of experimental back pain. Half of the participants started without the presence of experimental pain, and the other half started with the presence of experimental pain during the trunk perturbation trials. The two series of perturbation trials were separated by a 5-min rest period. As for the creep condition, all participants started the first series of 15 trunk perturbations before the creep deformation protocol, and the second series was performed immediately after. The two experimental conditions were carried out several days apart (minimum of 7 days) to allow full recovery from creep deformations. During these recovery days, participants were asked to avoid any unusual activity, such as a new physical activity. Finally, healthy participants from the control group participated in one protocol during which they were submitted to the same two series of 15 unexpected trunk perturbations with a 5-min rest between the two series (rest condition). Figure 1 represents the experiment timeline.

Fig. 1.

Fig. 1.

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Timeline of the experimental protocol.

At the beginning of each condition, kinematic sensors and EMG electrodes were placed on the participants. Once the instrumentation was in place, participants were asked to perform maximal voluntary contractions (MVCs) in trunk flexion and trunk extension directions. Two or three trials were performed in each direction. Participants were asked to perform a third trial only when their second MVC trial was 5% higher than the first trial. For trunk flexion MVC trials, participants had to pull anteriorly on a cable attached at the T8 level to a load cell (model LSB350; Futek Advanced Sensor Technology, Irvine, CA). For trunk extension, participants had to pull posteriorly on a cable. Verbal cues were provided by assessors to motivate the participants during MVC performances. The MVC trials, which consisted of ramp contractions, were performed in a semiseated position in a custom-made chair (see Fig. 2 and Trunk perturbation protocol). Ramp contractions consisted of progressively increased extensor muscle force for ~3 s to reach the maximal strength of these muscles.

Fig. 2.

Fig. 2.

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Illustration of the perturbation protocol.

Creep condition.

Before the beginning of the creep protocol and immediately after, the range of motion (ROM) of trunk flexions was measured by the same assessor. To induce spinal tissue creep, participants were asked to sit on a bench for 30 min. In this position, they were asked to bend forward to achieve a trunk flexion of ~75% of their maximal range of trunk flexion. In this 30-min interval, the participant’s trunk was supported by a table to minimize trunk muscle activity. If needed, a cushion was added on the table for the participant’s comfort. Moreover, a 90°knee flexion was required to limit the occurrence of hamstring muscle stretching. The trunk ROM was measured by placing a digital dual inclinometer (Dualer IQ Pro Digital Inclinometer; JTECH Medical) on the L1 and L5 vertebrae. Trunk ROM was assessed in a straight upright position, during which participants were asked to tilt the trunk forward as much as possible without bending the knees. Three attempts were performed before and after the creep deformation protocol. The trial with the highest trunk ROM was considered for analysis.

Experimental pain condition.

To induce experimental pain, thermal cutaneous stimulations were administered with a 9-cm2 contact thermode (model TSA-2001; MEDOC Advanced Medical Systems, Ramat Yishai, Israel) placed on the skin over the L3 spinous process, between the two EMG arrays. The thermode was placed at the beginning of the experiment, once the EMG was installed, and was kept in position during the experiment with a custom-made adjustable belt, while the belt was installed over the EMG. After each thermal stimulation, participants had to rate their perceived pain on a validated numerical rating scale including verbal and numerical guides: no pain (0/100), light pain (21/100), moderate pain (46/100), strong pain (75/100), and extreme pain (97/100) (Rainville et al. 1992). The level of noxious heat was individually adjusted to induce moderate pain. To achieve moderate pain, an ascending protocol was used: 15 s of noxious stimulation followed by a 15-s rest period without noxious stimulation. The ascending protocol started with the same baseline temperature for all participants set to 42°C and increased with steps of 0.5°C until the participant perceived pain corresponding to a moderate level. The highest temperature used was 50°C, to avoid any tissue damage. If a participant did not feel moderate pain at 50°C, he/she was excluded from the study. The temperature triggering moderate pain was used during the unexpected trunk perturbations. The noxious stimulation started 8 s before the random onset of the perturbation and stopped 1 s after the perturbation onset.

Trunk perturbation protocol.

To induce unexpected trunk perturbation, a custom-made apparatus was used to generate a posterior-to-anterior perturbation of the trunk. Participants were in a semiseated position with ~75° of flexion of the knee, ~110° of flexion of the hip, and the trunk in a natural straight position (Fig. 2). A harness was installed over the upper body and attached at the T8 level by a cable with a pulley system. The trigger was connected to a small motor by a cable. Once the motor started, it was able to pull the trigger and consequently initiate the trunk perturbation by releasing the tension in the cable, which forced the trunk to control anterior movement. A signal from the motor was sent to a computer to determine the exact moment of the perturbation onset. The trigger was also connected to a load cell (model LSB350; Futek Advanced Sensor Technology) to measure the force exerted by participants in trunk flexion. The magnitude of the trunk perturbation corresponded to 20% of the MVC in trunk flexion. Participants were instructed to maintain this pulling force and, once the perturbation was triggered, to return to their original position. With a computer screen, visual feedback was provided to the participants to help them reach the target force of 20% of trunk flexion MVC. To avoid any anticipation of the trunk perturbation, the onset of the perturbation varied among 1, 3, and 5 s, according to a random sequence generated by MATLAB (MathWorks, Natick, MA). Moreover, participants wore headphones to mute the sound of the perturbation trigger.

Data Acquisition

Myoelectric activity was recorded from the flexor and extensor trunk muscles. Before the application of any EMG electrode, each location site was prepared through the reduction of skin impedance by shaving body hair, gently exfoliating the skin with fine-grade sandpaper (Red DotTrace Prep; 3 M, St. Paul, MN), and wiping the skin with alcohol swabs. With regard to the extensor trunk muscles, surface EMG of the right and left erector spinae muscles was recorded with HD-EMG (model ELSCH064; LISiN-OT Bioelettronica, Turin, Italy). The HD-EMG consisted of two grids composed of 64 electrodes and organized in an 8 × 8 matrix (10-mm interelectrode distance). The center of each grid was located at L3 level, and the medial edge of the array was at ~2 cm from the L3 spinous process (to avoid any contact with the thermode). One bracelet ground electrode was placed on the right wrist. Signals from the bipolar HD-EMG were amplified (64-channel sEMG amplifier, SEA 64; LISiN-OT Bioelettronica; –3 dB, bandwidths 10–500 Hz) by a factor of 5,000 during the protocol. The signal was sampled at 2,048 Hz and converted to digital form by a 12-bit A/D converter. As for the flexor trunk muscles, rectus abdominis and external obliquus abdominis muscle activities were recorded bilaterally, with a differential Ag surface EMG sensor with a common mode rejection ratio of 92 dB at 60 Hz, a noise level of 1.2 μV, a gain of 10 V/V ± 1%, and a bandwidth of 20–450 ± 10% (model DE2.1; Delsys, Boston, MA) amplified by a factor of 10,000. The signal was sampled at 2,048 Hz with a 12-bit A/D converter (PCI 6024E; National Instruments, Austin, TX). Each bipolar signal was filtered with a band-pass filter in the frequency bandwidth 30–450 Hz (2nd-order Butterworth filter). Moreover, notch filters were also applied to the EMG signals to eliminate the 60 Hz and 100 Hz power line interferences and their harmonics. The same investigator assessed the placement of each electrode for all participants, to avoid interrater variability. Rectus abdominis electrodes were positioned parallel to the muscle fibers, so that they were located ~2 cm lateral and across from the umbilicus over the muscle belly (Criswell and Cram 2011). As for the external obliquus, the electrodes were placed lateral to the rectus abdominis and directly above the anterior superior iliac spine (halfway between the crest and the ribs parallel to the muscle fibers) (Criswell and Cram 2011). The myoelectric signals from both EMG acquisition systems were collected with OT Bioelettronica custom software. Muscle activity from all the trunk muscles (extensor and flexor) was normalized with respect to the trunk extension and flexion MVC values.

Kinematics of the trunk during perturbation trials were collected with a three-dimensional motion analysis system (Optotrak Certus; Northern Digital, Waterloo, ON, Canada). Kinematic sensors (light-emitting diodes) were placed, by the same assessor for each participant, on the left side of participants’ trunk over two anatomical landmarks: 1) L1 and 2) T11. These markers were positioned a few centimeters on the left side of the trunk to avoid creating interference with EMG signals. Data from kinematic sensors were sampled at 100 Hz and low-pass filtered with a dual-pass, fourth-order Butterworth filter with a cutoff frequency of 5 Hz. Finally, EMG data and kinematic data were synchronized through a signal triggered by OT Bioelettronica software and MATLAB (MathWorks).

Data Analysis

From HD-EMG signals, four variables were computed: the baseline activity, the reflex latency, the EMG reflex, and the area of spatial distribution of muscle activity. Left and right sides of the erector spinae muscles were analyzed separately. From trunk flexor EMG signals, reflex activity was also computed. To avoid inclusion of any voluntary responses, reflex response latencies superior to 300 ms from the perturbation onset were excluded from analysis.

Baseline activity.

Baseline activity of the erector spinae muscles corresponded to the mean EMG amplitude of the root mean square (RMS) with a 500-ms window before the onset of the trunk perturbation. The mean of all electrodes for each HD-EMG (left and right) was calculated.

Reflex latency.

Reflex latency was defined as the time delay from the perturbation onset to the reflex onset. To determine the reflex onset, HD-EMG signals were Butterworth filtered (6th order, 50 Hz cutoff frequency) and assessed with a sliding window of 25 ms (Larivière et al. 2010). Muscle activity onset was then computed by an automated method: the SD method (Hodges and Bui 1996). More precisely, the EMG onset was detected when the EMG signals exceeded three SDs above the mean baseline activity amplitude.

Erector spinae EMG reflex amplitude.

From each HD-EMG, the EMG reflex amplitude corresponded to the mean RMS value from a window of 100 ms, divided equally (50 ms) on either side of the reflex peak. The reflex peak corresponded to the highest RMS value after perturbation onset. The reflex peak had to be present in a 300-ms window following the perturbation onset to be considered in the analysis.

Spatial distribution area of reflex activity.

The spatial distribution area of reflex activity was computed using the muscle activity range of displacement (centroid) from the HD-EMG across the perturbation trials, a method described in a previous publication (Abboud et al. 2016b). The spatial distribution area of reflex activity represents the level of motor variability expressed as the muscle activity recruitment pattern.

Abdominal EMG reflex amplitude.

Across perturbation trials, reflex activity in the abdominal muscles rarely occurred. In the majority of participants, the EMG reflex amplitude did not exceed three SDs above the mean baseline activity amplitude following the second or third perturbation trials. Therefore, mean RMS values of the rectus abdominis and obliquus externus were computed based on the same 100-ms window used for erector spinae data analyses.

Trunk kinematics.

Trunk kinematics were analyzed by using the data from both kinematic sensors to create a vector. Trunk motion was obtained by calculating the trunk flexion angle between the T11–L1 vector and a horizontal vector relative to the ground. From the trunk motion, three variables were extracted. 1) The trunk angle values corresponded to the ROM between the starting position before the trunk perturbation and the maximal trunk flexion after perturbation onset. From the trunk angle, 2) peak velocity and 3) time to peak velocity were computed.

Statistical Analysis

For each dependent variable, the normality of distribution was evaluated with the Kolmogorov-Smirnov test and by visual inspection. Student’s t-tests for dependent samples were used to compare the area of reflex activity spatial distribution before and after the creep protocol as well as with and without experimental back pain. Student’s t-tests for dependent samples were also used to identify whether a difference occurred between the left and right sides of the abdominal EMG. A mixed-model two-way repeated-measures ANOVA was conducted to assess 1) the trial-to-trial adaptation effect across perturbations, 2) the condition effect (creep effect, experimental pain effect, or rest effect), and 3) the interaction effect (condition × adaptation) for each dependent variable (baseline activity, reflex latency, EMG reflex amplitude for erector spinae and abdominal muscles, and trunk kinematic variables). For the baseline activity, reflex latency, EMG reflex, and kinematic variables, the means of the first and last five perturbation trials of the first and second series of the 15 trunk perturbation trials were considered for the two-way repeated-measures ANOVA. When necessary, the Tukey post hoc test was performed for pairwise comparisons. For all statistical analyses, a P < 0.05 was considered to be significant.

RESULTS

During the experimental pain condition, the magnitude of the perturbation ranged from 40.0 to 79.4 N, with an average of 57.3 N. During the creep condition, the magnitude of the perturbation ranged from 39.7 to 78.6 N, with an average of 56.2 N. During the control condition, the magnitude of the perturbation ranged from 33.1 to 82.5 N, with an average of 53.6 N. These magnitudes are similar to those used in previous studies that used similar trunk perturbation protocols (Abboud et al. 2016b; Radebold et al. 2000).

In all conditions (creep, experimental pain, and control), 4% of all perturbation trials from HD-EMG recordings were excluded from the analyses because of the absence of a reflex response. These excluded trials corresponded to 4% in the creep condition, 5% in the experimental pain condition, and 3% in the control condition. Moreover, for one participant, the left electrode on the rectus abdominis muscle was removed from the analysis during the creep protocol because of a technical issue.

Regarding abdominal EMG, mean values of left and right rectus abdominis as well as mean values of left and right external obliquus were used for the analyses, since no statistical difference was identified between the sides (all P > 0.05).

Rest Condition

Between the first series of 15 trunk perturbations and the second series, erector spinae, rectus abdominis, and externus obliquus activity in the control condition showed a significant reduction of EMG reflex amplitude (all P < 0.05, except for the right side of the erector spinae, P = 0.12) (Table 1). A clear and significant adaptation effect across the perturbation trials before and after the rest period was observed in the erector spinae EMG reflex amplitude (only on the right side, P = 0.03; Table 1 and Fig. 3) and in the obliquus externus EMG reflex amplitude (P = 0.03). Most of the other EMG and kinematic variables did not change significantly before and after the rest period and did not adapt over perturbation trials (Table 1).

Table 1.

Mean values of all dependent variables for control group

P*
First 5 Trials Last 5 Trials Rest Adaptation
Flexion angle, °
    Prerest 4.8 (2.8) 4.7 (2.6) 0.23 0.98
    Postrest 5.0 (3.2) 5.1 (2.7)
Peak velocity, °/s
    Prerest 19 (7) 19 (7) 0.45 0.67
    Postrest 19 (7) 20 (7)
Time to peak velocity, ms
    Prerest 198 (67) 209 (75) 0.41 0.10
    Postrest 212 (80) 216 (74)
Baseline activity, % MVC
    L
        Prerest 9 (4) 8 (3) 0.80 0.04
        Postrest 9 (4) 8 (3)
    R
        Prerest 10 (5) 9 (5) 0.26 0.03
        Postrest 10 (5) 10 (5)
Reflex latency, ms
    L
        Prerest 129 (33) 128 (24) 0.10 0.79
        Postrest 131 (30) 135 (28)
    R
        Prerest 127 (35) 124 (20) 0.99 0.80
        Postrest 125 (24) 127 (25)
Erector spinae EMG reflex amplitude, % MVC
    L
        Prerest 35 (20) 31 (14) 0.03 0.06
        Postrest 29 (14) 17 (13)
    R
        Prerest 35 (14) 33 (15) 0.12 0.03
        Postrest 32 (13) 30 (12)
Abdominal EMG reflex amplitude, % MVC
    RA
        Prerest 10 (10) 8 (7) 0.03 0.07
        Postrest 8 (8) 8 (7)
    OE
        Prerest 10 (6) 9 (4) 0.02 0.03
        Postrest 9 (5) 8 (4)
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Values are means (SD). EMG, electromyography; L, left side of erector spinae; R, right side of erector spinae; MVC, maximal voluntary contraction; OE, obliquus externus; RA, rectus abdominis.

*

Based on repeated-measures ANOVA.

Fig. 3.

Fig. 3.

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Mean erector spinae EMG reflex amplitude results on the left side for all conditions. RMS, root mean square.

Creep Condition

Data from five participants were excluded from the ROM analyses because of technical measurements errors during the ROM assessment. Results showed that participants’ ROM in full trunk flexion increased from 37.7° (SD = 11.6) before the creep protocol to 39.9° (SD = 8.7) afterward (dependent t-tests, P = 0.10). The mean increase corresponded to 4% after the creep deformation protocol.

After the spinal tissue creep protocol, erector spinae baseline activity tended to be higher (significant only on 1 side of the erector spinae, P = 0.04) than before creep (Table 2). Moreover, baseline activity and erector spinae EMG reflex amplitude significantly decreased (adaptation effect) across trunk perturbation trials regardless of the presence or absence of creep (Table 2 and Fig. 3). All of the other EMG and kinematic variables did not significantly change before and after the creep condition and did not adapt over perturbation trials (Table 2). Moreover, dependent t-tests revealed no significant difference between pre- and postcreep conditions for the area of reflex activity spatial distribution of the right (precreep: mean 1.14, SD 0.32; postcreep: mean 1.05, SD 0.31; P = 0.25) or left (precreep: mean 1.22, SD 0.40; postcreep: mean 1.14, SD 0.32; P = 0.37) erector spinae muscles.

Table 2.

Mean and values of all dependent variables before and after creep protocol

P*
First 5 Trials Last 5 Trials Creep Adaptation
Flexion angle, °
    Precreep 5.8 (3.7) 5.3 (3.4) 0.10 0.60
    Postcreep 6.1 (3.8) 6.2 (4.3)
Peak velocity, °/s
    Precreep 20 (11) 18 (7) 0.10 0.38
    Postcreep 20 (8) 19 (7)
Time to peak velocity, ms
    Precreep 196 (58) 196 (60) 0.16 0.59
    Postcreep 208 (61) 198 (52)
Baseline activity, % MVC
    L
        Precreep 10 (7) 9 (7) 0.04 0.003
        Postcreep 11 (7) 10 (7)
    R
        Precreep 10 (8) 9 (8) 0.47 0.01
        Postcreep 10 (7) 10 (6)
Reflex latency, ms
    L
        Precreep 114 (14) 115 (23) 0.49 0.65
        Postcreep 115 (15) 117 (14)
    R
        Precreep 116 (17) 114 (15) 0.82 0.70
        Postcreep 115 (16) 116 (15)
Erector spinae EMG reflex amplitude, % MVC
    L
        Precreep 34 (18) 30 (15) 0.10 0.008
        Postcreep 32 (17) 28 (14)
    R
        Precreep 36 (17) 31 (16) 0.09 ≤0.001
        Postcreep 33 (15) 29 (12)
Abdominal EMG reflex amplitude, % MVC
    RA
        Precreep 14 (13) 13 (13) 0.55 0.12
        Postcreep 14 (14) 12 (12)
    OE
        Precreep 15 (15) 15 (18) 0.22 0.07
        Postcreep 15 (13) 11 (9)
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Values are means (SD). EMG, electromyography; L, left side of erector spinae; R, right side of erector spinae; MVC, maximal voluntary contraction; OE, obliquus externus; RA, rectus abdominis.

*

Based on repeated-measures ANOVA.

Experimental Pain Condition

The mean temperature needed to induce experimental low back pain was 48°C (SD = 0.9). During the experimental pain condition, participants scored their perceived low back pain with an average of 43/100 (SD = 7.5).

Erector spinae EMG reflex amplitude significantly decreased across trunk perturbation trials, regardless of the reported level of pain (the adaptation effect was only significant on 1 side, P = 0.04; Table 3). Most of the other dependent variables did not significantly change during the experimental pain condition (Table 3). Dependent t-tests revealed no significant difference in the pain condition vs. the condition without pain for the spatial distribution of erector spinae reflex activity on both the right (without pain: mean 1.09, SD 0.34; with pain: mean 1.18, SD 0.51; P = 0.34) and left (without pain: mean 1.14, SD 0.30; with pain: mean 1.14, SD 0.35; P = 0.99) sides.

Table 3.

Mean values of all dependent variables before and during experimental pain

P*
First 5 Trials Last 5 Trials Pain Adaptation
Flexion angle, °
    Without pain 5.7 (3.9) 5.2 (2.9) 0.81 0.54
    With pain 5.5 (2.7) 5.6 (2.9)
Peak velocity, °/s
    Without pain 20 (10) 18 (8) 0.60 0.47
    With pain 18 (7) 19 (8)
Time to peak velocity, ms
    Without pain 206 (67) 208 (64) 0.47 0.89
    With pain 202 (77) 199 (65)
Baseline activity, % MVC
    L
        Without pain 8 (5) 8 (4) 0.87 0.35
        With pain 8 (4) 8 (4)
    R
        Without pain 9 (6) 9 (6) 0.85 0.16
        With pain 9 (6) 9 (6)
Reflex latency, ms
    L
        Without pain 119 (22) 121 (24) 0.07 0.10
        With pain 121 (25) 128 (28)
    R
        Without pain 122 (26) 128 (32) 0.53 0.20
        With pain 123 (31) 123 (25)
Erector spinae EMG reflex amplitude, % MVC
    L
        Without pain 30 (17) 26 (13) 0.85 0.04
        With pain 31 (18) 26 (13)
    R
        Without pain 31 (16) 30 (15) 0.83 0.08
        With pain 34 (21) 28 (14)
Abdominal EMG reflex amplitude, % MVC
    RA
        Without pain 15 (16) 14 (14) 0.90 0.07
        With pain 16 (15) 14 (14)
    OE
        Without pain 13 (10) 11 (8) 0.59 0.02
        With pain 13 (10) 11 (10)
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Values are means (SD). EMG, electromyography; L, left side of erector spinae; R, right side of erector spinae; MVC, maximal voluntary contraction; OE, obliquus externus; RA, rectus abdominis.

*

Based on repeated-measures ANOVA.

DISCUSSION

The present study investigated how superficial lumbar muscles adapt after a spinal tissue creep deformation and during experimental pain while the neuromuscular system is challenged by a series of unexpected trunk perturbations. Despite an increase of pain perception during the pain condition, and an increased trunk ROM during the creep condition, the study showed that most neuromuscular outcomes were similar in all conditions. Moreover, this study is the first to show that neither experimental back pain nor creep deformation altered participants’ ability to adapt across unexpected trunk perturbation trials.

Creep Effect

A 30-min static trunk flexion was used to induce creep deformation in the lumbar passive structures. Previous studies have found that a static full-trunk flexion sustained for a period of 5–20 min was enough to induce creep deformation (McGill and Brown 1992; Shin et al. 2009). Moreover, it has been shown that creep deformation can be induced with a static flexion between 70% and 75% of full-trunk flexion lasting 30–60 min (Abboud et al. 2016a; Sánchez-Zuriaga et al. 2010).

In the present study, an increase of 4% of trunk ROM in flexion was found after the creep deformation, which is similar to a previous study using a similar protocol (Sánchez-Zuriaga et al. 2010). By contrast, results from the present study showed that trunk kinematics following an unexpected perturbation did not change under the influence of creep deformation. Results from a recent study showed that trunk posture (neutral vs. flexed) influences the level of muscle activation in the lumbar region when postural stability is challenged. When the trunk is flexed, a higher contribution of the passive system is observed (Maaswinkel et al. 2015). Sufficient stretching of passive structures within the elastic zone will trigger mechanoreceptor responses generating proprioceptive information, potentially improving sensory-motor control via appropriate and coordinated motor responses (Holm et al. 2002; Panjabi 1992a). It has been often proposed that increasing length and tension in the passive structures is associated with an increase in muscular activation to maintain joint stability (ligamento-muscular reflex; Solomonow 2006, 2009).

On the other hand, when tissue creep is present a reduction of the force transmission capabilities of the musculotendinous units could occur (Solomonow et al. 1999). Therefore, it can be hypothesized that an alternative muscle activation strategy was implemented to minimize trunk displacement when it was challenged by an unexpected perturbation (see Motor Adaptations).

In the present study, a slight increase of back muscle activity before the trunk perturbation onset was observed after the creep deformation, which supports the hypothesis that changes in muscle activity act as compensation mechanisms for spinal instability resulting from passive structure laxity (Solomonow et al. 1998). Nevertheless, once the perturbation is triggered the back muscle activity does not change between pre-and postcreep conditions as observed in this study. Previous studies failed to identify changes in muscle reflex activity when trunk muscles were preactivated before an unexpected postural perturbation (Stokes et al. 2000). Other studies suggested that increased trunk stiffness due to increased baseline activity leads to a reduction of muscle reflex activation (Granata and Rogers 2007; Shahvarpour et al. 2015). Moreover, the cocontraction of the trunk muscles (rectus abdominis, externus obliquus, and erector spinae muscles) did not increase after the creep protocol. The absence of change in muscle activity reflex after the creep protocol concurred with the fact that the passive components’ contribution to stabilize the spine is negligible, especially in the neutral zone (Panjabi 1992b; Solomonow 2006). Therefore, it can be suggested that alteration of passive components following a creep deformation does not trigger changes in back muscle activity needed to prevent spinal instability.

Experimental Pain Effect

Thermal stimulation has been used previously to activate selective nociceptive fibers (Bosshard et al. 2015; Yeomans et al. 1996). Thermal cutaneous pain has also been used previously to evoke acute low back pain in healthy participants and produce neuromuscular responses similar to the adaptations typically reported in patients with chronic low back pain (Dubois et al. 2011). In the study of Dubois et al., the authors observed a nociceptive stimulation yielding painful evaluations by both low back pain patients and healthy participants as well as typical increases in erector spinae muscle activity, often observed in patients with various levels of clinical pain.

The present study showed that trunk neuromuscular responses were similar with or without the presence of experimental back pain when the trunk was challenged by unexpected perturbation. It has been suggested that despite neuromuscular changes usually observed under the influence of experimental pain, the overall motor performance remains unchanged (Bank et al. 2013). For instance, in a recent study it was shown that pain did not interfere with global performance (movement errors) when participants walked on a treadmill at a control speed while facing a perturbation at the ankle (Bouffard et al. 2016). This could explain the absence of trunk kinematic alteration after an unexpected perturbation under the influence of pain. This behavior concurs with the minimal intervention principle, which states that the irrelevant aspects of a motor task should be left uncorrected in order to improve the resulting performance (Todorov and Jordan 2002). Therefore, it can be hypothesized that trunk movements triggered by the perturbations were too small to challenge spinal stability and that consequently no trunk kinematic adjustment was needed to optimize the neuromuscular system. As mentioned above, the magnitude of the perturbation was similar to that used in other similar trunk perturbation protocols (Abboud et al. 2016b; Radebold et al. 2000).

The presence of experimental back pain did not modify the erector spinae baseline activity. This observation is consistent with previous research (Boudreau et al. 2011; Gregory et al. 2008; Miller et al. 2013). Moreover, in a recent review it was proposed that pain has a negligible effect on the muscle experiencing it when it is at rest (Bank et al. 2013). Although lumbar muscle reflex latency is longer in patients with chronic low back pain (Abboud et al. 2017), the present study showed no difference with experimental back pain. Moreover, no change was found in EMG reflex responses. These observations may be surprising, since under the influence of experimental/acute pain, as proposed by the pain adaptation model (Lund et al. 1991), inhibition of agonist muscles is commonly described (Bank et al. 2013). However, inhibition of agonist muscles is not systematically observed in pain conditions. Hodges et al. described no consistent pattern of trunk muscle activity (flexor and extensor) adaptation under the influence of experimental back pain (Hodges et al. 2013). Moreover, the absence of EMG reflex change observed in the present study is in line with the finding of another study that used similar perturbation protocols in participants with acute low back pain (Gregory et al. 2008). Those authors also observed an increase of trunk muscle cocontractions. It has been recently suggested that an increase in trunk stiffness was also present with experimental pain and was correlated with a slight increase of trunk muscle cocontraction (Wong et al. 2016). Since spinal stiffness has been associated with spinal stability (Graham and Brown 2012), it could be suggested that the redistribution of muscle activity is enough to maintain spinal stability under the influence of experimental back pain. Moreover, since no increase in abdominal muscle activity was observed in the present study while participants were submitted to experimental back pain, it could be hypothesized that the redistribution of muscle activity occurred within the erector spinae muscle.

Motor Adaptations

To our knowledge, the present study is the first to investigate how erector spinae muscles adapt across a series of perturbation trials before and after a creep deformation protocol as well as with and without experimental low back pain. Our results showed that trunk kinematics remained constant across perturbation trials. Since participants did not change their maximal velocity after an unexpected trunk perturbation, it can be suggested that no modification of the time to peak velocity was necessary to maintain stability. This strategy was different from our previous observations, where participants took less time to stop their trunk while their maximal velocity reduced across perturbation trials (although not significant, P = 0.07) (Abboud et al. 2016b). These differences reflect the important motor redundancy provided by the trunk system to achieve a similar goal and serve as a note of caution regarding results’ generalizability when studying adaptation process in highly redundant motor systems.

As expected, without the influence of creep deformation or experimental back pain, a clear attenuation of back muscle activity was found through the repetition of the same unexpected trunk perturbation. This suggests that the CNS is able to modulate trunk neuromuscular responses based on a previous postural perturbation experience. However, when two experiences of the same unexpected trunk perturbation are partitioned by a new external condition, such as experimental pain or creep deformation, this ability is altered. It can be suggested that the learning process used by the CNS is partly reset under such circumstances. On the other hand, when a second set of the same unexpected trunk perturbation is conducted after a rest period, the CNS is still able to use the previous perturbation experience to adapt the motor output (Fig. 3). Indeed, participants continued to reduce their EMG reflex amplitude in the second series of perturbation trials in the control group. This observation confirms that the absence of erector spinae EMG reflex attenuation across perturbation trials under the influence of muscle fatigue is a consequence of muscle fatigue and not a learning effect (Abboud et al. 2016b). Interestingly, despite a lower EMG reflex value during the last perturbation trials of the control condition (without pain or before creep) compared with the first perturbation trials of the experimental condition (pain or creep), adaptations of EMG reflexes were also observed under these two experimental conditions, suggesting that participants are partially able to use across-trial redundancy to adapt their neuromuscular responses. In a recent study, it was shown that the attenuation of back muscle activity across perturbation trials was limited by the influence of muscle fatigue (Abboud et al. 2016b). Under the influence of muscle fatigue the spinal active muscle system is altered (e.g., motor unit frequency discharge) (Gandevia 2001; Taylor et al. 2016), and a migration of lumbar muscle activity occurs during a fatigue task (Abboud et al. 2014; Tucker et al. 2009). This suggests that back muscle fatigue reduces the number of available motor solutions to execute a given motor task, which could limit the ability of the CNS to use alternative motor strategies. In the present study, the spatial distribution of muscle activity was similar before and after the creep deformation, as well as with and without experimental back pain. Adaptation in muscle activity distribution within different regions of the erector spinae could be associated with changes in motor unit control in this muscle. Unlike muscle fatigue, creep deformation does not modify motor unit number availability, which may increase the number of motor solutions to achieve a desired goal. Nevertheless, when creep deformation and back muscle fatigue are combined, muscle activity spatial distribution is lower than that observed during back muscle fatigue only (Abboud et al. 2016a). It can be hypothesized that when passive components of the spine are the only altered stabilization structures trunk muscles are able to compensate for the loss, whereas when both of these components are altered trunk motor redundancy is reduced, limiting the number of motor solutions available to stabilize the spine when it is challenged. As for experimental pain, a similar level of variability, with or without pain, concurs with the model proposed by Madeleine, suggesting that acute pain leads to an increase of motor variability (Madeleine 2010). While these adaptations may have short-term benefit, in the long term these changes in neuromuscular control may have negative consequences on sensory-motor control (van Dieën et al. 2017). In light of the findings of the present study, it seems reasonable to suggest that, using the trunk system’s redundancy, the CNS is able to adapt neuromuscular responses to generate proper spinal stability based on a previous experience, even in the presence of experimental back pain or after a creep deformation.

Limitations

Potential limitations include the use of thermal cutaneous pain that may not exactly reflect clinical musculoskeletal pain. Experimental muscle pain can also be generated with intramuscular injections of hypertonic saline into muscles. However, there is some evidence suggesting that hypertonic saline can excite other motor axons (Kumazawa and Mizumura 1977; Weerakkody et al. 2003), which may alter the sensorimotor control independently from pain effects. Moreover, EMG activity from the injection site may be altered to avoid pain provocation from contraction. This effect is important because the source of nonspecific low back pain, which represents the majority of low back pain, does not necessarily originate from muscle pain. Another limitation of the present study is the absence of direct spinal tissue creep measurements and the fact that the protocol used to induce spinal tissue creep has not yet been proven to generate passive tissue creep. During the creep protocol, participants were asked to bend forward to a posture of ~75% of their maximum ROM while bracing their upper body on a table. This position might not have caused sufficient tension on posterior passive tissues of the spine. Nevertheless, previous studies showed alteration of trunk responses with a similar creep protocol (Abboud et al. 2016a; Sánchez-Zuriaga et al. 2010). Furthermore, one of the assessors was present during the entire creep protocol to verify that participants stayed in the same position. Indirect evidence, such as dose-response relationship, also supports the use of prolonged trunk flexion to create changes in passive supporting spine structures. It has been shown that creep deformation in the lumbar region increased with increasing exposure duration (Bazrgari et al. 2011; Muslim et al. 2013). In these studies, the authors used prolonged trunk flexion from 1 to 10 min to induce creep deformation and observed a significant increase of trunk flexion range of motion following the longer creep deformation protocol. Another limitation is the potential occurrence of sequence effects. A sequence effect was present across trunk perturbation trials in each condition (creep, pain). However, to minimize possible order effects of conditions, half of the participants started with the creep protocol and the other half started with the experimental pain protocol. Finally, a methodological consideration of the present study was the time window chosen to determine whether the trunk responses to a perturbation were reflex or voluntary activation. In light of a recent systematic review, it was pointed out that the authors disagreed on what should be considered as reflex responses (shorter than 120–300 ms) or voluntary movements (Abboud et al. 2017). Future studies should focus on determining standard latency values for trunk muscles.

Conclusions

The results of the present study suggest that the short-term effect on trunk neuromuscular control of creep deformation as well as experimental back pain was negligible. Moreover, similar neuromuscular adaptations between experimental back pain, creep deformation, and control conditions were present across the repetition of the same unexpected perturbation of the trunk. Finally, this study showed that the CNS chose to adopt a variable recruitment pattern of back muscle activation to face trunk perturbations under the influence of creep deformation or experimental back pain. It could be suggested that this strategy helped participants adapt across perturbation trials while maximizing motor performance.

GRANTS

This study was funded through the Natural Sciences and Engineering Research Council of Canada in the form of a scholarship.

DISCLOSURES

No conflicts of interest, financial or otherwise, are declared by the authors.

AUTHOR CONTRIBUTIONS

J.A., F.N., C. Dugas, and M.D. conceived and designed research; J.A. and C. Daneau performed experiments; J.A., C. Daneau, and F.N. analyzed data; J.A., C. Dugas, and M.D. interpreted results of experiments; J.A., C. Daneau, and F.N. prepared figures; J.A. drafted manuscript; J.A., C. Daneau, F.N., C. Dugas, and M.D. edited and revised manuscript; C. Dugas and M.D. approved final version of manuscript.

REFERENCES

  1. Abboud J, Lardon A, Boivin F, Dugas C, Descarreaux M. Effects of muscle fatigue, creep, and musculoskeletal pain on neuromuscular responses to unexpected perturbation of the trunk: a systematic review. Front Hum Neurosci 10: 667, 2017. doi: 10.3389/fnhum.2016.00667. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Abboud J, Nougarou F, Descarreaux M. Muscle activity adaptations to spinal tissue creep in the presence of muscle fatigue. PLoS One 11: e0149076, 2016a. doi: 10.1371/journal.pone.0149076. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Abboud J, Nougarou F, Lardon A, Dugas C, Descarreaux M. Influence of lumbar muscle fatigue on trunk adaptations during sudden external perturbations. Front Hum Neurosci 10: 576, 2016b. doi: 10.3389/fnhum.2016.00576. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Abboud J, Nougarou F, Pagé I, Cantin V, Massicotte D, Descarreaux M. Trunk motor variability in patients with non-specific chronic low back pain. Eur J Appl Physiol 114: 2645–2654, 2014. doi: 10.1007/s00421-014-2985-8. [DOI] [PubMed] [Google Scholar]
  5. Bank PJ, Peper CE, Marinus J, Beek PJ, van Hilten JJ. Motor consequences of experimentally induced limb pain: a systematic review. Eur J Pain 17: 145–157, 2013. doi: 10.1002/j.1532-2149.2012.00186.x. [DOI] [PubMed] [Google Scholar]
  6. Bazrgari B, Hendershot B, Muslim K, Toosizadeh N, Nussbaum MA, Madigan ML. Disturbance and recovery of trunk mechanical and neuromuscular behaviours following prolonged trunk flexion: influences of duration and external load on creep-induced effects. Ergonomics 54: 1043–1052, 2011. doi: 10.1080/00140139.2011.614357. [DOI] [PubMed] [Google Scholar]
  7. Blouin JS, Descarreaux M, Bélanger-Gravel A, Simoneau M, Teasdale N. Attenuation of human neck muscle activity following repeated imposed trunk-forward linear acceleration. Exp Brain Res 150: 458–464, 2003. doi: 10.1007/s00221-003-1466-9. [DOI] [PubMed] [Google Scholar]
  8. Bosshard SC, Stuker F, von Deuster C, Schroeter A, Rudin M. BOLD fMRI of C-fiber mediated nociceptive processing in mouse brain in response to thermal stimulation of the forepaws. PLoS One 10: e0126513, 2015. doi: 10.1371/journal.pone.0126513. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Boudreau S, Farina D, Kongstad L, Buus D, Redder J, Sverrisdóttir E, Falla D. The relative timing of trunk muscle activation is retained in response to unanticipated postural-perturbations during acute low back pain. Exp Brain Res 210: 259–267, 2011. doi: 10.1007/s00221-011-2629-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Bouffard J, Bouyer LJ, Roy JS, Mercier C. Pain induced during both the acquisition and retention phases of locomotor adaptation does not interfere with improvements in motor performance. Neural Plast 2016: 8539096, 2016. doi: 10.1155/2016/8539096. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Criswell E, Cram JR. Cram’s Introduction to Surface Electromyography. Sudbury, MA: Jones and Bartlett, 2011. [Google Scholar]
  12. Dubois JD, Piché M, Cantin V, Descarreaux M. Effect of experimental low back pain on neuromuscular control of the trunk in healthy volunteers and patients with chronic low back pain. J Electromyogr Kinesiol 21: 774–781, 2011. doi: 10.1016/j.jelekin.2011.05.004. [DOI] [PubMed] [Google Scholar]
  13. Gandevia SC. Spinal and supraspinal factors in human muscle fatigue. Physiol Rev 81: 1725–1789, 2001. doi: 10.1152/physrev.2001.81.4.1725. [DOI] [PubMed] [Google Scholar]
  14. Graham RB, Brown SH. A direct comparison of spine rotational stiffness and dynamic spine stability during repetitive lifting tasks. J Biomech 45: 1593–1600, 2012. doi: 10.1016/j.jbiomech.2012.04.007. [DOI] [PubMed] [Google Scholar]
  15. Granata KP, Rogers E. Torso flexion modulates stiffness and reflex response. J Electromyogr Kinesiol 17: 384–392, 2007. doi: 10.1016/j.jelekin.2006.10.010. [DOI] [PubMed] [Google Scholar]
  16. Gregory DE, Brown SH, Callaghan JP. Trunk muscle responses to suddenly applied loads: do individuals who develop discomfort during prolonged standing respond differently? J Electromyogr Kinesiol 18: 495–502, 2008. doi: 10.1016/j.jelekin.2006.12.005. [DOI] [PubMed] [Google Scholar]
  17. Hodges PW, Bui BH. A comparison of computer-based methods for the determination of onset of muscle contraction using electromyography. Electroencephalogr Clin Neurophysiol 101: 511–519, 1996. [DOI] [PubMed] [Google Scholar]
  18. Hodges PW, Coppieters MW, MacDonald D, Cholewicki J. New insight into motor adaptation to pain revealed by a combination of modelling and empirical approaches. Eur J Pain 17: 1138–1146, 2013. doi: 10.1002/j.1532-2149.2013.00286.x. [DOI] [PubMed] [Google Scholar]
  19. Holm S, Indahl A, Solomonow M. Sensorimotor control of the spine. J Electromyogr Kinesiol 12: 219–234, 2002. doi: 10.1016/S1050-6411(02)00028-7. [DOI] [PubMed] [Google Scholar]
  20. Kumazawa T, Mizumura K. Thin-fibre receptors responding to mechanical, chemical, and thermal stimulation in the skeletal muscle of the dog. J Physiol 273: 179–194, 1977. doi: 10.1113/jphysiol.1977.sp012088. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Larivière C, Forget R, Vadeboncoeur R, Bilodeau M, Mecheri H. The effect of sex and chronic low back pain on back muscle reflex responses. Eur J Appl Physiol 109: 577–590, 2010. doi: 10.1007/s00421-010-1389-7. [DOI] [PubMed] [Google Scholar]
  22. Lund JP, Donga R, Widmer CG, Stohler CS. The pain-adaptation model: a discussion of the relationship between chronic musculoskeletal pain and motor activity. Can J Physiol Pharmacol 69: 683–694, 1991. doi: 10.1139/y91-102. [DOI] [PubMed] [Google Scholar]
  23. Maaswinkel E, van Drunen P, Veeger DJ, van Dieën JH. Effects of vision and lumbar posture on trunk neuromuscular control. J Biomech 48: 298–303, 2015. doi: 10.1016/j.jbiomech.2014.11.030. [DOI] [PubMed] [Google Scholar]
  24. Madeleine P. On functional motor adaptations: from the quantification of motor strategies to the prevention of musculoskeletal disorders in the neck-shoulder region. Acta Physiol (Oxf) 199, Suppl 679: 1–46, 2010. doi: 10.1111/j.1748-1716.2010.02145.x. [DOI] [PubMed] [Google Scholar]
  25. McGill SM, Brown S. Creep response of the lumbar spine to prolonged full flexion. Clin Biomech (Bristol, Avon) 7: 43–46, 1992. doi: 10.1016/0268-0033(92)90007-Q. [DOI] [PubMed] [Google Scholar]
  26. Miller EM, Bazrgari B, Nussbaum MA, Madigan ML. Effects of exercise-induced low back pain on intrinsic trunk stiffness and paraspinal muscle reflexes. J Biomech 46: 801–805, 2013. doi: 10.1016/j.jbiomech.2012.11.023. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Muslim K, Bazrgari B, Hendershot B, Toosizadeh N, Nussbaum MA, Madigan ML. Disturbance and recovery of trunk mechanical and neuromuscular behaviors following repeated static trunk flexion: influences of duration and duty cycle on creep-induced effects. Appl Ergon 44: 643–651, 2013. doi: 10.1016/j.apergo.2012.12.004. [DOI] [PubMed] [Google Scholar]
  28. Nashner LM. Adapting reflexes controlling the human posture. Exp Brain Res 26: 59–72, 1976. doi: 10.1007/BF00235249. [DOI] [PubMed] [Google Scholar]
  29. Panjabi MM. The stabilizing system of the spine. Part I. Function, dysfunction, adaptation, and enhancement. J Spinal Disord 5: 383–389, 1992a. doi: 10.1097/00002517-199212000-00001. [DOI] [PubMed] [Google Scholar]
  30. Panjabi MM. The stabilizing system of the spine. Part II. Neutral zone and instability hypothesis. J Spinal Disord 5: 390–397, 1992b. doi: 10.1097/00002517-199212000-00002. [DOI] [PubMed] [Google Scholar]
  31. Radebold A, Cholewicki J, Panjabi MM, Patel TC. Muscle response pattern to sudden trunk loading in healthy individuals and in patients with chronic low back pain. Spine 25: 947–954, 2000. doi: 10.1097/00007632-200004150-00009. [DOI] [PubMed] [Google Scholar]
  32. Rainville P, Feine JS, Bushnell MC, Duncan GH. A psychophysical comparison of sensory and affective responses to four modalities of experimental pain. Somatosens Mot Res 9: 265–277, 1992. doi: 10.3109/08990229209144776. [DOI] [PubMed] [Google Scholar]
  33. Sánchez-Zuriaga D, Adams MA, Dolan P. Is activation of the back muscles impaired by creep or muscle fatigue? Spine 35: 517–525, 2010. doi: 10.1097/BRS.0b013e3181b967ea. [DOI] [PubMed] [Google Scholar]
  34. Shahvarpour A, Shirazi-Adl A, Larivière C, Bazrgari B. Trunk active response and spinal forces in sudden forward loading: analysis of the role of perturbation load and pre-perturbation conditions by a kinematics-driven model. J Biomech 48: 44–52, 2015. doi: 10.1016/j.jbiomech.2014.11.006. [DOI] [PubMed] [Google Scholar]
  35. Shin G, D’Souza C, Liu YH. Creep and fatigue development in the low back in static flexion. Spine 34: 1873–1878, 2009. doi: 10.1097/BRS.0b013e3181aa6a55. [DOI] [PubMed] [Google Scholar]
  36. Siegmund GP, Sanderson DJ, Myers BS, Inglis JT. Rapid neck muscle adaptation alters the head kinematics of aware and unaware subjects undergoing multiple whiplash-like perturbations. J Biomech 36: 473–482, 2003. doi: 10.1016/S0021-9290(02)00458-X. [DOI] [PubMed] [Google Scholar]
  37. Skotte JH, Fallentin N, Pedersen MT, Essendrop M, Strøyer J, Schibye B. Adaptation to sudden unexpected loading of the low back—the effects of repeated trials. J Biomech 37: 1483–1489, 2004. doi: 10.1016/j.jbiomech.2004.01.018. [DOI] [PubMed] [Google Scholar]
  38. Solomonow M. Sensory-motor control of ligaments and associated neuromuscular disorders. J Electromyogr Kinesiol 16: 549–567, 2006. doi: 10.1016/j.jelekin.2006.08.004. [DOI] [PubMed] [Google Scholar]
  39. Solomonow M. Ligaments: a source of musculoskeletal disorders. J Bodyw Mov Ther 13: 136–154, 2009. doi: 10.1016/j.jbmt.2008.02.001. [DOI] [PubMed] [Google Scholar]
  40. Solomonow M. Neuromuscular manifestations of viscoelastic tissue degradation following high and low risk repetitive lumbar flexion. J Electromyogr Kinesiol 22: 155–175, 2012. doi: 10.1016/j.jelekin.2011.11.008. [DOI] [PubMed] [Google Scholar]
  41. Solomonow M, Zhou BH, Baratta RV, Lu Y, Harris M. Biomechanics of increased exposure to lumbar injury caused by cyclic loading: Part 1. Loss of reflexive muscular stabilization. Spine 24: 2426–2434, 1999. doi: 10.1097/00007632-199912010-00003. [DOI] [PubMed] [Google Scholar]
  42. Solomonow M, Zhou BH, Harris M, Lu Y, Baratta RV. The ligamento-muscular stabilizing system of the spine. Spine 23: 2552–2562, 1998. doi: 10.1097/00007632-199812010-00010. [DOI] [PubMed] [Google Scholar]
  43. Stokes IA, Gardner-Morse M, Henry SM, Badger GJ. Decrease in trunk muscular response to perturbation with preactivation of lumbar spinal musculature. Spine 25: 1957–1964, 2000. doi: 10.1097/00007632-200008010-00015. [DOI] [PubMed] [Google Scholar]
  44. Taylor JL, Amann M, Duchateau J, Meeusen R, Rice CL. Neural contributions to muscle fatigue: from the brain to the muscle and back again. Med Sci Sports Exerc 48: 2294–2306, 2016. doi: 10.1249/MSS.0000000000000923. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Todorov E, Jordan MI. Optimal feedback control as a theory of motor coordination. Nat Neurosci 5: 1226–1235, 2002. doi: 10.1038/nn963. [DOI] [PubMed] [Google Scholar]
  46. Tucker K, Falla D, Graven-Nielsen T, Farina D. Electromyographic mapping of the erector spinae muscle with varying load and during sustained contraction. J Electromyogr Kinesiol 19: 373–379, 2009. doi: 10.1016/j.jelekin.2007.10.003. [DOI] [PubMed] [Google Scholar]
  47. van Dieën JH, Flor H, Hodges PW. Low-back pain patients learn to adapt motor behavior with adverse secondary consequences. Exerc Sport Sci Rev 45: 223–229, 2017. doi: 10.1249/JES.0000000000000121. [DOI] [PubMed] [Google Scholar]
  48. Weerakkody NS, Percival P, Hickey MW, Morgan DL, Gregory JE, Canny BJ, Proske U. Effects of local pressure and vibration on muscle pain from eccentric exercise and hypertonic saline. Pain 105: 425–435, 2003. doi: 10.1016/S0304-3959(03)00257-4. [DOI] [PubMed] [Google Scholar]
  49. Wong AY, Parent EC, Prasad N, Huang C, Chan KM, Kawchuk GN. Does experimental low back pain change posteroanterior lumbar spinal stiffness and trunk muscle activity? A randomized crossover study. Clin Biomech (Bristol, Avon) 34: 45–52, 2016. doi: 10.1016/j.clinbiomech.2016.03.006. [DOI] [PubMed] [Google Scholar]
  50. Yeomans DC, Pirec V, Proudfit HK. Nociceptive responses to high and low rates of noxious cutaneous heating are mediated by different nociceptors in the rat: behavioral evidence. Pain 68: 133–140, 1996. doi: 10.1016/S0304-3959(96)03176-4. [DOI] [PubMed] [Google Scholar]
  51. Zwarts MJ, Stegeman DF. Multichannel surface EMG: basic aspects and clinical utility. Muscle Nerve 28: 1–17, 2003. doi: 10.1002/mus.10358. [DOI] [PubMed] [Google Scholar]

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