Neuroscientist 2019 (Dec); 25 (6): 583–596 ~ FULL TEXT
Michael Lukas Meier, Andrea Vrana, and Petra Schweinhardt
Integrative Spinal Research,
Department of Chiropractic Medicine,
University Hospital Balgrist,
Motor control, which relies on constant communication between motor and sensory systems, is crucial for spine posture, stability and movement. Adaptions of motor control occur in low back pain (LBP) while different motor adaption strategies exist across individuals, probably to reduce LBP and risk of injury. However, in some individuals with LBP, adapted motor control strategies might have long-term consequences, such as increased spinal loading that has been linked with degeneration of intervertebral discs and other tissues, potentially maintaining recurrent or chronic LBP. Factors contributing to motor control adaptations in LBP have been extensively studied on the motor output side, but less attention has been paid to changes in sensory input, specifically proprioception.
Furthermore, motor cortex reorganization has been linked with chronic and recurrent LBP, but underlying factors are poorly understood. Here, we review current research on behavioral and neural effects of motor control adaptions in LBP. We conclude that back pain-induced disrupted or reduced proprioceptive signaling likely plays a pivotal role in driving long-term changes in the top-down control of the motor system via motor and sensory cortical reorganization. In the outlook of this review, we explore whether motor control adaptations are also important for other (musculoskeletal) pain conditions.
KEYWORDS: chronic pain; low back pain; motor control; motor cortex; muscle spindle; proprioception; somatosensory cortex
From the Full-Text Article:
Low back pain (LBP) is extremely common with a lifetime
prevalence around 75% to 84% [Thiese and others
2014] and is globally among the health conditions with
the highest numbers of years lived with disability [Vos and
others 2017]. In most instances of LBP, no underlying
pathology can be identified [Maher and others 2016],
resulting in the unfortunate diagnosis of “non-specific
LBP” (nsLBP). An acute episode of LBP spontaneously
resolves in one third of the patients within the first 3
months; however, about 65% of the patients still experience
LBP 1 year after LBP onset [Itz and others 2013].
Consequently, recurrent or chronic LBP (LBP persisting
for 12 weeks or more) is a common problem, with an
enormous individual, economic and societal burden [Hoy
and others 2014; van Tulder and others 2006]. Therefore,
advancing the understanding of factors contributing to the
chronification of LBP is a research priority [Hartvigsen
and others 2018]. Among factors such as genetic, physical
and psychosocial features, adaptions of motor control
likely play a significant role in chronic or recurrent LBP
[Hodges and others 2013] because they are associated
with several important factors contributing to LBP chronification,
including increased spinal tissue strains due to
potential loss of trunk control and enhanced trunk muscle
co-contraction, resulting in muscle fatigue [Madeleine
2010; van Dieën and others 2018b]. Both factors, loss of
trunk control and enhanced muscle co-contraction, have
been linked with sustained mechanical loading on spinal
tissues, conceivably potentiating degeneration of intervertebral
discs and other tissues [Lotz and Chin 2000; Paul
and others 2013; Urban and Roberts 2003; van Dieën and
The overarching hypothesis of this review is that
motor control adaptions induced by acute LBP play an
important role in the chronification of LBP. Following a
short introduction to human motor control and proprioception,
we summarize the findings on motor control
adaptions in LBP on the behavioral and neural level,
including (supra-)spinal and psychological contributions.
We integrate new research suggesting a powerful role of
reduced paraspinal proprioceptive input for the top-down
control of cortical sensorimotor circuits, probably associated
with neuroplastic changes. The resulting cortical
reorganization would potentially explain persistent and
dysfunctional motor control adaptions associated with
Motor Control and Proprioception
Motor control is responsible for spine posture, stability
and movement and arises from a constant interplay
between motor outputs to effectors (e.g., paraspinal muscles)
and sensory inputs (e.g., proprioception) on various
levels of the nervous system [Hodges and others 2013;
Riemann and Lephart 2002]. As described in Panjabi’s
model of spinal stability, appropriate motor control of the
trunk relies on the interplay of the passive (osteoligamentous
spinal structures), active (muscles) and control subsystems
(central nervous system), with the latter
integrating and coordinating sensorimotor information by
exerting direct control over the active subsystem [Panjabi
1992]. Human trunk posture and movement are inherently
unstable due to continuous neuromuscular noise
that needs to be controlled [Willigenburg and others
2013]. As a potential cause of low back pain, clinical
instability of the spine is defined as a failure of any of the
three subsystems leading to adaptions of the motor control
system [Hodges and others; Panjabi 2003].
Motor control adaptions are inevitably linked to adaptions
in somatosensory processing as we can only precisely
control what we can sense [Naito 2004]. Proprioception is
the key somatosensory feedback system [Gandevia and
others 2002; Sherrington 1908]. The importance of proprioception
for motor control is exemplified by patients
with a lack of proprioception due to, for example, large
fiber neuropathy [Goble and others 2011] or loss of
PIEZO2 receptor function [Chesler and others 2016].
Without visual input, these patients show impaired motor
control, including deficits in coordinated movement, force
control, and limb position sense [Chesler and others 2016;
Lajoie and others 1996; Rothwell and others 1982;
Sainburg and others 1995]. Proprioception is subserved
by mechanoreceptors on deep and superficial tissues.
Muscle spindles, located in the muscle belly parallel to the
extrafusal muscle fibers, act as the principal proprioceptors,
in addition to mechanoreceptors located in joints,
ligaments, tendons, fascia, and skin [Brumagne and others
2000; Proske and Gandevia 2012]. The important role of
muscle spindles in proprioception is illustrated by the
observation that vibration applied to a resting muscle can
produce illusions of limb movement and of displaced limb
position (mediated through primary [Ia] and secondary
[II] muscle afferents) [Burke and others 1976; Gilman
2002; Goodwin and others 1972; Proske and Gandevia
and electromyography (EMG) [Hodges and others
2003; Sohn and others 2013]. Adaptions in motor control
are also present in acute LBP patients, reflected by alterations
in the timing, magnitude and kinematics of lumbopelvic
coordination [Shojaei and others 2017a; Shojaei
and others 2017b; Sung and others 2015]. It has been suggested
that these changes, if persistent, predispose individuals
to recurrent and chronic LBP [van Dieën and
others 2017]. Indeed, compelling evidence indicates
altered motor control in chronic LBP patients based on,
for example, spine kinematics, EMG, and center of pressure
analysis [reviewed in Knox and others 2018].
Chronic LBP patients demonstrate motor control deficits
during standing and sitting [Della Volpe and others 2006;
Lafond and others 2009], during challenging tasks such
as one-legged standing [da Silva and others 2018] or during
gait and functional tasks [Christe and others 2017;
Hemming and others 2017]. Furthermore, the systematic
review by Knox and colleagues identified a delayed onset
of muscle activity with anticipatory and compensatory
postural responses to perturbations in patients with
chronic LBP [Knox and others 2018]. In sum, there is
substantial evidence for behavioral motor control adaptations
associated with LBP.
Behavioral and Motor System Adaptions in LBP
A plethora of studies indicate strong support for motor
control adaptions in LBP on a behavioral and motor system
level. Experimental LBP in healthy subjects provoked
adaptions of motor control that were characterized
by altered balance control and trunk muscle activity, captured
by changes of the center of pressure (using a foot
Nevertheless, the literature is relatively inconsistent
with respect to the nature of these motor control adaptions.
For example, in chronic LBP, spine kinematic patterns
during movement indicated a more rigid spine
[Christe and others 2016], in line with clinical observations
of a stronger coupling between thoracolumbar segments
during movement and generally less variability of
trunk movement in chronic LBP [Elgueta-Cancino and
others 2014; Moseley and Hodges 2006]. Furthermore,
using large-array surface EMG during a muscle fatigue
exercise, chronic LBP patients showed variability in
trunk muscle activity that increased less over time compared
to healthy subjects, suggesting fewer degrees of
freedom regarding trunk muscle recruitment configurations
[Abboud and others 2014]. However, the opposite
pattern of higher variability in trunk movements in
chronic LBP has also been observed [Silfies and others
2009; van Dieën and others 2018b; Vogt and others 2001].
A review on lumbar extensor muscle recruitment in acute,
subacute and chronic LBP patients highlighted high and
task-dependent variability in trunk muscle activation patterns
between and probably within individuals [van Dieën
and others 2003].
Similar to the observed variability in trunk movement
and related muscle activation patterns in individuals with
LBP, an analysis of the literature on motoneuron excitability
at cortical and spinal sites during pain indicated
inconsistent findings across studies [Hodges and Tucker
2011]. Cortically and spinally mediated changes of
motoneuron excitability during pain and nociception has
been distinguished by simultaneous recording of, for
example, the Hoffman reflex (H-reflex) and motor
evoked potentials (MEPs) at, for example, biceps or
erector spinae muscles [Hodges and Tucker 2011; Le
Pera and others 2001; Strutton and others 2005] or by
combining transcranial magnetic stimulation (TMS) at
the cervicomedullary junction (to activate the axons of
primary motoneurons) and at the primary motor cortex
(M1). The corticospinal neural drive has been reported to
be decreased in chronic LBP reflected by increased MEP
thresholds and lowered EMG activity of paraspinal muscles
following TMS over the vertex [Chiou and others
2014; Strutton and others 2005]. Similar findings of temporally
reduced MEPs of hand and arm muscles after
TMS of the primary motor cortex (M1) were reported in
a study of experimental pain in healthy subjects [Farina
and others 2001]. Interestingly, in this study, the reduction
in MEPs appeared to be caused exclusively by
supraspinal circuits because peripheral (M-wave) and
spinal cord (F- and H-waves) measures of excitability
were not affected. However, conflicting findings of
excitability changes with pain across the motor system
have been reported. MEPs, induced by TMS over M1, at
hand and biceps muscles increased during painful stimulation
[Del Santo and others 2007]. Furthermore, following
intervertebral disc lesion in pigs (damaging the
annulus fibrosis to provoke leakage of the nucleus pulposus),
presumably painful, excitability of spinal circuits
was slightly decreased but cortical excitability increased
immediately after the lesion, revealed by recording
MEPs of the multifidus muscle [Hodges and others
It is possible that some of the inconsistencies in
the literature stem from response patterns that differ
across specific muscles, even across different paraspinal
muscles [Hodges and Tucker 2011]. Recent work has
suggested a potential mechanism for increases in M1
excitability with pain: in chronic LBP, enhanced cortical
excitability of M1 was linked to a maladaptive homeostatic
mechanism (homeostatic plasticity), which is
reflected by a general disbalance of the ratio between
long-term potentials (synaptic strengthening) and longterm
depression (synaptic weakening) [Thapa and others
2018]. In line with the evidence demonstrating enhanced
cortical motor excitability in chronic LBP, patients failed
to maintain homeostatic plasticity by showing an excessive
synaptic strengthening, which was suggested as a
marker of cortical reorganization.
Today, it is clear that cortical motor circuits play an
important role in controlling trunk muscle excitability.
For a long time, it was assumed that cortical motor control
is more important for voluntary goal-directed movements
compared to “automatic” processes such as
postural adjustments and gait that have been associated
with subcortical circuits [Deliagina and others 2008].
However, evolving evidence indicates substantial cortical
motor involvement in automatic motor responses [Chiou
and others 2016; Chiou and others 2018; Gandolla and
others 2014; Petersen and others 2012]. In line with this,
TMS mapping of surface and (intra-muscular) fine-wire
EMG recordings of paraspinal muscles (multifidus and
erector spinae muscles) demonstrated a high degree of
functional specificity within M1, suggesting fine control
of segmental motion [Tsao and others 2011a]. In individuals
with chronic LBP, M1 representations (center of
gravity) of the longissimus and deep multifidus muscles
were observed to overlap, indicating less fine-grained
(“smudging”) representations of paraspinal muscles
[Tsao and others 2011b].
In addition, it has been demonstrated
that plastic changes of the trunk representation in
M1 were related to the severity of LBP [Schabrun and
others 2017; Tsao and others 2010] and shifts in the cortical
representation of trunk muscles have been associated
with deficits in postural control [Tsao and others 2008].
These changes in M1 organization seem to occur very
early as sustained experimental pain induced M1 reorganization
after 4 days, characterized by reduced intracortical
inhibition and increased facilitation [Schabrun and
others 2016]. However, similar to the reported variability
in behavioral findings and motoneuron excitability,
changes of the M1 representation in chronic LBP show
high between-subject variability [Elgueta-Cancino and
others 2018], indicating different LBP phenotypes of
motor adaption strategies.
Models of Motor Adaption in LBP
Several models have been proposed to predict the observed
variability of motor control strategies in LBP. A relatively
new model postulates a redistribution of activity within
(through changes in motoneuron recruitment) and between
muscles (e.g., increased and compensating activity of
superficial paraspinal muscles following an injury of deep
muscles), with the ultimate goal to protect tissues from
further pain and injury [Hodges 2011]. In contrast to previous
models postulating stereotypical inhibition or excitation
of muscles during pain [Lund and others 1991;
Roland 1986], the recent model accounts for the observed
differences in motor adaption strategies in pain by considering
complementary, additive or competitive effects on
spinal and supraspinal levels [Hodges and Tucker 2011].
Moreover, this model accounts for the redundancy of the
trunk motor control system that allows various muscle
recruitment configurations to achieve a certain goal
[Abboud and others 2018]. From a learning perspective,
individual-specific redistribution of muscle activity can be
explained through a reinforcement learning model [van
Dieën and others 2017]. Namely, motor adaptions due to
LBP are defined as the outcome of a learning process with
the goal to minimize a weighted sum of costs composed
of, for example, muscle activity costs, metabolic costs, or
costs associated with movement-related pain and loss of
control. The feeling of having control over trunk movement
(reward, positive reinforcement) or the reduction of
costs (e.g., movement-related pain, negative reinforcement)
will lead to the acquisition of new muscle activation
patterns [van Dieën and others 2017].
Two LBP phenotypes
representing the opposite ends of a spectrum of
motor control strategies have been suggested: Some individuals
with LBP show “tight” control whereas others
demonstrate “loose” control over trunk movement [van
Dieën and others 2018b] (Figure 1). Tight control is associated
with increased trunk muscle excitability, enhanced
muscle co-contraction and less trunk motor variability. In
contrast, loose control over trunk movement is related to
reduced muscle excitability and increased trunk motor
variability [van Dieën and others 2018b]. The reinforcement
learning model predicts that motor variability will
initially increase at the onset of LBP to allow for sufficient
degrees of freedom to adopt the least painful motor control
strategy which might lead to a normal strategy when
pain disappears [Hodges and others 2013; Madeleine and
others 2008; Moseley and Hodges 2006]. Furthermore,
increasing motor variability might prevent muscle fatigue
[Madeleine 2010]. However, in the long-term, motor
variability is expected to decrease due to increased costs
associated with loss of trunk control and pain [van Dieën
and others 2017]. This pattern of initially increased, followed
by reduced motor variability, is supported by similar
observations during the transition from acute to
chronic neck-shoulder pain [Madeleine 2010]. This is in
line with the dynamical systems theory of biological systems,
which proposes that, under certain conditions,
behavioral states switch to a new and stable movement
pattern (with less variability) when the increase of variability
reaches a critical point, reflected by a highly
unstable system [Stergiou and Decker 2011].
In the short term, motor control adaptions might have
beneficial effects by avoiding further pain or injury, either
through adopting a protective, stabilizing strategy to limit
movements (which might be painful, tight control) or
through applying a destabilizing strategy (loose control)
to limit muscle force exertion and related costs such as
metabolic costs, fatigue, and tissue loading [Ross and
others 2017; van Dieën and others 2017] (Figure 2A).
Furthermore, a loose control strategy might allow exploring
alternative and pain-free trunk motor control solutions.
However, prolonged motor control adaptions due
to LBP have been linked with permanently increased
loading on spinal tissues that either can be triggered by
excessive tissue strains due to loss of muscular control
(loose control) or by enhanced muscle co-contraction
(tight control) [van Dieën and others 2018b] (Figure 2B).
Excessive mechanical loading has been associated with
disruption of the intervertebral disc structure [Adams and
Roughley 2006; Urban and Roberts 2003], initiating a
cascade of cell-mediated responses, including cell
death [as shown in animal models; Lotz and Chin 2000],
probably leading to disc degeneration that maintains and
aggravates LBP [Lotz and others 1998; Paul and others
2013; van Dieën and others 2018b]. Furthermore, reduced
proprioceptive input (e.g., due to decreased trunk motor
variability) has been suggested to contribute to cortical
neuroplastic changes that might affect the organizational
structure in sensorimotor cortices and top-down trunk
motor control [van Dieën and others 2017].
provide an explanation for the observed changes in M1
motor maps, however, a direct link between motor control
strategies and M1 organization has not yet been
established [Elgueta-Cancino and others 2018; Goossens
and others 2018]. Furthermore, it is currently unclear
when and to which extent such alterations in M1 motor
maps are caused by impairments on the “input side,” that
is, the processing of paraspinal somatosensory inputs. As
described above, somatosensory input is an essential
component of the motor control system and particularly
proprioceptive impairment can contribute substantially to
motor control dysfunction [Borich and others 2015;
Riemann and Lephart 2002; Rosenkranz and others
2008]. In the following, we therefore summarize findings
on proprioception in LBP on a behavioral level, followed
by a discussion of potential cortical alterations induced
by altered proprioceptive input from paraspinal muscles.
Proprioceptive Impairments in LBP
On a behavioral level, LBP patients have been shown to
have impaired trunk proprioception. Individuals with
chronic LBP showed lower acuity for detecting changes
in trunk position [Lee and others 2010] and demonstrated
significantly higher trunk repositioning errors during
flexion of the back compared with pain-free individuals
[Newcomer and others 2000]. Similar to the existing literature
on motor behavior and motor system adaptions in
LBP, studies on proprioceptive function in LBP show
some heterogeneity [Hodges and others 2013]. A recent
systematic review and meta-analysis on lumbar proprioception
in LBP concluded that LBP patients indeed show
impairments in lumbar proprioception compared to painfree
individuals for active joint repositioning sense (JRS)
and detection threshold of passive motion in sitting position
[Tong and others 2017]. No effects were found for
active JRS in standing or passive JRS in sitting [Tong and
others 2017], probably because different proprioceptive
tests differ with regard to the required motor skills and
memory processes. In addition, using a force plate to analyze
postural sway on stable and unstable support surfaces,
vibratory stimulation of the triceps surae, tibialis
anterior, and paraspinal muscles revealed an altered proprioceptive
weighting in chronic LBP patients characterized
by an increased weighting of ankle proprioception
relative to trunk muscle proprioception [Brumagne and
others 2008; Claeys and others 2011]. Interestingly, in a
prospective study, a more ankle-steered proprioceptive
weighting has been identified as a risk factor for the
development of mild LBP in young individuals [Claeys
and others 2015]. However, the opposite result of no
association between proprioceptive deficits and the
development of LBP has also been reported in a study
involving almost 300 subjects [Silfies and others 2007],
emphasizing the need for more longitudinal research in
Proprioceptive information might be reduced or disrupted
as a result of traumatic damage of tissues, muscle
fatigue [Taimela and others 1999] and/or the activation of
nociceptors, which consequently interferes with motor
control [Thunberg and others 2002; van Dieën and others
2018b]. Persistent nociception leads to an enhanced activation
of the sympathetic nervous system [Nijs and others
2012], which directly innervates muscle spindles and
modulates their discharge [Radovanovic and others
2015]. Thus, it is conceivable that (physical or emotional)
stress associated with sympathetic nervous system activation
might depress the information flow from muscle
spindles, leading to deterioration of proprioceptive information
flow across the spinocortical axis. This might represent
a mechanism contributing to observed impairments
in trunk proprioception in LBP patients.
Yet, little is known about the cortical representation of
paraspinal somatosensory (in particular proprioceptive)
inputs to the primary somatosensory cortex (S1) which
play an essential role in accurate motor output [Borich
and others 2015; Riemann and Lephart 2002].
Cortical Targets of Somatosensory and Proprioceptive Input
The proprioceptive input axis to cortical targets has been
investigated in studies using muscle vibration on limbs,
primarily resulting in activation of primary sensorimotor
cortices contralateral to the stimulation site [Goble and
others 2012; Kavounoudias and others 2008; Naito and
others 2007]. However, evidence about the cortical representation
of paraspinal somatosensory inputs is scant. In
his pioneering work [Penfield 1947], Penfield identified
the hip and the shoulder on the convexity of the postcentral
gyrus and drew the back between these two areas on
the sensory Homunculus. In 2018, intracortical stimulation
in humans of BA1 in S1 identified the representations
of the thorax and abdomen to lie indeed between hip
and shoulder [Roux and others 2018] but the cortical
somatotopic representation of paraspinal proprioceptive
input along the thoracolumbar axis is still unclear and
needs further investigation. We first attempted to “map”
the lower back on a cortical level by applying manual
pressure stimuli on three lumbar segments [Boendermaker
and others 2014; Meier and others 2014]. These studies
revealed primarily activation patterns in medial parts of
S1 (Figure 3) and the secondary somatosensory cortex.
However, because manual pressure likely activated several
types of mechanoreceptors in different tissues, the
resulting cortical activation is not specifically attributable
to proprioceptive input. Furthermore, previous studies
investigating the sensory representation of the back did
not consider the heterogeneity of the S1 landscape: S1
consists of four distinct cytoarchitectonic areas, namely
Brodmann areas (BA) 3a, 3b, 1, and 2, of which each
includes a full somatotopic representation of the contralateral
body [Martuzzi and others 2014; Powell and
Animal and human studies have
revealed that body parts are represented at distinct positions
in these four subareas where BA 3a receives proprioceptive
information from muscles and joints and BA
3b, 1, and 2 process signals from the skin [Iwamura and
others 1993; Martuzzi and others 2014; Naito 2004;
Yamada and others 2016]. Nevertheless, the notion of
segregated cortical channels for proprioceptive and tactile
input has recently been challenged by research showing
that BA 3a as well as 3b respond to both types of
input, tactile and proprioceptive [Kim and others 2015].
Thus, the organizational structure of somatosensory input
from the back in S1, in particular of proprioceptive input,
is still not entirely clear. What is clear is that S1 reorganization
can lead to dysfunctions in motor output and motor
learning [Borich and others 2015] and, as detailed above,
that LBP is associated with impaired proprioception. It is
therefore plausible that degraded paraspinal proprioceptive
feedback is causally linked to impairments in motor
control in LBP via neuroplastic S1 changes [van Dieën
and others 2017]. Therefore, systematic cortical mapping
of paraspinal proprioceptive input will be essential for a
better understanding of its role in aberrant sensorimotor
integration and related potential maladaptive cortical
plasticity in chronic LBP [Makin and Bensmaia 2017;
Massé-Alarie and Schneider 2016].
Impairments of Somatosensory Input and Cortical Reorganization in LBP
In line with the notion that somatosensory input might be
a powerful driver of motor adaption and cortical reorganization,
sensory training using vibratory (i.e., stimulation
of muscle spindle afferents using vibration frequencies
around 80 Hz) stimulation of the affected hand muscles in
people with musician’s dystonia reshaped the cortical
sensorimotor organization toward a more differentiated
pattern that was associated with improved hand motor control
[Rosenkranz and others 2009]. Similarly, applying
vibration to erector spinae muscles in chronic LBP patients
significantly enhanced trunk motor control [Boucher and
others 2015]. A shifted sensory representation in S1 of
tactile input from the back was observed more than 20
years ago in a small group of chronic LBP patients by
magnetencephalography [Flor and others 1997]. As discussed
above, S1 (re)organization of proprioceptive
input from paraspinal muscle spindles is likely to be
more important pathophysiologically for the chronification
of LBP than that of tactile input [Beaudette and
The “Sensorial” Nature of M1: A Model of Cortical Reorganization in Chronic LBP?
Based on the “optimal control” model that uses internal
models based on sensory feedback, M1 has been traditionally
thought to send descending and `pure’ motor commands
(through forward connections) to peripheral
effectors to produce the desired movement [Genewein and
Braun 2012; Wolpert and Kawato 1998]. However, it has
been hypothesized that the brain recruits an alternative
approach to handle more complex muscle recruitment patterns
involved in complex and redundant systems such as
trunk motor control [Adams and others 2013; Borich and
others 2015]. In this “active inference” account of M1, M1
is suggested to model the proprioceptive consequences of
motorneuron activity rather than to simply issue motor
commands [Adams and others 2013]. The firing of alpha
motoneurons would be determined by the comparison at
the level of the spinal cord between descending proprioceptive
predictions from M1 and the proprioceptive input
from muscle spindle afferents to produce the desired (predicted)
movement trajectory. If a prediction error is present,
the discharge of alpha motoneurons is adapted until
the prediction error is zero [Adams and others 2013].
Simultaneously, gamma motor neurons optimize the sensitivity
of the muscle spindles. The proprioceptive information
resulting from muscle activity is transmitted to the
sensorimotor cortex (sensory reafference) for predictive
coding: backward projections from M1 to S1 subserve
proprioceptive predictions while forward projections from
S1 to M1 convey potential prediction errors that report the
difference between sensory information and prediction.
Potential error signals received by M1 are then used to
correct its representations so that its predictions improve
[Adams and others 2013]. In support of an active inference
role of M1, a study using functional electrical stimulation
(FES; provokes proprioceptive signaling through
sensory fiber stimulation that creates the impression of
muscle extension), functional magnetic resonance imaging
and dynamic causal modelling demonstrated that the
M1 output and the neural communication between M1
and S1 were sensitive to artificially altered proprioceptive
input during constant movement patterns [Gandolla and
others 2014]. More specifically, during FES-induced
alterations of proprioceptive signaling, a facilitatory effect
on the intrinsic connectivity of M1 to S1 was observed
(that was absent without FES), which was suggested to
reflect the updating of sensory predictions sent to spinal
motoneurons. In monkeys, M1 stimulation activated the
biceps or triceps muscles differentially dependent on the
degree of flexion of the monkey’s arm, further supporting
a role of M1 efferents in conveying proprioceptive predictions
An active inference role of M1 might have important
implications regarding motor control adaptions in the
presence of increased proprioceptive prediction errors that
might originate from reduced/disrupted proprioceptive
input, probably triggered by nociceptive input [Nijs and
others 2012; Thunberg and others 2002], enhanced activation
of the sympathetic nervous system [Radovanovic and
others 2015], muscle fatigue [Taimela and others 1999],
or reduced trunk motor variability [van Dieën and others
2017]. In principle, the central nervous system (CNS) can
minimize prediction errors in two ways:
(1) It can attempt to adapt the proprioceptive input by initiate/changing movements or redistribute muscle activity, therefore fulfilling proprioceptive predictions by spinal circuits or
(2) it can match its proprioceptive predictions (from M1) to the proprioceptive information inflow
[Adams and others 2013].
Figure 4 Text
Generally, the CNS aims to prevent passing the
prediction error to supraspinal circuits (and therefore
avoiding a correction) as the spinal circuity ought to
resolve any mismatch between descending predictions
and afferent feedback using local reflex arcs [Adams and
others 2013]. In the beginning, i.e. in acute LBP, the CNS
might be able to suppress increasing proprioceptive prediction
errors through movement/redistributing muscle
activity and increasing trunk motor variability to explore
alternative trunk motor recruitment patterns (Figutre 4A).
However, this approach might be limited when motor
solutions become less variable, as shown during the transition
from acute to recurrent or chronic LBP. In addition,
adopting a tight control strategy might additionally limit
trunk motor variability. Consequently, in this case, the
CNS might be forced to minimize proprioceptive prediction
errors by matching the descending predictions from
M1 to the reduced or disrupted proprioceptive input, probably
provoking neuroplastic adaptions in the long-term
(Figure 4B). This might provide an explanation for cortical
sensorimotor reorganization associated with a stable and
more rigid but unfavorable motor control pattern, potentially
leading to sustained increases in spinal loading,
degeneration of spinal tissues, and muscle fatigue.
Psychological Factors Contributing to the Adaptions of Motor Control in LBP
Finally, considering recent theories about motor adaption
from a learning perspective, the weighting of costs associated
with LBP might not only be driven by nociceptive
input or pain but also by pain-related cognitions [van
Dieën and others 2017]. Deficits in motor control may be
amplified or even be induced/generated by cognitiveemotional
factors such as anticipation or fear of pain
[Langevin and Sherman 2007; Tucker and others 2012].
In line with this, changes in motor unit discharge
(recorded with fine-wire electrodes in the quadriceps
muscle) during anticipation of pain were similar to
changes provoked by experimental activation of nociceptors
[Tucker and others 2012]. Furthermore, in chronic
LBP, fear of pain has been shown to alter mechanical
properties of the spine such as trunk stiffness [Karayannis
and others 2013].
Moreover, it has been shown that individuals
with high levels of pain catastrophizing tend to
adopt a tight motor control strategy when a painful stimulus
is applied, whereas those with low levels demonstrated
a loose motor control strategy [Ross and others
2017]. In line with this, in healthy subjects, it has further
been observed that negative pain cognitions are associated
with a reduction in variability of postural strategies
and stiffening of the spine (similar to those observed in
chronic LBP) that outlasted the experimental pain
[Moseley and Hodges 2006; Moseley and others 2004].
Therefore, sustained tightening of the trunk due to ongoing
anticipation of pain constitutes an important factor
that might contribute to the persistence of altered (tight)
motor control, possibly leading to recurrent and chronic
LBP in the long term due to increased spinal tissue loading,
reduced paraspinal proprioceptive input and cortical
Conclusions and Outlook
Research in the past two decades has provided important
evidence how motor control adaptions in LBP might contribute
to pain chronification through effects on spinal
tissue loading, associated itself with degeneration of
intervertebral discs and other tissues. However, the
underlying biological and psychosocial interactions are
still poorly understood and seem to vary across individuals,
reflected in the modest effect sizes of motor control
exercises, spurring a call for personalized interventional
therapies [van Dieën and others 2018a]. Yet, to unleash
the full potential of personalized treatments, more basic
research on motor adaptions in LBP is mandatory, especially
when considering the evolving evidence of cortical
circuits in driving motor control adaptions during the
course of LBP. Complementary findings from behavioral
and neuroimaging studies underscore the prominent role
of aberrant sensory processing in LBP.
novel research on the active inference account of M1, we
propose a potential mechanism how proprioceptive
impairments in LBP might ultimately force the CNS to
change its sensorimotor cortical organization. Although
the existence of different LBP phenotypes of motor control
adaptions needs further validation, a tight motor control
strategy (and probably maladaptive pain-related
cognitions) might be more prone to cortical reorganization
(compared with loose control) because of the more
strongly reduced trunk motor flexibility limiting the ability
of the CNS to increase motor variability and exploration
of new motor control patterns. Further research
efforts are necessary to clarify the functional relevance of
cortical reorganization in chronic LBP: Does it simply
represent an epiphenomenon of motor control adaption or
is it causally related to the occurrence of recurrent and
chronic LBP by reinforcing non-reversible motor control
patterns? Neuroimaging might help to reveal the potential
role of cortical markers (in particular, changes in cortical
mapping of altered paraspinal proprioceptive input) of
motor control adaptions at different stages of LBP by
incorporating biomechanical (e.g., spine kinematics) and
psychosocial (e.g., fear of movement-related pain)
Interestingly, altered motor control patterns have been
reported in other musculoskeletal pain condition, including
neck pain [Meisingset and others 2015] and knee osteoarthritis
[Tawy and others 2018]. Thus, it is possible that the
mechanisms potentially contributing to the chronification
of LBP discussed in this review might be important in
musculoskeletal pain in general. Moreover, motor control
adaptions might occur with pain irrespective of the tissue
type initially involved [Schilder and others 2012]. It is
then thinkable that, perhaps via similar mechanisms as
described here, pain that initially was not musculoskeletal
in nature leads to a secondary musculoskeletal pain problem.
This would of course aggravate and complicate the
clinical presentation of the patient, once more indicating
the importance of advancing our understanding of the
intricate interplay of pain and the motor system.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with
respect to the research, authorship, and/or publication of this
The author(s) disclosed receipt of the following financial support
for the research, authorship, and/or publication of this article:
Andrea Vrana is generously supported by ChiroSuisse and
the Foundation for the Education of Chiropractors in
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