Neural plasticity during motor learning with motor imagery practice: Review and perspectives

Abstract

In the last decade, many studies confirmed the benefits of mental practice with motor imagery. In this review we first aimed to compile data issued from fundamental and clinical investigations and to provide the key-components for the optimization of motor imagery strategy. We focused on transcranial magnetic stimulation studies, supported by brain imaging research, that sustain the current hypothesis of a functional link between cortical reorganization and behavioral improvement. As perspectives, we suggest a model of neural adaptation following mental practice, in which synapse conductivity and inhibitory mechanisms at the spinal level may also play an important role.

Full text

NEUROSCIENCE FOREFRONT REVIEW
NEURAL PLASTICITY DURING MOTOR LEARNING WITH MOTOR
IMAGERY PRACTICE: REVIEW AND PERSPECTIVES
CE
´LIA RUFFINO, CHARALAMBOS PAPAXANTHIS AND
FLORENT LEBON
*
UFR STAPS, Univ. Bourgogne Franche-Comte
´, BP 27877,
F-21000 Dijon, France
INSERM U1093, Univ. Bourgogne Franche-Comte
´, F-21000
Dijon, France
Abstract—In the last decade, many studies confirmed the
benefits of mental practice with motor imagery. In this
review we first aimed to compile data issued from
fundamental and clinical investigations and to provide the
key-components for the optimization of motor imagery
strategy. We focused on transcranial magnetic stimulation
studies, supported by brain imaging research, that sustain
the current hypothesis of a functional link between cortical
reorganization and behavioral improvement. As perspec-
tives, we suggest a model of neural adaptation following
mental practice, in which synapse conductivity and inhibi-
tory mechanisms at the spinal level may also play an impor-
tant role. Ó2016 Published by Elsevier Ltd on behalf of
IBRO.
Keywords: Motor imagery, TMS, Learning, Plasticity.
Contents
Introduction 61
What do behavioral and cognitive neurosciences reveal about
MI? 62
Motor learning with MI training 64
Optimal strategy for motor learning with MI 64
Combination of MI with other interventions 66
MI combined with physical practice 66
MI combined with action observation 66
MI combined with cortical stimulation 66
Cortical plasticity following MI practice 67
Cortical plasticity in the healthy population 67
Cortical plasticity during motor recovery 69
Conclusion and perspectives 70
Acknowledgement 71
References 71
Appendix 74
INTRODUCTION
Motor skills, such as playing piano, basketball, or writing,
are developed through extensive practice over
several years. Movement learning involves several
interconnected components: processing and collecting
sensory inputs relevant to action, applying a series of
decision-making strategies that define movement
parameters (e.g., direction, duration, force), and
activating feed-forward, reactive, and biomechanical
control processes during motor performance (Wolpert
and Flanagan, 2001). Two experimental paradigms are
frequently used to study the neural processes underlying
motor skill learning (Doyon and Benali, 2005; Shadmehr
et al., 2010 for a review): (1) motor sequence learning
with the incremental acquisition of movements in a speci-
fic behavior and (2) adaptation learning with the compen-
sation for changes in the body or environmental
dynamics. In both paradigms, several phases can be dis-
tinguished: (i) a fast phase, in which performance
improvement occurs within the first training session; (ii)
a consolidation phase, in which an enhancement of
performance occurs at least 6 h after the first practice
session; (iii) a slow phase, in which further gains can be
achieved across several training sessions; (iv) an
automatic stage, in which the motor task is performed
automatically with poor cognitive demand; and (v) a reten-
tion state, in which the motor performance can be exe-
cuted in the absence of any practice after a long delay
(Doyon and Benali, 2005; Halsband and Lange, 2006).
Physical practice is undeniably vital for the acquisition
and the consolidation of new motor skills (Robertson
et al., 2004). Two well-assessed complementary methods
for motor skill learning are action observation (Mattar and
Gribble, 2005; Naish et al., 2014 for a review) and motor
imagery – MI (Pascual-Leone et al., 1995; Gentili et al.,
2010; Gentili and Papaxanthis, 2015; Schuster et al.,
2011). During action observation, visual information
implicitly activates the so-called mirror neuron system
(e.g., Iacoboni et al., 1999; Buccino et al., 2001) and
may improve the observer’s motor planning process
(Pozzo et al., 2006; Sciutti et al., 2012). On the other
hand, MI is the explicit or implicit mental representation
of action without concomitant movements. Implicit MI is
commonly involved in mental rotation tasks, while
explicit MI is used when ones is specifically instructed to
mentally simulate an action. Different modalities frame
http://dx.doi.org/10.1016/j.neuroscience.2016.11.023
0306-4522/Ó2016 Published by Elsevier Ltd on behalf of IBRO.
*Correspondence to: F. Lebon, Universite
´de Bourgogne Franche-
Comte
´, Campus Universitaire, UFR STAPS, BP 27877, F-21078
Dijon, France. Fax: +33 3 80396749.
E-mail addresses: Celia.ruffino@u-bourgogne.fr (C. Ruffino),
Charalambos.papaxanthis@u-bourgogne.fr (C. Papaxanthis),
Florent.lebon@u-bourgogne.fr (F. Lebon).
Neuroscience 341 (2017) 61–78
61

MI: kinesthetic (based on sensory information normally
generated during actual movement), haptic (using cuta-
neous information to recreate the interaction with external
objects), visual (with external and internal perspectives),
or auditory. One can use these modalities independently
or combine them to potentiate the activation of the senso-
rimotor system during MI. Mental practice by means of MI
is increasingly used for motor learning in healthy people
(Dickstein and Deutsch, 2007) or for motor rehabilitation
in patients (Malouin et al., 2013a).
Over the past twenty years, many studies
have provided relevant information about the
neurophysiological mechanisms underlying MI.
Nonetheless, the neural stages (cortical, subcortical and
spinal) involved in MI process are mainly probed
separately. It is not clear yet whether motor learning
with MI equally affects central and peripheral neural
structures. This review aims to present recent findings
on the neural aspects following MI practice, to provide
guidelines about the strategy for motor learning with MI,
and to suggest a model of neural adaptation as a
perspective for future research. We particularly
discussed data from transcranial magnetic stimulation
(TMS) studies, supported by those recorded during
brain imaging research. TMS is a reliable and non-
invasive tool used in fundamental and clinical research
to probe the level of corticospinal excitability during MI
and the cortical plasticity after MI practice.
WHAT DO BEHAVIORAL AND COGNITIVE
NEUROSCIENCES REVEAL ABOUT MI?
For many years now, scientists have tried to understand
the functional and neural similarities between mental
and actual movements. The mental chronometry
paradigm, aiming to correlate the temporal content of
actual and mental actions, has been extensively used.
The results showed that the duration of both
movements is conventionally equivalent (see Guillot and
Collet, 2005 for a review). Regarding the neurophysiolog-
ical component, previous reviews, mainly focusing on
fMRI data, have excellently presented the neural link
between mental and actual states (He
´tu et al., 2013).
However, single-neuron recording studies showed
specific activations during MI in comparison to actual
movement (Amador and Fried, 2004; Leuthardt et al.,
2004; Anderson et al., 2011). For example, Amador and
Fried (2004) showed that the neurons in the supplemen-
tary motor area differentiated between actual and imag-
ined movements.
To extent these results, we presented TMS studies
that assessed the neural processes of MI and the
mechanisms of neural modulation following mental
practice with MI. This non-invasive technique with high
temporal resolution presents many advantages to
assess the level of corticospinal and intracortical
excitability. TMS is extensively used in cognitive
neuroscience to determine the involvement of brain
areas and the temporal specificity. In the mid-80s,
Barker et al. (1985) presented a technology designed
to stimulate cortical areas that was less painful than
electrical stimulation. The authors used a magnetic field
to activate neurons located a few centimeters under the
coil. A brief stimulation over the cortical representation
of a body part in M1 activates the corticospinal track
and induces a response in the corresponding contralat-
eral muscle. This response is called a motor-evoked
potential (MEP, see Loporto et al., 2011 for physiological
and technical details). TMS can also be placed over other
cortical areas to disrupt the activation of the targeted area
and to explore the neural network underlying a specific
behavior. Nowadays, this non-invasive technique is
extensively used in fundamental and clinical studies
and, by extension, in MI paradigms. A total of 164 articles,
published between 1995 and 2016, were found through
an online search with the PubMed (https://www.ncbi.
nlm.nih.gov/pubmed/) and Google Scholar (https://scho-
lar.google.fr/) databases, combining the terms ‘‘TMS” with
‘‘mental imagery”, ‘‘motor imagery” or ‘‘mental practice”.
We selected all articles that presented mental/motor ima-
gery and mental practice studies that used TMS as a
technique to probe the underlying neurophysiological
mechanisms (see Table A.1 in Appendix). Eighty-three
TMS papers on this topic, i.e. 50%, have been published
since 2010, showing the significant growing interest for
this research field. When placed over M1, TMS elicited
MEPs in the contralateral effector, a probe of corticospinal
excitability, mostly during explicit mental imagery (78% of
the papers; see Fig. 1) and very few during implicit mental
imagery (2.4%). To our knowledge, only five studies (3%)
measured corticospinal excitability before and after men-
tal practice with MI, controlling cortical plasticity (Pascual-
Leone et al., 1995; Bassolino et al., 2013; Leung et al.,
2013; Avanzino et al., 2015; Volz et al., 2015). Finally,
TMS placed over non-M1 areas in mental imagery studies
were used to disrupt activity in this area and to assess its
relevance to the mental task or to further understand the
neural network (e.g., Ganis et al., 2000; Lebon et al.,
2012b).
Fig. 1. Graphic distribution of transcranial magnetic stimulation
(TMS) studies in mental imagery research. Mental imagery embraces
motor imagery that includes all sensorimotor information that one can
experience when interacting with the environment and non-motor
imagery that involves any other activities that do not affect one’s
motor behavior (e.g., mental picturing or mental rotation of letters).
Explicit and implicit mental imagery is the mental representation that
one experiences consciously and unconsciously, respectively. Mental
practice is the repetition of mental representations used for learning,
training and rehabilitation. M1 = primary motor cortex; V1 = primary
visual cortex; rTMS = repetitive TMS.
62 C. Ruffino et al. / Neuroscience 341 (2017) 61–78

Single-pulse TMS over M1 is the main stimulation type
used in this field of research. Peak-to-peak amplitude of
the MEP is the most commonly reported measurement
and is used as a marker of corticospinal excitability at
the time of stimulation (Rossini et al., 1999). An increase
in the amplitude of the MEP recorded in the relaxed con-
tralateral muscle is generally observed during MI when
compared to rest (Fig. 2). This increase reflects a facilita-
tion of the corticospinal track, which is produced by a
decrease in the cortical motor threshold of the corre-
sponding muscle and/or a greater number of recruited
motor neurons (Kasai et al., 1997; Yahagi and Kasai,
1998). These corticospinal facilitatory effects indicate that
MI can induce online synaptic adaptations in M1, leading
to rapid shifts in output representation patterns (Rossi and
Rossini, 2004). It must be noted that this facilitation is
muscle-specific (Fadiga et al., 1998; Yahagi and Kasai,
1998, 1999; Rossini et al., 1999; Tremblay et al., 2001;
Facchini et al., 2002; Stinear and Byblow, 2003, 2004),
time-specific (Fadiga et al., 1998; Hashimoto and
Rothwell, 1999; Stinear and Byblow, 2003, 2004;
Stinear et al., 2006b; Levin et al., 2004), and content-
specific (Yahagi and Kasai, 1998; Li et al., 2004; Stinear
et al., 2006a; Mizuguchi et al., 2013). Indeed, MEP ampli-
tude increases only in the muscles that were functionally
related to the imagined movement (Marconi et al., 2007)
and for the period during which participants imagine the
movement. This muscle and time specificity is even more
pronounced when the imagery ability is greater (Lebon
et al., 2012a), i.e. when behavioral and psychophysiolog-
ical measurements during MI mimics those during actual
execution. Furthermore, kinesthetic imagery is more often
used in MI paradigms, since it activates the motor cortex
to a greater extent than visual imagery (Stinear et al.,
2006a). This is consistent with studies using different neu-
rophysiological techniques (e.g., Guillot et al., 2009b for
fMRI data and Stecklow et al., 2010 for EEG data).
Paired-pulse TMS was also used to assess short-
interval intracortical inhibition during MI (SICI, described
in Kujirai et al. (1993)). In this technique, two TMS pulses
are triggered over M1 with a single coil. The first sub-
threshold stimulus activates low-threshold inhibitory
inter-neurons. It is followed by a second suprathreshold
stimulus (between 1 and 5 ms) that makes the pyramidal
neurons fire. The percentage of SICI
is measured by dividing the MEP
amplitude elicited by the paired pulse
with the MEP amplitude elicited by
the single suprathreshold pulse. A
decrease in SICI was observed when
subjects imagined finger movements,
although no contraction was recorded
or expected (Abbruzzese et al., 1999;
Stinear and Byblow, 2004; Kumru
et al., 2008; Liepert and Neveling,
2009). This reduction of inhibition
within M1 could explain corticospinal
facilitation during MI (Ridding et al.,
1995).
Recently, double-cone coil TMS
protocols provided insights into inter-
hemisphere processes. For example, Lebon et al.
(2012b) stimulated the right inferior parietal lobule (rIPL)
12 ms prior to the contralateral M1. The authors used
the neuronavigated technique (TMS combined with MRI
data) to spot rIPL and the optimal scalp position in M1
(motor hotspot). They observed during MI a decrease in
MEP amplitude after the double stimulation, when com-
pared to MEP amplitude after a single TMS over M1.
These results support the idea that rIPL forms part of a
distinct inhibitory network that may prevent unwanted
movement during imagery tasks. However, this inhibitory
process may also involve other cortical and subcortical
areas (see Guillot et al., 2012 for a review). For example,
Lotze et al. (1999) found a differential activation in the
cerebellum during MI and actual execution: the greater
activation of the posterior lobe during MI may be involved
in movement inhibition while imagining.
Finally, another TMS technique, known as cortical
mapping, is able to assess the cortical (re)organization
of M1 during a specific task or after an event (motor
learning or injury, see Tyc and Boyadjian, 2006, for a
review). In this technique, a TMS map is generated by
measuring the amplitude of MEPs evoked at an identified
scalp site and quantifying the intensity and volume of the
activation (e.g., Brasil-Neto et al., 1993; Thickbroom
et al., 1999). A grid is positioned over M1 and centered
on the motor hotspot of the targeted muscle. Each point
of the grid is stimulated via the TMS coil and the potential
response is measured at the periphery. Note that the
number of, and the distance between, stimulation sites
vary across studies. Up to now, very few studies have
used this technique to assess cortical organization during
MI (e.g., Vargas et al., 2004; Marconi et al., 2007;
Bassolino et al., 2013). For example, Marconi et al.
(2007) mapped out the cortical representation of hand
and forearm muscles while imagining (or observing)
repeated opposition of the thumb and the little finger.
TMS mapping of the right and left hemisphere was per-
formed when participants imagined or observed move-
ments of the left and right hand, respectively. The
authors used a grid, with 49 points equally spaced by
1.5 cm, along the medio-lateral and the antero-posterior
axes. They measured the mean map area, defined as
the number of scalp positions stimulation of which evoked
Fig. 2. Muscle-specificity of corticospinal excitability. Motor-evoked potentials increased in flexor
carpi radialis (FCR), but not in extensor carpi radialis (ECR), during imagery of hand flexion
(courtesy of Kasai et al. (1997)).
C. Ruffino et al. / Neuroscience 341 (2017) 61–78 63

MEPs in the studied muscle, and the mean map volume,
set as the sum of MEP amplitude from all sites showing
MEPs in all participants. They found that MI and action
observation increased map area and map volume, when
compared to rest, in the prime mover (Opponens Pollicis)
and in the synergist muscles (forearm muscles) only. The
effect was even more marked in the left hemisphere. The
authors also observed a functional overlap in the cortical
representation of different muscles across tasks (rest,
MI and action observation; see Fig. 6 in Marconi et al.,
2007). They concluded that both MI and action observa-
tion do not change single muscle motor responses and
that the hand/forearm muscle maps extensively overlap
during motor-cognitive tasks. Interestingly, Vargas et al.
(2004) demonstrated that the cortical map reflects the
interference between the hand posture and the mental
simulation of a hand movement. When the posture was
compatible with the imagined movement, the cortical
map area in M1 was more extended when compared to
rest. The inverse pattern was observed for posture incom-
patible with MI. This modulation seems to result from the
interaction between the facilitatory effects driven by MI
and the hand-shaping effects driven by proprioceptive
information (Vargas et al., 2004). This increase in
excitability may relate to the fast phase of motor learning,
when one explicitly focuses on the components of the
movement.
The above-referenced papers suggest that the motor
cortex integrates internal (e.g., kinesthetic, haptic) and
external (e.g., visual, contextual) information to create a
neural representation of the simulated action. These
components may explain the benefits of MI during motor
learning.
MOTOR LEARNING WITH MI TRAINING
The literature in sport psychology has provided several
years ago relevant information about the positive effects
of MI practice on motor performance (see Feltz and
Landers, 1983; Driskell et al., 1994, for meta-analysis).
Athletes and musicians extensively use mental practice,
in addition to physical practice, to improve their dexterity
(Jeannerod, 2006). Mental practice with MI improves sev-
eral aspects of motor performance, such as muscle
strength (see, Yue and Cole, 1992; Ranganathan et al.,
2004), movement speed, accuracy and variability
(Pascual-Leone et al., 1995; Gentili et al., 2006, 2010;
Gentili and Papaxanthis, 2015). Recently, Schuster
et al. (2011) reported the characteristics of successful
MI interventions in five disciplines (sport, medicine, psy-
chology, education and music) from 133 studies. Benefits
after MI training occurred mostly in motor and strength-
related tasks, and with participants of both genders, aged
between 20 and 29 years (see Tables 3–7 in Schuster
et al., 2011, for an overview of MI training studies).
Interestingly, MI benefits rely on specific characteristics
such as the imagery modality (kinesthetic or visual), the
isochrony between imagined and actual execution, or
the environment in which the intervention is performed.
Several models offer a detailed description of the
key-components of MI content (e.g., the PETTLEP model,
Holmes and Collins, 2001; the MIIMS model, Guillot and
Collet, 2008). For example, Holmes and Collins (2001)
introduced the PETTLEP framework, building on findings
in the functional neuroscientific research literature and
experience in sport psychology. This method aims to facil-
itate designing MI interventions for athletes, and com-
prises seven components (physical, environment, task,
timing, learning, emotion and perspective). All published
experiments using the PETTLEP model indicated a posi-
tive effect of MI practice on performance (e.g., Smith
et al., 2008; Wakefield and Smith, 2009; Wright and
Smith, 2009).
Despite the fact that extensive proof exists
demonstrating the positive effects of mental training on
motor performance, little is known about the neural
origins of this benefit. The lack of information may be
due to the complexity of the motor tasks (e.g., mostly
whole-body movements) and the reported variables
(such as successful attempts at basketball shoots,
rather than analytical data from movement kinematics
and EMG). To fill this gap, recent studies, especially
over the past five years, have focused on simpler tasks
involving distal muscle movements and have used
behavioral and physiological recordings (e.g., mental
chronometry, kinematics, electrooculography) to infer
modulations of the nervous system. For example, Gentili
et al. (2006, 2010) conducted a couple of experiments
in which mental training aimed to improve movement
speed. Both experimental designs involved a target-
aiming sequence (from 1 to 11) that required arm move-
ments. The aim of the experiment was to reach with the
index the targets from 1 to 11 as fast as possible
(Fig. 3A). Participants were instructed to actually perform
the sequence (PP Group), to imagine themselves per-
forming it (MP Group), to train their eyes on the target
without moving their arm or imagining moving it (AC
Group), or to remain at rest (PC Group). In post-test ses-
sions, hand movement duration and peak acceleration
decreased and increased, respectively, only after physical
and MI practice (Fig. 3B). Interestingly, the authors also
observed a partial learning generalization, namely an
enhancement of motor performance for the non-training
sequence (from target 10 to 1). Finally, trial-by-trial
recordings showed that gains during mental practice fol-
lowed a similar asymptotic learning curve as seen during
physical training (Gentili et al., 2010). Recently, Gentili
and Papaxanthis (2015) demonstrated the superiority of
the dominant arm in motor learning with mental practice
for the same speed/accuracy trade-off task. The perfor-
mance increase was smaller in the non-dominant arm fol-
lowing acute MI training. The specific adaptations during
motor learning with mental practice have to be considered
in further MI research/intervention.
Optimal strategy for motor learning with MI
The different models (PETTLEP or MIIMS) consider the
parameters for which MI is efficient (see above). Recent
findings provided additional information aimed to perfect
the optimal strategy for motor learning with MI.
Heremans et al. (2011) investigated the functional role
of eye movements during MI practice of a speed-
64 C. Ruffino et al. / Neuroscience 341 (2017) 61–78

accuracy task (Fitts’ task). During a four-day training, par-
ticipants were required to imagine themselves aiming at
several targets with their non-dominant hand, either with
their eyes fixed or with no particular instructions about
eye movements in order to measure their spontaneous
eye-movement behavior. A third control group received
no training. The results showed that movement duration
decreased over time in all groups. Task accuracy and effi-
ciency, however, was enhanced to a greater extent after
MI training, and even more when participants followed
the trajectory with their eyes while imagining. The authors
concluded that eye movements during MI practice
affected the spatial parameters of the trained movement
only, thus confirming previous results that reported no
effects of eye movements on temporal parameters
(Gueugneau et al., 2008; Debarnot et al., 2011). Indeed,
Gueugneau et al. (2008) found that eye movements dur-
ing MI were not necessary to preserve the temporal sim-
ilarities with actual movement production. Interestingly,
Heremans et al. (2011) tested the intermanual transfer
of MI practice by measuring the performance of the
untrained (dominant) hand. They found that the greatest
performance gains appeared for the group of MI practice
accompanied by eye movement. The authors concluded
that eye movements during MI practice have an effect
on the central movement representation of a coordination
pattern. Altogether, during the learning process with MI
practice, the central nervous system may integrate eye
movements as an input to the internal predictive model,
and thus facilitate the accuracy of MI. The benefits of
mental practice may partially stem from the so-called
efferent copy, reflected in the activations of the motor
cortex. On the basis of an efferent copy of the motor
command and the actual state of the limb, the brain can
predict the future state of the limb – predicting the
consequences of a motor command
is called a forward model – and thus
improve motor performance and
recall movement parameters once
instructed to actually perform the
action (Wolpert and Flanagan, 2001).
Interestingly, some studies
highlighted the positive effects of
sleep after MI practice on memory
consolidation (Debarnot et al., 2009a,
b, 2010, 2011). For example, Debarnot
and colleagues found that a night’s
sleep (2009a) and a daytime nap fol-
lowing MI (2011) elicited improvement
in performance (accuracy and move-
ment duration) in a finger sequence
task, reflecting a significant offline con-
solidation process. By contrast, a com-
parable interval of time during the
daytime (without intervening sleep)
did not result in any performance
gains. Overall, these results reinforce
the idea that performance improve-
ment following MI are somewhat
sleep-dependent, thus suggesting that
a night’s sleep after MI practice results
in similar motor memory consolidation as when following
physical practice.
Another important parameter to consider before
starting a mental training is the duration of the session.
Indeed, Gentili et al. (2010) showed that the concentration
of the subjects decreases after 60 imagined movements’
repetitions. Although a mental training session does not
appear to induce neuromuscular fatigue (Rozand et al.,
2014), a recent study demonstrated that a prolonged
motor imagery session decrease the motor imagery accu-
racy (Rozand et al., 2016). The authors observed an
increase of imagined movement duration, after 100 repe-
titions, and this augmentation could be explained by the
emergence of mental fatigue. Surprisingly, the fatigue
was not observed when actual movements were inserted
between imagined movements. These results provide
valuable information on the maximum number of imag-
ined repetitions and on the prevention of mental fatigue
during MI practice.
Finally, the design of MI intervention is of importance
regarding the potential benefits of mental practice.
Debarnot et al. (2015) compared variable and constant
MI practice on visuomotor task performance. They found
that alternating the test task with similar imagined move-
ments but with different sequences induced a greater con-
solidation and a better transfer to novel sequence, after a
night’s sleep. In addition, motor learning with MI appears
to provide greater benefit in complex tasks than in simple
ones (Allami et al., 2008). These authors observed greater
motor performance enhancement when the difficulty of the
task increased, promoting greater potential gain.
A variable MI intervention oriented for complex motor
tasks and performed preferentially during late morning or
mid-afternoon may be the optimal strategy to achieve the
greatest benefits. The consolidation process may be
Fig. 3. Improvement of motor performance after motor imagery practice. The material and results
of Gentili et al.’s study (2006) are graphically represented here. (A) Material: the aim of the study
was to reach with the index the targets from 1 to 11 as fast as possible. (B) Results: the
approximate gains observed in the study are represented. The authors found a decrease of
movement duration and an increase of peak acceleration, only for the Physical (PP) and the
Mental Practice (MP) group. AC: active control group; PC: passive control group.
C. Ruffino et al. / Neuroscience 341 (2017) 61–78 65

prominent after a night’s sleep, supporting the neural
plasticity hypothesis induced by mental practice. To
further support the benefits of MI training, it is of
importance to probe the cognitive changes associated
with behavioral modulations in healthy subjects and
patients.
COMBINATION OF MI WITH OTHER
INTERVENTIONS
Above, we reviewed the benefits of mental practice with
MI on performance improvement. Some authors also
focused on the combination of MI with different
interventions, to further understand the contribution of
such techniques to cortical reorganization and motor
learning.
MI combined with physical practice
There is now growing evidence that a combination of MI
and movement execution induces greater, if not
equivalent, changes than mental or physical training
alone (e.g. Jackson et al., 2004; Vergeer and Roberts,
2006; Allami et al., 2008; Avanzino et al., 2009; Smith
et al., 2008, 2009). For example, Frank et al. (2014),
studying novice golfers, compared their putting perfor-
mances and their mental representation structures follow-
ing physical, mental or combined training. The authors
suggested that ‘‘mental practice promotes the cognitive
adaptation process during motor learning, leading to more
elaborate representations than physical practice only”. To
provide important information about the repartition and
the proportion of actual or imagined movements during
motor learning, Allami et al. (2008) compared, for a fixed
number of trials, different percentages of imagined move-
ments (0%, 25%, 50%, and 75%) completed by actual
execution for the remaining trials. The authors found that
the greater the number of imagined movements (distribu-
tion of 50% and 75% imagined trials), the greater the
motor improvement, especially when the task was
difficult.
Such a combined intervention is predominant in
rehabilitation studies, in which patients follow the
conventional recovery process. In these studies, the
experimental group is instructed to mentally rehearse
the movements of their affected limb and the control
group to perform a neutral cognitive task (Guillot et al.,
2009a, with burn patients; Page et al., 2001; Jackson
et al., 2004; Malouin et al., 2004, with stroke patients;
see Braun et al., 2006, and Malouin et al., 2013a for
reviews). In the majority of the studies mentioned above,
combined intervention led to superior motor recovery.
However, this positive outcome needs to be put into per-
spective. Malouin et al. (2013a) published a critical review
of the factors influencing benefits derived from mental
training, in terms of adherence to the training, the dose
of MI intervention, the relaxation component, the out-
comes measured, the group heterogeneity, the selection
of patients and the nature of MI instructions. The benefits
of MI delivery will only be relevant, especially in a clinical
environment, once all the components have been clearly
described and their respective efficacy understood. To
achieve a better performance with MI practice, Malouin
et al. (2013a) recommended first familiarizing the partici-
pants with MI. It seems also interesting to associate MI
with physical practice and to add sessions of self-
practice to increase the number of repetitions.
MI combined with action observation
During the 90s, a group of Italian scientists discovered
mirror neurons in the motor cortex of monkeys. These
neurons are activated both during actual execution and
during observation of the same task (Gallese et al.,
1996; Rizzolatti et al., 1996). In human studies, it has
been found that MEPs in hand muscles increased when
subjects observed hand movements of another subject
(e.g., Fadiga et al., 1995; Maeda et al., 2002). Interest-
ingly, MI and action observation encompass similar neural
processes, such as muscle-specificity. Gangitano et al.
(2001) showed that an increase in MEPs was closely
related to the different phases of hand flexion/extension:
greater MEPs in hand flexor muscles only during observa-
tion of the flexion phase. Interestingly, Sakamoto et al.
(2009) found that the combination of MI and observation
increased MEPs to a greater extent. This effect was only
observed when the two interventions were congruent.
More recently, Wright et al. (2014) showed that the facili-
tation of corticospinal excitability during the combined
condition was muscle-specific, i.e., only present in the
muscle involved in the task.
In their review, Vogt et al. (2013) highlighted the ben-
efits of combining MI and action observation for motor
performance, but also noticed that only few studies
explored their interaction. The authors suggested three
kinds of combination. First, during congruent MI and
action observation, the observer imagines the action,
while observing a third person performing the same type
of action. This combination may represent the most prac-
tically relevant scenario, and seems to induce stronger
activations in a number of execution-related areas
(Macuga and Frey, 2012). Secondly, one could imagine
an action in response to an observed movement, a com-
bination called coordinative MI and observation, also
known as joint action. This approach would reflect, to a
greater extent, daily interactions during which a reaction
more than an imitation is expected. Finally, conflicting
MI and action observation may be used to further under-
stand the biases effect of MI on observed actions, and
inversely. These different types of combination could offer
a novel approach, with a view to finding other applications
in sport, occupational therapy, and neurorehabilitation
(Vogt et al., 2013).
MI combined with cortical stimulation
In the case of motor impairment following central or
peripheral damage, functional rehabilitation through
physical execution is challenging and demanding. One
solution is to ‘boost’ activation of the motor network and
to potentiate functional reorganization. Recent
techniques, such as repetitive TMS and transcranial
direct current stimulation (TDCS), are relevant enough
to potentiate M1 and facilitate neuroplasticity during
66 C. Ruffino et al. / Neuroscience 341 (2017) 61–78

motor (re)learning (Reis and Fritsch, 2011). TDCS is a
non-invasive brain stimulation technique that applies a
weak direct electrical current via the scalp to modulate
cortical excitability in the human brain in a painless and
reversible way (Nitsche and Paulus, 2000). The current
can either hyperpolarize (cathodal stimulation) or depolar-
ize (anodal stimulation) neuronal membranes. Foerster
et al. (2013) investigated the association of MI practice
and TDCS on motor performance improvement. MI ses-
sions were accompanied with sham or active anodal stim-
ulation over the right supplementary motor area, right
premotor area, right cerebellum, right M1 or left dorsolat-
eral prefrontal cortex. The authors observed greater
motor improvement in the left (non-dominant) hemibody
after mental practice with anodal stimulation only over
right M1 and left dorsolateral prefrontal cortex. These
findings highlight the importance of the activation of those
areas in the long-term potentiation-like processes associ-
ated with motor learning following mental practice. More
recently, Saimpont et al. (2016) also studied the combina-
tion between MI practice and TDCS, on a finger tapping
task. As for the previous study, the application of electrical
stimulation by TDCS during MI practice induced greater
effect than MI practice alone or TDCS alone. More inter-
estingly, these effects remained observable 90 min after
the end of training. Although the combination of MI with
cortical stimulation did not contribute to a larger number
of publications, interest in this intervention may help to
further understand the neural mechanisms underlying
MI and to determine the most relevant way to enhance
motor performance following mental practice with MI.
CORTICAL PLASTICITY FOLLOWING MI
PRACTICE
Cortical representations over a lifetime are not fixed but
highly dynamic (Sanes et al., 1988; Buonomano and
Merzenich, 1998; Rossini et al., 2003). In response to
peripheral and central inputs and outputs, the architecture
of neural connections is continuously being reorganized.
Therefore, experience can modify brain structure
(Mulder, 2007) and constitutes an important component
in learning and, more especially, during recovery after
neural damage. The decrease of afferent information sent
to the brain, following disuse or impairment (e.g. deaf-
ferentation), induces a reduction in size of the muscle
topographical representation in the somatosensory
(Merzenich et al., 1983) and motor cortex (Avanzino
et al., 2011). These findings have been replicated exten-
sively (see Allard et al., 1991; Brasil-Neto et al., 1993;
Merzenich and Jenkins, 1993). Sensorimotor adaptations
during MI training reveal the integration of information
from the environment to construct and modulate in real-
time the motor program, even in the absence of voluntary
movement. Michel et al. (2013) showed that prism adap-
tation also occurred when participants imagined arm
pointing movements. This was testified by significant
after-effects following prism exposure associated with
mental practice. Using force field perturbation, Anwar
et al. (2011), Anwar and Khan (2013) found that MI
training induced greater after-effects and reduced muscle
co-contraction. The authors suggested that MI training
may facilitate motor learning and could be used to
increase the rate of adaptation. These findings indirectly
demonstrate cortical plasticity due to mental practice. In
this following section, we specifically focused on corti-
cospinal reorganization related to mental practice in
healthy participants and patients.
Cortical plasticity in the healthy population
Pascual-Leone et al. (1995) were the first to show cortical
reorganization induced by mental practice. Their study is
still widely quoted when reporting MI benefits on motor
performance. The authors used the TMS technique to
map the primary motor cortex area targeting the contralat-
eral hand muscles before and after a 5-day learning per-
iod. The task relevant to our topic consisted in repeating a
5-finger exercise on the piano in time with a metronome.
During 2-h practice sessions, participants were instructed
to either actually perform the task or to visualize their fin-
gers performing the exercise and to imagine the sound.
The performance of each participant was tested daily
and followed by TMS mapping. After 5 days of training,
both groups showed progressive skill improvement, testi-
fied by the reduced number of errors and the reduced
variability in the intervals between key presses. Similarly,
cortical representation of long finger flexor and extensor
muscles in contralateral M1 increased after actual and
mental practice (Fig. 4). This finding suggests that mental
training with MI produces cortical changes comparable to
those elicited through physical practice (Pascual-Leone
et al., 1995). An extension of this experiment is discussed
below.
To support these findings, Avanzino et al. (2015)
tested cortical plasticity in M1 following mental practice,
using the paired associative stimulation (PAS) technique.
This intervention consists in repeating the combination of
peripheral nerve stimulation and TMS. The inter-stimulus
interval of 10 and 25 ms reduces (long-term depression-
like plasticity, LTD) and increases (long-term
potentiation-like plasticity, LTP) corticospinal excitability,
respectively (Stefan et al., 2000, 2002; Ziemann, 2004).
Participants were instructed to actually or mentally repeat
finger opposition as quickly as possible during an acute
training session. Speed rate increased after both physical
and MI practice. The authors observed a reversal of the
PAS25 effect from LTP-like plasticity to LTD-like plasticity
following physical and MI practice. Interestingly, LTD-like
plasticity (PAS10 protocol) increased after physical prac-
tice, while it was occluded after MI practice. These results
reveal that, in addition to cortical reorganization, MI prac-
tice strengthened the synaptic connectivity (see
Rosenkranz et al., 2007 for actual motor learning).
Imaging studies (PET and fMRI) assessing the
hemodynamic changes in the brain further support
cortical reorganization following MI practice. For
example, Jackson et al. (2003) used a PET scan to demon-
strate that learning a sequential motor task through MI and
physical practice induces similar cerebral functional
changes, i.e., increased activation of the orbitofrontal
cortex and a decrease in the cerebellum. Moreover, the
findings concord with the hypothesis that MI practice
C. Ruffino et al. / Neuroscience 341 (2017) 61–78 67

improves performance, at least initially, by acting on the
preparation and anticipation of movements rather than
on execution per se (Jackson et al., 2003). Interestingly,
Lafleur et al. (2002) observed changes bilaterally in the
dorsal premotor cortex and cerebellum, and in the left infe-
rior parietal lobule during the early phase of physical learn-
ing. However, after the end of training, most of these brain
regions (e.g., cerebellum and dorsal premotor cortex) were
no longer significantly activated, suggesting that they are
critical for establishing the cognitive strategies and motor
routines involved in early sequence learning (Lafleur
et al., 2002). On the contrary, cortical activation after prac-
tice increased bilaterally in the medial orbitofrontal cortex
and striatum, as well as in the left rostral portion of the ante-
rior cingulate and a different region of the inferior parietal
lobule. The authors suggested that these structures play
an important role in the development of a long-lasting rep-
resentation of the movement sequence. Interestingly, a
similar pattern of dynamic changes was observed in both
phases of learning during MI practice. This latter finding
suggests that the cerebral plasticity
occurring during incremental acquisi-
tion of a motor sequence executed
physically is reflected in the covert pro-
duction of this skilled behavior using
MI (Lafleur et al., 2002). Similar results
were observed by Lacourse et al.
(2004). The authors compared the
functional reorganization of the cortex
after one week of intensive training of
mental and physical sequential move-
ments. Following MI practice, motor
performance improvement was
accompanied by activations of the
cerebellar, premotor and striatal
areas, while physical practice showed
increased activation in the striatal area
and decreased activation in the cere-
bellum. The principle of functional
equivalence (Jeannerod, 1994)
appears to extend from novel learning
to skilled learning phases for both
upper and lower limb movements
(Lacourse et al., 2005).
Dynamic changes in motor
behavior may be reinforced by
sensorimotor inputs evoked by overt
activation performed after mental
practice. In the study by Pascual-
Leone et al. (1995), the MI group
showed a significant increase in per-
formance after 5 days of training, but
this improvement was even greater
for the physical group. However, no
neurophysiological differences were
observed between the two groups
after 5 days of training. The difference
between behavioral and neurophysio-
logical data might be explained by the
limits of the TMS technique to identify
fine neural changes that could explain
performance differences. Studies using PET (Lafleur
et al., 2002; Jackson et al., 2003) or fMRI (Lacourse
et al., 2004) observed small but distinct differences in
intensity and location of brain activations between physical
and MI training. These differences in activation and perfor-
mance may arise from the absence of sensory feedback
while imagining. Pascual-Leone et al. (1995) showed an
equivalent performance between a physical and an MI
group, when the latter performed a 2-h physical practice
at the end of the fifth day of MI practice. This highlights
the importance of additional sensory feedback for the
consolidation of neural modifications induced by mental
training. When participants were unable to move after
imagining, no such cortical modulations were observed
(Crews and Kamen, 2006). Bassolino et al. (2013) showed
that the cortical map of the first dorsal interosseous mus-
cle, assessed by TMS, was reduced after 10 h of immobi-
lization of the hand and the forearm, even if participants
imagined moving their hand during the immobilization
period. This result supports the hypothesis of an
Fig. 4. M1 plasticity after mental practice measured by TMS. After physical and mental practice of
finger-sequence task, the authors observed a larger cortical map representing the long finger
flexor and extensor muscles in contralateral M1 (courtesy of Pascual-Leone et al. (1995)).
68 C. Ruffino et al. / Neuroscience 341 (2017) 61–78

afference-dependent relationship between MI practice
and cortical plasticity. In contrast, Clark et al. (2015)
recently showed that MI training reduced strength loss
and decreased the attenuation of voluntary activation nor-
mally induced by a four-week immobilization of the wrist.
The difference in the results in the studies of Bassolino
et al. (2013) and Clark et al. (2015) may be due to the type
of movements, object grasping in the first and grip force
with a high level of muscle contraction in the second study.
Recent studies have shown gradual activation of the corti-
cospinal track with an increasing level of imagined con-
tractions (Mizuguchi et al., 2013 and Helm et al., 2015).
Activation of the motor cortical regions via strong imagined
contractions may attenuate weakness and modulate neu-
rophysiological responses, by maintaining normal levels of
inhibition (Clark et al., 2015).
Cortical plasticity during motor recovery
Richardson (1964, 1967) first discussed the possibility of
using mental practice through MI as a viable technique
for physiotherapists in the motor rehabilitation process.
Recently, several review articles listed MI interventions
in various forms of neurological disorder (for example,
stroke, Parkinson’s disease, spinal cord injury, amputa-
tion) and discussed the benefits of mental training in motor
performance improvement (Jackson et al., 2001; Braun
et al., 2006; Sharma et al., 2006; de Vries and Mulder,
2007; Dickstein and Deutsch, 2007; Mulder, 2007;
Garrison et al., 2010; Malouin et al., 2013b) or presented
changes in MI ability associated with motor impairment
(Simmons et al., 2008; Malouin and Richards, 2010;
Guillot et al., 2012). In numerous studies, MI rehearsals
induced greater motor improvement or at least a reduction
of the decline.
In this review, we have focused specifically on the
engagement of the motor network during MI in patients
and the cortical reorganization facilitated by mental
practice after impairment. While it is well-established
that MI training induces neural plasticity during the
recovery period, less is known about the origin of this
modulation and its link with motor rehabilitation. Kaneko
et al. (2003) studied, in eight orthopedic patients, corti-
cospinal and spinal excitability after immobilization with
splints for 3–6 weeks, at rest, while imagining, or during
10% maximum voluntary contraction. After immobiliza-
tion, the authors reported a decrease of MEP amplitude
during MI, without changes in spinal excitability. This
result suggests that a cortical reorganization following
immobilization may impact the capacity to reactivate M1
during MI. More recently, Hovington and Brouwer
(2010) assessed the engagement of the corticospinal
network in stroke patients during MI accompanied by
visual or auditory cues, or both. The authors showed that
cued MI facilitated MEPs associated with healthy and
paretic muscles related to the imagined task. These find-
ings suggest that MI may integrate the feedbacks
induced by sensory cues to facilitate the cortical
reorganization.
To better understand the plasticity of the corticospinal
network, Cicinelli et al. (2006) mapped out finger
representation in the affected and unaffected hemi-
spheres (after stroke), at rest and while imagining. The
authors found that MI induced an enhancement of the fin-
ger map area and volume in both hemispheres in a way
that partly corrected the abnormal asymmetry between
affected and non-affected hands seen in the rest condi-
tion. These findings indicate that these patients were able
to recruit the corticospinal circuit relative to the prime
mover when imagining, whatever the stroke lesion loca-
tion. However, an inability to image any movement after
stroke has been reported in specific patient cases. This
cognitive impairment is known as ‘chaotic motor imagery’
(Sharma et al., 2006). The authors defined it ‘‘as an
inability to perform motor imagery accurately or, if having
preserved accuracy, demonstration of temporal uncou-
pling”. Chaotic motor imagery may be limb-specific,
affecting distal but not proximal movement in patients with
parietal damage (Sirigu et al., 1996). It would be of
interest to determine whether the inability to imagine
movements in these patients reflects inactivation of the
motor neural network. Indeed, it might be essential to
determine the capacity of patients to generate properly
actual movements and to evaluate the potential for corti-
cal reorganization before integrating these patients into
rehabilitation programs based on mental practice.
Few studies demonstrated the reorganization of M1
with TMS mapping at rest following disuse with no
intervention. Liepert et al. (1995) showed a decrease in
map areas at rest after disuse of the targeted muscle.
The area reduction was correlated to the duration of immo-
bilization. In contrast, Zanette et al. (1997) observed
enhanced motor excitability (in area and volume) after
upper limb immobilization in patients with unilateral wrist
fracture. They hypothesized that the discrepancy between
the two studies may be related to the persistence of pain,
to the different durations of immobilization, or to the body
part affected. In those cases, impairment at the periphery
induces changes centrally. In the same way, injuries at the
central level (such as stroke) induce reorganization of M1
and impairments at the periphery, even if the anatomical
structures of the muscles are not damaged. Mapping M1
with TMS supplies valuable information about the motor
cortical reorganization after stroke and the functional
effects of rehabilitation programs (Traversa et al., 1997).
To our knowledge, no TMS experiment has reported
the reorganization of the cortical map following mental
practice in patients with motor impairments. Only
Bassolino et al. (2013) mapped cortical changes after
mental practice and action observation in healthy partici-
pants whose hand joints were immobilized for ten hours
(see above for details). In contrast, studies using fMRI
focused on these neurophysiological changes in patients
(see Butler and Page, 2006; Page et al., 2009). One pos-
sible reason is that cortical mapping with TMS design is
time-consuming (about 2 h) and, due to the demanding
level of arousal and concentration, it might not be advis-
able for patients.
C. Ruffino et al. / Neuroscience 341 (2017) 61–78 69

CONCLUSION AND
PERSPECTIVES
This review provided relevant
information, based on the latest
researches, to optimize the benefits
of mental practice with MI in motor
learning. Such motor improvements
were associated to brain modulation.
While the TMS technique is
presented as reliable technique to
evaluate cortical reorganization, one
has to keep in mind its limitations
(Burke and Pierrot-Deseilligny,
2010). The peripheral response
elicited by TMS is an indicator of cor-
ticospinal excitability at a specific time
point, under defined conditions. It is
worth noting that the projection from
M1 to motoneurons is influenced by
other projections, cortical and/or
spinal. The results from TMS studies
give a partial picture of the activated
neurophysiological network during
the mental simulation of action. To
fully understand the general essence
of MI, the association with other
techniques is important (fMRI, PET,
magnetoencephalography, oculome-
try, electroencephalography, etc.) and the interdisciplinar-
ity is essential (e.g., neurophysiology, neuropsychology).
In this review, we have illustrated motor improvement
following MI practice and the concomitant reorganization
of cortical structures. Interestingly, recent findings open
up new prospects regarding neural adaptations
occurring at the spinal level. Grospre
ˆtre et al. (2016)
showed that, during MI, a subliminal motor output was dri-
ven along the corticospinal track to reach spinal struc-
tures without activating alpha-motoneurons. While
previous studies found disparate results regarding spinal
excitability modulation (facilitation for Bonnet et al.,
1997; Cowley et al., 2008; inhibition for Oishi et al.,
1994), Grospre
ˆtre et al. (2016) used two types of stimula-
tion and two reliable techniques to ensure the potential
effects of MI on spinal structures. Cervico-medullar-
evoked potentials (CMEP) and Hoffmann (H) reflexes
were elicited by stimulating the descending axons at the
cervicomedullary junction and the peripheral nerve,
respectively. Although both responses probe spinal
excitability, CMEP is a direct measurement of the
pyramido-motoneuronal junction (Taylor, 2006), and H-
reflex provides information about the transmission
between Ia afferences and alpha-motoneurons. When
the targeted limb was kept in a constant position, CMEPs,
but not H-reflexes, increased during MI in comparison to
rest. This ensured that descending cortico-spinal tracks,
but not alpha-motoneurons, were activated. Then, two
techniques (passive muscle lengthening and H-reflex
conditioning) were used to activate low-threshold pre-
synaptic interneurons (e.g., Daniele and MacDermott,
2009; Duclay et al., 2011), known to reduce the amplitude
of H-reflex at rest (Mizuno et al., 1971; Pinniger et al.,
2001). In both conditions, the reduction of H-reflex was
suppressed during MI, highlighting the effect of a sublim-
inal motor output activating low-threshold spinal struc-
tures. The inhibition induced by pre-synaptic interneuron
activation during lengthening is removed by the descend-
ing volleys generated during MI via other inhibitory
interneurons (see Fig. 5 in Grospre
ˆtre et al., 2016).
With this new evidence, we should consider neural
adaptation following MI practice at a broader level. In
addition to neural plasticity at the cortical level, the
reinforcement of synapse conductivity and the decrease
of pre-synaptic inhibition at the spinal level might also
be part of neural modulation after MI practice. We
suggest here a neural adaptation model for MI (Fig. 5):
– At the cortical level, both the cortical map representing
trained muscles and the corticospinal excitability would
increase during the first weeks of learning, then would
decrease with performance stabilization in the auto-
matic phase. At first, cortico-cerebellum and cortico-
striatal networks are activated in the learning phase,
while only the second one recalls the motor patterns
when the movement is automatized, as confirmed by
the different cortical activations associated with MI
expertise (Guillot et al., 2008).
– At both cortical and spinal levels, the neural process of
long-term potentiation may occur to strengthen the
synapse (for review, see Nicoll et al., 1988). This
mechanism is observed following rTMS in humans
and animals (e.g., Wang et al., 1996; Post et al.,
1999) or following high frequency stimulation and
pairing in single neurons (e.g., Paulsen, 2000). The
Fig. 5. Neural adaptation model of mental practice with motor imagery. The chart describes the
three phases related to learning, from the initial phase to the automatic phase, in relation to three
potential neurophysiological processes (cortical reorganization, long-term potentiation and
presynaptic inhibition). The graphical representations on the right depict the three processes
occurring at the cortical (1 and 2) and spinal (2 and 3) levels. The first picture shows the cortical
map modulation (increase and decrease) within the primary motor cortex. The second picture
shows the greater synapse sensitivity through the conduction of neurotransmitters. The third
picture shows the decrease of presynaptic inhibition at the alpha-motoneuron level. The dotted red
arrows illustrate the subliminal motor output generated during motor imagery and its influence on
presynaptic interneurons.
70 C. Ruffino et al. / Neuroscience 341 (2017) 61–78

subliminal motor output generated during MI may rein-
force the sensibility and conductivity of synapses in the
corticospinal tracks involved (Avanzino et al., 2015).
– At the spinal level, the decrease in presynaptic inhibi-
tion may also facilitate signal conductivity. The increas-
ing influence of descending volleys on spinal structures
is a key-component of motor expertise in specific activ-
ity (Tahayori and Koceja, 2012). After actual eccentric
training, which exacerbates the influence of cortical
volleys on presynaptic inhibitory interneurons, Duclay
et al. (2008) showed a decrease in H-reflex amplitude.
The descending motor output elicited during MI might
induce similar changes in presynaptic inhibition.
In reference to most recent publications, we discussed
the potential neural adaptations following mental practice
with MI. Both cortical and spinal modulations may play a
role in the motor learning process. While most studies
focused on macroscopic cortical activations, a perspective
of research would be to give considerations to synapse
adaptation and spinal excitability during MI practice.
Further investigation of these mechanisms may improve
the understanding of MI benefits on motor performance.
Acknowledgement—C.R. is a doctoral research fellow supported
by a grant from the French Ministry of Education and Research.
This work was supported by grants from the University of Bur-
gundy and the Regional Funds of Burgundy (FABER/FEDER pro-
ject), awarded to F.L.
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APPENDIX
Table A.1. List of publications using TMS to study mental imagery
TMS over M1 during explicit mental imagery
1995 Izumi et al. Facilitatory effect of thinking about
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74 C. Ruffino et al. / Neuroscience 341 (2017) 61–78

1997 Kiers et al. Facilitatory effect of thinking about
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1998 Yahagi et Kasai. Facilitation of motor evoked
potentials (MEPs) in first dorsal interosseous (FDI)
muscle is dependent on different motor images.
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1999 Fadiga et al. Corticospinal excitability is specifically
modulated by motor imagery: a magnetic stimulation
study. Neuropsychologia. 37:147–58.
Rossini et al. Corticospinal excitability modulation to
hand muscles during movement imagery. Cereb.
Cortex 9:161–67.
Jeannerod et Frak. Mental imaging of motor activity
in humans. Curr Opin in Neurobiol. 9:735–39.
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during motor imagery in human subjects. Neurosci
Lett. 236:113–16.
Hashimoto et Rothwell. Dynamic changes in
corticospinal excitability during motor imagery. Exp
Brain Res. 125:75–81.
Yahagi et Kasai. Motor evoked potentials induced by
motor imagery reveal a functional asymmetry of
cortical motor control in left-and right-handed human
subjects. Neurosci Lett. 276:185–88.
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evidence from transcranial magnetic stimulation. Ital
J Neurol Sci. 20:37–41.
2001 Filippi et al. Effects of motor imagery on motor
cortical output topography in Parkinson’s disease.
Neurology 57:55–61.
Tremblay et al. Modulation of corticospinal
excitability during imagined knee movements. J
Rehab Med 33:230–34.
2002 Facchini et al. Focal enhancement of motor cortex
excitability during motor imagery: a transcranial
magnetic stimulation study. Acta Neurol Scand
105:146–51.
2003 Stinear et Byblow. Motor imagery of phasic thumb
abduction temporally and spatially modulates
corticospinal excitability. Clin Neurophysiol.
114:909–14.
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during negative motor imagery. J Neurophysiol.
90:2303–09.
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finger movements: a combined fMRI and TMS study.
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motor imagery after disuse of an upper limb in
humans. Clin Neurophysiol 114:2397–03
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in the left hemisphere during action observation: a
single- and paired-pulse transcranial magnetic.
Neuropsychologia 41:1272–78.
2004 Vargas et al. The influence of hand posture on
corticospinal excitability during motor imagery: a
transcranial magnetic stimulation study. Cereb
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Li et al. Effects of motor imagery on finger force
responses to transcranial magnetic stimulation. Brain
Res Cogn Brain Res. 20:273–80.
Stinear et Byblow. Modulation of corticospinal
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We classified the publications into 5 themes: (1) TMS over M1 during explicit
mental imagery; (2) TMS or rTMS for perturbation of mental imagery; (3) Review
about mental imagery and TMS; (4) TMS over M1 during implicit mental imagery;
(5) TMS over V1 during mental imagery. TMS = transcranial magnetic
stimulation; rTMS = repetitive TMS; M1 = primary motor cortex; V1 = primary
visual cortex.
(Received 9 May 2016, Accepted 17 November 2016)
(Available online 25 November 2016)
78 C. Ruffino et al. / Neuroscience 341 (2017) 61–78