Nishimura et al. Journal of Physiological Anthropology (2018) 37:16
https://doi.org/10.1186/s40101-018-0175-9

ORIGINAL ARTICLE

Open Access

Effect of visual orientation on mu
suppression in children: a comparative
EEG study with adults
Yuki Nishimura1,2* , Yuki Ikeda1,2, Airi Suematsu1 and Shigekazu Higuchi3

Abstract
Background: The human mirror neuron system exists in adults, and even in children. However, a significant,unanswered question in the literature concerns age differences in the effect of visual orientation of human body
movements. The observation of actions performed by others is known to activate populations of neural cells called
mirror neuron system. Moreover, the power of mu rhythms (8–13 Hz) in the EEG is known to decrease while performing
and observing human movements. Therefore, the mu rhythm could be related to the activity of the mirror neuron
system. This study investigated the effects of the visual perspective on electroencephalography responses to hand actions
in two age groups.
Methods: The participants were 28 elementary school students and 26 university students. Videos of the two hands
operating switches were used as stimuli. The electroencephalogram mu rhythm (8–13 Hz) was measured during stimuli
presentation as an index of mirror neuron system activity.
Results: Adult participants showed significant mirror neuron system activation under both conditions, although no effectof visual perspectives was observed. On the other hand, children only reacted to egocentric stimuli and not to the others.
Conclusions: These findings confirmed the suggested differences in the activity of the mirror neuron system between
different age groups. The demonstration that brain activities related to mirroring change during development could help
explain previous findings in the literature.
Keywords: Mirror neuron system, Mu suppression, Association model, Growth and development

Background
The mirror neuron system (MNS) is a cluster of neurons
activated during both performance and observation ofbody movements [1]. They were named by Rizzolatti etal., who first discovered these neurons because of theircharacteristic of mirroring, which they observed during
an experiment on motor neurons of the macaque monkey [2–4]. The existence of MNS in the human brain
was suggested by the results of studies using neurophysiological techniques for measuring human brain activity including single-cell recording [5–8]. It wassuggested that they might be related to action* Correspondence: y.nishimura.941@s.kyushu-u.ac.jp
1
Graduate School of Integrated Frontier Sciences, Kyushu University, 4-9-1
Shiobaru, Minami-ku, Fukuoka City, Fukuoka, Japan
2
Research Fellow of Japan Society for the Promotion of Science, 4-9-1 Shiobaru,
Minami-ku, Fukuoka City, Fukuoka, Japan
Full list of author information is available at the end of the article

understanding because the MNS is more sensitive totransitive actions than intransitive actions [9]. Moreover,social cognitive functions such as imitation, empathy,
and recognition of facial expression, which are known tobe essential functions in building a society, are also related to the MNS [10–15]. Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG)
have been used for the measurement of MNS activity inhumans because invasive cannot be used due to ethicalreasons. EEG mu suppression has been used for thispurpose because of its relatively fast response time, reduced environmental restrictions, and the ease of applying to infants and children [16–20]. Braadbaart et al.
conducted simultaneous measurement of fMRI and EEG
to test the reliability of mu wave suppression as ameasure of MNS activity. They concluded that mu wave
is a possible measure of MNS activity. However,© The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Nishimura et al. Journal of Physiological Anthropology (2018) 37:16

contamination with other brain regions has been indicated [21–24].
The MNS can be found even in children. It is wellknown that a developing child shows imitating behavior,and this is thought to be the result of the emerging
MNS [25]. Many studies have been conducted with autism spectrum disorder (ASD) children to investigate therelationship between MNS dysfunction and ASD [19].
However, less attention has been given to the MNS oftypically developing children. Moreover, most participants used to test the existence of the MNS, and its
characteristics have ranged from infancy to kindergarten
age groups [26], or those past their adolescence.
Past studies have suggested long- and short-term modulation of MNS activity [27–29]. One possible explanationof the plasticity of MNS is association learning, in whichassociations between somatosensory and visual information are repeatedly established during the development
and form mirror-like responses [30]. Therefore, a study
comparing typically developing elementary school students and typically developing adults could contribute tounderstanding the process of acquiring and refining the
MNS through adaptation and development.
Many studies have been conducted to determine thedistinguishing characteristics of the MNS, and several
factors that affect MNS activity have been reported. The
spatial-visual orientation of stimuli is one of the basic
factors that could change this activity; however, no unified view of the effect has been established to date.
There are several studies using different neurophysiological methods that have reported greater mirroring activity resulting from an egocentric perspective compared
to an allocentric perspective [31–34]. On the other hand,
there are also studies that have reported opposite results
indicating a stronger effect of allocentric stimuli on
eliciting MNS activity [35, 36]. Moreover, Burgess et al.
found no difference between the two perspectives. They
concluded that the participants’ MNS were flexible
enough to act at the same level even when the perspective changed [37]. However, all these results have beenobtained from adult participants. To our knowledge,
there is no study that has examined the effect of visualorientation on the MNS of children. Moreover, no study
has directly compared the effect of visual orientation between children and adults.
The aim of this study was to determine the effect ofthe viewer’s perspective on mu desynchronization inchildren. We designed an experiment to directly compare elementary school children and adults to clarify theeffect of visual perspective on children’s mirroring activity. Social brain activity and biological features dramatically change during adolescence [38]. Therefore, it isworthy not to include adolescent participants to highlight the age difference. Children have completed lessPage 2 of 9

associative learning than adults. Therefore, we expecteda greater mu wave power attenuation in children whileobserving egocentric stimuli, because associative learning in children would be conducted mainly throughself-oriented sensorimotor events. The event-related
desynchronization of the mu wave was measured in children and adults because of its convenience and the low
degree of invasiveness.

Methods
Participants

Advertisements recruited healthy elementary school students (N = 28; 14 boys and 14 girls; aged 8 to 12 years,
mean age 9.8 ± 1.3 years) and healthy university students(N = 26; 13 men and 13 women; aged 19 to 30 years,
mean age 22.7 ± 1.9 years) as participants. All the participants or their parents reported that they wereright-handed, and had normal or corrected-to-normal
vision. They had not diagnosed as having developmental
disorder ever since and were naïve to the purpose of theexperiment. The participants or their parents were informed that the privacy of the participants would beprotected. Furthermore, the participants or their parents
gave their written informed consent before participationin the study.
The procedure of the study was approved by the Ethics
Committee of Kyushu University. The study was conductedaccording to the principles of the Declaration of Helsinki.
Equipment

The study was conducted in an acoustically and electrically sealed room. A 64-channel EEG was recorded using
an EEG amplifier (Net Amps 200 64-channel EEG amp.,
EGI) and a sensor net (Hydrocel Geodesics Sensor Net,
EGI) with acquisition software (Net Station 4.3.1, EGI)
running on a computer (Power Book G4, Apple Inc.).
The amplifier’s hardware low-pass filter was set to
100 Hz, and electrode impedance was maintained to remain under 70 kΩ as suggested by EGI. The data was
sampled at 250 Hz. Stimuli were delivered with Presentation Ver. 18.1 (NBS Inc.) and an LCD (E2351VR-BN,
LG Electronics) refreshing on 60 Hz using Cz as reference electrode. The display was placed at 0.7 m ahead of
the participant seated in the middle of the room.
StimuliVideo clips that were each 2 s in length (1280 × 720 px,
60 fps, visual angle 16°) were repeatedly presented witha black background in egocentric and allocentric perspectives to elicit brain activity. The egocentric video
shows two hands appearing from the bottom of thescreen to operate the switch from the neutral position toturn lights on. The video for the allocentric condition
was a 180°-rotated version of the egocentric stimulus,

Nishimura et al. Journal of Physiological Anthropology (2018) 37:16

ensuring identical physical properties among the two
conditions (Fig. 1). The video clips were developed basedon previous findings of pronounced effects of hand
movement and hand-operated tools on MNS activity[39, 40]. A static picture of fireworks was presented as
the target for a button-pressing request that was added
to maintain the participants’ attention.
Stimuli presentation was conducted in three blocks ofvideos consisting of 45 stimuli (135 in total; 60 of each condition, egocentric and allocentric; and 15 target pictures)interrupted by two short breaks. A white fixation cross ona black background was displayed for 1000–2000 ms before the video presentation. Target pictures were set to disappear simultaneously when the button was pressed. Afterthe video playback, a black screen was inserted for an interval of 2 s. The order of presentations was randomized.
Procedure

After the sensor net was applied, the participants sat
comfortably on a chair facing the monitor placed on adesk. EEG mu wave event-related desynchronization(ERD) of the onset of stimuli was measured during thepresentation of stimuli. Several previous experiments
and meta-analyses including spontaneous recording offMRI and EEG have indicated that mu wave attenuation
is a reliable measure of MNS activity in adults, children,and infants [21, 41–46]. Participants were requested tolook at the center of the display during the experimentand refrain from making any eye or body movements as
far as possible.
EEG analysis

First, raw EEG data were imported into the EMSE Suite
Ver. 5.5.2 (Source Signal Imaging Inc.) and werere-referenced to the linked left and right mastoids. The

Page 3 of 9data were filtered by an IIR band-pass filter (high end
70 Hz, low end 0.5 Hz, filter order 3). Trials containing
potential(s) greater than ± 70 μV that originated from artifacts were excluded by manual inspection (mean numberof accepted trials per condition 48.17 ± 7.73). After the selection, six participants (three adults and three children)were omitted from further analysis due to insufficientnumbers of acceptable trials (≦ 20 trials per condition).
Next, mu ERD was calculated using R Ver. 3.4.4 (R CoreTeam) [47] by using the following procedure: (1) According to the study by Oberman et al., [19], the average mu
wave power, 8~13 Hz of the baseline period (− 700 to −500 ms before stimulus onset) was calculated by the
Hanning window and fast Fourier transform (FFT). (2)The suppression rate was calculated by ([A − R]/R) × 100
with A being the average mu power during 1100 to2000 ms after stimulus onset (from the onset of movement in the video to the end) and R being mu power during the baseline period. (3) These steps were repeated forall stimuli presentation in each condition.
Finally, ERDs of the channels were averaged across theregions of interest (ROI) to improve the reliability of thedata (Fig. 2). The left central (LC) region included channels 15, 16, 20, 21, and 22; the mid-central (MC) region
included channels 4, 7, 54, and 65 (Cz); and the rightcentral (RC) region included channels 41, 49, 50, 51, and
53. The mid-occipital (MO) regions consisting of channels 35, 37, and 39 were also added to the analysis tocompare occipital activity.
R version 3.4.4 (R Core Team) [47] was used for the analysis. Kolmogorov-Smirnov test operated on the ERD
confirmed that the data was normally distributed(D = 0.051, p = 0.28). Firstly, a one-sample t test was conducted on ERD data at each ROI to check whether significant mu suppression occurred during stimuli presentation
relative to the baseline. Secondly, in order to takeFig. 1 Example of stimuli presented during the EEG recording. Initially, no hands were displayed in the video. After approximately 1 s, the hands
appeared holding switches and operating them to turn on the lights. Left: In the egocentric condition, the hands appeared from the bottom of
the screen so that the action was observed as the person’s own action. Right: In the allocentric condition, the spatial orientation was rotated by 180°

Nishimura et al. Journal of Physiological Anthropology (2018) 37:16

Fig. 2 Sensor layout of the EEG cap used in the current study. Eachdot represents one of 65 channels. Channels included in the four ROIs
are circled

Page 4 of 9within-subject correlations originated from the repeatedmeasurements into account while testing the effect ofview point on central and occipital ERD as target
variable, we used linear mixed-effect model (LMM:
age-group, condition and ROI as fixed effects, and“subject” as random effect) [48, 49]. The values werecompared using mixed-design analysis of variance(ANOVA) for the fitted model with Satterthwaite’s
method for the estimation of the denominator degreeof freedom [48]. We first conducted mixed-design
three-way ANOVA with age group (children andadults), anterior-posterior position (central and occipital), and condition (egocentric and allocentric) as fixed
effects to test the effect of the viewpoint on central andoccipital ERD. Since interactions were observed between all three factors, additional ANOVAs wereconducted separately in central and occipital regions.
In the central region, mixed-design three-way ANOVA(2 × age group; 3 × ROI; and 2 × condition) was
conducted to test the effect of viewpoint on ERD. In
the occipital region, a mixed-design two-way ANOVA(2 × age group and 2 × condition) was conducted onalpha wave ERD. The significance level for all the tests
was set at 0.05.

Fig. 3 Grand-average mu and alpha event-related desynchronization recorded in children and adults. The darker line represents the ERD waveform forthe egocentric condition, and the lighter line represents the waveform for the allocentric condition

Nishimura et al. Journal of Physiological Anthropology (2018) 37:16

Results
Grand averaged mu and alpha ERD waveforms are shownin Fig. 3. Figure 4 shows mu suppression of the two age
groups for each condition. One-sample t tests showed mu
event-related suppression by egocentric stimuli to be significantly different from zero over all three central ROIs
for both children (LC: t(24) = − 3.234, p = 0.004; MC:t(24) = − 4.251, p < 0.001; RC: t(24) = − 1.764, p < 0.090)
and adults (LC: t(22) = − 6.938, p < 0.001; MC: t(23) = −6.678, p < 0.001; RC: t(23) = − 7.325, p < 0.001). This indicated a significant mu power attenuation during stimuli
presentation relative to the baseline. The mu ERD of
allocentric stimuli was not significantly different from zerofor children’s LC (t(24) = − 0.823, p = 0.419) and RC(t(24) = − 0.933, p = 0.360), whereas the MC ofchildren (t(24) = − 2.309, p = 0.030) and adults (LC: t(22)= − 7.062, p < 0.001; MC: t(23) = − 6.762, p < 0.001; RC:t(23) = − 6.747, p < 0.001) indicated significant difference
from zero.
Figure 5 shows the alpha suppression of both age groups
for each condition. One-sample t tests indicated significant alpha suppression from zero around the MO region
for all stimuli in both children (egocentric: t(24) = − 5.906,
p < 0.001; allocentric: t(24) = − 7.4332, p < 0.001) andadults (egocentric: t(22) = − 4.710, p < 0.001; allocentric:t(22) = − 3.997, p < 0.001).
The conditional and marginal coefficient of determination for the model fitted by LMM was R2c = 0.883 andR2m = 0.209 for the first model (group, condition andanterior-posterior position as fixed effects, and “subject” asrandom effect), R2c = 0.927 and R2m = 0.301 for the model
for central regions (group, condition and ROI as fixed effects, and “subject” as random effect), and R2c = 0.827 andR2m = 0.002 for the model for occipital region (group andPage 5 of 9

condition as fixed effects, and “subject” as random effect).
Conditional R2 is interpreted as variance explained by both
fixed and random factors while marginal R2 is interpreted
as variance explained only by the fixed factors [50]. Importantly, mu ERD variance was explained by the fixed factors
for about 30% while alpha ERD at occipital region was
mainly explained by the random factors and not by the
fixed factors at all.
The first ANOVA showed a significant interaction ofgroup, anterior-posterior position, and condition (F(1,234.2) = 6.462, p = 0.012). Therefore, we separated thedataset of central and occipital regions for the further analysis. The ANOVA on central ROIs showed a significant
main effect of age group (F(1, 46) = 25.222, p < 0.001) anda trend of the group × condition interaction (F(1, 46) =3.236, p = 0.079) on mu ERD. Based on our hypothesisthat effect of visual perspective differs between groups, we
further investigated this interaction by examining the effect of condition by calculating pairwise least squares
means differences [48]. Figure 4 shows condition difference for children (t(46.0) = 2.16, p = 0.036) suggesting thatthe mu wave ERD of children was greater in the egocentric condition, whereas there was no significant difference
for adults (t(46.0) = − 0.421, p = 0.676). In contrast, an
ANOVA conducted on alpha ERD measured around MO
showed neither a significant main effect (F(1, 46) = 0.175,
p = 0.678), group (F(1, 46) = 0.001, p = 0.973), nor an interaction (F(1, 46) = 0.977, p = 0.328) (Fig. 5). This suggests thatthe attentional level which is reflected in the occipital alphawas kept at the same level in both groups at both conditions.

Discussion
The current study was designed to investigate whether
there was an effect of differences in visual orientation on

Fig. 4 Mean mu wave ERD difference over three ROIs between egocentric and allocentric conditions a for children and b for adults (LC, MC, andRC). The filled bar represents the egocentric condition, and the outlined bar represents the allocentric condition. Error bars show ± 1 standard
errors. Significant differences from zero are indicated. †p < 0.1; *p < 0.05; **p < 0.01. It is assumed that brain activation is greater in regions where astronger ERD is observed

Nishimura et al. Journal of Physiological Anthropology (2018) 37:16

Page 6 of 9

Fig. 5 Alpha wave ERD difference between conditions (egocentric and allocentric) a for children and b for adults over the mid-occipital (MO)region. The filled bar represents the egocentric condition, and the outlined bar represents the allocentric condition. The error bars display
standard errors. Significant differences from zero are indicated. **p < 0.01

children’s mu wave oscillation compared to adults whenobserving identical hand movements from two different
viewpoints. Results indicated that only the children’s
EEG response was affected by the change in visual orientation, whereas there was no significant effect of the perspective on adults’ mu wave ERD. Additionally, alphawave ERD over the occipital region did not show any
significant main effect nor interaction related to the condition, which is indicative of similar occipital cortex activity regardless of the condition or the age group.
Children

There was no significant mirroring activity in children in
response to allocentric stimuli, which could be attributed
to the degree of associative learning in children. In
addition to the “adaptive model” of MNS, a developmental
perspective on the MNS has been suggested by the relatively new “association model” [30]. This model explains
the acquisition of MNS and its plasticity throughsensory-motor association learning during development.
In this model, associative learning, for example, can takeplace through the visual-motor integration of a person’s
own hand movements [51, 52]. Therefore, associative
learning could later result from egocentric and allocentric
perspectives. A lower level of learning is expected to resultin less mirroring activity. There is some evidence that age
modulates the effect of motor learning during the elementary school period [53], which is suggestive of an ongoingprocess of association learning during that period.

Another possible explanation of these results is spatial
perspective taking ability. It is known that this psychological ability is acquired during development along withthe development of the frontal lobe function [54, 55].
These studies suggested that the egocentric view is morefamiliar to us whereas the allocentric view requires additional frontal intervention, which is insufficiently developed in children. Also, during spatial perspective taking
tasks, somatosensory, premotor, and supplementary motor
brain regions overlap with brain regions employed by the
MNS [56–58], which is suggestive of a strong relationshipbetween perspective taking and mirroring neural activity.
Thus, the results of this study are explained by spatial perspective taking ability, as well as by development.
AdultsThere has been much interest in the effect of the visualperspective on MNS activity, and a large number ofstudies have been conducted on this topic. Results of different studies conducted on adult participants have suggested the superiority of the egocentric perspective ineliciting human and primate MNS activity [31–34],
which are inconsistent with the results of this study.
Moreover, our results on adults are inconsistent withstudies that have reported the superiority of the allocentric perspective [35, 36]. Therefore, the results of thisstudy must be interpreted with care. There are, however,certain differences between previous and the current
study, including the number of hands that were used as

Nishimura et al. Journal of Physiological Anthropology (2018) 37:16

Page 7 of 9

stimuli. Observing bimanual movements, for example,
might require different patterns of motor coding.
The new model that takes the developmental aspect of
MNS into consideration predicts that mirroring response should increase for actions with strongly established associations [30]. As suggested in the literature by
Burgess et al., our adult participants might have alreadycompleted their association learning. As a result, theymight have lost the novelty value of allocentric stimuli,
which might have eliminated the differential effect of experimental conditions on adults [37].

Authors’ contributions
YN conceived and designed the study, performed the experiments and thestatistical analysis, and drafted the manuscript. YI and AS helped to carry out
the experiments and analyzed the data. YI and SH participated in designingand coordinating the experiment and helped to draft the manuscript. All authors
have read and approved the final manuscript.

Limitations and future study

Publisher’s Note

The mu wave frequency band was set to 8–13 Hz regardless of the age group, which is the same bandwidth
used in previous studies [42, 59–61]. However, the peakalpha wave differs according to age. Mean alpha peakfrequency is approximately 9.4 Hz for participants in thecurrent study [62]. Although alpha wave attenuation andmu wave attenuation have different sources as suggestedby the present study, reconsideration of the frequency
band of children’s mu wave may provide a more robust
result. Furthermore, certain studies have suggested thatmu suppression could include alpha suppression and its
reliability has to be considered carefully [22–24, 63].
Additional study with the same design but using different neurophysiological methods is also required in the
future. In addition, collecting individual’s autism-related
quotient may aid to assess the putative relation between
ASD and MNS activity in the future study.

Springer Nature remains neutral with regard to jurisdictional claims in publishedmaps and institutional affiliations.

Conclusion
In conclusion, this study indicated that children’s MNS
activity could be affected by the visual orientation of astimulus. Along with the results of data on adults, ourfindings contribute to the understanding of developmental aspects of the MNS. It is suggested that further research using multistep age groups ranging fromchildhood to adolescence and adulthood is required.
Abbreviations
ANOVA: Analysis of variance; EEG: Electroencephalogram; LMM: Linear mixedeffect model; MNS: Mirror neuron system
Acknowledgements
We thank Ms. Kuroki, Ms. Yoshikawa, Ms. Nishino, and teachers of elementary
schools for their help in recruiting participants. We also thank Mr. Fujiwara,
Dr. Lee, Ms. Tada, and other laboratory members for their technical support.
Funding
This work was supported by the Japan Society for the Promotion of Science(16J04125).
Availability of data and materials
The datasets used and/or analyzed during the current study are available fromthe corresponding author on reasonable request.

Ethics approval and consent to participate
All subjects gave their written informed consent after a complete explanationof this study before participating in the study. The study was performed inaccordance with the guidelines of the Declaration of Helsinki and was approvedby the ethics committee of the Kyushu University.
Competing interests
The authors declare that they have no competing interests.

Author details
1
Graduate School of Integrated Frontier Sciences, Kyushu University, 4-9-1
Shiobaru, Minami-ku, Fukuoka City, Fukuoka, Japan. 2Research Fellow of Japan
Society for the Promotion of Science, 4-9-1 Shiobaru, Minami-ku, Fukuoka City,
Fukuoka, Japan. 3Faculty of Design, Kyushu University, 4-9-1 Shiobaru,
Minami-ku, Fukuoka City, Fukuoka, Japan.
Received: 26 March 2018 Accepted: 24 May 2018

References
1. Iacoboni M. Imitation, empathy, and mirror neurons. Annu Rev Psychol.
2009;60:653–70. Available from:. https://doi.org/10.1146/annurev.psych.60.
110707.163604.
2. Di Pellegrino G, Fadiga L, Fogassi L, Gallese V, Rizzolatti G. Understanding
motor events: a neurophysiological study. Exp Brain Res. 1992;91:176–80.
Available from: http://link.springer.com/10.1007/BF00230027.
3. Gallese V, Fadiga L, Fogassi L, Rizzolatti G. Action recognition in the
premotor cortex. Brain. 1996;119(Pt 2):593–609. Available from: https://doi.
org/10.1093/brain/119.2.593.
4. Rizzolatti G, Fadiga L, Gallese V, Fogassi L. Premotor cortex and therecognition of motor actions. Cogn. Brain Res. 1996;3:131–41. Available
from: https://doi.org/10.1016/0926-6410(95)00038-0.
5. Fadiga L, Fogassi L, Pavesi G, Rizzolatti G. Motor facilitation during action
observation: a magnetic stimulation study. J Neurophysiol. 1995;73:2608–11.
6. Mukamel R, Ekstrom AD, Kaplan J, Iacoboni M, Fried I. Single-neuron
responses in humans during execution and observation of actions. Curr.
Biol. 2010;20:750–6. Available from: https://doi.org/10.1016/j.cub.2010.02.045.
7. Strafella a P, Paus T. Modulation of cortical excitability during action observation:a transcranial magnetic stimulation study. Neuroreport. 2000;11:2289–92.
8. Babiloni C, Del Percio C, Vecchio F, Sebastiano F, Di Gennaro G, Quarato PP,
et al. Alpha, beta and gamma electrocorticographic rhythms insomatosensory, motor, premotor and prefrontal cortical areas differ inmovement execution and observation in humans. Clin. Neurophysiol. 2016;
127:641–54. Available from: https://doi.org/10.1016/j.clinph.2015.04.068.
[cited 2015 Sep 10].
9. Iacoboni M, Molnar-Szakacs I, Gallese V, Buccino G, Mazziotta JC, Rizzolatti G.
Grasping the intentions of others with one’s own mirror neuron system.
PLoS Biol. 2005;3:e79. Available from: https://doi.org/10.1371/journal.pbio.
0030079 . [cited 2015 May 27].
10. Carr L, Iacoboni M, Dubeau M-C, Mazziotta JC, Lenzi GL. Neural mechanismsof empathy in humans: a relay from neural systems for imitation to limbic
areas. Proc Natl Acad Sci USA. 2003;100:5497–502. Available from: https://doi.org/10.1073/pnas.0935845100.
11. Ferrari PF, Gallese V, Rizzolatti G, Fogassi L. Mirror neurons responding tothe observation of ingestive and communicative mouth actions in themonkey ventral premotor cortex. Eur. J Neurosci. 2003;17:1703–14. Available
from: https://doi.org/10.1046/j.1460-9568.2003.02601.x.
12. Gallese V, Goldman A. Mirror neurons and the simulation theory of mindreading. Trends Cogn. Sci. 1998;2:493–501. Available from: https://doi.org/10.
1016/S1364-6613(98)01262-5.

Nishimura et al. Journal of Physiological Anthropology (2018) 37:16

13. 1. Molenberghs P, Cunnington R, Mattingley JB. Is the mirror neuron system
involved in imitation? A short review and meta-analysis. Neurosci Biobehav
Rev [Internet]. 2009;33:975–80. Available from: http://linkinghub.elsevier.
com/retrieve/pii/S014976340900044X.
14. Rizzolatti G, Sinigaglia C. The functional role of the parieto-frontal mirror
circuit: interpretations and misinterpretations. Nat. Rev. Neurosci. 2010;11:
264–74. https://doi.org/10.1038/nrn2805.
15. Woodruff CC, Martin T, Bilyk N. Differences in self- and other-induced Mu
suppression are correlated with empathic abilities. Brain Res. 2011;1405:69–
76. https://doi.org/10.1016/j.brainres.2011.05.046.
16. Pineda JA. The functional significance of mu rhythms: Translating “seeing”
and “hearing” into “doing.” Brain Res Rev [Internet]. Department of
Cognitive Science and Neuroscience, University of California, San Diego, San
Diego, CA 92037-0515, United States; 2005;50:57–68. Available from: https://doi.org/10.1016/j.brainresrev.2005.04.005.
17. Désy MC, Lepage JF. Skin color has no impact on motor resonance: evidence
from mu rhythm suppression and imitation. Neurosci Res. 2013;77:58–63.
18. Marshall PJ, Young T, Meltzoff AN. Neural correlates of action observationand execution in 14-month-old infants: an event-related EEG
desynchronization study. Dev Sci. 2011;14:474–80.
19. Oberman LM, McCleery JP, Hubbard EM, Bernier R, Wiersema JR,
Raymaekers R, et al. Developmental changes in mu suppression to observed
and executed actions in autism spectrum disorders. Soc Cogn Affect
Neurosci. 2013;8:300–4.
20. Warreyn P, Ruysschaert L, Wiersema JR, Handl A, Pattyn G, Roeyers H.
Infants’ mu suppression during the observation of real and mimicked goaldirected actions. Dev Sci. 2013;16:173–85.
21. Braadbaart L, Williams JHG, Waiter GD. Do mirror neuron areas mediate murhythm suppression during imitation and action observation? Int. J
Psychophysiol. 2013;89:99–105. https://doi.org/10.1016/j.ijpsycho.2013.05.019.
22. Hobson HM, Bishop DVM. Mu suppression – A good measure of the humanmirror neuron system? Cortex [Internet]. 2016 [cited 2016 Apr 18];82:290–
310. Available from: https://doi.org/10.1016/j.cortex.2016.03.019.
23. Fox NA, Bakermans-Kranenburg MJ, Yoo KH, Bowman LC, Cannon EN,
Vanderwert RE, et al. Assessing human mirror activity with EEG mu rhythm: ameta-analysis. Psychol Bull. 2016;142:291–313. https://doi.org/10.1037/bul0000031.
24. Bowman LC, Bakermans-Kranenburg MJ, Yoo KH, Cannon EN, Vanderwert
RE, Ferrari PF, et al. The mu-rhythm can mirror: Insights from experimental
design, and looking past the controversy. Cortex [Internet]. Elsevier; 2017;96:
121–5. Available from: https://doi.org/10.1016/j.cortex.2017.03.025. [cited
2018 May 7].
25. Lepage J-F, Théoret H. EEG evidence for the presence of an action
observation-execution matching system in children. Eur J Neurosci[Internet]. 2006;23:2505–10. Available from: http://doi.wiley.com/10.1111/j.
1460-9568.2006.04769.x.
26. Hunnius S, Bekkering H. What are you doing? How active and observational
experience shape infants’ action understanding. Philos Trans R Soc B Biol Sci[Internet]. 2014;369:20130490–20130490. Available from: https://doi.org/10.
1098/rstb.2013.0490.
27. Catmur C, Walsh V, Heyes C. Sensorimotor learning configures the humanmirror system. Curr Biol [Internet]. 2007;17:1527–31. Available from: https://doi.org/10.1016/j.cub.2007.08.006. [cited 2015 Dec 9].
28. Ferrari PF, Tramacere A, Simpson EA, Iriki A. Mirror neurons through the lens of
epigenetics. Trends Cogn. Sci. 2013;17:450–7. https://doi.org/10.1016/j.tics.2013.07.003.
29. Wiggett AJ, Hudson M, Tipper SP, Downing PE. Learning associations
between action and perception: Effects of incompatible training on bodypart and spatial priming. Brain Cogn [Internet]. 2011;76:87–96. Available
from: https://doi.org/10.1016/j.bandc.2011.02.014. [cited 2017 Jan 20].
30. Heyes C. Where do mirror neurons come from? Neurosci Biobehav Rev.
2010;34:575–83. https://doi.org/10.1016/j.neubiorev.2009.11.007.
31. Caggiano V, Fogassi L, Rizzolatti G, Pomper JK, Thier P, Giese MA, et al. Viewbased encoding of actions in mirror neurons of area F5 in macaque premotor
cortex. Curr. Biol. 2011;21:144–8. https://doi.org/10.1016/j.cub.2010.12.022.
32. Drew AR, Quandt LC, Marshall PJ. Visual influences on sensorimotor EEG
responses during observation of hand actions. Brain Res. 2015;1597:119–28.
https://doi.org/10.1016/j.brainres.2014.11.048. [cited 2018 Mar 29].
33. Fu Y, Franz EA. Viewer perspective in the mirroring of actions. Exp Brain Res[Internet]. 2014;232:3665–74. Available from: https://doi.org/10.1007/s00221014-4042-6.
34. Jackson PL, Meltzoff AN, Decety J. Neural circuits involved in imitation andperspective-taking. NeuroImage. 2006;31:429–39.

Page 8 of 935. Frenkel-Toledo S, Bentin S, Perry A, Liebermann DG, Soroker N. Dynamics ofthe EEG power in the frequency and spatial domains during observationand execution of manual movements. Brain Res. 2013;1509:43–57. https://doi.org/10.1016/j.brainres.2013.03.004.
36. Kilner JM, Marchant JL, Frith CD. Modulation of the mirror system by social
relevance. Soc Cogn Affect Neurosci. 2006;1:143–8.
37. Burgess JD, Arnold SL, Fitzgibbon BM, Fitzgerald PB, Enticott PG. A
transcranial magnetic stimulation study of the effect of visualorientation on the putative human mirror neuron system. Front Hum
Neurosci [Internet]. 2013;7:Article679. Available from: https://doi.org/10.
3389/fnhum.2013.00679.
38. Blakemore S-J. The social brain in adolescence. Nat Rev Neurosci. 2008;9:
267–77.
39. Isoda K, Sueyoshi K, Ikeda Y, Nishimura Y, Hisanaga I, Orlic S, et al. Effect of
the hand-omitted tool motion on mu rhythm suppression. Front Hum
Neurosci [Internet]. Frontiers; 2016;10:Article 266. Available from: https://doi.
org/10.3389/fnhum.2016.00266. [cited 2016 May 26].
40. Perani D, Fazio F, Borghese NA, Tettamanti M, Ferrari S, Decety J, et al.
Different brain correlates for watching real and virtual hand actions.
Neuroimage [Internet]. Affiliation: Institute of Neuroscience and BioimagingCNR, Milan, Italy; Affiliation: Scientific Institute H San Raffaele, Milan, Italy;
Affiliation: University Vita-Salute, Milan, Italy; Affiliation: University of MilanoBicocca, Milan, Italy; Affiliatio. 2001;14:749–58. Available from: https://doi.org/
10.1006/nimg.2001.0872.
41. Muthukumaraswamy SD, Johnson BW, McNair NA. Mu rhythm modulation
during observation of an object-directed grasp. Cogn Brain Res. 2004;19:195–201.
42. Oberman LM, Hubbard EM, McCleery JP, Altschuler EL, Ramachandran VS,
Pineda JA. EEG evidence for mirror neuron dysfunction in autism spectrum
disorders. Cogn Brain Res [Internet]. Affiliation: Center for Brain andCognition, UC San Diego, San Diego, CA 92093-0109, United States;
Affiliation: Department of Psychology, UC San Diego, 9500 Gilman Drive,
San Diego, CA 92093-0109, United States; Affiliation: Department of
Rehabilitation; 2005;24:190–8. Available from: https://doi.org/10.1016/j.
cogbrainres.2005.01.014. [cited 2014 Jul 11].
43. Perry A, Bentin S. Does focusing on hand-grasping intentions modulate
electroencephalogram μ and α suppressions? Neuroreport [Internet]. 2010;
21:1050–4. Available from: https://doi.org/10.1097/WNR.0b013e32833fcb71.
44. Stroganova T, Orekhova E, Posikera IN. EEG alpha rhythm in infants. Clin
Neurophysiol [Internet]. 1999;110:997–1012. Available from: https://doi.org/
10.1016/S1388-2457(98)00009-1.
45. Takemi M, Masakado Y, Liu M, Ushiba J. Event-related desynchronizationreflects downregulation of intracortical inhibition in human primary motor
cortex. J Neurophysiol. 2013;110:1158–66. https://doi.org/10.1152/jn.01092.
2012. [cited 2015 Dec 3].
46. Woodruff CC, Maaske S. Action execution engages human mirror
neuron system more than action observation. Neuroreport.
2010;21:432–5.
47. R Core Team. R: a language and environment for statistical computing. R
Foundation for Statistical Computing [Internet]. Vienna, Austria; 2018.
Available from: https://www.r-project.org/.
48. Kuznetsova A, Brockhoff PB, Christensen RHB. lmerTest Package: Tests in
Linear Mixed Effects Models. J Stat Softw [Internet]. 2017;82. Available from:https://doi.org/10.18637/jss.v082.i13.
49. Bates D, Mächler M, Bolker B, Walker S. Fitting Linear Mixed-Effects Models
Using lme4. J Stat Softw [Internet]. 2015;67. Available from: https://doi.org/
10.18637/jss.v067.i01.
50. Nakagawa S, Schielzeth H. A general and simple method for obtaining R 2
from generalized linear mixedeffects models. O’Hara RB, editor. Methods
Ecol Evol [Internet]. 2013;4:133–42. Available from: https://doi.org/10.1111/j.
2041-210x.2012.00261.x. [cited 2018 Apr 21].
51. Cook R, Press C, Dickinson A, Heyes C. Acquisition of automaticimitation is sensitive to sensorimotor contingency. J Exp Psychol Hum
Percept Perform [Internet]. 2010;36:840–52. Available from: https://doi.
org/10.1037/a0019256.
52. Cooper RP, Cook R, Dickinson A, Heyes CM. Associative (not Hebbian)learning and the mirror neuron system. Neurosci. Lett. 2013;540:28–36.
https://doi.org/10.1016/j.neulet.2012.10.002.
53. Chan JSY, Luo Y, Yan JH, Cai L, Peng K. Children’s age modulates the effectof part and whole practice in motor learning. Hum Mov Sci [Internet]. 2015;
42:261–72. Available from: https://doi.org/10.1016/j.humov.2015.06.002.
[cited 2017 Jan 23].

Nishimura et al. Journal of Physiological Anthropology (2018) 37:16

54. Epley N, Morewedge CK, Keysar B. Perspective taking in children and adults:
equivalent egocentrism but differential correction. J Exp Soc Psychol. 2004;
40:760–8.
55. Surtees ADR, Apperly IA. Egocentrism and automatic perspective taking inchildren and adults. Child Dev. 2012;83:452–60. https://doi.org/10.1111/j.
1467-8624.2011.01730.x.
56. Creem SH, Downs TH, Wraga M, Harrington GS, Proffitt DR, Downs JH. An fMRI
study of imagined self-rotation. Cogn Affect Behav Neurosci. 2001;1:239–49.
57. Ruby P, Decety J. Effect of subjective perspective taking during simulationof action: a PET investigation of agency. Nat Neurosci. 2001;4:546–50.
58. Wraga M, Shephard JM, Church JA, Inati S, Kosslyn SM. Imagined rotationsof self versus objects: an fMRI study. Neuropsychologia. 2005;43:1351–61.
59. Eismont E V., Makhin SA, Bakunova A V., Kaida AI, Pavlenko VB. Properties of
the EEG μ rhythm and its reactivity during the performance, observation,
imitation, and auditory recognition of movements in children aged 4–14
years. Hum Physiol [Internet]. 2017;43:274–9. Available from: https://doi.org/
10.1134/S0362119717030057.
60. Oberman LM, Ramachandran VS, Pineda JA. Modulation of mu suppression inchildren with autism spectrum disorders in response to familiar or unfamiliar
stimuli: the mirror neuron hypothesis. Neuropsychologia. 2008;46:1558–65.
61. Raymaekers R, Wiersema JR, Roeyers H. EEG study of the mirror neuron
system in children with high functioning autism. Brain Res [Internet].
Elsevier B.V. 2009;1304:113–21. Available from: https://doi.org/10.1016/j.
brainres.2009.09.068. [cited 2016 May 6].
62. Miskovic V, Ma X, Chou C-AA, Fan M, Owens M, Sayama H, et al.
Developmental changes in spontaneous electrocortical activity and networkorganization from early to late childhood. Neuroimage. 2015;118:237–47.
https://doi.org/10.1016/j.neuroimage.2015.06.013. [cited 2015 Jun 26].
63. Muthukumaraswamy SD, Johnson BW. Primary motor cortex activation
during action observation revealed by wavelet analysis of the EEG. Clin
Neurophysiol [Internet]. 2004;115:1760–6. Available from: https://doi.org/10.
1016/j.clinph.2004.03.004. [cited 2015 Oct 5].

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