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Sensitivity to perception level differentiates two
subnetworks within the mirror neuron system
Shiri Simon and Roy Mukamel
Sagol School of Neuroscience and School of Psychological Sciences, Tel-Aviv University, Tel Aviv 69978, Israel
Correspondence should be addressed to Roy Mukamel, Sagol School of Neuroscience and School of Psychological Sciences, Tel-Aviv University, Tel Aviv
69978, Israel. E-mail: rmukamel@post.tau.ac.il
Abstract
Mirror neurons are a subset of brain cells that discharge during action execution and passive observation of similar actions.
An open question concerns the functional role of their ability to match observed and executed actions. Since understanding
of goals requires conscious perception of actions, we expect that mirror neurons potentially involved in action goal coding,
will be modulated by changes in action perception level. Here, we manipulated perception level of action videos depicting
short hand movements and measured the corresponding fMRI BOLD responses in mirror regions. Our results show that
activity levels within a network of regions, including the sensorimotor cortex, primary motor cortex, dorsal premotor cortex
and posterior superior temporal sulcus, are sensitive to changes in action perception level, whereas activity levels in the
inferior frontal gyrus, ventral premotor cortex, supplementary motor area and superior parietal lobule are invariant to such
changes. In addition, this parcellation to two sub-networks manifest as smaller functional distances within each group of
regions during task and resting state. Our results point to functional differences between regions within the mirror neurons
system which may have implications with respect to their possible role in action understanding.
Key words: fMRI; mirror neuron system; conscious perception; action observation
Introduction
Mirror neurons are a specialized subset of brain cells with visuo-
motor properties that discharge during both action execution
and passive observation of actions performed by others. These
cells were originally discovered in the ventral premotor cortex
of the macaque monkey (area F5) (Dipellegrino et al., 1992;
Gallese et al., 1996; Rizzolatti et al., 1996) and were subsequently
demonstrated in other areas in the human and non-human
motor pathway (Gallese et al., 2002; Fogassi et al., 2005; Gazzola
and Keysers, 2009; Caspers et al., 2010; Mukamel et al., 2010;
Molenberghs et al., 2012). These areas—largely consisting of the
primary and premotor cortices, the inferior frontal gyrus and
parietal regions—were termed the mirror neuron system (MNS).
While the existence and anatomical distribution of cells
with mirroring properties is now widely accepted, there is still
strong debate with respect to the functional significance and
the source from which such cells gained their capacity to match
observed with executed actions (Heyes, 2010; Hickok, 2009,
2013). One account suggests that mirroring properties have a
role in cognitive functions such as action and intention under-
standing. In support of this view are physiological evidence in
primates which indicate that mirror neuron responses are sen-
sitive to action goals rather than specific low-level kinematics
(Rizzolatti and Sinigaglia, 2010; Rizzolatti and Fogassi, 2014). For
example, observation of actions with similar kinematics but dif-
ferent action goals have been shown to evoke different neural
responses in fronto-parietal mirror neurons (Umilta et al., 2001;
Fogassi et al., 2005; Iacoboni et al., 2005). A complementary evi-
dence demonstrates that different action kinematics having the
same goal evoke similar neural response (Umilta et al., 2008).
Additionally, recent neuropsychological studies on patients
with temporal, parietal, and frontal lesions are consistently
Received: 12 September 2016; Revised: 17 December 2016; Accepted: 29 January 2017
V
CThe Author (2017). Published by Oxford University Press.
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1
Social Cognitive and Affective Neuroscience, 2017, 1–10
doi: 10.1093/scan/nsx015
Original article
associated with poor performance in tasks of action perception
and understanding (Urgesi et al., 2014). Nonetheless, an alterna-
tive account suggests that the MNS does not represent action
and intention understanding and that the functional properties
of mirror neurons are merely a byproduct of associative learn-
ing formed through sensorimotor experience which is gained
during the course of individual development (Del Giudice et al.,
2009; Hickok, 2009; Heyes, 2010). This is supported by the fact
that the activity within the mirror system can be dynamically
remapped with training (Catmur et al., 2007; Press et al., 2007;
Catmur et al., 2011). According to Csibra, understanding the ac-
tions and intentions of others is achieved outside the motor
system, and action mirroring is the consequence of later pro-
cessing (Csibra, 2007).
It is plausible that mirror neurons which are distributed over
distinct regions within the sensorimotor system, hold diverse
functional roles. While mirror neurons in some regions might
have a role in coding the goal of an action, in other regions such
functional properties may have evolved as a result of extensive
simultaneous experience in which specific observed and exe-
cuted actions are temporally correlated. Since understanding of
goals requires conscious perception of the relevant action, we
should expect that mirror neurons potentially involved in ac-
tion goal coding, will be modulated by changes in the level of ac-
tion perception. A recent behavioral study demonstrated that
masked implied-action primes affected motor preparation and
execution only when they were consciously perceived.
Nonetheless, subsequent action perception was affected by the
primes, also when they were not consciously perceived (Mele
et al., 2014). We have recently shown, that EEG mu and beta os-
cillation power over sensorimotor cortices are modulated by the
level of action perception (Simon and Mukamel, 2016).
Oscillation power over sensorimotor regions in these frequency
bands serve as index to infer mirror neuron activity (Pineda,
2005). While in our EEG study consciously perceived actions
were associated with stronger mu and beta suppression, the
EEG response was also significant during observation of non-
perceived actions relative to pre-stimulus baseline in which no
action was presented. As suggested by this latter finding, the
MNS might operate even without conscious awareness of ac-
tions. Such function of the MNS might result in behavioral phe-
nomenon as the Chameleon effect in which people tend to
implicitly imitate others during social interactions (Chartrand
and Bargh, 1999). Taken together, the findings above raise the
question of how modulation of action perception level affects
activity levels across different regions within the MNS.
In the current study, we addressed this issue by examining
whether and how modulation of conscious perception of ac-
tions modulates the activation and functional distances within
various regions of the MNS. To this end, we manipulated per-
ception level by rendering short hand movement videos invis-
ible to conscious perception, and measured the corresponding
fMRI BOLD responses in various regions of the MNS. Our results
point to two subnetworks within the MNS with different func-
tional properties—one sensitive and one invariant to the level
of action perception.
Materials and methods
Participants
Seventeen healthy, right-handed adults (7 males; mean age
26.27, range 19–35 years) participated in this study. Two subjects
were excluded from the analysis due to excessive head
movement (>2 mm). Participants were recruited from the gen-
eral population of students at Tel Aviv University and were
compensated for their participation with either course credit or
payment. Prior to the experiment, all participants provided writ-
ten informed consent to participate. The study conformed to
the guidelines approved by the Tel Aviv University Ethical com-
mittee, and the Sheba Medical Center Helsinki committee. In
the resting state analysis, we used an open source resting state
dataset downloaded from the NITRC project (Neuroimaging
Informatics Tools and Resources; https://www.nitrc.org/frs/?
group_id¼296). The original resting state dataset included 23
subjects (8 males; range 20–40). For comparison purposes with
the size of the main experimental dataset, the first 15 subjects
(matched in age and gender) were used.
Stimuli
Participants were scanned under four experimental conditions:
masked (M) and non-masked (NM) that were presented in either
high or low opacity. In the ‘M’ conditions, perception level was
manipulated by using a modification of the continues flash sup-
pression (CFS) paradigm (Tsuchiya and Koch, 2005) to allow
masking of short videos rather than static images. By present-
ing an otherwise visible stimulus of an action video exclusively
to one eye while simultaneously presenting strong dynamic
noise to the other eye, the CFS procedure allowed us to mask
the action videos from visual awareness. Target and masking
videos lasted 2 s and overlapped in space. The CFS display con-
sisted of three possible target action videos of different hand
movements and three masking videos of different Mondrian
patterns. Target videos were presented either with high opacity
or low opacity. We used anaglyph glasses with filters of chro-
matically opposite Red and Cyan colors for the left and right
eyes, respectively, such that the target videos were always pre-
sented in the cyan-scale (i.e. to the right eye). The mask was
therefore always presented in red-scale (i.e. to the left eye). The
target stimuli in the ‘NM’ condition were identical to the ‘M’
stimuli, and instead of presenting the Mondrian pattern to the
left eye, the Mondrian pattern was replaced by a uniform black
screen (Figure 1A).
Task
The experiment comprised of a total of six runs corresponding
to three masked (M) and three NM runs presented in alternating
order. Each masked run comprised of trials with a CFS display
(2 s) and an inter-trial interval (ITI) of 8 s during which subjects
had to fixate on a cross (þ). In order to probe the subjects’ per-
ception level throughout the experiment, on one-third of the
‘M’ condition trials subjects had to provide information regard-
ing their level of perception. Such trials started with the 2 s pres -
entation of the CFS display followed by a 6-s presentation of
fixation point. Then, perception level of the subjects was probed
by two means—accuracy and confidence. First, subjects were
presented with three representative images of the three actions
and an empty box corresponding to no perceived action. The lo-
cation of images on the screen corresponded with four buttons
and subjects were instructed to press the button corresponding
to the image representing the action they perceived. The loca-
tion of the images on the screen, and thus the mapping between
buttons and action videos, was randomized across trials in
order to avoid motor preparation which has been shown to re-
sult in BOLD response in MNS regions (Jeannerod, 1999;
Cunnington et al., 2006). Finally, the participants reported their
2|Social Cognitive and Affective Neuroscience, 2017, Vol. 00, No. 0
confidence level, namely to what extent they are confident
in their report, on a scale from 1 to 4. A report of ‘4’ corres-
ponded to cases in which subjects perceived a sequence of
dynamic movements and were sure which action out of the
three was displayed. A report of ‘1’ in confidence level corres-
ponded with cases in which subjects did not perceive a move-
ment at all. In case subjects could perceive the action based on
a single frame or a flash of an image, they were asked to report
an intermediate level of confidence (2 or 3). The time limit for
each report was set to 2 s. The NM runs were identical to the
masked runs except that we did not probe the subject’s percep-
tion since in a pretest preceding the experiment we found per-
ception level in the NM condition to be at ceiling (see
Procedure). During each NM run we also introduced 6 action
execution trials (18 execution trials in total) in which subjects
observed for 6 sec a red cross sign instructing them to press rap-
idly and repetitively with both left and right fingers until the
sign disappeared.
In the masked condition, changes in opacity of target
video were coupled with changes in perception. Since the two
cannot be distinguished, we also used the two different opac-
ities in the NM condition where perception level is at
ceiling. During each functional run (either ‘M’ or ‘NM’), half of
the trials were presented with high target opacity (H) and half
of the trials were presented with low target opacity (L). Trial
types were intermixed in a pseudorandom order. Each condi-
tion (‘M-H’, ‘M-L’, ‘NM-H and ‘NM-L’) consisted of 81 trials in
total (27 trials for each one of the three target movements). The
subjects reported their perception level (by means of accuracy
and confidence level) in 27 ‘M-H’ trials and 27 ‘M-L’ trials. Thus
in each subject, perception was probed from 54 masked trials
(Figure 1B).
Procedure
The low-opacity level was adjusted for each participant indi-
vidually in two behavioral pre-tests in order to control percep-
tion level. We set the low opacity level such that the target will
be invisible in the masked condition, but entirely visible in the
NM condition. These pre-tests were conducted inside the scan-
ner right before the main fMRI experiment. The aim of the first
pre-test was to determine the low opacity level in which sub-
jects still perceive the target stimulus in the NM condition but
not in the masked condition. We presented the CFS stimuli of
different actions in random order and probed the subjects’ per-
ception as to which action was displayed. Opacity level of target
video was varied using the simple up-down staircase procedure
(Leek, 2001). In this procedure opacity level was reduced follow-
ing trials in which the subject’s response was correct and opa-
city level was increased when his\her response was incorrect.
We started at the highest (100%) opacity level. Correct responses
were followed by a decrease in opacity at constant steps of 18%
until an incorrect response occurred. We than started to in-
crease the opacity level in slightly smaller steps of 14.4%. Every
time there was a change in the response from correct to incor-
rect or vice versa, we reduced the step size by 20% from the last
step size. The pre-test ended when the opacity level converged
and step size was smaller than half percent. We set the low opa-
city level in the actual experiment to 50% of the opacity level ob-
tained in this pre-test in order to eliminate perception in the
masked low-opacity condition. In the second pre-test, we veri-
fied the subjects could still fully perceive the targets in the low
opacity level of the NM condition (as determined from the previ-
ous step). In this pre-test, each of the three hand movement
stimuli was presented in the low opacity without a mask ten
times in random order, and subjects were asked to report the
action perceived (similar to the first pre-test). The opacity level
of each subject, determined from the first pre-test, was kept
constant during the entire fMRI experiment across the low-
opacity masked and NM conditions.
Data acquisition
Functional imaging was performed on a 3T Siemens
Magnetom Prisma scanner with a 64 channel head coil
located at the Strauss Computational neuroimaging center, Tel-
Aviv University. For each subject, 33 interleaved ascend-
ing echo-planar T2*-weighted slices were acquired for each
volume, covering the brain from the vertex to the occipital
lobe (slice thickness ¼3 mm, slice gaps ¼0 mm, in-plane reso-
lution ¼1.7181.718 mm, TR ¼2000 ms, TE ¼35 ms, flip
angle ¼90, field of view ¼220220 mm
2
, matrix size ¼128128).
Masked (M) runs lasted 13:12 min each (396 time points), and
‘NM’ runs lasted 11:12 min each (336 time points). For anatom-
ical reference, a whole brain high-resolution T1-weighed scan
(voxel size 111 mm) was acquired for each subject. The
NITRC resting state dataset was obtained on a 3T General
Electric scanner with an 8 channel head coil recorded by Pekar
J.J. and Mosofsky S.H. An echo-planar imaging sequence was
used to obtain the functional data (TR ¼2500 ms; number of
time points per subject ¼123).
Data analysis
fMRI data analysis was performed using ‘Brain Voyager QX’ v.
2.8 software package (Brain Innovation, Maastricht, the
Netherlands). Data preprocessing included cubic spline slice-
time correction, trilinear/sinc three-dimensional (3D) motion
correction, temporal high-pass filtering at 0.006 Hz and spatial
smoothing with a 6-mm Gaussian (FWHM). Functional images
were co-registered to the anatomical scans and both were
transformed into the standardized coordinate system of
Talairach (Talairach and Tournoux, 1988). Data analysis was
performed using the general linear model (GLM).
ROIs localization and analysis
Regions of interest (ROIs; see Figure 3) were defined at the multi
subject level. We used a conjunction of two GLM contrasts: NM
observation >rest and action execution trials >rest, to reveal
brain regions within the mirror neuron network. The resulting
map was corrected for multiple comparisons by controlling the
false discovery rate (Benjamini and Hochberg, 1995) and thresh-
olded at q(FDR) <0.05, with a minimum cluster size of 15 voxels.
A subsequent single subject GLM was performed for all voxels
in each ROI, and the average beta estimate across voxels was
computed for each condition. Beta values were calculated for
the contrast of each experimental condition vs rest. In the GLM
design matrix, separate regressors were used for observation
conditions (‘M-H’, ‘M-L’, ‘NM-H’, ‘NM-L’), the perception reports
in the masked runs, and the execution trials in the NM runs.
Effects of interest were examined using repeated measures ana-
lysis of variance (ANOVA) and planned one tailed paired ttests
with significance level of a¼0.05.
Functional dissimilarity analysis
For each subject, we calculated a functional dissimilarity
index between BOLD signals across the different mirror regions
S. Simon and R. Mukamel |3
(see above). This index is based on correlation distance between
fMRI time-course in each ROI:
di;j¼1Xn
k¼1ðxik
xiÞXn
k¼1ðxjk
xjÞ
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
Xn
k¼1ðxik
xiÞ2
rffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
Xn
k¼1ðxjk
xjÞ2
r
where
xi¼1
nX
n
k¼1
xik
xj¼1
nX
n
k¼1
xjk:
For each defined ROI in each subject, we Z-score
normalized the time course of the BOLD signal in each voxel,
and averaged the signal across all voxels. This procedure
yielded one representative time-course for each ROI. Next, we
calculated the distance between the activation of each pair of
ROIs using the above dissimilarity measure, yielding a matrix of
all pairwise distances. In order to visualize all pair-wise dis-
tances between all ROIs, we used classical multi-dimensional
scaling (MDS) (Borg and Groenen, 2005). MDS displays the NxN
dissimilarity distance matrix between all pairs of regions in a
2D plot such that the distances between ROI pairs are preserved
as well as possible. We also examined whether the functional
dissimilarity across the different MNS regions remains stable
regardless of experimental condition. To this end, we performed
the same analysis on resting state data of a separate group of
subjects.
Results
Behavioral results
Subjects responded within the time limits to 96.85% of the probe
trials (33% of masked trials; see Methods). In two trials on aver-
age (6 maximum in one subject) responses were missed. In the
NM condition (as measured for low-opacity condition during
the second pre-test), subjects reported seeing the target video in
100% of the trials and all trials were also correctly recognized.
Since perception in the NM low condition was at ceiling, we did
not probe the behavior from NM high opacity trials. In the
masked condition (as measured during the main experiment),
subjects reported seeing the target video in 97.9 60.8%
(mean 6SEM%) of t he high-opacity trials, and 22.7 62.3% of the
low-opacity trials (Cohen’s d¼10.93) (Figure 2A). In the high-
opacity condition, most of the reported seen trials were also
correctly recognized (mean 6SEM%: 81.13 62.9%). In contrast,
perception accuracy was markedly reduced in the low-opacity
masked condition (32.1 64.6%) (Figure 2B). Accuracy, as re-
ported by the subjects in the low opacity masked condition was
not significantly different from chance [33.3%; t(14) ¼0.27,
P¼0.78; two-tailed paired t-test]. These accuracy levels corres-
ponded with reported confidence levels. 91.2 62.6% of masked
low opacity trials were reported with the lowest confidence
level (1) and 93.5 62.2% of the masked high opacity trials were
reported with the highest confidence level (4) (Figure 2C). These
behavioral results confirm that our experimental manipulation
was successful in rendering low opacity actions in the masked
condition invisible to perception. Thus while in the NM condi-
tion, opacity level did not affect perception (which was at ceil-
ing), in the masked condition opacity level correlated with
perception.
High Opacity ('H')
Masked
('M')
Non
Masked
('NM')
Low Opacity ('L')
view video
(2s)
xation
(6s)
view video
(2s)
X
motor execution
(6s)
33% / # trials
10% / # trials
AB
C
time
1 2 3 4
report
action
(RT<2s)
rate
condence
(RT<2s)
xation
(8s)
xation
(8s)
xation
(8s)
Fig. 1. Experimental design. (A) The experiment included three masked (M) and three non-masked (NM) functional runs presented in alternating fashion. In each
run, half of the trials were presented with high target opacity (H) and half of the trials with low target opacity (L) in random order. (B) The ‘M’ runs comprised of a 2-s
CFS display (containing one of three different target videos depicting a specific hand movement presented to one eye, and one of the three masking videos
of different Mondrian patterns presented to the other eye). The video was followed by an Inter Trial Interval that lasted 8 s of a fixation cross (þ). One-third
of the ‘M’ condition trials were followed by the participants’ report of their perception. The participants reported which action was presented and their level of confi-
dence on a scale from 1 to 4. The duration of accuracy and confidence reports was limited to 2 s. The ‘NM’ runs comprised of a 2 s presentation of the target videos to
the right eye and a blank screen to the left eye, followed by an 8 s inter trial interval (ITI) of fixation cross. We also introduced six execution trials at each ‘NM’ run in
which the fixation cross turned red for 6 s, and subjects were instructed to press rapidly and repetitively with both left and right fingers until the fixation cross
disappeared.
4|Social Cognitive and Affective Neuroscience, 2017, Vol. 00, No. 0
ROI localization
We defined ROIs of the putative MNS for all subjects by using a
conjunction analysis of observation and execution trials. To this
end we performed a GLM conjunction analysis of the contrasts
NM observation >rest and execution trials >rest (see Methods
for details). We detected 12 regions which included the left pri-
mary motor cortex (M1), the left sensory-motor cortex (SMC),
the supplementary motor area (SMA), two patches in the right
dorsal premotor cortex (PMd), right ventral premotor cortex
(PMv), the right inferior frontal gyrus (IFG), right intra parietal
sulcus (IPS), the right temporal-parietal junction (TPJ) and pos-
terior superior temporal sulcus, the lateral occipital cortex bilat-
erally (LOC) and the right primary visual cortex (V1) (see Table 1;
Figure 3C). The significant patches of activation in visual areas
(V1, LOC), obtained in our localizer are not surprising given that
visual stimuli were present both in the observation and execu-
tion conditions. Since these visual regions are not considered
integral parts of the MNS, we did not include them further in
our ROI analysis.
GLM analysis
The time-course of each voxel in the ROIs was fit with a GLM
using the standard hemodynamic response function used in
BrainVoyager. For each voxel, the beta value for each condition
vs rest (masked high, masked low, NM high, NM low) was ex-
tracted and averaged across all voxels in each ROI. At the group
level, we performed a three-way repeated measures ANOVA to
the effects of masking (M/NM), opacity level (H/L) and ROI. This
analysis revealed main effects for masking [F(1,14) ¼13.78,
P<0.01] and ROI [F(8,112) ¼7.05, P<0.01]. Interaction effects
were reveled for masking and ROI [F(3,54) ¼3.69, P<0.05], as
well as for opacity level and ROI [F(8,112) ¼4.09, P<0.01]. The
three-way interaction was not significant [F(1,14) ¼1.32,
P¼0.27]. In our previous EEG study, we found sensitivity to ac-
tion perception level in frontal electrodes (Simon and Mukamel
2016). Therefore in the current study, we exploited the high ana-
tomical resolution of fMRI to differentiate between various MNS
regions based on such sensitivity. To inspect which ROIs were
sensitive to differences in the level of action perception, we first
examined in which ROIs the masked condition was significantly
stronger in the high vs low opacity trials (DM). These regions in-
clude the left M1 [mean difference high low opacity 6SEM
across subjects: 0.35 60.15, t(14) ¼2.22, P<0.05; one tailed
paired t-test], the left SMC [0.24 60.09, t(14) ¼2.51, P<0.05], the
right PMd [0.36 60.12, t(14) ¼2.85, P<0.05] and the right
pSTS\TPJ [0.44 60.07, t(14) ¼5.56, P<0.01]. In order to verify
these differences are not attributed to mere changes in opacity
level, we compared these differences with the similar subtrac-
tion of the low opacity beta value from the high opacity beta in
the NM condition (DNM). The ROIs in which ‘DM’ was signifi-
cantly larger than DNM included the same ROIs as above:
the left M1 [mean difference DMDNM 6SEM across subjects:
0.41 60.21; t(14) ¼1.86, P<0.05], left SMC [0.31 60.08; t(14) ¼
3.62, P<0.01], right PMd [0.34 60.15; t(14) ¼2.19, P<0.05], and
right pSTS\TPJ (0.29 60.11; t(14) ¼2.71, P<0.01). We considered
these ROIs as sensitive to differences in the level of action per-
ception regardless of changes in opacity level. In the remaining
ROIs, DM (the activation in high relative to low opacity trials in
the masked condition), was not significantly different than zero
[t(14) ¼0.74, P ¼0.23 in the SMA, t(14) ¼0.94, P ¼0.17 in right
PMv, t(14)¼1.16, P ¼0.13 in the right IFG and t(14) ¼0.71, P ¼0.24
in the right SPL]. Additionally, DM and DNM were not signifi-
cantly different in the SMA [mean difference DM-DNM 6SEM
across subjects: 0.04 60.05; t(14) ¼0.73, P ¼0.23], in the right
PMV [0.00 60.22; t(14) ¼0.03, P ¼0.48], right IFG [0.03 60.21;
t(14) ¼0.15, P ¼0.43], and in right SPL [0.10 60.18; t(14) ¼0.55,
P¼0.29]. We considered these ROIs as insensitive to differences
in the level of action perception (Figure 4). The only regions in
which DNM was significantly larger than zero was the TPJ
0
20
40
60
80
100
High Opacity Low Opacity
C
% Reported condence levels
(out of Masked trials)
A
B
0
20
40
60
80
100
0
20
40
60
80
100
% Reported seen trials
Masked
Non-Masked
Level 2
Level 1
Level 3
Level 4
Masked
Non-Masked
% Correct reports
(from reported seen trials)
High Opacity Low Opacity
High Opacity Low Opacity
Fig. 2. Behavioral results. (A) Masking in the low-opacity condition resulted in a
sharp drop in perception from ceiling (100% in the NM condition) to 22.7% in the
masked condition. In the high opacity trials, perception remained high even
with masking (97.9%). Since perception was already at ceiling in the NM low-
opacity condition, we did not measure it again in the NM high-opacity condi-
tion. Dashed bars therefore represent ceiling performance (based on the corres-
ponding low-opacity NM trials). (B) Out of the trials that were reported seen in
the masked condition, 81.1% were correctly recognized in high opacity and
32.1% in low opacity. (C) Most trials in the masked high-opacity condition were
rated with the highest confidence level, while most trials in the masked low-
opacity condition were rated with the lowest confidence level. All bar graphs
represent mean group results (N¼15) 6SEM across subjects.
S. Simon and R. Mukamel |5
[t(14) ¼1.89, P <0.05]. In all other regions, DNM was not signifi-
cantly different than zero.
Functional dissimilarity analysis
We further examined the relationships within and between the
sensitive and insensitive mirror regions with respect to action
perception as revealed in the previous step. We performed a
functional dissimilarity analysis in which we calculated the
functional distances between all ROIs. For each ROI in each sub-
ject, we averaged the time-courses of the voxels and concaten-
ated the averaged time-courses across all runs. We then
calculated the functional distance between the time-courses of
each pair of ROIs. These distances are also visualized in two
dimensions using MDS (Figure 5; see Methods for details). The
mean functional distance between pairs of sensitive ROIs across
subjects was significantly smaller than the mean functional dis-
tance between mixed ROI pairs, when one ROI was taken from
the sensitive and the other from the insensitive group of regions
[mean distance (Md) 6SEM: 0.48 60.01 within sensitive ROIs
and 0.69 60.01 between sensitive and insensitive ROIs,
t(14) ¼19.43, P<0.001; two tailed paired t-test across subjects].
The same effect was obtained for the insensitive ROIs group
[Md 6SEM: 0.47 60.01 within insensitive ROIs, t(14) ¼10.47,
P<0.001]. These results suggest that the MNS ROIs comprise of
two sub groups of regions that are functionally distinct with re-
spect to their sensitivity to action perception. There was no sig-
nificant difference between the mean functional distance
LH RH
Non-Masked Observation > Rest
Execution > Rest
Conjunction of Execution & Non-Masked Observation > Rest
A
B
C
8.00
3.02
t(14)
p<.009235
8.00
2.57
t(14)
p<.02219
4
8.00
3.61
t(14)
p<.002859
Fig. 3. Localization of the mirror neuron network. Group level (n¼15) RFX GLM maps (corrected for multiple comparisons with q(FDR)<0.05) using (A) the contrast of
NM observation (high and low opacity) vs rest, (B) the contrast of Execution vs rest and (C) the conjunction of (A) and (B). Regions of interest (ROIs) were defined accord-
ing to this conjunction.
Table 1. Regions of interest (ROIs) detected by GLM conjunction analysis of the contrasts: execution >rest and non-masked observation >rest
trials
Location Cluster size (no. voxels) Talairach coordinates (mean activation)
xYZ
Left primary motor cortex (M1) 193 53 740
Left sensorimotor cortex (SMC) 151 53 17 40
Supplementary motor area (SMA) 2696 2153
Right dorsal premotor cortex (PMd):
Superior cluster 255 46 449
Inferior cluster 536 55 443
Right inferior frontal gyrus (IFG) 468 34 17 11
Right ventral premotor cortex (PMv) 415 43 4 30
Right intra-parietal sulcus (IPS) 290 33 50 46
Right temporal-parietal junction (TPJ) and posterior
superior temporal sulcus (pSTS)
2425 57 35 20
Right lateral occipital cortex (LOC) 1949 38 57 16
Left LOC 2345 37 64 16
Right primary visual cortex (V1) 556 31 87 7
Note: All regions with cluster size 15 and FDR corrected (q <0.05) are listed.
6|Social Cognitive and Affective Neuroscience, 2017, Vol. 00, No. 0
within the sensitive ROIs relative to the mean functional dis-
tances within the insensitive ROIs [t(14) ¼0.49, P¼0.63].
Intrigued by this finding, we were further interested in testing
whether this pattern of functional dissimilarity between the
mirror ROI subgroups depends on the experimental condition.
To that end, we conducted a follow-up exploratory analysis in
which we performed the same analysis on resting state data
from an additional set of subjects (see methods). Similar to the
results obtained with our task data, the mean functional dis-
tance during rest between sensitive ROI pairs (Md 6SEM:
0.43 60.03), and the mean distance between insensitive pairs
(Md 6SEM: 0.48 60.08), were both smaller relative to the mean
distance between mixed pairs [Md 6SEM: 0.61 60.04;
t(14) ¼9.07, P<0.001 for sensitive pairs; t(14) ¼6.13, P<0.001 for
insensitive pairs]. This finding suggests that the partitioning of
rPMd
lM1
lSMC
rTPJ
SMA
rIFG
rIPS
rPMv
rPMd
lM1
lSMC
rTPJ
SMA
rIFG
rIPS
rPMv
rPMd
lM1
lSMC
rTPJ
SMA
rIFG
rIPS
rPMv
Sensitive ROIs
Insesitive ROIs
AB
-0.2
-0.1
0
0.1
0.3
0.0
0.1
0.2
0.3
0.4
0.5
0.6
r
0.2
-0.3
0
-0.1
-0.2-0.3` 0.1 0.2 0.3 0.4
Coordinate 1
Coordinate 2
Fig. 5. Functional distances during the experiment time course. (A) Correlation matrix between MNS ROIs based on the concatenated time-courses from all functional
runs (see Methods for details). Bold lines delineate the sensitive (red) and insensitive (blue) ROIs as revealed in the GLM analysis. (B) Two-dimensional plot of all func-
tional distances between ROIs using MDS (based on the distance matrix in A). The distances within each group of ROIs (sensitive/insensitive to perception level) are sig-
nificantly smaller than the distances between the groups (see text).
-0.3
0.0
0.3
0.6
1
le SMC
-0.3
0.0
0.3
0.6
1
le M1
-0.3
0.0
0.3
0.6
1
right PMd
1
-0.3
0.0
0.3
0.6
1
right SPL
-0.3
0.0
0.3
0.6
1
right PMv
-0.3
0.0
0.3
0.6
right TPJ/pSTS
-0.3
0.0
0.3
0.6
1
right IFG
-0.3
0.0
0.3
0.6
1
SMA\preSMA
Perception-Sensitive Perception-Insesitive (N=15, *p < 0.05, **p < 0.01)
Mask Non-Mask
Beta (
High Opacity-Low Opacity)
B
A
RHLH
SPL
TPJ
PMd
PMv
IFG
SMA\
preSMA
M1
SMC
**
** *
*
pSTS
*
*
*
*
*
Fig. 4. Differential Sensitivity to Perception level within the mirror neuron network. (A) The conjunction map from Figure 3C, color coded according to sensitive and in-
sensitive regions. Red color coded ROIs were found sensitive to the level of action perception beyond changes in opacity level, whereas the blue color coded ROIs were
found insensitive to perception level as defined from the analysis in (B). (B) For each ROI the beta differences between high and low opacities were separately calculated
in the masked and NM conditions. In the Masked condition, changes in opacity level corresponded with strong changes in perception level (see figure 2) while in the
NM condition perception was not affected. Changes in opacity level resulted in larger beta differences in the masked condition relative to NM condition in the right
pMd, right TPJ, left M1 and left SMC. This suggests stronger sensitivity to perception level in these regions (*P<0.05, **P<0.01, error bars represent standard error).
S. Simon and R. Mukamel |7
MNS ROIs to two distinct subnetworks is more general and
holds true beyond their sensitivity to action perception.
Discussion
In the present study, we investigated whether and how percep-
tion level modulates the activation magnitude within MNS re-
gions. To this end, we manipulated the perception level of
videos depicting different hand movements, and measured cor-
responding changes in the fMRI BOLD signal. Our results sug-
gest that the MNS can be divided to two functionally distinct
sub-networks with respect to their correspondence between ac-
tivity level and conscious perception of observed actions. Mirror
regions that are sensitive to perception level included M1 and
SMC in the left hemisphere and PMd, and pSTS/TPJ of the right
hemisphere. Mirror regions that were found insensitive to per-
ception level included the SMA, right IFG, PMv and SPL. This
parcellation to two subnetworks was also expressed in smaller
functional distances between regions within each network rela-
tive to regions across the two networks both during task and
resting state.
Among the mirror regions we localized in the current study,
the sensitive regions (e.g. the left M1, left SMC and the right
PMd) seem to share a common function that is tightly linked to
action execution mechanisms. The unique presence of most
corticospinal projections from the primary motor cortex and
PMd of the monkey (Dum and Strick, 1991; He et al., 1993, 1995)
suggests that these regions are the only ones within the MNS
that may have direct influence on action generation and execu-
tion (Stefano, 2015). Many transcranial magnetic stimulation
(TMS) studies in humans rely on the motor evoked potentials
elicited when stimulating M1 (Priori et al., 1998) and some dem-
onstrate shorter reaction times in response to stimulation of
the PMd (Chambers et al., 2007). These evidence add further sup-
port to the notion that these regions possibly signal the final
output to the muscles necessary for execution of an action. The
somatosensory cortex is sensitive to movements of skin and
muscles and co-activates with M1 and PMd due to its strong re-
ciprocal connections to them. We recently demonstrated stron-
ger mirror activity, as recorded from electroencephalography
(EEG) over the sensorimotor channels, for consciously perceived
vs non-perceived actions (Simon and Mukamel, 2016). Although
the spatial resolution of EEG is low, these channels most prob-
ably correspond with activity in the sensorimotor cortices. It is
most likely that the effect we found in EEG originates from the
sensitive regions as defined in the current study. In the current
fMRI study we found that an ROI consisting of the TPJ and ex-
tending to the posterior STS is also sensitive to changes in ac-
tion perception level regardless of opacity level. Several reports
have linked the TPJ to spatial (Macaluso and Driver, 2001;
Corbetta and Shulman, 2002) and re-orienting (Geng and Vossel,
2013) attentional processes as well as to social interaction (Krall
et al., 2015). Converging evidence identified the pSTS as a major
hub of the MNS that has a crucial role in action perception and
recognition (Grossman et al., 2000; Grossman et al., 2004).
Disruption of the function in the pSTS either by transcranial
magnetic stimulation (Grossman et al., 2005) or as a result of de-
generative brain disease (Nelissen et al., 2010) impairs the per-
ception of biological motion and/or action understanding.
The insensitive regions, in which no activation differences
with respect to action perception level were found, are consist-
ently associated with response inhibition mechanisms.
Activation during successful response inhibition tasks (e.g. go/
no-go, stop signal or Stroop) were reported in the right IFG
(Brass et al., 2005; Bien et al., 2009; Chikazoe et al., 2009; Dodds
et al., 2011; Sebastian et al., 2013; Erika-Florence et al., 2014;
Sebastian et al., 2016), right PMv (Bien et al., 2009; Chikazoe et al.,
2009; Dodds et al., 2011; Levy and Wagner, 2011; Sebastian et al.,
2013), pre-SMA (Sebastian et al., 2013; Erika-Florence et al., 2014)
and parietal regions (Bien et al., 2009; Sebastian et al., 2013).
Virtual lesions induced by TMS to the IFG (Chambers et al., 2007;
Swann et al., 2012) and pre-SMA (Swann et al., 2012; Obeso et al.,
2013) impaired inhibition performance. Enhanced activations in
the PMv, SMA, IFG and SPL were found during response inhib-
ition while anticipating a reward (Rosell-Negre et al., 2014), and
during expectation for a stop signal to occur (Vink et al., 2015).
The mirror system may be utilized for perceptual anticipation
and prediction of ongoing actions time courses (Chaminade
et al., 2001; Kilner et al., 2007; Lamm et al., 2007; Schubotz, 2007),
and evidence for the involvement of the IFG (Hampshire et al.,
2010; Avenanti et al., 2013) and PMv (Bischoff et al., 2014) in this
process have been reported. The lack of differences in the cur-
rent study between perceived and not perceived conditions in
these regions could be a result of top-down expectation of an
impending action to appear in the non-perceived trials of the
masked-low condition. We cannot rule out the possibility that
greater anticipation in the non-perceived trials might increase
the activity in these regions and narrow the differences be-
tween perceived and non-perceived trials.
Our parcellation of the MNS to sensitive/insensitive regions
with respect to action perception goes along with the earlier re-
ports of differential sensitivity within MNS to action inhibition
and anticipation. Our finding that functional distance patterns
remained similar across perception task and resting state con-
ditions even in a separate group of subjects, suggest that each
group of MNS regions might consist a somewhat independent
functional network regardless of task. This idea is further sup-
ported by a study of Molinari et al. (2013) using independent
component analysis on resting-state and action observation
task fMRI data. The study identified two networks with good
spatial correspondence between task and rest related maps.
The first network included portions of the anterior parietal cor-
tex including the somatosensory cortex and dorsal parts of the
premotor cortex in proximity to M1 corresponding with our sen-
sitive regions network. The second network included more pos-
terior portions of the parietal lobe and more ventral premotor
parts extending toward the IFG corresponding with our insensi-
tive network. The activity of these networks is at least in part
supported by direct anatomical connections between their
nodes (Molinari et al., 2013). In a meta-analytic connectivity
study, modeling of the IFG independent of employed paradigm,
determined the strongest functional connections for the right
IFG with the left IFG/Insula, bilateral portions of the ventral pre-
motor cortex, SMA and pre-SMA corresponding to the insensi-
tive network (Sebastian et al., 2016). Taken together these data
support the existence of two sub networks within the mirror
system which as our current study suggests differ also on the
dimension of sensitivity to action perception level.
In the current study, we distinguished between two neuro-
anatomical networks within the MNS with respect to their sen-
sitivity to the level of action perception. To date, the discussion
regarding the functional role of the MNS in action and intention
understanding has mostly addressed this system as a whole,
and possible functional variability between the different nodes
has been less emphasized. The current results support the no-
tion that the MNS comprises of (at least) two subsystems. Given
that action understanding requires conscious perception, the
8|Social Cognitive and Affective Neuroscience, 2017, Vol. 00, No. 0
current results contribute to the discussion concerning the
functional role of the different regions within the MNS to this
important cognitive function.
Funding
This study was supported by the I-CORE Program of the
Planning and Budgeting Committee and The Israel Science
Foundation (grant No. 51/11), The Israel Science Foundation
(grants Nos 1771/13 and 2043/13), and Human Frontiers
Science Project (HFSP) Career Development Award
(CDA00078/2011-C) (R.M.); The Sagol School of Neuroscience
fellowship (S.S.). The funders had no role in study design,
data collection and analysis, decision to publish, or prepar-
ation of the manuscript.
Acknowledgements
The authors thank, O. Ossmy, R. Gilron, D. Reznik, M. Mazor
and L. Mudrik for their fruitful comments on the
manuscript.
Conflict of interest. None declared.
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