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Sensitivity to perception level differentiates two subnetworks within the mirror neuron system

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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.
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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
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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
xiÞXn
k¼1ðxjk
xjÞ
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
Xn
k¼1ðxik
xiÞ2
rffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
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
condence
(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 condence 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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10 | Social Cognitive and Affective Neuroscience, 2017, Vol. 00, No. 0
... In a clever pair of experiments, Shiri Simon and Roy Mukamel (2015a;2015b) separately used EEG and fMRI to test the hypothesis that MN-related electrical activity and hemodynamic responses, respectively, are dependent on conscious processing. Predicated on the assumption that action understanding requires conscious understanding, they asked whether putative measures of MN activity would show sensitivity to whether observed stimuli were perceived consciously. ...
... The fMRI version of this experiment was very similar in design, though it included an additional opacity manipulation, with half of the observed hand actions being presented with low opacity, and hence being consciously perceived less often. Focusing on the hemodynamic response differences to consciously and not-consciously perceived stimuli, Simon and Mukamel (2015b) found multiple regions believed to contain MNs, including dorsal PMC, primary motor cortex (M1) and somatosensory cortex that were more active when the stimuli were consciously perceived. Two additional and adjacent regions were also preferentially activated by consciously perceived stimuli: 1) The pSTS, a region that is not believed to contain MNs, but is suggested to provide the biological motion detection needed to activate the MN system, and 2) The TPJ -an area not known to contain MNs but commonly believed to be involved in inferential processes associated with so-called mentalizing as well as self-other discrimination. ...
... Therefore, it should probably be assumed that any instance of measuring mu suppression likely reflects mirror-and non-mirror related activity. Nonetheless, the results of this pair of studies (Simon & Mukamel, 2015a;2015b) are intriguing in their consistency with the hypothesis that, to the extent that MN activity is associated with action understanding, it is necessarily associated with conscious perception. Mizuguchi et al. (2016) provided evidence that what they refer to as the action observation network (AON), which includes premotor and inferior parietal regions, is insensitive to inferences about another person's actions while TPJ and pSTS are sensitive. ...
Chapter
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Mirror neurons have generated intense interest since their discovery in the early 1990s because they offer a potential neural mechanism for linking the observation of a conspecific’s action to the representation of the motor plan for that action in the observer’s brain. Much progress has been made in the last two and one half decades, but much remains mysterious as well. In this chapter we discuss research in macaque monkeys and what has been revealed about the functional, anatomical and connectivity characteristics of mirror neurons. We also discuss the use of non-invasive brain imaging to measure mirror neurons, considering the pros and cons. Further discussion concerns what role mirror neurons play in action understanding as well as various models of mirror neuron function.
... Elle montre en outre que l'IPL aurait une organisation actotopique, à savoir que : les actions consistant à ramener un objet à soi (« saisir », « tirer ») activent la partie ventrale de l'AIP (présumée de l'homme), alors que les actions consistant à éloigner de soi (« laisser tomber », « pousser ») activerait la partie dorsale de cette même aire [61]. Simon et al. [62] montrent également que le RNM serait constitué de deux sous réseaux : l'un sensible aux niveaux de perception de l'action observée (incluant M1, PMd, STS), l'autre insensible à ceux-ci (incluant SMA, IFG, PMv, SPL). ...
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Résumé En 1992, le Laboratoire de physiologie humaine de l’université de Parme (Italie) publie une étude décrivant, chez le macaque, des neurones « miroirs » s’activant à la fois lorsque le singe réalise une action et lorsqu’il observe un expérimentateur effectuer cette même action. L’équipe de recherche à l’origine de cette découverte postule que le système des neurones miroirs est la base neurale de notre capacité à comprendre l’action d’autrui au travers d’une cartographie motrice de l’action observée sur le répertoire moteur de l’observateur (direct-matching hypothesis). Cette conception rencontre néanmoins de sérieuses critiques. Ces critiques tentent de relativiser la fonction des neurones miroirs en les replaçant au sein d’un maillage d’interdépendances neurocognitives et sensorielles. En somme, la caractéristique essentielle de ces neurones est d’associer le traitement de l’information sensorielle, notamment visuelle, avec celui de l’information motrice. Leur fonction élémentaire serait ainsi de fournir une simulation motrice de l’action observée, à partir des informations visuelles de celle-ci. Ils peuvent contribuer, de concert avec d’autres aires cérébrales non-miroirs, à l’identification/prédiction du but de l’action et à l’interprétation de l’intention de l’acteur qui l’effectue. L’étude de la connectivité et des synchronisations à haute fréquences des différentes aires cérébrales en jeu lors de l’observation d’une action apporterait probablement des informations importantes quant à la contribution dynamique des neurones miroirs à la « compréhension » de l’action d’autrui. La présente revue a pour vocation d’offrir au lecteur une analyse actualisée des preuves scientifiques relatives aux neurones miroirs et de leur fonction élémentaire, ainsi que de l’éclairer quant à leur contribution à notre faculté d’interpréter et de comprendre l’action d’autrui.
... This network comprises frontal and parietal regions typically considered as part of the motor pathway (e.g., premotor, and supplementary motor areas). Interestingly, some regions within the AON respond to subliminally presented actions (i.e., in lack of reported conscious perception) while other regions are sensitive to the degree of visual awareness (Simon and Mukamel, 2017). Evidence from other techniques such as EEG (Muthukumaraswamy and Johnson, 2004;Simon and Mukamel, 2016), MEG (Hari et al., 1998) and transcranial magnetic stimulation (TMS) (Fadiga et al., 1995) provide further support for sensory-evoked responses in motor regions. ...
Article
Learning a motor skill requires physical practice that engages neural networks involved in movement. These networks have also been found to be engaged during perception of sensory signals associated with actions. Nonetheless, despite extensive evidence for the existence of such sensory-evoked neural activity in motor pathways, much less is known about their contribution to learning and actual changes in behavior. Primate studies usually involve an overlearned task while studies in humans have largely focused on characterizing activity of the action observation network (AON) in the context of action understanding, theory of mind, and social interactions. Relatively few studies examined neural plasticity induced by perception and its role in transfer of motor knowledge. Here, we review this body of literature and point to future directions for the development of alternative, physiologically grounded ways in which sensory signals could be harnessed to improve motor skills.
... Moreover, involvement of brain regions remote from zones of maximal atrophy may reflect distributed functional network effects (for example, visual cortical activity has been shown to be modulated by amygdala 75 ) in conjunction with disease-related network connectivity changes, which are known to extend beyond the atrophy maps that conventionally define particular FTD syndromes 76 . Taken together, the present neuroanatomical findings are compatible with the previously proposed, hierarchical organisation of embodied representations supporting emotional decoding and empathy 13,48,77,78 : whereas early visual and motor areas may support automatic imitation via low-level visual and kinematic representations, higher levels of the processing hierarchy engage the human 'mirror' system and substrates for semantic, evaluative and mentalising processes that drive explicit emotion identification. ...
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Automatic motor mimicry is essential to the normal processing of perceived emotion, and disrupted automatic imitation might underpin socio-emotional deficits in neurodegenerative diseases, particularly the frontotemporal dementias. However, the pathophysiology of emotional reactivity in these diseases has not been elucidated. We studied facial electromyographic responses during emotion identification on viewing videos of dynamic facial expressions in 37 patients representing canonical frontotemporal dementia syndromes versus 21 healthy older individuals. Neuroanatomical associations of emotional expression identification accuracy and facial muscle reactivity were assessed using voxel-based morphometry. Controls showed characteristic profiles of automatic imitation, and this response predicted correct emotion identification. Automatic imitation was reduced in the behavioural and right temporal variant groups, while the normal coupling between imitation and correct identification was lost in the right temporal and semantic variant groups. Grey matter correlates of emotion identification and imitation were delineated within a distributed network including primary visual and motor, prefrontal, insular, anterior temporal and temporo-occipital junctional areas, with common involvement of supplementary motor cortex across syndromes. Impaired emotional mimesis may be a core mechanism of disordered emotional signal understanding and reactivity in frontotemporal dementia, with implications for the development of novel physiological biomarkers of socio-emotional dysfunction in these diseases.
Thesis
One of the essential characteristics that differentiate animal and plant species is their ability to move in space. It thus appears that motor skills condition the development of cognition. In this respect, the present thesis begins with a triple observation, that: (1) attention is subordinated to action, (2) there is an intimate relationship between attentional control and sensorimotor control through the exercise of sustained attention, and (3) there is a second (inverse) relationship between attentional control and sensorimotor control through the exercise of stillness. Through work on brain electrophysiology in different attentional conditions - action observation, attention deficit (with or without hyperactivity), and mindfulness meditation - the present thesis aims to contribute to the identification of brain dynamics underlying attentional control and the ways in which the exercise of this control can, in turn, modulate the brain's procedural activities. After a detailed review of the fundamental properties of attention, the general principles of electroencephalogram, and the neural correlates underlying attentional control, we preliminarily focused on the oscillatory dynamics associated with visual attention. From an experimental point of view, the aim was to distinguish the different functional components (visual, attentional, sensorimotor) of the brain rhythms by modifying the visual information (an animation of walking) passively submitted to the subject's attention. On this basis, we next explored brain dynamics in children with attention deficit (with/without hyperactivity, ADHD) during an attention/inhibition task (Cue-GO/NoGO). We showed an alteration of the rhythms linked to the processing of visual information. From a neuroanatomical point of view, our data indicated that this deficit would be based on an imbalance between the two fronto-parietal attention systems, ventral-medial and dorso-lateral, which could make these children more sensitive to the salience of visual information and induce less flexibility in cognitive control. In contrast, we showed that the 'non-reactive' dimension of mindfulness altered the temporal dynamics of large-scale neural networks. This effect appeared to be support by increased cerebellum activity, and to induce less (re)activity of the attentional salience network to distractions. The theoretical and potentially clinical implications of these results are discussed, taking into account the specific scientific context of each study, the analytical tools used (event-related potentials, source location, microstates) and their limitations. In sum, our data suggest that mindfulness meditation may induce a reorganization of the cortico-subcortical loops that govern attentional behavior, and may be useful in the treatment of ADHD.
Article
Background: Graded motor imagery (GMI) therapy is a neural rehabilitative physiotherapy that has been shown to alleviate the severity of complex regional pain syndrome, phantom limb pain and disability. Objective: To identify neural networks associated with the use of graded mirror therapy (MT) while imagining hand movements. Methods: We made a block-design functional magnetic resonance imaging study of MT included three experiments: (1) immobile unimanual MT (IU-MT), in which the right hand flexed and made a fist, which then remained immobile; (2) mobilization unimanual MT (MU-MT), in which the right hand performed a flexion-extension movement; and (3) mobilization bimanual MT (MB-MT), in which both hands performed a flexion-extension movement. When subjects started their hand movements, they gazed at the mirror and imagined the same movement behind the mirror. Results: We discovered that the sensorimotor area of the left brain, superior temporal gyrus/middle temporal gyrus (STG/MTG) of the right brain and visual areas were activated by IU-MT. In MU-MT, only the STG/MTG was activated. Furthermore, MB-UT mostly activated the sensorimotor area and STG of the right brain. However, there were no brain areas activated by MU-MT compared with IU-MT or MB-MT; however, MB-MT activated more motor areas than IU-MT. Importantly, we determined that the level of mirror imagery was negatively correlated with signals in the mirror neuron system (MNS) and positively related with the signals in the sensorimotor areas. Conclusions: We suggest that graded MT might be a sequential therapeutic program that can enhance the sensorimotor cortex. The MNS might have an initiating role in graded MT. Thus, there is the possibility that graded MT is a helpful treatment strategy for the rehabilitation of dysfunctional patients.
Article
Seeing an agent perform an action typically triggers a motor simulation of that action in the observer's Mirror Neuron System (MNS). Over the past few years, it has become increasingly clear that during action observation the patterns and strengths of responses in the MNS are modulated by multiple factors. The first aim of this paper is therefore to provide the most comprehensive survey to date of these factors. To that end, 22 distinct factors are described, broken down into the following sets: six involving the action; two involving the actor; nine involving the observer; four involving the relationship between actor and observer; and one involving the context. The second aim is to consider the implications of these findings for four prominent theoretical models of the MNS: the Direct Matching Model; the Predictive Coding Model; the Value-Driven Model; and the Associative Model. These assessments suggest that although each model is supported by a wide range of findings, each one is also challenged by other findings and relatively unaffected by still others. Hence, there is now a pressing need for a richer, more inclusive model that is better able to account for all of the modulatory factors that have been identified so far.
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Introduction The ability to understand actions and intentions of others is of great importance to social relationships and is associated with the mirror neuron system of the human brain. Whether conscious perception of specific actions is necessary to trigger activity in this system, or alternatively whether this response is independent of conscious perception is not known. Methods We addressed this issue by rendering videos of right hand movements invisible to conscious perception, and measuring electroencephalogram (EEG) power suppression in the mu (8–13 Hz) and beta (15–25 Hz) range as index corresponding to the magnitude of mirror neuron activity. Results In the beta range over bilateral sensorimotor sites, we find that suppression indices follow the reported perceptual level of subjects with stronger suppression for consciously perceived trials. Furthermore, in the nonperceived trials, oscillation power is significantly suppressed relative to baseline. In the low mu range (8–10 Hz), oscillation power over the left sensorimotor site is significantly more suppressed in the consciously perceived versus nonperceived trials. Conclusions Our data suggest that the intensity of mirror system responses during action observation decreases with the observers' perception level yet remains significant during observation of invisible actions. Such subliminal activity could help explain phenomena such as covert imitation.
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Illusions that produce perceptual suppression despite constant retinal input are used to manipulate visual consciousness. Here we report on a powerful variant of existing techniques, continuous flash suppression. Distinct images flashed successively at approx10 Hz into one eye reliably suppress an image presented to the other eye. The duration of perceptual suppression is at least ten times greater than that produced by binocular rivalry. Using this tool we show that the strength of the negative afterimage of an adaptor was reduced by half when it was perceptually suppressed by input from the other eye. The more completely the adaptor was suppressed, the more strongly the afterimage intensity was reduced. Paradoxically, trial-to-trial visibility of the adaptor did not correlate with the degree of reduction. Our results imply that formation of afterimages involves neuronal structures that access input from both eyes but that do not correspond directly to the neuronal correlates of perceptual awareness.
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The right inferior frontal cortex (rIFC) is frequently activated during executive control tasks. Whereas the function of the dorsal portion of rIFC, more precisely the inferior frontal junction (rIFJ), is convergingly assigned to the attention system, the functional key role of the ventral portion, i.e., the inferior frontal gyrus (rIFG), is hitherto controversially debated. Here, we used a two-step methodical approach to clarify the differential function of rIFJ and rIFG. First, we used event-related functional magnetic resonance imaging (fMRI) during a modified stop signal task with an attentional capture condition (acSST) to delineate attentional from inhibitory motor processes (step 1). Then, we applied coordinate-based meta-analytic connectivity modeling (MACM) to assess functional connectivity profiles of rIFJ and rIFG across various paradigm classes (step 2). As hypothesized, rIFJ activity was associated with the detection of salient stimuli, and was functionally connected to areas of the ventral and dorsal attention network. RIFG was activated during successful response inhibition even when controlling for attentional capture and revealed the highest functional connectivity with core motor areas. Thereby, rIFJ and rIFG delineated largely independent brain networks for attention and motor control. MACM results attributed a more specific attentional function to rIFJ, suggesting an integrative role between stimulus-driven ventral and goal-directed dorsal attention processes. In contrast, rIFG was disclosed as a region of the motor control but not attention system, being essential for response inhibition. The current study provides decisive evidence regarding a more precise functional characterization of rIFC subregions in attention and inhibition.
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The common approach to the multiplicity problem calls for controlling the familywise error rate (FWER). This approach, though, has faults, and we point out a few. A different approach to problems of multiple significance testing is presented. It calls for controlling the expected proportion of falsely rejected hypotheses — the false discovery rate. This error rate is equivalent to the FWER when all hypotheses are true but is smaller otherwise. Therefore, in problems where the control of the false discovery rate rather than that of the FWER is desired, there is potential for a gain in power. A simple sequential Bonferronitype procedure is proved to control the false discovery rate for independent test statistics, and a simulation study shows that the gain in power is substantial. The use of the new procedure and the appropriateness of the criterion are illustrated with examples.
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We recorded electrical activity from 532 neurons in the rostral part of inferior area 6 (area F5) of two macaque monkeys. Previous data had shown that neurons of this area discharge during goal-directed hand and mouth movements. We describe here the properties of a newly discovered set of F5 neurons ("mirror neurons', n = 92) all of which became active both when the monkey performed a given action and when it observed a similar action performed by the experimenter. Mirror neurons, in order to be visually triggered, required an interaction between the agent of the action and the object of it. The sight of the agent alone or of the object alone (three-dimensional objects, food) were ineffective. Hand and the mouth were by far the most effective agents. The actions most represented among those activating mirror neurons were grasping, manipulating and placing. In most mirror neurons (92%) there was a clear relation between the visual action they responded to and the motor response they coded. In approximately 30% of mirror neurons the congruence was very strict and the effective observed and executed actions corresponded both in terms of general action (e.g. grasping) and in terms of the way in which that action was executed (e.g. precision grip). We conclude by proposing that mirror neurons form a system for matching observation and execution of motor actions. We discuss the possible role of this system in action recognition and, given the proposed homology between F5 and human Brocca's region, we posit that a matching system, similar to that of mirror neurons exists in humans and could be involved in recognition of actions as well as phonetic gestures.
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In this article, we treat the mirror neuron system defined as a set of brain regions active both when an individual performs an action and when he or she perceives another individual performing a similar action. In particular, we examine the mirror neuron network in monkeys considering the cortical regions involved in this mechanism and their connections, as well as their functional properties studied using single-neuron recording. In addition, we report the evidence for the existence of a mirror neuron system in humans, as revealed by transcranial magnetic stimulation studies.
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Modern neurosurgical concepts call for not only "seeing" but also for "localizing" structures in three-dimensional space in relationship to each other. Hence there is a need for a reference system. This book aims to put this notion into practice by means of anatomical and MRI sections with the same stereotaxic orientation. The purpose is to display the fundamental distribution of structures in three-dimensional space and their spatial evolution within the brain as a whole, while facilitating their identification; to make comparative studies of cortico-subcortical lesions possible on a basis of an equivalent reference system; to exploit the anatomo-functional data such as those furnished by SEEG in epilepsy and to enable the localization of special regions such as the SMA in three-dimensional space; and to apply the anatomical correlations of this reference system to neurophysiological investigations lacking sufficient anatomical back-up (including PET scan).
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We review evidence for partially segregated networks of brain areas that carry out different attentional functions. One system, which includes parts of the intraparietal cortex and superior frontal cortex, is involved in preparing and applying goal-directed (top-down) selection for stimuli and responses. This system is also modulated by the detection of stimuli. The other system, which includes the temporoparietal cortex and inferior frontal cortex, and is largely lateralized to the right hemisphere, is not involved in top-down selection. Instead, this system is specialized for the detection of behaviourally relevant stimuli, particularly when they are salient or unexpected. This ventral frontoparietal network works as a 'circuit breaker' for the dorsal system, directing attention to salient events. Both attentional systems interact during normal vision, and both are disrupted in unilateral spatial neglect.
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The chameleon effect refers to nonconscious mimicry of the postures, mannerisms, facial expressions, and other behaviors of one's interaction partners, such that one's behavior passively rind unintentionally changes to match that of others in one's current social environment. The authors suggest that the mechanism involved is the perception-behavior link, the recently documented finding (e.g., J. A. Bargh, M. Chen, & L. Burrows, 1996) that the mere perception of another' s behavior automatically increases the likelihood of engaging in that behavior oneself Experiment 1 showed that the motor behavior of participants unintentionally matched that of strangers with whom they worked on a task. Experiment 2 had confederates mimic the posture and movements of participants and showed that mimicry facilitates the smoothness of interactions and increases liking between interaction partners. Experiment 3 showed that dispositionally empathic individuals exhibit the chameleon effect to a greater extent than do other people.
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The subjective belief of what will happen plays an important role across many cognitive domains, including response inhibition. However, tasks that study inhibition do not distinguish between the processing of objective contextual cues indicating stop-signal probability and the subjective expectation that a stop-signal will or will not occur. Here we investigated the effects of stop-signal probability and the expectation of a stop-signal on proactive inhibition. Twenty participants performed a modified stop-signal anticipation task while being scanned with functional magnetic resonance imaging. At the beginning of each trial, the stop-signal probability was indicated by a cue (0% or > 0%), and participants had to indicate whether they expected a stop-signal to occur (yes/no/don't know). Participants slowed down responding on trials with a > 0% stop-signal probability, but this proactive response slowing was even greater when they expected a stop-signal to occur. Analyses were performed in brain regions previously associated with proactive inhibition. Activation in the striatum, supplementary motor area and left dorsal premotor cortex during the cue period was increased when participants expected a stop-signal to occur. In contrast, activation in the right inferior frontal gyrus and right inferior parietal cortex activity during the stimulus-response period was related to the processing of contextual cues signalling objective stop-signal probability, regardless of expectation. These data show that proactive inhibition depends on both the processing of objective contextual task information and the subjective expectation of stop-signals. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.