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Inferior Frontal Gyrus Activity Triggers Anterior Insula Response to Emotional Facial Expressions

Authors:
  • Dell Medical School, University of Texas at Austin

Abstract

The observation of movies of facial expressions of others has been shown to recruit similar areas involved in experiencing one's own emotions: the inferior frontal gyrus (IFG), the anterior insula and adjacent frontal operculum (IFO). The causal link between activity in these 2 regions, associated with motor and emotional simulation, respectively, has remained unknown. Here using psychophysiological interaction and Granger Causality Modeling, we show that activity in the IFO is causally triggered by activity in the IFG, and that this effective connectivity is specific to the IFG. These findings shed new light on the intricate relationship between motor and affective components of emotional empathy.
Inferior Frontal Gyrus Activity Triggers Anterior Insula Response to
Emotional Facial Expressions
Mbemba Jabbi
University of Groningen and National Institutes of Mental
Health, Bethesda, Maryland
Christian Keysers
University of Groningen
The observation of movies of facial expressions of others has been shown to recruit similar areas involved
in experiencing one’s own emotions: the inferior frontal gyrus (IFG), the anterior insula and adjacent
frontal operculum (IFO). The causal link between activity in these 2 regions, associated with motor and
emotional simulation, respectively, has remained unknown. Here using psychophysiological interaction
and Granger Causality Modeling, we show that activity in the IFO is causally triggered by activity in the
IFG, and that this effective connectivity is specific to the IFG. These findings shed new light on the
intricate relationship between motor and affective components of emotional empathy.
Keywords: emotional contagion, facial mimicry, mirror neuron system, insula, inferior frontal gyrus
Emotions play a key role in our lives and understanding the
emotions of other people is essential for adequate social function-
ing. However, how our brain associates feelings to the facial
expressions of other people’s emotions remains poorly understood.
Mirror neurons were shown to respond while a monkey per-
forms a goal directed action as well as when the monkey sees or
hears another individual perform a similar action (e.g., breaking
the shell of a peanut apart; Fogassi, Ferrari, Gesierich, Rozzi,
Chersi, & Rizzolatti, 2005; Gallese et al., 1996; Keysers et al.,
2003; Kohler et al., 2002). When these neurons were first discov-
ered, the concept of motor simulation gained great popularity. This
concept demonstrated that although we witness the actions of
others, our brain simulates their behavior by activating part of the
neurons involved in executing the same action—“as if” the ob-
server was doing the same. Although in the monkey, evidence for
mirror neurons is mainly restricted to goal directed actions (but see
Ferrari, Gallese, Rizzolatti, & Fogassi, 2003), the concept of
simulation has been extended to sensations in the somatosensory
cortex (Blakemore, Bristow, Bird, Frith, & Ward, 2005; Keysers et
al., 2004) and emotions in the anterior insula and adjacent frontal
operculum (IFO; Carr, Iacoboni, Dubeau, Mazziotta, & Lenzi,
2003; Jabbi, Swart, & Keysers, 2007; Jackson, Meltzoff, &
Decety, 2005; Singer et al., 2004, 2006; van der Gaag, Minderaa,
& Keysers, 2007; Wicker et al., 2003) in humans (Gallese, Key-
sers, & Rizzolatti, 2004; Goldman & Sripada, 2005; Keysers &
Gazzola, 2006; Singer, 2007a, 2007b). Neuroscientific support for
extending the concept of simulation to emotions primarily stems
from two lines of research that examine whether observing the
emotional facial expressions of other individuals activates regions
involved in (a) performing similar facial expressions and (b)
experiencing similar emotions and sensations.
Carr et al. (2003) and Leslie, Johnson-Frey, and Grafton (2004)
asked participants to observe and imitate facial expressions and
found extensive sectors of the ventro-lateral frontal cortex includ-
ing BA45 in the inferior frontal gyrus (IFG) to be involved in both
the observation and the imitation of facial expressions. Hennen-
lotter et al. (2005) asked participants to view and execute smiles,
and found a network including the right IFG to be involved in both.
Van der Gaag et al. (2007) instructed participants to observe
moving patterns, neutral facial movements (blowing up the
cheeks), and emotional facial expressions (disgust, fear, and
happy) in an event related fashion, and asked them to subsequently
produce all four observed facial movements. Contrasting the ob-
servation of facial expressions against the movies of pattern mo-
tion that do not match the observer’s motor vocabulary, they found
that, of the brain regions involved in the execution of facial
expressions, only a relatively circumscribed network involving the
right BA45 and bilateral MTG responded more to all the facial
expressions (neutral or emotional) compared to pattern motion
(van der Gaag et al., 2007).
In the monkey, the most ventral sector of F5 contains mirror
neurons that respond both during the production and observation
of facial movements (Ferrari et al., 2003). This area is considered
to be the homologue of human Broca’s area in the IFG (Petrides,
Cadoret, & Mackey, 2005). Taken together, the existence of facial
mirror neurons in region F5 of the monkey and voxels shared
between the observation and execution of facial expressions in the
human IFG suggest that in humans, mirror neurons within these
voxels could transform observed facial expressions into a pattern
Mbemba Jabbi, Social Brain Lab, BCN Neuroimaging Center, Depart-
ment of Neuroscience, University Medical Center Groningen and Section
on Integrative Neuroimaging, Clinical Brain Disorders Branch, Genes
Cognition and Psychos’s Program, National Institutes of Mental Health,
Bethesda, Maryland; Christian Keysers, Social Brain Lab, BCN Neuroim-
aging Center, Department of Neuroscience, University Medical Center
Groningen, University of Groningen.
This study was supported by a Marie Curie Excellence Grant of the
European Commission and a VIDI grant of the Dutch Science Foundation
(N.W.O.) to Christian Keysers. We thank Remco Renken and Luca Nanetti
for implementing and calculating the Granger Causality Values, Marte
Swart for data collection, and Aarthi Padmanabhan for comments.
Correspondence concerning this article should be addressed to Christian
Keysers, BCN Neuroimaging Center, University Medical Center Gro-
ningen, Antonius Deusinglaan 2, 9713 AW Groningen, the Netherlands.
E-mail: c.m.keysers@rug.nl
Emotion Copyright 2008 by the American Psychological Association
2008, Vol. 8, No. 6, 775–780 1528-3542/08/$12.00 DOI: 10.1037/a0014194
775
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of neural activity that would be suitable for producing similar
facial expressions and provide the basis for a motor simulation of
facial expressions (Keysers & Gazzola, 2006; van der Gaag et al.,
2007). However, these putative mechanisms would not be limited
to emotional facial expressions. van der Gaag and collaborators did
not find significant differences between the observation (and pro-
duction) of neutral versus emotional facial movements in the
lateral aspects of the IFG. In line with this finding, this form of
motor simulation has sometimes been referred to as “cold” simu-
lation because it is not specific to the “heat” of affect (Gallese et
al., 2004). In contrast to the active IFG during both the observation
and the execution of facial expressions, in human functional MRI
(fMRI) studies, the primary motor cortex has been found to be
typically active only during the execution of goal directed actions
and facial expressions, but not during their observation (e.g., Carr
et al., 2003; Gazzola, Aziz-Zadeh, & Keysers, 2006, Gazzola et al.,
2007; Hennenloter et al., 2004; Leslie et al., 2004; van der Gaag et
al., 2007). This suggests that the observation of facial expressions
triggers a motor simulation in regions involved in higher motor
functions (i.e., BA6, 44, 45, and SMA/pre-SMA), but that this sim-
ulation does not automatically lead to the activation of the primary
motor cortex region that would produce overt facial movements.
Wicker et al. (2003) and Jabbi et al. (2007) examined whether brain
regions involved in experiencing emotions (instead of expressing
them as discussed earlier) are activated while people view emotional
facial expressions. In these studies, participants were shown movies of
faces expressing disgust and subsequently exposed them to unpleasant
odors (Wicker et al., 2003) or tastes (Jabbi et al., 2007). They found
that a transition zone between insula and frontal operculum, a region
they label IFO (because their reported activation regions consistently
encompassed both the anterior insula and frontal operculum), was
active both during the experience of disgust and while viewing the
disgust of other individuals. The IFO is also shown to activate while
participants view (Botvinick et al., 2005; Jackson et al., 2005; Jack-
son, Rainville, & Decety, 2006; Lamm, Batson, & Decety, 2007;
Moriguchi et al., 2007; Morrison, Lloyd, di Pellegrino, & Roberts,
2004; Saarela et al., 2007) or are aware (Singer et al., 2004, 2006) that
another individual is in pain and when they experience pain them-
selves. To underline that this region is not specifically involved in
mapping aversive experiences of one’s self and while being aware of
others’ similar aversive experiences, the same region is also shown to
be involved in the experience of gustatory pleasure and while viewing
pleased facial expressions (Jabbi et al., 2007).
More important, the overlapping regions of the IFO are more
strongly activated during the observation of another individual’s
emotions if the participant reports being more prone to sharing the
distress of others (Jabbi et al., 2007) as well as during the aware-
ness of another individual’s pain, in more empathically concerned
individuals (Singer et al., 2004). Together, these data suggest that
the brain may not only perform a cold motor simulation of what
the emotionally expressive face of the other individual is doing (in
the IFG), but also a hot (i.e., affect laden) simulation of what the
other individual is feeling (in the IFO). Lesions in the IFO have
been shown to lead (among other complex deficits of emotional
awareness) to an impairment of the experience and recognition of
disgust in particular (Adolphs, Tranel, & Damasio, 2003; Calder,
Keane, Manes, Antoun, & Young, 2000).
In summary, there is evidence that the right BA45 within the IFG
is involved during both the observation and execution of facial move-
ments and that the IFO is involved during both the observation of
facial expression and the experience of similar emotions. However, a
notable difference between activations in BA45 and the IFO is that the
former is similarly strong for emotional and neutral facial movements
whereas the latter is stronger for emotional facial expressions. This
supports the idea that activity in BA45 may reflect a form of cold
motor simulation whereas that of the IFO may underlie a hot simu-
lation of emotional feeling states (Damasio, 1999, 2003; Gallese &
Goldman, 1998; Gallese et al., 2004).
The critical question that remains unanswered is whether acti-
vations during the observation of facial expressions in BA45 and
the IFO reflect two independent processes or are causally related
with activity in BA45 triggering activity in IFO or vice versa.
To examine this question, we performed a multilevel functional
connectivity analyses on data previously acquired using fMRI
from 18 participants while they viewed movies of emotional and
neutral facial expressions. In the movies, actors sipped a liquid
from a cup and reacted by displaying a disgusted or neutral facial
expression. As reported elsewhere (Jabbi et al., 2007), the same
participants also experienced unpleasant and neutral tastes in a
separate session of fMRI scanning to determine the location of the
(right) IFO region common to the observation and experience of
gustatory emotions and its empathic related activation patterns.
Facial movements of the actors are the main source of informa-
tion about their emotions, and BA45 in particular, has been shown
in a separate experiment to respond similarly during the observa-
tion of emotional and neutral facial expressions, whereas the IFO
responded more during the observation of emotional compared to
neutral facial expressions (van der Gaag et al., 2007). With this in
mind, and in accord with the proposals of Carr et al. (2003) and
Dapretto et al. (2006), we hypothesized that activity in BA45 may
causally determine activity in the IFO of our participants during
the observation of facial expressions and that this functional con-
nectivity should be effectively stronger while viewing emotional
compared to neutral facial expressions.
To test this hypothesis, we applied a novel combination of two
methods for the analysis of functional connectivity. First, using
psychophysiological interaction (PPI) analysis of brain activity
(Friston et al., 1997), we tested whether the IFO is effectively more
connected with BA45 during the observation of emotional com-
pared to neutral facial expressions, and whether such a pattern of
effective connectivity is restricted to BA45. Second, to determine
if the changes of effective connectivity reflect a causal influence
from BA45 3IFO, we applied Granger Causality modeling
(Geweke, 1982, 1984; Goebel, Roebroeck, Kim, & Formisano,
2003; Roebroeck, Formisano, & Goebel, 2005; see Method),
which is based on the rationale that if BA45 causally influences the
IFO more than vice versa, the state of BA45 at time tshould
predict the state of the IFO at time t1 better than the state of the
IFO at time tthat of BA45 at time t1.
Method
Participants and Procedure
We used the fMRI data of 18 participants who viewed an actor
sip a liquid from a cup and look either disgusted or neutral, and
later experienced unpleasant tastes (Jabbi et al., 2007).
776 JABBI AND KEYSERS
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Image Acquisition
Images were acquired using a Philips 3T whole-body scanner
(Best, The Netherlands) using a circular sense head coil. T2-
weighted echo-planar sequencing was performed with 39 inter-
leaved 3.5 mm thick axial slices with 0 mm gap (TR 2,000 ms,
TE 30 ms, flip angle 80°, FOV 224 mm, 64 64 matrix
of 3.5 3.5 3.5 mm voxels). At the end of each functional scan,
a T1-weighted anatomical image (1 11 mm) parallel to the
bicommissural plane, covering the whole brain was acquired.
Statistical Parametric Mapping (SPM2; Wellcome Department
of Cognitive Neurology, London; http://www.fil.oin.ucl.ac.uk)
was used for the preprocessing and data analysis. All functional
volumes were realigned to the first acquired volume and images
were then coregistered to each individual’s anatomical space and
subsequently spatially normalized to obtain images with a voxel
size of 2 22 mm (Friston et al., 1995). All volumes were then
smoothed with an 8 mm full-with half-maximum isotropic Gauss-
ian kernel. For the time series on all 18 participants, high-pass
filters with cut-off points at 106 s for the observation conditions
were included in the filtering matrix to remove low-frequency
noise and slow-drifts in the signal.
Condition-specific effects at each voxel were estimated using
the general linear model. Participant’s contrast maps were then
compared against a null hypothesis using a ttest across partici-
pants to implement a random effect analysis.
PPI Analysis
The analysis was conducted according to the methods suggested
by Friston et al. (1997). First, for each participant, we extracted the
time course of activity in the IFO. To achieve this, we used the
peak of the activation cluster derived from the random effect group
analysis (overlap between the observation of disgust-neutral inclu-
sively masked with the experience of disgust-neutral, see Jabbi et
al., 2007) as a starting point (MNI [Montreal Neurological Insti-
tute]: x52 y18 z⫽⫺6). For each individual participant, we
used the results of the observation runs at a statistical threshold of
p.05 uncorrected, placed the cursor at the group peak (MNI:
x52 y18 z⫽⫺6) and pressed the VOI button. In many cases,
there was a slight jump of the cursor to the nearest suprathreshold
voxel (see Table 1). The eigenvalue of a sphere of 5 mm around
these coordinates were then extracted. The PPI analysis function in
SPM2 was then used to build a design matrix suitable to estimate
the PPI, including three columns per run reflecting the time course
of the IFO, the psychological variable (1s while participants
viewed disgusted facial expressions, 1 while they viewed neutral
facial expressions and 0s elsewhere), and the product of the IFO
and the psychological variable. The GLM was then used to deter-
mine parameter estimates for all three components, and the 18
parameter estimates of the interaction were entered into a one
sample ttest to assess whether it differed from zero on average
across the population.
To examine if the a priori expectation that the right BA45 shows
the hypothesized effective connectivity pattern, we first restricted
our analysis to the ipsilateral BA45 and applied a small volume
correction using a region of interest encompassing the cytoarchi-
tectonic maximum probability maps for the right BA45 (Eickhoff
et al., 2006). We then extended the analysis to the entire brain to
examine if effects are regionally specific to the right BA45.
Granger Causality Modeling
In addition to the time course of the IFO, we extracted the time
course in the right BA45 that was found to be effectively more
connected to the IFO during the emotional compared to the neutral
facial expressions from the peak of the Group PPI analysis defined
above (MNI x56 y36 z⫽⫺12). For each participant, within
the GLM of the observation condition ( p.05 uncorrected), we
navigated to these coordinates and pressed the VOI button, often
leading to a slight shift to the nearest suprathreshold voxel (see
Table 1). We then extracted the eigenvalue ofa5mmsphere for
both ROIs and subsequently included the extracted IFG/BA45
versus IFO time courses derived from these two 5 mm sphere
ROIs in the Granger Causality modeling using a Matlab
(www.mathworks.com)-based script.
Granger causality is a linear autoregressive model of time series
that is based on the concept that each data point X
t
(the measured
value at time t) can be modeled as a linear combination of kprevious
data points, starting from a lag l1. The number kis called the order
of the model. According to previous studies, for fMRI, both kand lare
best set to 1 (Goebel et al., 2003; Roebroeck et al., 2005). This means
that the time series of a voxel or ROI X can be modeled using an
autoregressive model including the immediate past of the same voxel
(X
t
⫽␣X
t–1
ε
t
). If one suspects that another voxel Ymay have a
causal influence on X, one can expand the auto regression to incor-
porate the past of Yas well X
t
⫽␣X
t–1
⫹␤Y
t–1
ε
t
. Granger
(1969) then proposed that if the amount of variance explained by this
new model is significantly higher than that of the purely autoregres-
sive model, it is said then that Y“Granger causes” X. In other words,
a directional influence in time from Yto Xis detected when the
combined past of Xand Yare characterized by a significantly in-
Table 1
Center of 5 mm Radius Sphere Used for the PPI Analysis in
MNI Coordinates
Participant
IFO IFG
xyzxyz
1 5218 6523210
2 5218 6563012
3 52 18 0 56 28 12
4 50 20 –10 56 30 12
5 5218 6563012
6 5418 2562616
7 5216 2563012
8 50 18 –14 56 24 12
9 4814 65634 6
10 56 22 –2 60 26 14
11 52 18 –8 56 30 12
12 52 18 –6 56 30 12
13 52 18 –6 54 28 10
14 52 18 –6 56 30 12
15 54 18 –8 52 32 12
16 50 18 –6 56 30 12
17 48 16 –12 54 26 12
18 52 18 –6 60 26 8
Average 51.6 17.8 –6.22 55.7 29 11.5
SEM 0.46 0.38 0.82 0.48 0.61 0.49
Note. PPI psychophysiological interaction; MNI Montreal Neuro-
logical Institute; IFO anterior insula and adjacent frontal operculum;
IFG inferior frontal gyrus.
777
SPECIAL SECTION: MOTOR SIMULATION CAUSES EMOTIONAL CONTAGION
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creased explanatory power over the past of Xalone. The mathematic
framework for assessing Granger Causality was laid out by Geweke
(1982), who demonstrated how the total amount of linear dependence,
or feedback, between two time series can be decomposed into three
components: the amount of linear influence exerted over time, respec-
tively by Xon Yand by Yon X, and the amount of information that
cannot be assigned neither to XY nor to YX because a lack of temporal
resolution in data acquisition: the so-called “instantaneous causality.”
Granger Causality was first applied to fMRI data by Goebel et al.,
2003 and Roebroeck et al., 2005, who have emphasized the fact that
although the absolute values of Granger Causality suffer from the
relatively slow sampling frequency of fMRI, the difference between
the Granger Causality values from X3Yand Y3Xremain reliable.
Accordingly, we calculated the Granger Causality between IFG and
IFO in both direction, and test whether they differ at the group level.
Results
A traditional general linear model analysis published elsewhere
(Jabbi et al., 2007) showed that a sector of the right IFO was
involved both during the viewing of disgust and the experience of
disgust. This region serves as the reference region for the present
analysis (Figure 1a). The fact that the vision of disgusted facial
expressions produces stronger activations in this region in more
empathic individuals, as assessed by self-report questionnaires, links
such activity to empathic emotional sharing (Jabbi et al., 2007).
By applying the PPI method to identify functional connectivity
pathways using the right IFO (see Figure 1) as the seed region
during the observation of disgusted facial expressions relative to
neutral ones, we found that voxels in right BA45 are indeed
significantly more strongly correlated with the IFO during the
vision of disgusted compared to neutral facial expressions (Fig-
ure 1b; p
unc
.005, p
fdr
.05 within right BA45, extent threshold
of 10 voxels). Given that the participants in this study did not
perform an explicit facial expression execution task while in the
scanner, we could not ensure that the region of BA45 was indeed
involved in the control of facial expressions. We extracted the
parameter estimates of the peak voxel in BA45 (x56, y36,
z⫽⫺12) from data obtained from different participants during the
observation and execution of facial expressions of van der Gaag et
al. (2007) and found significant activations both during the obser-
vation (H
0
:neutral fear disgust happy 0, p.0003) and
execution (H
0
:neutral fear disgust happy 0, p.002)
of facial expressions (one-tailed ttest, n17 participants). How-
ever, these voxels did not differentiate emotional from neutral
facial expressions (execution: fear disgust happy-3neutral
0, p.4; observation: fear disgust happy-3neutral 0, p
.2). Together, these findings provide the first evidence that a
functional link may exist between BA45 and the IFO that is
modulated by the emotional content of a social stimulus.
In a second step, we examined if this pattern of effective
connectivity was restricted to BA45. We conducted a whole brain
analysis and used a threshold of p
unc
.005 for the PPI analysis
at the random-effects level in SPM2. This analysis revealed that no
other brain areas showed a detectable stimulus dependent augmen-
tation of their correlation with the IFO during emotional compared
to neutral facial expressions at p.005. In particular, the primary
motor cortex or the primary somatosensory cortex did not show
such a change of correlation.
To obtain further insights into the link between the IFO and
BA45, we performed a Granger Causality analysis (Geweke, 1982,
1984; Goebel et al., 2003; Granger, 1969; Roebroeck et al., 2005;
see Method). Granger Causality from BA45 to IFO (4.16 0.95
SEM) was significantly larger than that from IFO to BA45 (1.22
0.21 SEM) both according to a two-tailed ttest (matched pair, p
.0123) or a permutation test ( p.0106; Nichols & Holmes, 2001).
The finding is indicative of a causal relationship between IFG
activity and IFO activity according to the definition of Granger
Causality, and shows that this causality was predominantly from
the IFG to the IFO.
Discussion
Here we examine the functional link between the IFO and BA45
during the observation of facial movements. The literature suggests that
activity in right BA45 during the observation of facial expressions may
reflect a cold motor simulation of the observed facial movements—motor
because the same voxels were active while participants produced facial
expression and cold because the degree of activity is similar for emotional
and neutral facial movements (van der Gaag et al., 2007). Activity in the
IFO on the other hand has been suggested to reflect the hot empathic
sharing of other individual’s emotional feeling because it is more strongly
activated in more empathic individuals and for the observation of emo-
tional compared to neutral facial expressions (Jabbi et al., 2007; Pfeifer,
Iacoboni, Maxxiotta, & Dabretto, 2008; Singer et al., 2004; van der Gaag
et al., 2007; Keysers & Gazzola, 2007). This interpretation is also sup-
ported by studies showing that the IFO is involved in experiencing the
participant’s own feeling states (Craig, 2004; Critchley, 2005; Damasio,
1999, 2003; Gray et al., 2007). However, the question regarding the
functional link between BA45 and IFO activity still remains unanswered.
It has been suggested that for emotional facial expressions, the putative
cold motor simulation in BA45 could be the trigger for the putative hot
Figure 1. (A) Overlapping activations (yellow) between the observation
of other people’s (green) and own experience (red) of disgusting taste
relative to neutral taste (Jabbi, Swart, & Keysers, 2007). Activations are
shown on the mean anatomical images of the 18 participants normalized on
the MNI template. The overlaps are shown at p.01, uncorrected with a
cut-off point at 10 voxels (x52; y18; z⫽⫺6 MNI coordinates), that
is, with the likelihood of a false positive in the resulting logical AND
function being equal to p
2
.0001. (B) Functional connectivity map
between the right IFG (BA45) at (x54; y24; z17 MNI coordinates)
and the seed region of the right IFO (lower yellow activation cluster in A)
as shown on the anatomy toolbox template (Eickhoff, Heim, Zilles, &
Amunts, 2006).
778 JABBI AND KEYSERS
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This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
emotional simulation in the IFO (Carr et al., 2003; Dapretto et al., 2006),
but this proposal has never been experimentally tested.
Using psychophysiological interaction analyses, we show for
the first time that the right IFO, common to observing and expe-
riencing emotions, is indeed more functionally connected to the
ipsilateral, right BA45 during the observation of emotional com-
pared to neutral facial expressions. In addition, using Granger
Causality, we show that this functional connectivity is not only
correlational but causal in nature (Granger, 1969). Finally, we
showed that the influence of BA45 on the IFO is stronger than the
influence of the IFO on BA45. To our knowledge, this represents
the first empirical evidence in support of the idea that motor
simulation is causally linked to emotional simulation (It should be
noted that finding significantly higher Granger Causality values
from IFG 3IFO compared with IFO 3IFG does not exclude the
possibility that significant information does flow from IFO 3IFG,
nor that the IFG is the only input to IFO).
This finding may have important implications for our under-
standing of emotion perception. Lipps (1907) suggested that seeing
someone else’s emotional facial expression triggers the observer to
adopt a similar facial expression (facial mimicry). The observer
then senses the state of his face, and this process in turn triggers
internal emotional feeling states in the observer that correspond to
those now displayed by the observer’s face (facial feedback). As a
result, the observer shares both facial expression and emotional
feeling state with the person he observes (emotional contagion),
and this sharing allows the observer to feel what is going on in the
other individual (emotional understanding) and eventually empa-
thize. This account is similar to that proposed by James (1884).
Our current finding is compatible with the gist of this proposal:
Activity in BA45 may indeed reflect a certain sharing of motor
components of the observed facial expression, and our Granger
Causality analysis suggests that this activity in BA45 triggers
activity in the IFO, which may reflect a sharing of the emotional
feeling state. However, our findings constrain the idea of Lipps
(1907) in that the IFO appears causally linked with BA45, but not
with somatosensory or primary motor areas—at least at the statis-
tical threshold we used and in an experimental setting in which
overt facial mimicry was not explicitly instructed. If facial feed-
back in the classical sense of Lipps were to be the only trigger for
sharing the affect of the people, somatosensory areas (needed
to sense the observer’s facial mimicry) would be the most robust
source of modulation of the IFO. This was not the case in our
study. Instead, BA45 was the strongest source of modulation,
suggesting that instead of a long facial feedback loop as suggested
by Lipps (involving the overt production of a similar facial ex-
pression and its somatosensation), a covert, shorter direct connection
between areas putatively involved in high-level motor simulation
(BA45) with areas putatively involved in emotion sharing (IFO) may
exist, bypassing the need for overt facial mimicry. The idea that a
covert motor simulation may be sufficient to trigger emotion sharing
may also help explain why the amount of overt facial mimicry does
not reliably correlate with the amount of emotional sharing in a
number of experiments (Blairy, Herrara, & Hess, 1999; Gump &
Kulik, 1997; Hess, Blairy, & Philipport, 1999).
Given that the degree of overt facial mimicry is known to vary
depending on a number of factors (Bourgeois & Hess, 1999;
McHugo, Lanzetta, & Bush, 1991) including whether one is in a
collaborative or competitive context with an observed individual
(Lanzetta & Englis, 1989), repeating our analyses in an experiment
that systematically manipulates such variables will be critical to
determine how functional connectivity and overt facial mimicry co-
vary. Measuring electromyography during scanning, although meth-
odologically challenging, may help address these issues in the future.
Applying a similar causal connectivity analysis to experiments exam-
ining the perception of the sound of emotions will be important to
understand the generality of the findings presented here.
In sum, although the current experiment used viewing of facial
expressions as the source of emotional information, a similar system
may apply to other channels: the sound of mouth actions for instance
triggers activity in sectors of the IFG involved in producing similar
sounds (Gazzola et al., 2006), and emotional vocalizations (e.g., baby
cries or retching) trigger emotional sharing (Martin & Clark, 1987;
Schneider, Gur, Gur, & Muenz, 1994). Together, these findings and
our demonstration of a functional influence of the motor IFG on the
more affect related IFO during the observation of vivid disgusted
facial expressions, underscores the important role of motor simulation
in social emotional perception. This dovetails with the fact that motor
behavior (including vocalization, weeping, etc.) is the only observable
cue to other people’s emotions.
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Received January 31, 2008
Revision received August 6, 2008
Accepted August 15, 2008
780 JABBI AND KEYSERS
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... Our study considers only three representative sub-regions: Inferior Frontal Gyrus (IFG), Supplementary Motor Cortex (SMA), and Primary Motor Cortex (M1). IFG is responsible for encoding the intention of actions (Jabbi, 2008). SMA is responsible for the initialization of the action sequence (Rizzolatti and Luppino, 2001). ...
... The Superior Temporal Sulcus (STS) is a high-order perception area that integrates visual and auditory information about the body and facial actions (Keysers and Gazzola, 2014). The connection between the Motor Cortex and the Emotion Cortex is bidirectional (Jabbi, 2008). The connection between the Perception Cortex and the Motor Cortex is also bidirectional (Kilner and Frith, 2007), but for the affective empathy process in our study, we only considered the connection from the Perception Cortex to the Motor Cortex. ...
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... It has been identified with a mirror neuron system (Iacoboni et al., 1999;Jabbi and Keysers, 2008;Van 475 Overwalle and Baetens, 2009) that responds to the movements of others, and may facilitate the 476 understanding of others' intentions and feeling of empathy. We previously suggested that this system's 477 activation is consistent with HSPs' bias toward noticing positive expressions in others and high 478 empathy . ...
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Previously, researchers used functional MRI to identify regional brain activations associated with sensory processing sensitivity (SPS), a proposed normal phenotype trait. To further validate SPS as a behavioral entity, to characterize it anatomically, and to test the usefulness in psychology of methodologies that assess axonal properties, the present study correlated SPS proxy questionnaire scores (adjusted for neuroticism) with diffusion tensor imaging measures. Participants (n=408) from the Young Adult Human Connectome Project that are free of neurologic and psychiatric disorders were investigated. We computed mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD) and fractional anisotropy (FA). A voxelwise, exploratory analysis showed that MD and RD correlated positively with SPS proxy scores in the right and left subcallosal and anterior ventral cingulum bundle, and the right forceps minor of the corpus callosum (peak Cohens D effect size = 0.269). Further analyses showed correlations throughout the entire right and left ventromedial prefrontal cortex, including the superior longitudinal fasciculus, inferior fronto-occipital fasciculus, uncinate and arcuate fasciculus. These prefrontal regions are generally involved in emotion, reward and social processing. FA was negatively correlated with SPS proxy scores in white matter of the right premotor/motor/somatosensory/supramarginal gyrus regions, which are associated with empathy, theory of mind, primary and secondary somatosensory processing. Region of interest (ROI) analysis, based-on previous fMRI results and Freesurfer atlas-defined areas, showed small effect sizes, (+0.151 to -0.165) in white matter of the precuneus and inferior frontal gyrus. Other ROI effects were found in regions of the dorsal and ventral visual pathways and primary auditory cortex. The results reveal that in a large, diverse group of participants axonal microarchitectural differences can be identified with SPS traits that are subtle and in the range of typical behavior. The results suggest that the heightened sensory processing in people who show SPS may be influenced by the microstructure of white matter in specific neocortical regions. Although previous fMRI studies had identified most of these general neocortical regions, the DTI results put a new focus on brain areas related to attention and cognitive flexibility, empathy, emotion and low-level sensory processing, as in the primary sensory cortex. Psychological trait characterization may benefit from diffusion tensor imaging methodology by identifying influential brain systems for traits.
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