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Special issue: Research report
Distinct neural processes are engaged in themodulation of mimicry by socialgroup-membership and emotional expressions
Birgit Rauchbauer a,b, Jasminka Majdand�zi�c a,b, Allan Hummer c,d,Christian Windischberger c,d and Claus Lamm a,b,*
a Social, Cognitive and Affective Neuroscience Unit, Department of Basic Psychological Research and Research
Methods, Faculty of Psychology, University of Vienna, Vienna, Austriab Cognitive Science Research Platform, University of Vienna, Vienna, Austriac MR Center of Excellence, Medical University of Vienna, Vienna, Austriad Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
1 Note that although the term “racial” has been mostly used inprevious work, this term and its use has some problematic con-notations in its public use (for instance motivating measuresagainst certain racial groups based on their presumed “biologi-cally determined” inferiority). We therefore prefer to use the term“ethnicity” as a more neutral description of what we are dealingwith e i.e., differences between individuals in socio-cultural andphysical, but not in biological-genetic terms (AAPA, 1996; see also(Lamm & Majdand�zi�c, 2015; Rie�cansky, Paul, K€olble, Stieger, &Lamm, 2014).
1. Introduction
Imagine yourself in a conversation with a friend, or even
somebody you have just met. You laugh and have a good time
and then you might come to notice that you're sitting in the
Table 1 e Behavioral results of the interaction effect (A) Group £ Congruency and (B) Emotion £ Congruency; mean RT oncongruent and incongruent trials in the SAMT, in ms; italic numbers referring to standard error of the mean (SE).
parietal lobule (rSPL), the right TPJ and the right superior frontal
gyrus (rSFG). We used the REX (Region-of-interest extraction)
Toolbox implemented in Matlab (http://web.mit.edu/swg/
software.htm) to extract, for each participant, the mean
parameter estimates of the contrasts [Out-group Incongruent >Out-group Congruent], respectively [Happy Incongruent >Happy Congruent] from the ROIs. Subsequently, Pearson cor-
relations were calculated between these values and the
behavioralmimicry effect of the out-group, aswell as the happy
condition (mean RTs: Incongruent e Congruent). Note that the
correlation analysis has been performed in line with previous
recommendations aiming to avoid biased/inflated results (Vul,
Harris, Winkielman, & Pashler, 2009). The imaging data used to
define the ROIswas based on a contrast exploiting the different
levels of the factorial design, and hence a priori independent of
the individual differences in the behavioral parameters (reac-
tion times). Moreover, we also calculated only one single cor-
relation value (as opposed to repeated testing within our ROIs).
This implies that our correlation analyses were neither circular
nor that they could be inflated by repeated testing (Kriegeskorte
et al., 2009).
3. Results
3.1. Behavioral results
3.1.1. SAMTThe three-way repeated measures ANOVA on the factors
GROUP � EMOTION � CONGRUENCY revealed a significantmain effect
of CONGRUENCY [F(1,26) ¼ 216.35, p < .001, partial h2 ¼ .84] in the
expected direction of higher mean RT for incongruent than
congruent trials (incongruent: M ¼ 707.12 msec, SE ¼ 38.3;
congruent: M ¼ 627.99, ms, SE ¼ 38.21). We found a significant
GROUP � CONGRUENCY interaction [F(1,26) ¼ 9.45, p ¼ .005, partial
h2 ¼ .27], as well as an EMOTION � CONGRUENCY interaction
[F(1,26)¼ 13.01, p¼ .001, partial h2 ¼ .33] (see Table 1). All other
effects were not significant (all p-values � .09, effect size
estimates � .11).
Thus from the significant interaction effect of
GROUP � CONGRUENCY, as well as EMOTION � CONGRUENCY it follows
that also the mimicry effect (i.e., the RT difference between
incongruent and congruent trials) exhibits the equivalent
significant effects of GROUP and EMOTION. For the factor GROUP a
higher mimicry effect was found when out-group than when
in-group stimuli were presented (Out-group: M ¼ 86.17, ms,
SE ¼ 6.39; In-Group: M ¼ 71.01 msec, SE ¼ 5.46). The results
also revealed that the mimicry effect was bigger for happy
than for angry faces (Happy: M ¼ 85.22 msec, SE ¼ 6.25;
Angry: M ¼ 71.96 msec, SE ¼ 5.12). The interactions
GROUP � EMOTION were not significant (p ¼ .29, partial h2 ¼ .042).
Incorporating SEX/GENDER in the two-way repeated measures
ANOVA as between-subject factor did not reveal any
significant sex/gender differences in the mimicry effect
(p-values � .29, effect size estimates � .045). In the absence of
behavioral effects, we also did not analyze the imaging data
with respect to sex/gender.
3.1.2. Threat IATFrom the 41 participants included in fMRI analyses, data of
five participants were incomplete, due to technical errors, and
had to be excluded from analysis. In the remaining 36 par-
ticipants (20 males) a D-value of medium effect size (M ¼ .43,
SE ¼ .05) was observed. This indicates that Black people are
implicitly more associated with threat, whereas White people
are more associated with security. Correlation analyses
(Pearson correlation) did not reveal significant correlations
between the results of the IAT and the behavioral measures of
the mimicry effect.
3.1.3. Attitudes towards Black ScaleData of 40 participants entered analysis; data of one partici-
pant was missing. Participants exhibited a neutral explicit
attitude towards blacks (M ¼ 4.27, SE ¼ .06).
3.2. fMRI results
3.2.1. Mimicry regulation: incongruent versus congruenttrialsTesting for main effects of mimicry regulation (contrast:
mean/Incongruent > mean/Congruent, i.e., mean of all re-
gressors from conditions showing incongruent movements
versusmean of all conditions showing congruentmovements)
revealed activation clusters in a large number of brain areas.
Frontal activation was found in the right and left superior
frontal gyrus (SFG), as well as the left precentral gyrus (PCG)
and the middle frontal gyrus (MFG). Moreover activation in
bilateral AI was found, with the cluster on the right side
extending into the right IFG. In addition a cluster in MCC
extending into the supplementary motor area (SMA) and
rostral cingulate zone (RCZ) was activated, and another clus-
ter in a slightly more anterior portion of cingulate cortex was
only slightly above the chosen significant threshold (p ¼ .051).
Parietal activation was found in the left posterior parietal
cortex (comprising the left IPL and left superior parietal lobule
(SPL)) extending into the postcentral sulcus on the left side
and into the precuneus on the right side. In the right hemi-
sphere activation in the rTPJ was identified. For a detailed list
of all activated areas see Table 2. Confining analyses to the
sub-sample of 27 participants with correctly logged behavioral
data did not reveal any further activated brain areas. Besides,
in this sub-sample all the mentioned areas, except for
Table 3 e Local maxima of activation clusters (MNI stereotactic coordinates) resulting from the contrast between Happy(Incongruent vs Congruent trials) masked inclusively with Happy (Incongruent vs Congruent trials) versus Angry(Incongruent vs Congruent trials), respectively corresponding for the contrast between Angry (Incongruent vs Congruenttrials) masked inclusively with Angry (Incongruent vs Congruent trials) versus Happy (Incongruent vs Congruent trials).SPL ¼ superior parietal lobule, TPJ ¼ temporo-parietal junction, SMA ¼ supplementary motor area, SFG ¼ superior frontalgyrus, IOG ¼ inferior occipital gyrus. Threshold p ¼ .05, cluster level multiple comparison correction (selection thresholdp ¼ .001).
Area Hemisphere Peak MNI-coordinates Cluster size(voxels) T-value p-value (corrected)
mimicry. While previous evidence has shown that mimicry
is modulated by social cues, our main intention was to show
how it is regulated in accordance to distinct affiliative goals.
On a process level we had hypothesized that distinct social-
cognitive and behavior regulation processes, as well as shifts
in sensorimotor processing would be involved in the adap-
tive regulation of mimicry to achieve these distinct goals,
and that this should be reflected in the engagement of
distinct neural networks. The behavioral results show that
mimicry was increased in the presence of happy facial ex-
pressions, and that the same effect was observed in the
presence of out-group members. These similar behavioral
effects were accompanied by differential modulations of the
neural networks involved in task processing. Increases in
mimicry when happy facial expressions were presented
were accompanied by activation of the rTPJ, as well as of the
dPMC-SPL circuit. On the other hand, higher mimicry when
out-group members were presented was associated with
activation increases in a network including aMCC/RCZ and
AI, as well as the vPMC-IPL. In the following sections, we will
Table 4 e Local maxima of activation clusters (MNI stereotactic c(Incongruent vs Congruent trials) masked inclusively with Out-g(Incongruent vs Congruent trials), respectively of the contrast beinclusively with In-group (Incongruent vs Congruent trials) versIPL ¼ inferior parietal lobule, SFG ¼ superior frontal gyrus, SMAMCC¼mid-cingulate cortex, MTG¼middle temporal gyrus; Thr(selection threshold p ¼ .001).
Area Hemisphere Peak MNI-coord
x y
Out-group (Incongruent > Congruent) masked inclusively with Out-grou
IPL Left �34 �42
Anterior insula Right 32 24
SFG Right 22 �8
SMA/MCC Left þ Right 2 8
Rolandic operculum/IFG Left �52 2
Anterior insula Left �28 22
MTG Left �48 �58
In-group (Incongruent > Congruent) masked inclusively with In-group (I
Cerebellar vermis/Left cerebellum 4 �64
interpret these findings in detail and discuss their relevance
and putative functional role for the implicit regulation of
mimicry.
4.1. Effects of social cues on mimicry behavior
We found three main behavioral effects, which directed the
analyses of the functional imaging data. First, we replicated
the congruency effect previously found in automatic imitation
paradigms (Brass et al., 2000; Brass, et al., 2001; Brass,
Derrfuss, & von Cramon, 2005; Heyes, Bird, Johnson, &
Haggard, 2005; Sowden & Catmur, 2015; Spengler, et al.,
2009), with higher reaction times on incongruent than on
congruent trials. This confirmed that our participants “auto-
matically” mimicked the task-irrelevant hand stimulus.
Interestingly, reaction times for both incongruent and
congruent trials were on average about 100 msec longer than
those found in other imaging studies which had not added
social-affective stimuli (for example Brass, Derrfuss, & von
Cramon, 2005). Thus, increased attentional processing of the
oordinates) resulting from the contrast between Out-grouproup (Incongruent vs Congruent trials) versus In-grouptween In-group (Incongruent vs Congruent trials) maskedus Out-group (Incongruent vs Congruent trials).¼ supplementary motor area, IFG ¼ inferior frontal gyrus,eshold p¼ .05, cluster level multiple comparison correction
mimicry when happy faces were presented resulted in acti-
vation in the right SPL and dPMC. This might suggest that in
this condition, sensorimotor processing was shifted towards
processing the response to the task-relevant number cue for
the sake of task-adherence. On the other hand, when out-
group faces were presented, sensorimotor contributions in
the vPMC/left IPL network were increased. This suggests that
regulation of mimicry in this condition was accompanied by a
shift of sensorimotor processing towards visuospatial prop-
erties of the task-irrelevant hand. These observed shifts in
sensorimotor processing might suggest that the regulation of
mimicry by social-affective cues is driven by input modula-
tion. On the other hand, we also observed changes in activa-
tion of the rTPJ, reflecting self-other distinction processes that
have been related to output modulation of the mimicry
response (Heyes, 2011). In line with this, the involvement of
the AI/MCC network for behavior regulation according to
detected saliency (in our case threat) in the environment
(Medford& Critchley, 2010; Shackman et al., 2011) could speak
for output modulation regulating mimicry behavior goal-
directedly. Thus, based on the current data alone, we cannot
fully discern the involvement of in- or output modulation in
the modulation of mimicry to social-affective cues, and our
interpretations remain speculative. Further studies should
aim to further clarify the pathways by which mimicry is
regulated in response to social context stimuli. A more time-
sensitive measure, as event-related brain potential (ERP)
studies, might be able to tap into the temporal dynamics of
this modulation and thereby possibly capture processes
attributable to in- or output modulation.
We suggest that along sensorimotor mechanisms, the
processes of self-other distinction and behavioral regulation
are involved in the modulation of mimicry to social-affective
information in general. Yet, we did not replicate previous
findings regarding the involvement of mPFC in the modula-
tion of mimicry by contextual information (Wang&Hamilton,
2012, 2015; Wang, Ramsey, et al., 2011). Note though that the
involvement of mPFC in these studies has been attributed to
the processing of eye gaze (Wang & Hamilton, 2012; Wang,
Ramsey, et al., 2011) or pro- and antisocial priming (Wang &
Hamilton, 2015). In our study, gaze was not varied, and we
used clearly valenced facial expressions. Hence, the clear
social-affective nature of our paradigm could have also
resulted in lower mentalizing demands, which could also
explain the absence of mPFC activations.
5. Conclusion
Our study demonstrates that automatic imitation paradigms
are a valid tool to investigate the influence of social-affective
cues on mimicry. Our results show that subtle manipula-
tions of such social-affective cues significantly affect both
behavioral and neural measures of mimicry. Crucially, our
findings suggest that the regulation ofmimicry is not a unitary
phenomenon. Depending upon the affiliative goals, it may be
supported by distinct social-cognitive, behaviorally regulative,
and sensorimotor processes. Thus, the present study confirms
the notion that despite its automaticity, mimicry is a highly
context-sensitive and implicitly modifiable motor response,
and provides further evidence on how the regulation of this
response is supported by distinct neuro-cognitive processes.
Acknowledgments
The study was supported by the Viennese Science and Tech-
nologyFund (WWTF,CS11-005, to CL). The authorswould like to
thank Christina Rauchbauer and Abla Marie-Jose Bedi for
lending a helping hand; Doris Lamplmair and Andreas Martin
for invaluable support in participant recruitment and data
collection; Stefan Stieger for highly appreciated support
regarding the IAT; Ludwig Huber (Veterinary University of
Vienna, Messerli Research Institute) for valuable discussions of
the research design.
Supplementary data
Supplementary data related to this article can be found at
http://dx.doi.org/10.1016/j.cortex.2015.03.007.
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