YNIMG-11344; No. of pages: 10; 4C: 2, 3, 5, 6, 8 NeuroImage xxx (2014) xxx–xxx

Contents lists available at ScienceDirect

NeuroImage journal homepage: www.elsevier.com/locate/ynimg

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Article history: Accepted 3 May 2014 Available online xxxx

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Keywords: Triadic interactions Mentalizing system Mirror neuron system Social cognition fMRI

Department of Psychiatry and Psychotherapy, Charité — Universitätsmedizin Berlin, Campus Mitte, Charitéplatz 1, 10117 Berlin, Germany Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Luisenstraße 56, Haus 1, 10099 Berlin, Germany Institute of Medical Psychology, Charité — Universitätsmedizin Berlin, Luisenstraße 57, 10117 Berlin, Germany

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Coordinated triadic interactions, involving oneself, another person, and an external object, are considered a uniquely human skill. However, the exact mechanisms underlying the ability to engage in such social interactions remain hitherto unknown. We used functional neuroimaging to investigate the neural signature of triadic interactions. For this purpose, participants viewed pictures of objects in a 3 T functional magnetic resonance imaging scanner and were asked whether they could imagine this object in a social interaction with another person. We also aimed to dissociate this process from, as well as to find commonalities with, purely self-referential or otherreferential processing. In all trial-types, we found activations in core mentalizing brain areas (medial prefrontal cortex, posterior cingulate cortex, precuneus and temporoparietal junction). Furthermore, triadic engagements, but not self-referential or other-referential processing, were associated with activations in classical mirror neuron areas (inferior frontal gyrus and inferior parietal lobe). Finally, mentalizing networks showed a strong functional connectivity with mirror neuron areas exclusively during triadic engagements. These results suggest that the imagined interaction of two agents is processed in a more complex neural social cognitive network than purely self- or other-referential considerations. © 2014 Published by Elsevier Inc.

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Introduction

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Social cognition is nothing uniquely human per se. It is rather an essential component of every-day life in most species (Rushworth et al., 2013). Social interactions among animals can be quite complex. Some apes are even able to infer basic intentions from observing others' goal-directed actions and to respond to them accordingly (Tomasello et al., 2005). A question which has occupied philosophers for decades and more recently also entered the domain of social cognitive neuroscience is: what is it that makes human social cognition so special? One aspect certainly includes the special sense of self, or selfknowledge (D'Argembeau and Salmon, 2012). For instance, humans are able to use and integrate information from past experiences to form a coherent picture of their own person. With this knowledge, they can reflect on their relationship to the world, relate specific objects in their environment to themselves and experience them as selfreferential (Northoff and Bermpohl, 2004). This capacity is referred to as self-referential processing (i.e. Fossati et al., 2003; Gusnard et al., 2001; Kelley et al., 2002; Kircher et al., 2000; Northoff and Bermpohl,

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Kristin Trapp a,⁎, Stephanie Spengler a, Torsten Wüstenberg a, Corinde E. Wiers a,b, Niko A. Busch b,c, Felix Bermpohl a,b

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Imagining triadic interactions simultaneously activates mirror and mentalizing systems

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⁎ Corresponding author. E-mail address: [email protected] (K. Trapp).

2004; Northoff et al., 2006, 2009; Ochsner et al., 2005; Phan et al., 2004; Platek et al., 2006; Sajonz et al., 2010; Schneider et al., 2008). In a similar vein, an additional aspect includes the ability to understand what is going on not only in one's own mind, but also in other people's minds, and to differentiate their mental states from one's own mental state (Emery, 2005; Tomasello et al., 2005). With this knowledge, humans can reflect on the relationship of another person to the world, relate specific objects to the other person and assign them otherreferentiality. This ability is subsumed under the term ‘theory of mind’ — understanding the mental state of another person (i.e. Baron-Cohen et al., 1997; Castelli et al., 2000; Fletcher et al., 1995; Gallagher et al., 2000; Grèzes et al., 2004; Heatherton et al., 2006; Spengler et al., 2009, 2010; Vogeley et al., 2001). In order to correctly infer the mindset of another person, an additional process might be necessary that provides the basis for processing the actions performed by the other. This capacity is known as action processing or action understanding (Buccino et al., 2004; Gazzola et al., 2007; Iacoboni et al., 1999; Rizzolatti and Fabbri-Destro, 2008), but for a critical view on the lastmentioned term, refer to Hickok (2009). Each of these three social cognitive skills has become extensively studied in neuroimaging research. Despite these considerable investigations concerning mentalizing processes related to oneself or another person, surprisingly few attempts have been made to study social cognitive processes involving

http://dx.doi.org/10.1016/j.neuroimage.2014.05.003 1053-8119/© 2014 Published by Elsevier Inc.

Please cite this article as: Trapp, K., et al., Imagining triadic interactions simultaneously activates mirror and mentalizing systems, NeuroImage (2014), http://dx.doi.org/10.1016/j.neuroimage.2014.05.003

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Participants were recruited through advertisements from the Charité University Medicine Berlin and Humboldt University Berlin. All of them were native German-speaking young adults. Exclusion criteria were age under 18 or over 35 years, left-handedness (according to the Edinburgh handedness inventory, Oldfield, 1971), personal or familial (first-degree relatives) history of neurological or mental illness, psychotropic medication, previous alcohol or substance abuse, pregnancy or nursing and any other contraindications to MRI. Participants were free from axis-I and axis-II psychiatric disorders, according to the Mini International Neuropsychiatric Interview (M.I.N.I., Ackenheil et al., 1999).

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In the present study, we used pictures of neutral objects in an eventrelated functional Magnetic Resonance Imaging (fMRI) design to investigate the neural correlates underlying coordinated triadic relations. Furthermore, we aimed to dissociate triadic engagements from purely self-referential or other-referential thoughts. To this end, participants were asked whether they could imagine this object in a social interaction with another person (triad-trials). Thereby, participants had to imagine the performance of an action and to acknowledge the other person as an intentional agent willing to interact. To observe the effect of self-referential thoughts, participants were asked whether this object was self-relevant to them (self-trials). Analogously, other-referential thoughts were investigated by asking the participants whether they thought that this object was self-relevant to Angela Merkel (other-trials). In a control task, participants had to decide whether this object contained iron (iron-trials) (Fig. 2). Based on previous research, which identified commonly activated brain areas during self-referential processing and theory of mind tasks, we hypothesized to find activations in the main structures of the mentalizing system (MNZ), (for reviews see Beer and Ochsner, 2006; Van Overwalle, 2009, 2011; Van Overwalle and Baetens, 2009) during all trial-types. These comprise the medial prefrontal cortex (MPFC) including the anterior cingulate cortex (ACC), the posterior cingulate cortex (PCC), the precuneus and the temporoparietal junction (TPJ) (see Amodio and Frith, 2006; Frith and Frith, 2006; Mar, 2011; Northoff et al., 2006, for reviews). This network has been related to the human ability to reflectively infer another person's mental state (Frith and Frith, 2010), which can be thought of as providing a “thirdperson grasp” of the person's mindset (Schilbach, 2010; Schilbach et al., in press). In contrast to self- and other-trials, we expected activations not only in brain areas associated with high-level mentalizing processes, but also in brain areas associated with more low-level action processing during triad-trials. The mirror neuron system (MNS) has been implicated in these low-level mechanisms. It is activated during action perception and execution, regardless of whether these actions are actually performed (i.e. Grafton et al., 1992), imitated (Aziz-Zadeh et al., 2006; Heiser et al., 2003; Iacoboni et al., 1999) or only imagined (Decety and Grezes, 2006; Decety et al., 1994; Grafton et al., 1996; Iacoboni et al., 1999; Munzert et al., 2009). The main structures of the MNS include the ventral premotor cortex (Brodmann area (BA) 6 and BA 44, inferior frontal gyrus (IFG) pars opercularis) and the anterior part of the inferior parietal lobe (IPL) (see Gallese et al., 2004; Gallese et al., 2013; Ocampo and Kritikos, 2011; Rizzolatti and Fabbri-Destro, 2008 for reviews, and Rizzolatti and Sinigaglia, 2010). This network has been related to the ability to infer another person's action goals and intentions, which can be thought of as providing a “first-person grasp” of the person's motor behavior (Rizzolatti and Sinigaglia, 2010). Triadic interactions, by representing a form of “second-person engagements” (Schilbach et al., in press), could activate both these networks and be thought of as providing a “second-person grasp” of the person's mental state and motor goals.

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oneself and another person. This lack of investigations even led some authors to formulate a very apt comparison between the neural correlates underlying social interactions and the “dark matter of social neuroscience” (Schilbach et al., in press). However, these knowledge gaps remain mainly due to methodological difficulties while special interest in social interactions increases (Becchio et al., 2010; Hari and Kujala, 2009; Schilbach, 2010; Schilbach et al., in press). Lately, it has been suggested that participating in social interactions provides a different basis for the comprehension of the other person than the mere observation of an interaction, and that part of the insight gained about the other person can only be formed and thus resides in the reciprocity between the partners engaged (Schilbach et al., in press). A rather complex type of social interactions is represented by triadic engagements. In such interactions, oneself and another person coordinate their respective actions in an activity engaging an external object, possibly motivated by a shared goal (Fig. 1). While some animals are able to participate in basic or limited triadic interaction – such as defending in alliances or group hunting (Boesch and Boesch, 1989; de Waal and Suchak, 2010; Tomasello et al., 2005) – these higher-level triadic engagements, including shared goals and experiences as well as coordinated behavior, are another facet of social cognition that is unique to humans (Rekers et al., 2011; Saxe, 2006; Tomasello and Carpenter, 2005; Tomasello et al., 2005). Investigations aiming to reveal the neural correlates underlying triadic interactions have only recently begun. Joint actions, as a superordinate concept of triadic interactions, remain an under-researched topic. Only few virtual reality tasks have been conducted to study these processes and the results have been conflicting. The MNS has been found to play a central role in joint action tasks by some others authors (Newman-Norlund et al., 2007b, 2008) while others suggest an only indirect role for this network (Kokal et al., 2009). However, most previous studies involving a second person did either focus on the perception and processing of the other person's action, i.e. action processing (e.g., Buccino et al., 2004; Gazzola et al., 2007; Iacoboni et al., 1999), or on the identification of the other person's mental state or intention, i.e. theory of mind (e.g., Ferstl and von Cramon, 2002; Gallagher et al., 2000; Sommer et al., 2007) and were non-triadic. However, it may be assumed that triadic interactions involve both, action processing on a most basic level, as well as theory of mind (i.e., the recognition of the mental state of another person — in addition to self-referential processing). Action processing is most likely required since participation in a triadic interaction requires the partners to coordinate and represent the own as well as the partner's respective action plans in order to perform complementary or competing roles and finally reach the (shared) goal (Tomasello et al., 2005). In contrast, mentalizing about oneself or another person requires more abstract reasoning abilities and is needed to infer one's own or the other person's intentions without the necessity to represent the actions by itself (Van Overwalle and Baetens, 2009).

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Fig. 1. Illustration of triadic relations. Red arrows: Triadic engagements involving the own person (self), another person (other), and an external entity (object). Blue arrows: Individual engagements with an external entity.

Please cite this article as: Trapp, K., et al., Imagining triadic interactions simultaneously activates mirror and mentalizing systems, NeuroImage (2014), http://dx.doi.org/10.1016/j.neuroimage.2014.05.003

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Experimental procedure

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The experiment we report here was part of a larger study investigating the influence of different mood states on distinct mentalizing processes. A mood induction procedure was used to introduce sad and neutral mood states in each participant. However, for the purposes of this article, only the neutral-mood experiment is considered and reported. Our set of pictorial stimuli comprised 360 normative and standardized photographs, selected from the Bank of Standardized Stimuli (Brodeur et al., 2010). The photographs were pseudorandomly allocated to one of three stimulus sets, in such a way that each set contained 120 photographs. Out of these sets, two were pseudorandomly chosen for each participant and the respective mood states. Thus, a single set (120 pictures) was presented during the neutral mood state. Each image depicted a single object on a white background (Fig. 2). We used this novel set of neutral pictures because results of a pilot study suggested that these stimuli had a neutral valence and were not arousing or influenced by social desirability. This was again confirmed in a post-scanning rating session in the present study, in which all participants, on average, rated each of the images as being neutral and not arousing (p b .001 for both scales). We were able to demonstrate the adequateness of this set of stimuli for utilization in mentalizing tasks by showing the self-reference effect in memory (the superiority effect for items encoded in reference to the self, see Rogers et al., 1977, for a meta-analysis see Symons and Johnson, 1997). During the scanning session, participants performed three different mentalizing and one control task. Each trial began with the presentation of an image showing an object. Above the object, one out of four “cue”words was presented, specifying the task to be performed (Fig. 2). The trial types were (1) Triad (“Can you imagine that object in a social interaction with another person?”), (2) Self (“Is that object self-relevant to you?”), (3) Other (“Do you think that object is self-relevant to Angela Merkel?”. Comment: Angela Merkel is the current German prime minister), or (4) Iron (“Is iron part of that object?”), of which the lastmentioned type served as a low-level control task. Participants

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Behavioral data analysis

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By means of PASW Statistics 15 (IBM Corp., www.ibm.com/ software/de/analytics/spss/), we computed separate one-way analyses of variance (ANOVAs) for repeated-measures (within subject factor: trial-type; levels: triad, self, other, iron) for the dependent variables response times, proportion of response types (yes/no) and source memory scores. The memory scores were analyzed using the discriminability score d' (Green and Swets, 1966). We calculated this score with the Palamedes toolbox (http://www.palamedestoolbox.org/). Additionally, the proportion of correct responses for every trial-type was calculated.

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MRI data were acquired on a 3 T Siemens TIM Trio scanner equipped with a 12-channel phased-array head coil. A total of 405 functional T2*-weighted echo-planar images (EPI, 32 transversal slices, repetition time: 2 s, echo time: 30 s, flip angle: 80°, image matrix: 64 × 64, voxel size 3.5 × 3.5 × 3.45 mm3) were collected for each participant within a single functional run. The acquisition was obtained in an ascending (ventral to dorsal) interleaved even-odd slice order. Moreover, the B0-field was mapped using a gradient-echo pulse sequence (TR = 438 ms, TE[1] = 5.19 ms, TE[2] = 7.65 ms, flip angle = 60°), spatial orientation and resolution were the same as described above.

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responded with a left- or right-handed button press (yes/no) and these response options were counterbalanced across participants. The functional run consisted of 30 pictures per trial-type, each presented for 2 s. In order to optimize the estimation of the eventrelated hemodynamic response, trials were separated by a variable interstimulus interval (2000–6000 ms, jitter step width 250 ms) and images were presented in a pseudorandomized order (Dale, 1999). During the interstimulus interval, participants passively viewed a fixation cross. Optimal sequences of trial-types and trial-onsets were calculated prior to the scanning session by means of Monte Carlo simulations on the basis of the canonical hemodynamic response model by Friston et al. (1995). To test for the self-reference effect, participants were given a selfpaced surprise source memory test after the scanning session was completed. All 120 images were presented again and participants had to decide which of the four tasks (triad, self, other, or iron) accompanied that image during the scanning session. The experiment was programmed in Presentation (Neurobehavioral Systems Inc., Albany, CA, http://www.neurobs.com/). Pictures were presented via a video projector with a resolution of 1024 × 768 pixels onto a screen mounted at the MR head coil (scanning sessions) or via a standard computer monitor with the same resolution (source memory test). Responses were collected via fiber optic response devices (fORP, Current Designs Inc., Philadelphia, PA, http://www.curdes.com/).

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The Beck Depression Inventory II (BDI-II, Beck et al., 1996) was used as a self-report measure of depression. Participants were included if their scores were within the minimal range (b 13). One participant had to be excluded based on this criterion (BDI score = 33). In total, 19 participants were included in the study (9 men, 10 women; mean age 26.5 years; SD: 3.78 years). All participants gave written informed consent in accordance with the Declaration of Helsinki and received financial compensation for participation. The Ethics Committee of the Charité Berlin approved the study.

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Fig. 2. Experimental paradigm. Photographs of objects served as stimuli (obtained from the Bank of Standardized Stimuli). All trial types (triad, self, other, and iron) were presented in a pseudorandomized order. The trial duration was 2 s and the interstimulus interval 2–6 s. In total, the experiment consisted of 120 trials (30 trials/trial-type).

Please cite this article as: Trapp, K., et al., Imagining triadic interactions simultaneously activates mirror and mentalizing systems, NeuroImage (2014), http://dx.doi.org/10.1016/j.neuroimage.2014.05.003

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Results

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Behavioral results

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Response times The one-way ANOVA for repeated measures revealed a main effect of trial-type [F(1,18) = 7.25, p b .001] on response times. Post hoc tests showed that participants' response times were shortest in the ironcondition in comparison to self-, other- and triad-judgments [p = .046, p = .02, p = .001, respectively]. Furthermore, response times were shorter for self-judgments than for triad-judgments [p = .013] and we observed a trend for reaction times being shorter in the othercondition in comparison to the triad-condition [p = .057]. None of the other contrasts reached significance [p N .314 for all]. Mean response times are listed in Table 1.

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Proportions of “yes”- and “no”-responses There was no main effect of trial-type [F(1,18) = 2.05, p = .118] on yes/no responses. The mean proportions of “yes”-responses are listed in Table 1.

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We processed and analyzed the imaging data with the Statistical Parametric Mapping 8 (SPM8) software package (http://www.fil.ion. ucl.ac.uk/spm/). Preprocessing included (i) the correction of acquisition delay between slices, (ii) the correction of head movements and spatial distortions using the B0-fieldmap, (iii) the spatial co-registration of the mean EPI with each participants' individual structural image, (iv) the spatial segmentation of the structural image into tissue classes and the estimation of the set of linear and non-linear transformation parameters into the standard space as defined by the ICBM space template for European brains, (v) the spatial normalization of all EPI images with this set of parameters, (vi) the re-sampling of resulting images to an isotropic voxel size (3.5 × 3.5 × 3.5 mm3) and (vii) the spatial filtering of all normalized images with an isotropic Gaussian kernel of 8 mm fullwidth at half maximum (FWHM). The preprocessed data were then analyzed within the general linear framework as implemented in SPM8. On the single subject level, condition specific event-related neural activity was modeled by means of finite response functions. The corresponding Blood Oxygenation Level Dependent (BOLD) responses were computed by convolving these functions with the canonical hemodynamic response function as implemented in SPM8. Finally, the resulting time series were temporally down-sampled regarding the acquired number of functional images. In this way, we defined four regressors for the experimental trial types (triad, self, other, iron), and two regressors for right- and left-handed button presses during the task period. To account for signal fluctuations only caused by movement × susceptibility interactions, six additional regressors comprising the rigid-body movement parameters from motion correction were also included. Before fitting the model, a temporal high-pass filter with a cut-off frequency of 1/128 Hz was applied to the data to remove lowfrequency noise. Serial correlations in time series were removed using an autoregressive model of first order [AR(1)]. After this procedure, the model parameters were estimated by means of restricted maximum likelihood algorithm (ReML). The resulting parameter estimates were used to specify linear contrast images for each condition (triad, self, other, iron) and differences between the condition of interest and the control condition (triad N iron, self N iron, other N iron). These contrast images were subsequently used in a one-way within-subject ANOVA on group-level analysis. This enabled us to perform a conjunction analysis testing the conjunction null hypothesis (as implemented in SPM8) and to dissociate triadtrials from self- and other-trials. Only activations surviving a statistical threshold of p b 0.05 (whole brain family-wise error-corrected) and with a minimal cluster extend of at least 4 adjacent voxels were considered for report and discussion. Anatomical structures corresponding to the obtained functional results were identified with help of the SPM anatomy toolbox (Eickhoff et al., 2005) and coordinates are given in ICBM-space. Rfxplot (http://rfxplot.sourceforge.net/) was used to calculate contrast estimates for each region's peak voxel. Furthermore, we conducted a post hoc exploratory psychophysiological interaction (PPI) analysis (Friston et al., 1997; Gitelman et al., 2003) in order to assess the functional coupling within the MZS as well as between the MZS and MNS and its modulation by the

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different experimental conditions. By means of PPI, brain areas which are differentially coupled to a seed region as a function of change in the participants' psychological (or experimental) state can be determined. As seed regions, we used spheres with a diameter of 8 mm centered at the peak voxels of the mentalizing areas (MPFC: [-5 63 24], left [-47 -67 31] and right TPJ [55 -63 31] and PCC/Precuneus [-1 -60 34]) which were identified in the conjunction analysis. For each seed region, we extracted the subject-specific eigenvariate time series. These time series were adjusted for the effects of interest and deconvolved with the canonical hemodynamic response function to estimate the associated neural activity (Gitelman et al., 2003). Afterwards, the time series were multiplied by a vector coding for the different contrasts element-by-element. The resulting PPI term was reconvolved with the canonical hemodynamic response function and served as primary regressor in seed voxel specific single subject connectivity models. These models contained as additional regressors the seed voxel time series itself, the contrast coding vector convolved with the hemodynamic response function, the hemodynamic model of all remaining conditions and the head motion parameters. After model estimation, linear contrast images were computed for the PPI term (describing the effect of condition on the connection strength, condition dependent connectivity) and for the seed voxel correlations (describing the condition independent connectivity). These contrast images were entered into random effects group analyses using one-sample T-tests. Due to our research question, we focused further analysis on mentalizing and mirror networks. For the MZS, we concentrated on the areas that were identified in the conjunction analysis. For the MNS, a literature-based probabilistic ROI was created (for details see Supplementary Methods SI). To assess the functional connectivity between a certain seed area and the MZS, T-contrasts were inclusively masked with this MZS-ROI. Similarly, in order to reveal the functional connectivity between a certain seed area and the MNS, all T-contrasts were inclusively masked with the MNS-ROI. For functional coupling that occurred independently of the experimental conditions, only activations surviving a threshold of p b 0.05 (whole brain family-wise error-corrected) and with a minimal cluster extend of at least 4 adjacent voxels were considered for report and discussion. In contrast, for functional coupling that occurred as a function of the experimental condition, the threshold was set to p b 0.05, cluster size corrected for multiple comparisons. To this end, the probability of finding a cluster of a certain size by chance within a statistical map of certain smoothness and for a given threshold was estimated using the “AlphaSim” implementation of the Resting-State fMRI Data Analysis Toolkit “REST” (rest.restfmri.net/, Song et al., 2011).

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In addition, we collected one high-resolution 3D T1-weighted magnetization prepared rapid acquisition gradient-echo structural image (MPRAGE, 192 sagittal slices, repetition time: 19 ms, echo time: 2.5 ms, flip angle: 9°, image matrix: 256 × 256, voxel size: 1 × 1 × 1 mm3) for each participant at the end of the scanning session. During the whole scanning session, foam padding was used to minimize head motion.

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Table 1 Reaction times, proportion of “yes”-responses, and memory task results.

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Discriminability score (d') (±SD)

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Triad Self Other Iron

2086.10 (±243.94) 1972.57 (±193.34) 2016.92 (±220.15) 1902.69 (±150.00)

.454 (.211) .490 (.189) .388 (.191) .416 (.123)

.581 (.137) .791 (.151) .693 (.182) .663 (.197)

1.112 (.470) 2.008 (.720) 1.554 (.728) 1.444 (.831)

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Reaction times and responses were collected during the scanning session. Subsequently, a self-paced surprise memory test was conducted. The proportion of correct answers and the discriminability score d' were calculated. Mean results are given. SD: standard deviation.

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Differences in source memory performance between trial types We found a main effect of trial type [F(1,18) = 12.8, p b .001] on source memory performance by using a repeated-measures ANOVA. Post hoc tests revealed that source memory performance was best for self-trials in comparison to other-trials [p = .009], triad-trials [p b .001] and iron-trials [p = .002]. Also, other-trials were remembered better than triad-trials [p = .013] and iron-trials were better remembered than triad-trials by trend [p = .076]. No other comparison reached significance [p N .373 for all]. The mean proportion of

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Common activity during triad-, self-, and other-trials: (triad ∩ self ∩ other) In order to explore regional overlaps in brain activity between the three target conditions triad, self, and other, we conducted a conjunction analysis testing the conjunction null hypothesis. This analysis

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correct responses as well as d'-values for each trial-type are given 412 in Table 1. 413

Fig. 3. Conjunction analysis. A–D: Depicted are brain areas that were commonly activated during triad-, self-, and other-trials. These included the core mentalizing areas medial prefrontal cortex (MPFC), posterior cingulate cortex (PCC), precuneus and temporoparietal junction (TPJ). The statistical threshold was p = 0.05, familywise error-corrected. L: Left side, R: Right side. Color bar depicts z-values. E: Contrast estimates for core mentalizing areas at peak voxels (MPFC-5, 63, 24, PCC/precuneus-1, -60, 34, TPJ -47, -67, 31).

Please cite this article as: Trapp, K., et al., Imagining triadic interactions simultaneously activates mirror and mentalizing systems, NeuroImage (2014), http://dx.doi.org/10.1016/j.neuroimage.2014.05.003

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Table 2 Brain areas activated in the conjunction triad ∩ self ∩ other. Brain structure (CP %)

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MPFC: arMFC TPJ

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PCC/precuneus Middle temporal gyrus Cerebellum (lobule VIIa crus I + II ~ 62%) FEF, SMA: superior frontal gyrus (BA 6 ~ 30%) VLPFC: inferior frontal gyrus (p. orbitalis) Lingual gyrus

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6.02 6.13 5.37 5.87 6.57 5.77 5.13 4.74 4.71

b.001 b.001 .001 b.001 b.001 b.001 .003 .018 .020

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−5 −47 55 −1 −61 31 −5 −47 −8

63 −67 −63 −60 −11 −77 14 25 −53

24 31 31 34 −15 −33 59 −8 3

Abbreviations: BA: Brodmann area, CP: cytoarchitectonic probability, H: hemisphere, FWE: family-wise error-corrected, L: left, MNI: Montreal Neurological Institute, p: p-value, R: right, vox: voxel, Z: Z-value; arMFC: anterior rostral medial frontal cortex, FEF: frontal eye fields, MPFC: medial prefrontal cortex, PCC: posterior cingulate cortex, SMA: supplementary motor area, TPJ: temporoparietal junction, VLPFC: ventrolateral prefrontal cortex, gray: mentalizing areas.

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revealed overlapping activations in core regions of the MZS, particularly the MPFC, bilateral TPJ, and left precuneus (Fig. 3, Table 2).

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Discussion

The present results provide first insights into the neural correlates underlying a rarely studied and uniquely human facet of social cognition, namely coordinated triadic social interactions. We found concurrent involvement of, and increased coupling strength between, the mirror neuron system (MNS) and the mentalizing system (MZS) during triadic interactions. Specifically, the IPL and IFG of the MNS as well as the MPFC, the TPJ, and the precuneus of the MZS were activated during triad-trials. Additionally, positive modulation of the coupling strength by triad trials was observed between the MPFC and the left IFG as well

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Explorative post hoc seed voxel correlations and psycho-physiological interaction (PPI) analysis We first analyzed seed voxel correlations that occurred independently of the experimental condition. Strong functional connectivity was observed between each mentalizing seed region and the remaining mentalizing areas. Also, all mentalizing seed regions were functionally coupled to MNS regions, i.e., the IFG and the IPL (Fig. 5A, Inline Supplementary Tables S1–S4).

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Distinct activity during triad-, self-, and other-trials To dissociate activations during triad-trials from activations in selfand other-trials, we calculated the contrast triad N (self & other). We found activations in areas of the classical MNS, namely the left IFG and left IPL. In contrast, we found activations in a part of the MZS, the left ACC, by contrasting self N (triad & other). The effect of other-trials over the remaining trial-types was calculated analogously as other N (self & triad). We also found activations in core areas of the MZS, the right TPJ and right PCC/Precuneus (Fig. 4, Table 3).

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Inline Supplementary Tables S1–S4 can be found online at http://dx. doi.org/10.1016/j.neuroimage.2014.05.003. The PPI analysis revealed significant positive modulation of coupling strength between certain mentalizing and mirror areas by the triadic condition. Particularly, positive modulation of connectivity between the MPFC and the left IFG by the contrasts triad N (self & other) and triad N other was observed. Also, positive modulation was found between the left TPJ and the left IFG and IPL by triad-in comparison to other-trials (Fig. 5B, Inline Supplementary Table S5). Inline Supplementary Table S5 can be found online at http://dx.doi. org/10.1016/j.neuroimage.2014.05.003.

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Fig. 4. Dissociating triad-, self-, and other-trials. A: Rendered image. Activations at locations 1–16 mm beneath brain surface are shown. A–C: Depicted are brain areas that were activated during the contrasts triad N (self & other) (blue), self N (triad & other) (cyan), and other N (triad & self) (green). The former contrast elicited activations in the core mirror areas, inferior frontal gyrus (IFG) and intraparietal lobe (IPL), whereas both latter contrasts elicited activations in the core mentalizing areas. In particular, the contrast self N (triad & other) showed activation in the anterior cingulate cortex and other N (triad & self) in the right posterior cingulate cortex/precuneus and the right temporoparietal junction. The statistical threshold was p = 0.05, familywise error-corrected. L: Left side, R: Right side. Color bars depict z-values. E: Contrast estimates for core mirror areas at peak voxels (IFG-50, 14, 20, IPL -43, -46, 41).

Please cite this article as: Trapp, K., et al., Imagining triadic interactions simultaneously activates mirror and mentalizing systems, NeuroImage (2014), http://dx.doi.org/10.1016/j.neuroimage.2014.05.003

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Table 3 Brain regions activated in the contrasts triad N (self & other), self N (other & triad), and other N (self & triad). Brain structure (CP %)

BA

H

Cluster size (vox)

Z (peak)

p (FWE)

MNI coord. (mm)

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Triad N (self & other) VLPFC: inferior frontal gyrus (p. triangularis, p. opercularis) Inferior temporal gyrus Inferior parietal lobe ALPFC: middle frontal gyrus

y

z

44, 45, 46

L

87

5.10

.004

−50

14

20

20 40 10

L L L

17 7 4

5.67 4.87 4.69

b.001 .010 .021

−57 −43 −43

−53 −46 46

−8 41 3

Self N (other & triad) ACC

32

L

4

4.67

.022

−1

42

−5

Other N (self & triad) PCC/precuneus TPJ

7, 31 39

R R

25 7

5.16 4.74

.003 .017

3 48

−56 −63

31 27

F

t3:5 t3:6

x

Abbreviations: BA: Brodmann area, CP: cytoarchitectonic probability, H: hemisphere, FWE: family-wise error-corrected, L: left, MNI: Montreal Neurological Institute, p: p-value, R: right, vox: voxel, Z: Z-value; ACC: anterior cingulate cortex, ALPFC: anterolateral prefrontal cortex, PCC: posterior cingulate cortex, TPJ: temporoparietal junction, VLPFC: ventrolateral prefrontal cortex, gray: mentalizing areas, green: mirror areas.

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as between the left TPJ and left IFG and IPL. In contrast, during purely self-referential-processing as well as other-referential-processing, we found activations in the main structures of the MZS only. Thus, the additional recruitment of the MNS and its strengthened functional connectivity with the MZS may differentiate triadic, coordinated social interactions from individual relations and provide a “second-person perspective” (Schilbach, 2010; Schilbach et al., in press) of the other's mental state and motor goals. Our results contribute to a current debate regarding the interaction and roles of the MNS and MZS. There is little consensus in the literature on the relation between these two systems. Some researchers argue that they are largely independent of each other (i.e. Jacob and Jeannerod, 2005; Liew et al., 2011; Saxe and Wexler, 2005) or at least rarely activated simultaneously (for a meta-analysis see Van Overwalle, 2009). It has been suggested that the MNS transits to MZS as tasks get more abstract and require higher-level goal intention interpretations as compared to automatic low-level goal interpretations (Van Overwalle and Baetens, 2009). Others hold the view that there is some form of interaction, for instance that information represented in the MNS may be passed on to the MZS for further reflection and evaluation (Brass et al., 2007; de Lange et al., 2008; Etzel et al., 2008; Keysers and Gazzola, 2007; Lombardo et al., 2010; Ohnishi et al., 2004; Uddin et al., 2007). For instance, Spunt and Lieberman (2012b) found contributions from- and effective connectivity between parts of the MNS and MZS during an emotional Identification-Attribution task. They hence suggested that emotional behavior involves facilitative input from the MNS to the MZS. In accordance with these findings, our results demonstrate that special cases exist in which the MNS and MZS are recruited simultaneously and functional connectivity between them increases. Furthermore, we found the concurrent activation in a task that did not require the understanding of emotions but in one that emphasized reflecting on social triadic engagements. Our data thus support the view that there is an interaction between the MNS and MZS and that this interplay is not limited to the understanding of emotions but that it is also of special importance in social triadic interactions. Coordinated triadic behavior implies that both partners focus their attention on the same object (joint attention). This process has been studied by a number of different paradigms, for instance by gaze direction and gaze contact (Bristow et al., 2007; Schilbach et al., 2006, 2010). Moreover, the observation, imitation and production of hand gestures or object-oriented hand movements (Montgomery et al., 2007) were investigated as well as the neural correlates underlying communicationinitiating gestures, such as calling a person's name or making eye contact (Kampe et al., 2003). Typically, these studies found activations in either the MNS (Montgomery et al., 2007; Newman-Norlund et al., 2007b, 2008; Shibata et al., 2011; Spunt et al., 2011) or the MZS

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(Bristow et al., 2007; Kampe et al., 2003; Schilbach et al., 2006, 2010; Spunt et al., 2011), depending on the different requirements of those studies. For instance, depending on the aims of these distinct investigations, they were mainly approaching these social cognitive processes from two different perspectives. They were either interested in a more basic level of action perception or a higher level of mentalizing processes. However, by using these types of “isolation paradigms” (Becchio et al., 2010), participants cannot develop a feeling of being socially involved in an interaction. Being involved in an interaction, in contrast to the mere observation, could lead to changes in the neural signature, though (Becchio et al., 2010; Schilbach et al., in press). Our paradigm allowed a feeling of self-involvement within an imagined interaction and our results provide evidence for the assumption that those changes are grounded in the simultaneous activation of MNS and MZS. Coordinated behavior also presupposes the mutual adjustments of actions (joint action). The MNS has been implicated in action observation–execution coupling necessary for joint actions (Gallese et al., 2004, 2013; Ocampo and Kritikos, 2011; Rizzolatti and Fabbri-Destro, 2008; Rizzolatti and Sinigaglia, 2010). This coupling seems to be especially important for the execution of complementary actions and these actions have been shown to elicit increased activations in core regions of the MNS in comparison to imitative behavior (Newman-Norlund et al., 2007a; Newman-Norlund et al., 2007b; Newman-Norlund et al., 2008; Shibata et al., 2011). We assume that coupling of action execution and observation is especially important in coordinated triadic engagements and specifically in collaborative ones since these require complementarity to a high degree. In future investigations, it would be interesting to specify and compare different types of triadic interactions (for instance, collaborative vs. competitive ones) to further enhance our understanding of these social encounters. We would expect elevated activations in areas of the MNS during collaboration due to the reasons mentioned above. In addition, we would predict elevated activations in areas of the MZS, since a precise representation of the other's goal is necessary during a successful collaboration. In contrast, both partner's have the exact same goal during a competition (Tomasello et al., 2005). The aforementioned action observation–execution coupling probably involves a predictive component to allow the anticipation of the other's next moves (Vesper et al., 2010). To be able to respond to a given action in an appropriate way, it must be understood ‘how’ the action was performed and also ‘why’ the action was executed in the first place. In contrast to triad-trials, self- and other-trials are lacking the interactive (or predictive) component, and thus require only an understanding of ‘why’ the action is performed. A recent model proposed by Thioux et al. (2008) subdivides action processing into three branches with distinct levels of abstractness: understanding ‘how’ the action is done, ‘what’ is done (both associated with the MNS) and finally ‘why’

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Please cite this article as: Trapp, K., et al., Imagining triadic interactions simultaneously activates mirror and mentalizing systems, NeuroImage (2014), http://dx.doi.org/10.1016/j.neuroimage.2014.05.003

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reasons argue against this view. First, the instructions given to participants before the experiment included an action component when selfand other-relatedness were exemplified as “objects that are used frequently by the person”. Second, it is assumed that motor imagery is a rapid process that allows quick goal identification while mentalizing seems to be more cognitively demanding and thus more timeconsuming (i.e. Van Overwalle and Baetens, 2009). In the present experiment however, longest response times were found for triad-trials. Third, we compared the location of the clusters that were identified in the present study by the contrast triad N (self & other) with the location of MNS clusters found by classical MNS studies and motor imagery studies. For this purpose, we computed literature based probabilistic ROIs for these areas (MNS-ROI and MI-ROI, respectively; for methodical details see Supplementary Methods SI). These ROIs served as spatial Bayesian priors for the calculation of the posterior probabilities for the locations of our peak effects most likely associated with the MNS. The probability that the effect within the left IFG belongs to the MI-ROI was below 5%. This finding suggests that triad-trials activate a part of the left IFG that is different from activations induced by pure motor imagery paradigms (Inline Supplementary Fig. S1). In contrast, for the inferior parietal part of MNS, we could not exclude the influence of motor imagery on the elevated brain response in triadic trials. Inline Supplementary Fig. S1 can be found online at http://dx.doi. org/10.1016/j.neuroimage.2014.05.003. Our results add to the existing knowledge in the domain of self- and other-referential stimulus processing. We replicated previous findings by showing a preference for self-referential processing in the ventral MPFC (Kelley et al., 2002; Lombardo et al., 2010) and a preference for other-referential processing in the right TPJ and right PCC (Lombardo et al., 2010; Saxe et al., 2006). Regarding these two processes, we extended earlier findings by showing that also neutral objects are sufficient to elicit activations in these brain areas if they were set into the appropriate individual socio-cognitive context. In contrast, previous studies mainly used pictorial or verbal stimuli, which were not neutral and thus most likely confounded by valence or social desirability, since people tend to perceive mainly positive information as being self-referential in contrast to negative information (self-positivity bias, Heine et al., 1999; Mezulis et al., 2004; Pahl and Eiser, 2005). In conclusion, our results provide evidence for a simultaneous engagement of and increased functional coupling between the MNS and MZS during triadic interactions. Furthermore, our findings point to the similarities as well as the differences between triadic and purely selfor other-referential processing and suggest that in certain situations, such as triadic interactions, cooperation between MNS and MZS may be advantageous. The key feature of situations leading to simultaneous activations might be the participation in social interactions, which

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it is done (associated with the MZS) (see also Spunt et al., 2011). Our findings lend support to their model by showing that self- and othertrials, requiring understanding ‘why’ an action is performed, selectively recruited the MZS. In contrast, triad-trials, requiring understanding ‘why’ an action is performed and additionally ‘how’ it is performed, recruited the MZS and the MNS and positively modulated the coupling strength between these areas. Likewise, Spunt and Lieberman (2012a) supported this tripartite model with the help of an elegant experiment designed to dissociate the distinct systems for action processing. They found a primarily right-lateralized MNS recruitment when action was perceived during a video presentation. In contrast, textual information conveying the same action information did not elicit these activations. However, Spunt and Lieberman (2012a) observed left-lateralized MNS activations in trials requiring implementation understanding regardless of modality (video or text). Moreover, they found the involvement of predominantly left-hemispheric MZS for the process of understanding the aim of the action, or ‘why’ it was performed. Our findings support and extend their results by showing that left-lateralized recruitment of the MNS and left-lateralized increases in functional coupling between the MZS and MNS – involving the MPFC, the left IFG, the left IPL and the left TPJ – are also observed by interactions imagined from images (Fig. 5B). Moreover, we also found largely left-lateralized activations in the MZS, resembling their finding on inferring the motive of an action. Since we did not present stimuli that allowed direct action perception, we did not observe right-lateralized MNS activations. A recent experiment on communicative intentions (Ciaramidaro et al., in press) found concurrent recruitment of MNS and MZS, results similar to our findings. In their study, participants were presented with video clips showing actors either with (i.e. offering an object) or without (i.e. individually acting upon the object) communicative intentions. They concluded that both, the MNS and MZS contribute to the encoding of these intentions. We add to this finding by showing that intention-reading is not a necessary requirement but that participation in, or even the imagination of, a more basic triadic interaction is sufficient to simultaneously activate both systems and to induce an increase their coupling strength. We were able to show that this interplay between the MNS and MZS is not limited to direct action observation. In this way, our paradigm allowed us to exclude factors that may recruit additional, possibly confounding processes, such as the presence of an actor, eye contact, or gaze direction. However, we acknowledge that, beside the advantages that arise due to the pure imagination of interactions, important differences could be present during real interactions. As a potential limitation of our study, we cannot exclude the possibility that motor imagery was required to a higher degree during triad-trials as compared to self- and other-trials. Yet, some important

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Fig. 5. Functional connectivity. A: Condition independent functional connectivity (seed voxel correlations). The statistical threshold was p = 0.05, family wise error-corrected. B: Condition dependent functional connectivity (PPI). Positive modulation of functional connectivity by the condition triad N other. Significant positive modulation between the MPFC and the IFG was also found by the condition triad N (self & other). The statistical threshold was p = 0.05, cluster size corrected. C: Condition dependent functional connectivity (PPI). Positive modulation of functional connectivity by the condition self N other. The statistical threshold was p = 0.05, cluster size corrected. As seed areas, we used spheres with a diameter of 8 mm centered on peak voxels of mentalizing areas (MPFC: [-5 63 24], left [-47 -67 31] and right TPJ [55 -63 31] and PCC/Precuneus [-1 -60 34]) as identified in the conjunction analysis. L: Left side, R: Right side. Mirror areas are depicted in green.

Please cite this article as: Trapp, K., et al., Imagining triadic interactions simultaneously activates mirror and mentalizing systems, NeuroImage (2014), http://dx.doi.org/10.1016/j.neuroimage.2014.05.003

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Acknowledgments

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The study was supported by the German Federal Ministry of Education and Research (BMBF 01KR1207C).

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Appendix A. Supplementary data

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Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.neuroimage.2014.05.003.

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References

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Imagining triadic interactions simultaneously activates mirror and mentalizing systems.

Coordinated triadic interactions, involving oneself, another person, and an external object, are considered a uniquely human skill. However, the exact...
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