Psychological Research DOI 10.1007/s00426-014-0634-9

ORIGINAL ARTICLE

Uncovering the interaction between empathetic pain and cognition Kesong Hu · Zhiwei Fan · Shuchang He

Received: 17 September 2014 / Accepted: 24 November 2014 © Springer-Verlag Berlin Heidelberg 2014

Abstract Recent studies have demonstrated that empathizing with pain involves both cognitive and affective components of pain. How does empathetic pain impact cognition? To investigate this question, in the present study, participants performed a classic color–word Stroop task that followed a pain portraying or a corresponding control image. We found that observing pain experience in another had a basic slowing down effect on Reaction times (RTs) during neutral Stroop trials. Further, it affected cognition in a way that it decreased interference and increased facilitation. Moreover, our findings revealed that RTs during the incongruent and congruent trials were essentially unchanged by pain observing (empathy vs. control). The data are best accounted by a two-opposing effect model that empathetic pain impacts cognition through two different ways: it slows down performance in general, and facilitates performance during incongruent and congruent trials in particular. In this way, the present study also lends support to an idea that all components of empathy should be understood from an integrative approach.

Introduction Empathy for pain enables observers to understand what it feels like when someone else experiences pain and sadness K. Hu (&) Human Neuroscience Institute, Department of Human Development, Cornell University, Ithaca, NY 14853, USA e-mail: [email protected] Z. Fan · S. He Department of Psychology, Peking University, Beijing, People’s Republic of China

(Gallese, 2003; Goubert, Craig & Buysse, 2009). For instance, observing noxious injury to another person automatically activates a representation of that state in the observer (Davis, 1983; Prinz, 1997; Singer, 2006; Singer & Lamm, 2009). As a special psychological state, empathetic pain (empathy for pain) has fascinated researchers for centuries (De Vignemont & Singer, 2006; Ickes, 1997; Keysers, 2011; Singer & Lamm, 2009). In the last decades, there has been an increasing number of studies which emphasized the affective component of empathetic pain. For instance, Singer et al. (2004) claimed that affective component, rather than the cognitive component, plays the dominant role in empathetic pain (for a similar conclusion, see Jackson, Meltzoff & Decety, 2005; Morrison et al., 2004; but see Keysers, Kaas & Gazzola, 2010). With the advent of functional MRI(fMRI), a mounting literature indicates that watching painful expression induced significant activation in the anterior insula (e.g., Jackson et al., 2005; Saarela et al., 2007), the anterior cingulate cortex (e.g., Jackson et al., 2005; Saarela et al., 2007), and the amygdale (e.g., Botvinick et al., 2005) —the activation of this neural network also reflects a general aversive response (e.g., Choi, Padmala & Pessoa, 2012; Lim, Padmala & Pessoa, 2009; Yamada & Decety, 2009). These findings thus support a perspective in which empathetic pain is similar to the acute stress and threat. Yet, on the other hand, it should be noted that the affective component of empathetic pain arises from perception and understanding of others’ emotional states (Decety & Jackson, 2004). Because of this, there are also scientists who view empathetic pain as cognitive in nature. For instance, one can voluntarily imagine or mimic another person’s painful feelings without any affective response to them (Davis, 1996). Avenanti, Bueti, Galati & Aglioti, (2005) specifically demonstrated that watching a needle

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prick a specific hand muscle reduced motor excitability in the same muscle in the observer. This study, therefore, suggests that empathetic pain relies on sensory representations––it of course does not exclude the role of affective component in empathetic pain. In fact, it has also been demonstrated that empathetic pain is involved with inhibitory processes which prevent the observer from experiencing pain when observing another experiencing pain (Kraskov, Dancause, Quallo, Shepherd & Lemon, 2009; Van Damme, Legrain, Vogt & Crombez, 2010). In support of this perspective, recent conceptual framework postulates that empathetic pain involves both affective and cognitive components, and is often accompanied by desires to terminate, reduce, or escape its presence (Davis, 1996; Lamm, Decety J & Singer, 2011; Preston & de Waal, 2002; Price, 2000). Specifically, researchers are now starting to paint a picture which complements this notion that people’s response to empathetic pain could be quite automatic, as the empathy is involved with multiple independent but interacting components and mechanisms (De Vignemont & Jacob, 2012, Keysers, 2011; Singer et al., 2006). To date, there have been only a small number of studies investigating the impact of empathetic pain on attention. For instance, attending to people in pain mobilized the observer to react to threatening situations, with heightened arousal and attention (Decety, 2011), and the detection of visual stimuli was faster when preceded by an empathetic painful stimulus at the corresponding location (Van Damme, Crombez & Lorenz, 2007). Whereas it is clear that empathetic pain affects attention, how it affects higher executive function remains unknown. One proposition is that empathetic pain impairs executive function. For instance, resource models predict that cognition is typically impaired in the presence of task-irrelevant emotional items, as the resources needed for central processing are utilized by these emotional distractors (e.g., Eysenck & Calvo, 1992; Eysenck, Derakshan, Santos & Calvo 2007; Mathews & Mackinitosh, 1998; Okon-Singer, Alyagon, Kofman, Tzelgov & Henik, 2011; Pessoa, 2009). Another proposition is that empathetic pain improves executive function. Evidence supporting this perspective comes from the attention facilitation models (Easterbrook, 1959; also see Callaway, 1959; Callaway & Dembo, 1958). This theory presumes that empathetic pain overloads the attention system and reduces the attention resources available for less relevant information processing. Also plausible, however, is the third possibility that the effect of empathetic pain is quite flexible, rather than fixed (for a similar view, see Huntsinger, 2013). As mentioned above, empathetic pain is closely related to, yet different from, general negative emotion, and people’s reaction to another one’s physiological pain can be quite automatic and even accompanied by avoidance-type motor behaviors. Given that empathetic pain has multi-dimensional properties

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(e.g., affective component, inhibitory processing component), especially the potential reciprocal connections between empathy and cognition (Okon-Singer, LichtensteinVidne & Cohen, 2013), empathetic pain may give rise to simultaneous opposing facilitation and inhibition effects on cognitive processing, like threat of bodily harm anticipation (Hu et al., 2012). In the present study, we assessed these different models via investigating empathetic pain effects on cognition during a standard color–word Stroop task (Stroop, 1935; MacLeod, 1991). The Stroop task was used as it measures the ability to inhibit interference from an over-learned/automatic response, i.e., pronouncing a written word (Stroop, 1935; Posner & Snyder, 1975; for a review, see Macleod, 1991, 1992). In a standard color–word Stroop task, participants were required to actively identify the color of the font in which a word was presented, while ignoring the word itself. Typically, it takes less or more time to identify the color when the color and word are congruent (e.g., the word “red” in red ink) or incongruent (e.g., the word “red” in blue ink), respectively, compared to the baseline neutral condition (e.g., a string of Xs in red ink). The decrease in response time during congruent condition is known as Stroop facilitation effect, while the increase in response time during incongruent condition is termed Stroop interference effect. In Hu et al. (2012), we reported that threat anticipation (induced by mild electrical shock) has two opposing effects on cognition—a basic slowing down effect during neutral Stroop trials, while a reduced-distractor effect on congruent and incongruent trials. Considering the multi-dimensional properties of empathetic pain, as well as the integrative mechanism underlying, we predicted that empathetic pain leads to flexible effects across cognitive conditions as well. For instance, it may lead to opposing effects on congruent (e.g., inhibitory effect) and incongruent trials (e.g., facilitatory effect), respectively, compared to that on neutral trials. Specifically, the potential opposing effects of empathetic pain perhaps would be different from that in Hu et al. (2012), if empathetic pain is different from threat anticipation in nature. However, the data pattern would be much simple if empathetic pain is close to or just is a kind of emotion. According to resource models or attention facilitation models, empathetic pain would lead to impaired or improved performance, respectively. Note that the multi-dimensional properties of empathetic pain (e.g., affective component, cognitive component, and inhibitory component) make the present study qualitatively different from most of the previous emotion studies (e.g., Booth & Sharma, 2009, with aversive noise; Erthal et al., 2005, with unpleasant pictures; Hu et al., 2012, with threat anticipation).

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Method Participants Twenty undergraduate and graduate students from Peking University were recruited (age range = 19–27, mean 22; 5 males, all right-handed). All had normal or correct-tonormal color vision and were naı¨ve to the purpose of the experiment. Participants were tested individually; each received 20 RMB (about US $3) for participating. All participants were treated in accordance with the Declaration of Helsinki and its latest amendments, and provided a written informed consent before participating in the study. Stimuli and procedure The experiments were conducted on a Pentium IV computer running E-Prime software (Schneider, Eschman, & Zuccolotto, 2002), with participants viewing the screen from a distance of approximately 60 cm. A computer keyboard was directly in front of the subject and its Num Lock pad was used as the response device. Experimental stimuli included a set of digital color images (visual angel: 12.6° 9 9°) and Stroop stimuli (visual angel: 2.3° 9 2.3°). For the images, they showed incidents that may happen in everyday life shot from the first-person perspective so that participants would not have to perform mental rotation before understanding and judging it. In particular, those images were slightly blurred with a Gaussian filter to remove any gender or age bias. Half showed painful events and the

Fig. 1 Experimental paradigm and example stimuli. a The trial began with a fixation display (750 ms), followed by a pain portraying (here indexed by “empathy”) or a corresponding control image (here “control”) stimuli (2,000 ms). After a 1,000-ms interval display, the target appeared for 1,000 ms. During the target period, a Stroop stimulus (a Chinese character in the actual experiment; see text) was presented and involved neutral, congruent, and incongruent conditions (for simplicity, not all task phases are displayed here). English word “BLUE” is equal to the character “蓝” in Chinese. b Example stimuli for empathy manipulation (empathy vs. control) (color figure online)

other half showed non-painful events that were identical in physical properties in terms of context, brightness and contrast (see Fig. 1 for example). The images used in this study were selected from a larger sample on the basis of the pain intensity rating. Five-point scale ratings of the images (1 = not painful at all through 5 = extremely painful) by 30 independent raters indicated that the painful and non-painful images were significantly different (painful = 3.45, SD = 1.12; non-painful = 1.13, SD = 0.40; t(29) = 20.70, p \ 0.0001, d = 7.69), validating their affective content. As Stroop task stimuli, the Chinese characters “红(RED in English)”, “蓝(BLUE)”, “绿(GREEN)”, or “黄(YELLOW)” were displayed on the screen either in the color indicated by the word (congruent condition) or in a randomly mismatching color (incongruent condition). Neutral stimuli consisted of a cross (X) in different colors by which the length of the target stimuli was kept the same across all Stroop trials. The color red, blue, green and yellow were defined with RGB values as (255,0,0), (0,0,255), (0,128,0) and (255,255,0), respectively. As Fig. 1 shows, each trial started with a fixation display (visual angel: 1° 9 1°) for 750 ms and was followed by an empathetic painful or a corresponding control (non-painful) stimulus for 2,000 ms. Participants were required to view these stimuli (no response was required). Following a 1,000-ms interval, a target stimulus containing a colored word or a cross “X” appeared for 1,000 ms. Finally, each trial ended with a 2,000-ms black display. In all trials, a fixation was shown starting at trial onset until the target stimulus. Once the target stimulus appeared, participants were required to identify the color of the font in which a

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Data analysis Performance in the Stroop Task was measured by participants’ reaction times (RTs), and error rates. For each participant, median RTs for correct response for each condition were calculated. The rationale for using the median of RT rather than the mean here was to minimize the impact of long and/or short RTs on the measure, as those RTs would potentially exaggerate group difference (Miller, 1988; Ratcliff, 1993)1. Median RT and error rate data were submitted to 2 Empathy For the present study, we also looked at the mean RT data for all participants. In fact, the median and mean RTs produced similar results, indicating that the data pattern did not arise from slow response on trials during empathetic condition. For a similar approach, see Bindemann, Burton, Hooge, Jenkins & de Haan, (2005), Schlaggar et al., (2002), Tama´s Kincses et al., (2008), and Tipper, Driver and Weaver, (1991).

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word (or cross) was presented, while ignoring the word/ cross itself. For instance, if the color of the stimulus was red, participants were required to hit the button “1” as soon as possible. For others, color blue, green and yellow corresponded to the button 2, 3 and 4, respectively. Participants performed five “sessions”, each comprising 36 trials in which empathetic painful (hereafter, empathy) and non-painful (control) trials were randomly mixed. Trials were balanced between empathy and control conditions. Also, each level of congruency (congruent, neutral, and incongruent) was balanced and trials were presented in a way that no word or color was the same as in the preceding trial, thus minimizing priming effects (Mayr, Awh & Laurey, 2003). Prior to testing, each participant completed a Chinese version of Spielberger State-Trait Anxiety Inventory (Spielberger, 1983), which assesses personality characteristics related to sensitivity to anxiety (Lamm, Nusbaum, Meltzoff & Decety, 2007). This translated version has been evaluated to have good validity and reliability (Shek, 1993). After the experiment, subjects were debriefed about how they felt during the experiment.

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(empathy, control) 9 3 Congruency (congruent, neutral, and incongruent) repeated-measure ANOVA procedures. To evaluate potential models, two additional repeated ANOVAs were also conducted (see below). Stroop interference and facilitation effects were assessed as the difference between incongruent and neutral trials (I–N), and between neutral and congruent trials (N–C), respectively. Planned comparisons were then performed to test the empathy effect on these indexes. The interaction score was defined by ([I–N]empathy − [I–N]control), which allowed us to evaluate the empathy by congruency interaction. Following Cohen (1992), effect sizes were reported as partial η2 (small = 0.01; medium = 0.06; large = 0.14) for ANOVAs, and as d (small = 0.30; medium = 0.50; large = 0.80) for planned comparison t tests. As did elsewhere (e.g., Hu et al., 2013), we also ran an across-subject robust regression analysis between anxiety and RT scores (the robust fit function from Matlab, Mathworks, Natick, MA, USA) to probe potential relationships between individual anxiety levels and interference/interaction scores (i.e., how interference/interaction changed as a function of individual differences), given that standard Pearson correlation is very sensitive to even a few influential data points (Wilcox, 2005). This analysis was done separately for state and trait anxiety.

Results We submitted median RTs to 2 Empathy (empathy, control) 9 3 Congruency (congruent, neutral, and incongruent) repeated-measure ANOVAs (Fig. 2, left panel). RT data revealed a main effect of Congruency [F(2,38) = 33.00, p \ 0.001, η2 = 0.63], as well as interaction of congruency 9 empathy [F(2,38) = 4.30, p = 0.021, η2 = 0.18]. The main effect of Empathy did not reach significance [F (1,19) = 2.81, p = 0.110, η2 = 0.13]. Further, the contrast between incongruent trials in empathy and control conditions did not reach a significant difference, t(19) = −0.72,

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Fig. 3 Stroop facilitation and interference during empathetic pain (“empathy”) and control conditions (“control”). Error bars indicate standard errors of the mean (SEM)

p = 0.480, d = 0.33. Also, the contrast between congruent trials (empathy vs. control) was non-significant, t (19) = −0.14, p = 0.888, d = 0.07. To evaluate the basic effect of empathetic pain, we contrasted neutral trials (empathy vs. control). A salient difference (approximately 36 ms, SEM = 11.48) was detected during painful versus neutral trials, t(19) = 3.16, p = 0.005, d = 1.45. Because the main focus was to evaluate aspects of RT data that informed the types of models, we ran two additional repeated ANOVAs (for a similar approach, see Hu et al., 2012; Padmala & Pessoa, 2011). First, we probed the interference effect via empathy (empathy, control) by congruency (neutral, incongruent) ANOVA. It revealed a significant interaction effect [F(1,19) = 7.73, p = 0.015, η2 = 0.29]. Second, we probed the facilitation effect via empathy (empathy, control) by congruency (neutral, congruent) ANOVA. Similarly, the interaction effect reached significance [F(1,19) = 5.22, p = 0.034, η2 = 0.22]. The effects of Stroop interference (I–N) and facilitation (N–C) were made clear in the Fig. 3. Planned comparisons indicated that Stroop interference was significant in both control, t(19) = 6.31, p \ 0.0001, d = 1.63, and empathy conditions, t(19) = 3.47, p \ 0.003, d = 2.97. During control condition, the interference was 118 ms (SEM = 18.70), yet this effect was largely decreased during empathy condition (73 ms, SEM = 21.17), which was confirmed by a pairwise t test, t(19) = 2.69, p = 0.015, d = 1.27. The Stroop facilitation trend appeared during control condition (about 8 ms, SEM = 7.35), though it did not reach statistical significance, t(19) = 1.08, p = 0.292, d = 0.512. This effect was robust during empathy 2

Stroop facilitation effect is generally small, unstable and often referred to as “fragile” (Kalanthroff & Henik, 2013; MacLeod & MacDonald, 2000). Therefore, the non-significant Stroop facilitation effect here was not surprising. One reason perhaps is that in the present study, the neutral stimulus was a cross “X” (for a discussion, see MacLeod, 1991, p172).

condition, 46 ms (SEM = 12.67), t(19) = 3.60, p = 0.002, d = 1.70. Apparently, Stroop facilitation was increased in empathy condition (empathy vs. control), t(19) = 2.28, p = 0.034, d = 1.08. Error rate data were processed with the same procedure (Fig. 2, right panel). The repeated ANOVA analysis [2 Empathy (empathy, control) 9 3 Congruency (congruent, neutral, and incongruent)] only revealed a main effect of congruency [F(2,38) = 4.32, p = 0.038, η2 = 0.19]. The interaction of congruency 9 empathy was not significant [F(2,38) = 1.94, p = 0.167, η2 = 0.09], nor was the main effect of empathy [F(1,19) = 0.06, p = 0.804, η2 \ 0.001]. Further analysis indicated that the marginal main effect of congruency was driven by the interference effect (0.05, SEM = 0.02) under the non-painful condition, that is, the error rate was higher in incongruent trials, compared to that in neutral trials (t(19) = 2.19, p = 0.042, d = 0.02). Finally, robust regression analysis showed a significant positive linear relationship between the state anxiety and interference (I–N) under control condition (R2 = 0.3080, p = 0.014), indicating that the interference difference increased with state anxiety. This relationship was not observed under empathy condition (R2 = 0.1639, p = 0.331). Further, the relationship between state anxiety and the interaction score ([I–N]empathy − [I–N]control) did not reach significance (R2 = 0.0118, p = 0.786). No other significant relationships were observed between trait anxiety and interference/interaction scores.

Discussion In the present study, we investigated the interaction between empathetic pain and cognition. Empathy was manipulated using task-irrelevant pain portraying, and control images preceded the Stroop task. As mentioned above, the fivepoint scale rating of the pain portraying images validated the affective content (also see Gu et al., 2010; Gu, Liu, Van Dam, Hof & Fan, 2012; Jackson et al., 2005). Consistently, post-experiment debriefing confirmed that all participants felt that pain was incurred to others when the painful images were presented during experiments. We observed an increase in reaction time (i.e., slower RT) during the empathetic pain condition (empathy vs. control), which was revealed on task performance during Stroop neutral trials. Further, the impact of empathetic pain was also detected in interference (incongruent vs. neutral) and facilitation (congruent vs. neutral) effects. It decreased interference effect and increased facilitation effect. It thus appears that the interaction between empathetic pain and cognition follows a two-opposing effect model, which is in accordance with our major research hypothesis. First, the basic effect of empathetic pain on task performance was obtained during neutral

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trials (empathy vs. control). It is worthy to note that this slowing down effect (36 ms) is similar to the impact of negative emotion reported elsewhere (e.g., negative emotion pictures, Erthal et al., 2005; Hartikainen, Ogawa, & Knight, 2000). Remarkably, in our previous study, we observed a very close RT increasing effect of acute stress (41 ms) (threat anticipation, Hu et al., 2012). Next, we evaluated the influence of empathetic pain on interference by probing response during incongruent trials. The interaction of empathy (empathy, control) by congruency (incongruent, neutral) was detected, whereby the sizable interference effect observed during control conditions largely decreased during the empathetic pain condition (see Fig. 3 right panel). We noted that RTs during the incongruent condition were essentially unchanged in the empathy condition, compared to control condition. We propose that empathetic pain reduced the distractor effect in incongruent condition (attention focus narrowed to the relevant “color” dimension), and thus decreased the Stroop interference effect. Third, we investigated the influence of empathetic pain on the facilitation effect. The interaction of empathy (empathy vs. control) by congruency (neutral, congruent) was also detected, indicating that the negligible facilitation effect during the control condition was boosted during the painful condition (see Fig. 3, left panel). The robust facilitation effect obtained under empathy condition is very impressive. A close inspection revealed that the RTs for the congruent trials between empathy and control condition were not significantly different. A potential interpretation is related to the attention facilitation model (see below). Of note, in the present study, we balanced all trials, such that the potential cognitive

processing adaptation, i.e., the enhanced cognitive function after presentation of a congruent (also, incongruent) trial was not explicit in our study (Mayr et al., 2003). What are the implications of our findings? It is straightforward that the present data were only partly consistent with resource models, and at the same time, partly consistent with attention facilitation model. On the one hand, empathetic pain had a slowing down effect on performance. Though it only appeared during neutral trials, we propose that this was actually a part of the RTs during all empathetic painful trials (up arrow in Fig. 4, left panel). This is consistent with the resources theory which claims that stress/anxiety has adverse effects on cognition (e.g., Eysenck & Calvo, 1992; Eysenck, et al., 2007; Okon-Singer et al., 2011; Pessoa, 2009). On the other hand, empathy improved performance via decreasing the interference effect (incongruent vs. neutral) and increasing the facilitation effect (congruent vs. neutral). A possible interpretation is that attention narrowing mechanism decreased irrelevant information processing (i.e., “word” dimension) during incongruent trials (Easterbrook, 1959; also Callaway, 1959; Callaway & Dembo, 1958), and improved both irrelevant and relevant dimensions (i.e., “word”, “color”) processing during congruent trials, as those two dimensions integrally led to the correct response(down arrow in Fig. 4, left panel). Finally, the facilitation effect equally opposed the generalized slowing down effect, as disclosed in the neutral trials. Through this way, RTs of the congruent and incongruent trials showed no difference between empathy and control conditions, respectively. As described above, we reasoned that attention narrowing mechanism facilitated the “irrelevant” item (“word” dimension) processing during congruent trials, but

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Current study Fig. 4 Comparison of empathetic pain and threat effects on cognition: a summary (Note: not drawn exactly to scale). Left side: effects of empathetic pain (present study). Right side: effects of threat anticipation, adapted from Hu et al. (2012). For the present study, the

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Hu et al. (2012) effects of the empathetic pain were evidenced as a basic slowing down effect in general (red) and a facilitation effect during both incongruent and congruent trials in particular (blue). C congruent, N neutral, I incongruent (color figure online)

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narrowed its processing during incongruent trials. The distinctive attention narrowing functions are reminiscent of some important opinions in the Stroop literature. For example, researchers proposed that Stroop interference occurs within an analyzer (e.g., Durgin, 2003; Klein, 1964; Luo, 1999; Virzi & Egeth, 1985). If so, attention narrowing facilitates this analysis and improves performance. Note that in the congruent trials, both of the two dimensions (“word”, “color”) led to correct response; while in the incongruent trials, “word” dimension led to incorrect response. Critically, there has been evidence that attention narrowing led people to work in a more focused manner (Chajut & Algom, 2003) and could be activating (Gardner, 1990). Taken together, it is logic to assume that under empathetic pain condition, attention narrowing mechanism worked in a flexible, interactive and integrated way—it facilitated the cognitive processing in both congruent and incongruent trials. We believe that the present results generally fit well with our recent two-opposing effect model (Hu et al., 2012)— moreover, it sets constraints on that model, suggesting that the two opponent effects are flexible(see Fig. 4, left panel), rather than fixed as we previously hypothesized. In Hu et al. (2012), we demonstrated that the threat anticipation decreased both Stroop interference and facilitation effects (Fig. 4, right panel). The data were interpreted in terms of that the irrelevant dimension was attention narrowed (“filtered out”) in both incongruent and congruent trials (arrows with contrary directions; Fig. 4 right panel). We are aware that Lamm et al. (2007) proposed that the effect of empathetic pain actually is not specific to pain, but to the exposure to aversive and potentially threatening information in general. It is true that in both Hu et al. (2012) and the present study, the threat and empathy generally showed similar opposing effects. Yet, the data patterns were different on congruent trials between threat anticipation (Hu et al., 2012) and empathetic pain conditions (present study, see the dashed line in the Fig. 4). Therefore, the present study actually indicates that empathetic pain is qualitatively different than general negative information exposure, including threat anticipation. From this perspective, the present study also lends support to an idea that all components of empathetic pain should be understood from an integrative approach. There is another possible interpretation for our results. Some researchers proposed a “tuning down emotional brain” opinion (Cohen, Henik & Moyal, 2012; Van Dillen, Heslenfeld & Koole, 2009; Okon-Singer, Tzelgov & Henik, 2007; Pessoa, McKenna, Gutierrez & Ungerleider, 2002; Shafer et al., 2012). For instance, Cohen et al. (2012) showed that in incongruent Flanker task trials, participants ignored negative pictures. This view is in line with the resource models which claim that the processing resources are limited. With respect to Stroop task, there is a

competition between two sources of information, not just in incongruent trials, but also in congruent trials (although both lead to the correct response) (Carter, Mintun & Cohen, 1995; Goldfarb & Henik, 2007; Milham et al., 2002; Posner & DiGirolamo, 1998). If so, perhaps the detection and resolution of conflict (incongruent trials) and competition (congruent trials) consumed resources, by which the empathy processing was tuned down. In other words, under both incongruent and congruent conditions, the empathy effects were eliminated (e.g., Tzelgov, Meyer & Henik, 1992). With regard to the neutral trials (“x” stimulus), they may be easier or involve different cognitive mechanisms compared to the incongruent and congruent trials (e.g., semantic networks). From this perspective, it appears that empathetic pain shapes cognition in two different ways, pertaining to the task load. It should be noted that in our previous work (Hu et al., 2012), the recorded physiology data (Galvanic skin resistance, GSR) were not altered as a function of congruency, suggesting that the cognitive manipulation there was not sufficiently strong to tune down the emotional brain. Nevertheless, future studies combing performance measures with ERP/fMRI may provide useful insight into the mechanism of empathy. In the present study, there was no correlation between state/trait anxiety measure and Stroop effect during empathetic pain condition. This opens a general question on whether the pain experience taken place in the actor represented in the image really drives the onlooker to empathize with the actor3. In absolute terms, the lack of correlation between trait/state anxiety and Stroop effect imposes caution on interpreting the data as a result of empathy effect (Valentini, 2010). However, at least two issues should be considered here. First, the direct correlation between personality and behavioral/neuroimaging data during empathy condition was seldom observed (Decety, 2010). Second, in the present study, we did observe a positive correlation of state anxiety and Stroop interference effect (incongruent–neutral) during control (non-painful) condition, which indicated that participants with higher state anxiety level showed greater interference during the control condition (Bishop, 2008; Eysenck et al., 2007; Eysenck & Calvo, 1992). We, therefore, speculate that the empathetic pain was highly salient to all participants, decreasing the chance of inter-individual variance observation (Rhudy & Meagher, 2000). Definitely, future study is required to determine this issue. Finally, the error rate was very low. The repeated 2 empathy 9 3 congruency ANOVA only revealed the main effect of congruency. Neither the main effect of empathy nor the interaction of empathy and congruency reached 3

We are grateful to an anonymous reviewer for pointing this out to us.

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significance. It was impressive that the main effect of congruency was driven by the interference effect under the control (non-painful) condition, that is, the error rate was higher in incongruent trials, compared to that in neutral trials. This result is of relevance in understanding the contribution of processing effectiveness during empathetic pain condition (Eysenck et al., 2007). In summary, using a mixed design, we investigated the interaction between empathetic pain and cognition. Our results show that empathy for pain affects cognition in two opposing ways: it slows down performance in general, and facilitates performance during congruency (incongruent and congruent) trials in particular. Cast in broader terms, these findings, together with Hu et al. (2012) could have important implications for updating the present uni-models (e.g., resources and facilitation models) to flexible bimodels to interpret the complexity of human behavior. Acknowledgments We thank Eve De Rosa and Adam Anderson for funding support. This research was also supported by a research grant to Shuchang He (Natural Science Foundation of China, Grant no. 81271491/H0920). We thank Luiz Pessoa, Deborah A. Pearson and Noga Cohen for their helpful comments during the early stages of this research. Thanks also to Xiaosi Gu and Jin Fan for their empathy stimuli package. In addition, we thank three anonymous reviewers for very constructive suggestions during the review process, and all the participants for their contribution. Conflict of interest K. Hu, Z. Fan and S. He declare that they have no conflicts of interest.

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