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W3199860418 abstract "Article Figures and data Abstract eLife digest Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract Empathy for pain engages both shared affective responses and self-other distinction. In this study, we addressed the highly debated question of whether neural responses previously linked to affect sharing could result from the perception of salient affective displays. Moreover, we investigated how the brain network involved in affect sharing and self-other distinction underpinned our response to a pain that is either perceived as genuine or pretended (while in fact both were acted for reasons of experimental control). We found stronger activations in regions associated with affect sharing (anterior insula [aIns] and anterior mid-cingulate cortex) as well as with affective self-other distinction (right supramarginal gyrus [rSMG]), in participants watching video clips of genuine vs. pretended facial expressions of pain. Using dynamic causal modeling, we then assessed the neural dynamics between the right aIns and rSMG in these two conditions. This revealed a reduced inhibitory effect on the aIns to rSMG connection for genuine pain compared to pretended pain. For genuine pain only, brain-to-behavior regression analyses highlighted a linkage between this inhibitory effect on the one hand, and pain ratings as well as empathic traits on the other. These findings imply that if the pain of others is genuine and thus calls for an appropriate empathic response, neural responses in the aIns indeed seem related to affect sharing and self-other distinction is engaged to avoid empathic over-arousal. In contrast, if others merely pretend to be in pain, the perceptual salience of their painful expression results in neural responses that are down-regulated to avoid inappropriate affect sharing and social support. eLife digest Empathy enables us to share and understand the emotional states of other people, often based on their facial expressions. This empathic response involves being able to distinguish our own emotional state from someone else’s, and it is influenced by how we recognize that person’s emotion. In real life, knowing and identifying whether the facial expression we are witnessing reflects genuine or pretended pain is particularly important so that we can appropriately react to someone’s emotions and avoid unnecessary personal distress. How our brains manage to do this is still heavily debated. Two areas, the anterior insular (aIns for short) and the mid-cingulate cortex, appear to be activated when someone ‘feels’ someone else’s pain. However, these regions might just automatically be triggered by vivid emotional facial expressions, regardless of whether we really respond to that pain. To examine this question, Zhao et al. measured brain activity as healthy adults watched video clips of people either feeling or pretending to feel pain. The activation of aIns was particularly related to the emotional component that someone shared with another person’s genuine pain, but not to pretended pain. This suggests that neurons in the aIns track a truly empathic response when seeing someone who is actually experiencing pain. Effective connectivity analyses which reflect how brain areas ‘crosstalk’ also revealed distinct patterns when people viewed expressions of genuine, as opposed to pretended pain. Zhao et al. focused on the interactions between the alns and the right supramarginal gyrus, a brain region which helps to distinguish another person’s emotions from our own. This crosstalk tracked others’ feelings when participants viewed expressions of genuine but not of pretended pain. Put together, these findings provide a more refined model of empathy and its neural underpinnings. This will help further our understanding of conditions such as autism or depression, in which a person’s social skills and emotional processing are impaired. Introduction As social beings, our own affective states are influenced by other people’s feelings and affective states. The facial expression of pain by others acts as a distinctive cue to signal their pain to others, and thus results in sizeable affective responses in the observer. Certifying such responses as evidence for empathy, however, requires successful self-other distinction, the ability to distinguish the affective response experienced by ourselves from the affect experienced by the other person. Studies using a wide variety of methods convergently have shown that observing others in pain engages neural responses aligning with those coding for the affective component of self-experienced pain, with the anterior insula (aIns) and the anterior mid-cingulate cortex (aMCC) being two key areas in which such an alignment has been detected (Lamm et al., 2011; Rütgen et al., 2015; Jauniaux et al., 2019; Xiong et al., 2019; Zhou et al., 2020; Fallon et al., 2020, for meta-analyses). However, there is consistent debate on whether activity observed in these areas should indeed be related to the sharing of pain affect or whether it may not rather result from automatic responses to salient perceptual cues – with pain vividly expressed on the face being one particularly prominent example (Zaki et al., 2016, for review). It was thus one major aim of our study to address this question. In this respect, contextual factors, individuals’ appraisals, and attentional processes would all impact their exact response to the affective states of others (Gu and Han, 2007; Hein and Singer, 2008, for review; Lamm et al., 2010; Forbes and Hamilton, 2020; Zhao et al., 2021). Recently, Coll et al., 2017 have thus proposed a framework that attempts to capture these influences on affect sharing and empathic responses. This model posits that individuals who see identical negative facial expressions of others may have different empathic responses due to distinct contextual information and that this may depend on identification of the underlying affective state displayed by the other. In the current functional magnetic resonance imaging (fMRI) study, we therefore created a situation where we varied the genuineness of the pain affect felt by participants while keeping the perceptual saliency (i.e., the quality and strength of pain expressions) identical. To this end, participants were shown video clips of other persons who supposedly displayed genuine pain on their face vs. merely pretended to be in pain. Note that for reasons of experimental control, all painful expressions on the videos had been acted. This enabled us to interpret possible differences between conditions to the observers’ appraisal of the situation rather than to putative visual and expressive differences. This way, we sought to identify the extent to which responses in affective nodes (such as the aIns and the aMCC) genuinely track the pain of others, rather than resulting predominantly from the salient facial expressions associated with the pain. Another major aim of our study was to assess how self-other distinction allowed individuals to distinguish between the sharing of actual pain vs. regulating an inappropriate and potentially misleading ‘sharing’ of what in reality is only a pretended affective state. We focused on the right supramarginal gyrus (rSMG), which has been suggested to act as a major hub selectively engaged in affective self-other distinction (Silani et al., 2013; Steinbeis et al., 2015; Hoffmann et al., 2016; Bukowski et al., 2020). Though previous studies have indicated that rSMG is functionally connected with areas associated with affect processing (Mars et al., 2012; Bukowski et al., 2020), we lack more nuanced insights into how exactly rSMG interacts with these areas, and thus how it supports accurate empathic responses. Hence, we used dynamic causal modeling (DCM) to investigate the hypothesized brain patterns of affective responses and self-other distinction for the genuine and pretended pain situations, focusing on the aIns, aMCC, and their interaction with rSMG. Furthermore, we investigated the relationship between neural activity and behavioral responses as well as empathic traits. In line with the literature reviewed above, we expected that, on the behavioral level, genuine pain would result in – alongside the obvious other-oriented higher pain ratings – higher self-oriented unpleasantness ratings. On the neural level, we predicted aIns and aMCC to show a stronger response to the genuine expressions of pain, but that these areas would also respond to the pretended pain, but to a lower extent. Differences in rSMG engagement and distinct patterns of this area’s effective connectivity with aIns and aMCC were expected to relate to self-other distinction, and thus to explain the different empathic responses to genuine pain vs. pretended pain. Results Behavioral results Three repeated-measures ANOVAs were performed with the factors genuineness (genuine vs. pretended and pain [pain vs. no pain]), for each of the three behavioral ratings. For ratings of painful expressions in others (Figure 1C, left), there was a main effect of the factor genuineness: participants showed higher ratings for the genuine vs. pretended conditions, Fgenuineness (1, 42) = 8.816, p=0.005, η² = 0.173. There was also a main effect of pain: participants showed higher ratings for the pain vs. no pain conditions, Fpain (1, 42) = 1718.645, p<0.001, η² = 0.976. The interaction term was significant as well, Finteraction (1, 42) = 7.443, p=0.009, η² = 0.151, and this was related to higher ratings of painful expressions in others for the genuine pain compared to the pretended pain condition. For ratings of painful feelings in others (Figure 1C, middle), there was a main effect of genuineness: participants showed higher ratings for the genuine vs. pretended conditions, Fgenuineness (1, 42) = 770.140, p<0.001, η² = 0.948. There was also a main effect of pain, as participants showed higher ratings for the pain vs. no pain conditions, Fpain (1, 42) = 1544.762, p<0.001, η² = 0.974. The interaction for painful feelings ratings was significant as well, Finteraction (1, 42) = 752.618, p<0.001, η² = 0.947, and this was related to higher ratings of painful feelings in others for the genuine pain compared to the pretended pain condition. For ratings of unpleasantness in self (Figure 1C, right), there was a main effect of genuineness: participants showed higher ratings for the genuine vs. pretended conditions, Fgenuineness (1, 42) = 74.989, p<0.001, η² = 0.641. There was also a main effect of pain: participants showed higher ratings for the pain vs. no pain conditions, Fpain (1,42) = 254.709, p<0.001, η² = 0.858. The interaction for unpleasantness ratings was significant as well, Finteraction (1, 42) = 73.620, p<0.001, η² = 0.637, and this was related to higher ratings of unpleasantness in self for the genuine pain compared to the pretended pain condition. In sum, the behavioral data indicated higher ratings and large effect sizes of painful feelings in others and unpleasantness in self for the genuine pain compared to the pretended pain condition. Ratings of pain expressions also differed in terms of genuineness, at comparably low effect size, though they were expected to not show a difference by way of our experimental design and the pilot study. Figure 1 Download asset Open asset fMRI experimental design and behavioral results. (A) Overview of the experimental design with the four conditions genuine vs. pretended, pain vs. no pain. Examples show static images, while in the experiment participants were shown video clips. (B) Overview of experimental timeline. At the outset of each block, a reminder of ’genuine‘ or ’pretended‘ was shown (both terms are shown here for illustrative purposes, in the experiment either genuine or pretended was displayed). After a fixation cross, a video in the corresponding condition appeared on the screen. Followed by a short jitter, three questions about the video were separately presented and had to be rated on a visual analogue scale. These would then be followed by the next video clip and questions (not shown). (C) Violin plots of the three types of ratings for all conditions. Participants generally demonstrated higher ratings for painful expressions in others, painful feelings in others, and unpleasantness in self in the genuine pain condition than in the pretended pain condition. Ratings of all three questions were higher in the painful situation than in the neutral situation, regardless of whether in the genuine or pretended condition. The thick black lines illustrate mean values, and the white boxes indicate a 95% CI. The dots are individual data, and the “violin” outlines illustrate their estimated density at different points of the scale. (D) Correlations of painful feelings in others and unpleasantness in self for the genuine pain and the pretended pain (the relevant questions were highlighted with a green rectangular). Results revealed a significant Pearson correlation between the two questions in the genuine pain condition, but no correlation in the pretended pain condition. The lines represent the fitted regression lines, bands indicate a 95% CI. We also found a significant correlation between behavioral ratings of painful feelings in others and unpleasantness in self in the genuine pain condition, r = 0.691, p<0.001, while in the pretended pain condition, the correlation was not significant, r = 0.249, p=0.107 (Figure 1D). A bootstrapping comparison showed a significant difference between the two correlation coefficients, p=0.002, 95 % Confidence Interval (CI) = [0.230, 1.060]. fMRI results: mass-univariate analyses Three contrasts were computed: (1) genuine: pain – no pain, (2) pretended: pain – no pain, and (3) genuine (pain – no pain) – pretended (pain – no pain). Across all three contrasts, we found activations as hypothesized in bilateral aIns, aMCC, and rSMG (Figure 2A and Table 1). Figure 2 Download asset Open asset Neuroimaging results: mass-univariate analyses. (A) Activation maps of genuine: pain – no pain (top), pretended: pain - no pain (middle), and genuine (pain – no pain) – pretended (pain – no pain) (bottom). As expected, we found brain activations in the bilateral aIns, aMCC, and rSMG in all three contrasts (except for the bottom contrast, where the right aIns is only close to the significance threshold). (B) The multiple regression analysis demonstrated significant clusters in the left (peak: [–42, 15,–2]) and right anterior insular cortex (peak: [45, 5, 8]) that were positively correlated with the ratings of unpleasantness in self comparing genuine pain vs. pretended pain. All activations are thresholded with cluster-level family-wise error correction, p<0.05 (p<0.001 uncorrected initial selection threshold). The lines of the scatterplots represent the fitted regression lines, bands indicate a 95% confidence interval (CI). Table 1 Results of mass-univariate functional segregation analyses in the MNI space. Region labelBACluster sizeXYZt-valueGenuine: pain - no painLingual_R18183,73211−84−313.38Temporal_Pole_Sup_R383033−3313.31Supp_Motor_Area_R85155112.96Supp_Motor_Area_R83175012.92Supp_Motor_Area_L8−5174812.56Insula_L45−3226612.32Insula_R453329312.09Frontal_Inf_Oper_R4451141512.01Frontal_Inf_Oper_R4450121811.79Precentral_L6−4233911.72Fusiform_R2046336−5−415.58Pretended: pain - no painSupp_Motor_Area_R859,6655204811.80Supp_Motor_Area_L8−6185011.14Frontal_Inf_Oper_L44−50151510.39Insula_R45332909.81Insula_L45−293009.60Frontal_Inf_Tri_R444715269.21Precuneus_L735,136−9−714110.27Parietal_Inf_L39−32−51419.39Precuneus_R79−69388.44Temporal_Mid_L21−53−4757.67Occipital_Mid_L19−44−7827.47Parietal_Inf_R3939−50417.25Temporal_Mid_R2212,97051−20–67.70Lingual_R1712−86−27.40Fusiform_R3747−33−275.32Occipital_Mid_R1833−8635.23Cingulum_Mid_R231666−3−14276.35Cingulum_Mid_L23−3−24325.57Temporal_Pole_Sup_R475893235−337.18Frontal_Sup_Orb_R111741−243.36Genuine (pain – no pain) – pretended (pain – no pain)SupraMarginal_L401877−66−21324.94Postcentral_L1−50−21263.75SupraMarginal_R40183363−20425.09Rolandic_Oper_R4059−15144.47Insula_L131299−38−3−25.01Rolandic_Oper_L4−45−684.8Cingulum_Ant_L321138041174.54Cingulum_Mid_R32224324.45Cingulum_Mid_L2402354.43Cingulum_Ant_R8232274.42Lingual_R1810039−84−35.72Calcarine_R1718−7883.61Insula_R13225398−33.91Rolandic_Oper_R13410113.77 To identify whether or which brain activity was selectively related to the behavioral ratings described above, we performed a multiple regression analysis where we explored the relationship of activation in the contrast genuine pain – pretended pain with the three behavioral ratings. We found significant clusters in bilateral aIns, visual cortex, and cerebellum that could be selectively explained by the ratings of self-unpleasantness rather than ratings of painful expressions in others or painful feelings in others (Figure 2B). DCM results We performed DCM analysis to specifically examine the modulatory effect of genuineness on the effective connectivity between the right aIns and rSMG. More specifically, we sought to assess whether the experimental manipulation of genuine pain vs. pretended pain tuned the bidirectional neural dynamics from aIns to rSMG and vice versa, in terms of both directionality (sign of the DCM parameter) and intensity (magnitude of the DCM parameter). If the experimental manipulation modulated the effective connectivity, we would observe a strong posterior probability (pp>0.95) of the modulatory effect. Our original analysis plan was to include aMCC in the DCM analyses, but based on the fact that aMCC did not show as strong evidence (in terms of the multiple regression analysis) as the aIns of being involved in our task, we decided to use a more parsimonious DCM model without the aMCC. We found strong evidence of inhibitory effects on the aIns to rSMG connection both in the genuine pain condition and in the pretended pain condition (Figure 1A-C). Comparing the strength of these modulatory effects on the aIns to rSMG connection revealed a reduced inhibitory effect for genuine pain as opposed to pretended pain, t41 = 2.671, p=0.011 (meangenuine pain = −0.821, 95% CI = [−0.878, −0.712]; meanpretended pain = −0.934, 95% CI = [−1.076, −0.822]; Figure 3C). There was no evidence of a modulatory effect on the rSMG to aIns connection. Figure 3 Download asset Open asset DCM results and brain-behavior analyses. (A) ROIs included in the DCM: aIns (blue; peak: [33, 29, 2]) and rSMG (green; peak: [41, –39, 42]). (B) Posterior probability of modulatory effects for the genuine pain and the pretended pain. (C) The group-average DCM model. Green arrows indicate neural excitation, and orange arrows indicate neural inhibition. Importantly, we found strong evidence of inhibitory effects on the connection of aIns to rSMG for both the genuine pain condition and the pretended pain condition. Values without the bracket quantify the strength of connections and values in the bracket indicate the posterior probability of connections. All DCM parameters of the optimal model showed greater than a 95% posterior probability (i.e., strong evidence) except for the intrinsic connection of aIns to rSMG (pp = 0.80). Paired sample t-test showed less inhibitory effects of the aIns-to-rSMG connection for the genuine pain than the pretended pain. This result is highlighted with a gray rectangular. Data are mean ± 95% CI. (D) The multiple linear regression model revealed a positive correlation between the inhibitory effect and painful feelings in others and not with the other two ratings for genuine pain but no correlation for pretended pain. Individual associations between modulatory effects, behavioral ratings, and questionnaires To examine how the modulatory effects from the DCM were related to the behavioral ratings, we computed two multiple linear regression models for each condition. For the genuine pain condition, we find that the modulatory effect was significantly related to the rating of painful feelings in others (t = 2.317, p=0.026), but not related to the rating of either painful expressions in others (t = −1.492, p=0.144) or unpleasantness in self (t = 0.058, p=0.954). For the pretended pain condition, none of the ratings was significantly related to the modulatory effect (Figure 3D). The variance inflation factors (VIFs) for three ratings in both models were calculated to diagnose collinearity, showing no severe collinearity problem (all VIFs < 5; the smallest VIF = 1.132 and the largest VIF = 4.387). In addition, we tested two multiple stepwise linear regression models to investigate whether subscales of all three questionnaires could explain modulatory effects for genuine pain and pretended pain. In the genuine pain condition, we found that the modulatory effect was significantly explained by scores of two subscales, that is affective ability and affective reactivity of the ECQ: Fmodel (1, 39) = 6.829, p=0.003, R2 = 0.270; Baffective ability = 0.052, beta = 0.497, p=0.002; Baffective reactivity = −0.040, beta = −0.421, p=0.008. No significant predictor was found with the other questionnaires (i.e., IRI and TAS). In the pretended pain condition, none of the three questionnaires significantly predicted variations of the modulatory effect. No severe collinearity problem was detected for either regression model (all VIFs < 2; the smallest VIF = 1.011 and the largest VIF = 1.600). Discussion In this study, we developed and used a novel experimental paradigm in which participants watched video clips of persons who supposedly either genuinely experienced pain or merely pretended to be in strong pain. Combining mass-univariate analysis with effective connectivity (DCM) analyses, our study provides evidence on the distinct neural dynamics between regions suggestive of affect processing (i.e., aIns and aMCC) and self-other distinction (i.e., rSMG) for genuinely sharing vs. responding to pretended, non-genuine pain. With this, we aimed to clarify two main questions: First, whether neural responses in areas such as the aIns and aMCC to the pain of others are indeed related to a veridical sharing of affect, as opposed to simply tracking automatic responses to salient affective displays. And second, how processes related to self-other distinction, implemented in the rSMG, enable appropriate empathic responses to genuine vs. merely pretended affective states. The mass-univariate analyses suggest that the increased activity in aIns for genuine pain as opposed to pretended pain properly reflects affect sharing. As aforementioned, the network of affective sharing and certain domain-general processes (e.g., salience detection and automatic emotion processing) overlap in aIns and aMCC (Zaki et al., 2016, for review). This indicates that indeed, part of the activation in these areas could be related to perceptual salience, which is why it has been widely debated as a potential confound of empathy and affect sharing models (Zaki et al., 2016, for review; Lamm et al., 2019, for review). However, when comparing genuine pain versus pretended pain, activity in these areas was not only found to be stronger in response to genuine pain, but the increased activation in aIns was also selectively correlated with ratings of self-oriented unpleasantness and was not correlated with either other-related painful expressions or painful feelings in terms of the regression analysis. That only aIns and not also aMCC shows such correlation may be explained by previous studies, according to which aIns is more specifically associated with affective representations, while the role of aMCC rather seems to evaluate and regulate emotions that arise due to empathy (Fan et al., 2011; Lamm et al., 2011; Jauniaux et al., 2019). Taken together, the activation and brain-behavior findings provide evidence that responses in aIns (and to a lesser extent also the aMCC) are not simply automatic responses triggered by perceptually salient events (otherwise the increased aIns activation should also be explained by other behavioral ratings in the sense of shared influence by domain-general effects). Rather, they seem to track the actual affective states of the other person, and thus the shared neural representation of that response (see Zhou et al., 2020, for similar recent conclusions based on multi-voxel pattern analyses). Our findings are also in line with the proposed model of Coll et al., 2017, which suggests that affect sharing is the consequence of emotion identification. More specifically, while part of the activation in the aIns and aMCC is indeed related to an (presumably earlier) automatic response, the added engagement of these areas once they have identified the pain as genuine shows that only in this condition, they then also engage in proper affect sharing. Ideally, one should be able to discern these processes in time, but neither the temporal resolution of our fMRI measurements nor the paradigm in which we always announced the conditions beforehand would have been sensitive enough to do so. Thus, future studies including complementary methods, such as EEG and MEG, and tailored experimental designs are needed to pinpoint the exact sequence of processes engaged in automatic affective responses vs. proper affect sharing. Beyond higher activation in affective nodes supporting (pain) empathy, increased activation was also found in rSMG. The inferior parietal lobule was shown to be generally engaged in selective attention, action observation, and imitating emotions (Bach et al., 2010; Pokorny et al., 2015; Gola, 2017; Hawco et al., 2017). Importantly, a specific role in affective rather than cognitive self-other distinction has been identified for rSMG (Silani et al., 2013; Steinbeis et al., 2015; Bukowski et al., 2020). Based on such findings, it has been proposed that the rSMG allows for a rapid switching between or the integration of self- and other-related representations, as two processes that may underpin the functional basis of successful self-other distinction (Lamm et al., 2016, for review). Theoretical models of empathy and related socio-affective responses suggest that such regulation is especially important to avoid so-called empathic over-arousal, which would shift the focus away from empathy and the other’s needs, toward taking care of one’s own personal distress (Batson et al., 1987, for review; Decety and Lamm, 2011, for review). Concerning the current findings, we thus propose that the higher rSMG engagement in the genuine pain condition reflects an increasing demand for self-other distinction imposed by the stronger shared negative affect experienced in this condition. Beyond these differences in the magnitude of rSMG activation, the DCM analysis demonstrated less inhibition on the aIns-to-rSMG connection for genuine pain compared to pretended pain. Note that our focus on the right aIns rather than bilateral aIns was because it is located in the same hemisphere as the right SMG. Various theoretical accounts suggest that areas such as the aIns and rSMG may play a key role in comparing self-related information with the sensory evidence (Decety and Lamm, 2007, for review; Seth, 2013, for review). According to recent theories on predictive processing (Clark, 2013, for review) and active inference (Friston, 2010, for review), the brain can be regarded as a “prediction machine”, in which the top-down signals pass over predictions and the bottom-up signals convey prediction errors across different levels of cortical hierarchies (Chen et al., 2009; Friston, 2010, for review; Bastos et al., 2015). It is suggested that these top-down predictions are mediated by inhibitory neural connections (Zhang et al., 2008; Bastos et al., 2015; Miska et al., 2018). Our findings align with such views, by suggesting that the inhibitory connection from aIns to rSMG can be explained as the predictive mismatch between the top-down predictions of self-related information (e.g., personal affect) and sensory inputs (e.g., pain facial expressions). This suppression of neural activity leads to an explaining away of incoming bottom-up prediction error. This is reflected by the absence of any condition-dependent modulatory effects on the rSMG to aIns connection, suggesting that the influence of the task conditions is sufficiently modeled by the predictions from aIns to rSMG. Therefore, the stronger inhibition for pretended pain, compared to genuine pain, could indicate a higher demand to overcome the mismatch between the visual inputs and the agent’s prior beliefs and contextual information about the situation (i.e., “this person looks like in pain, but I know he/she does not actually feel it”). We speculate that a dynamic interaction between sensory-driven and control processes is underlying the modulatory effect: when individuals realized after an initial sensory-driven response to the facial expression that it was not genuinely expressing pain, control, and appraisal processes led to a reappraisal of the triggered emotional response, and thus a dampening of the unpleasantness. The reduced inhibition in the genuine pain condition could moreover be a mechanism that explains the higher rSMG activation in this condition. Model comparison showed that the best model to explain the inhibitory effect with the behavioral ratings for both the genuine and pretended pain is the model without interactions between ratings. That is, if any behavioral rating contributed to the modulation of aIns to rSMG, the effect would be more likely coming from single ratings rather than their interactions. 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W3199860418 title "Author response: Neural dynamics between anterior insular cortex and right supramarginal gyrus dissociate genuine affect sharing from perceptual saliency of pretended pain" @default.
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