How do the emotions of others affect us? The human anterior cingulate cortex (ACC) responds while experiencing pain in the self and witnessing pain in others, but the underlying cellular mechanisms remain poorly understood. Here we show the rat ACC (area 24) contains neurons responding when a rat experiences pain as triggered by a laser and while witnessing another rat receive footshocks. Most of these neurons do not respond to a fear-conditioned sound (CS). Deactivating this region reduces freezing while witnessing footshocks to others but not while hearing the CS. A decoder trained on spike counts while witnessing footshocks to another rat can decode stimulus intensity both while witnessing pain in another and while experiencing the pain first-hand. Mirror-like neurons thus exist in the ACC that encode the pain of others in a code shared with first-hand pain experience. A smaller population of neurons responded to witnessing footshocks to others and while hearing the CS but not while experiencing laser-triggered pain. These differential responses suggest that the ACC may contain channels that map the distress of another animal onto a mosaic of pain- and fear-sensitive channels in the observer. More experiments are necessary to determine whether painfulness and fearfulness in particular or differences in arousal or salience are responsible for these differential responses.

We find that the rat ACC indeed contains emotional mirror neurons. Most of these show a preference for one of our first-hand experiences, with the majority responding more to Laser than CS. Spike decoding provides evidence for common coding across observed and experienced pain. Deactivating this region reduces freezing while witnessing footshocks but not while hearing the CS. Together, this suggests the rat ACC maps the experience of another animal onto a mosaic of pain- and fear-sensitive neurons in the observer, and this region is necessary for emotional contagion to trigger freezing.

In what follows, we first present the multiunit activity (MUA) from our silicon probes. MUA pools the spiking activity of thousands of neurons within ∼0.2 mm of each electrode contact [] and is particularly stable across days [], which is desirable given that our ShockObs, Laser, and CS conditions were recorded in sessions spread across 2 days. With this signal, we explore whether the rat ACC has locations showing activity that overlaps across observed and experienced emotions in a way that approximates the mesoscopic spatial scale of human fMRI. We then examine the activity of those single neurons that could be reliably isolated and tracked across multiple sessions to test whether overlap at the MUA level indeed reflects the presence of mirror neurons, and whether such mirror neurons are selective and instantiate a common code. Furthermore, we characterize behavioral responses during the time of MUA and single-cell responses to examine what might drive ACC responses. Finally, we will address a last question: (4) is ACC activity necessary to get contaged by the distress of another? We transiently deactivated the ACC using muscimol microinjections in a new group of animals while exposing them to HighShockObs and CS.

A number of specific methodological choices were made in our paradigm. We chose rats, because area 24 of the rat ACC (formally referred to as Cg1 and Cg2) is similar in cytoarchitecture and connectivity to the ACC implicated in pain empathy in humans [] and is activated by the distress of others [], and rats are large enough to facilitate chronic recordings in awake behaving animals. We pre-exposed the observers to footshocks 2–3 weeks before the main experiment, because having experienced electroshocks is critical in rats for showing robust signs of vicarious distress (freezing) while witnessing another animal receive electroshocks []. This suggests emotional contagion in this paradigm is mediated in part by sensory cues that the animal learns to decode through self-experience, with the sound and sight of the shock reactions playing significant roles []. We used footshocks to the demonstrator because this is the best characterized trigger of emotional contagion in rats. During pre-exposure, we paired the shocks with a tone to later compare responses to self-pain (Laser) and others’ pain (ShockObs) against the fear triggered by hearing this fear-conditioned tone (CS) played again. Because shocks to the implanted animal would induce artifacts in the recordings, to test responses to self-pain without compromising signal quality, instead of shocks we used a COheat laser calibrated to trigger a nocifensive reaction, a well-characterized pain-induction method [].

Here, we use a previously established model of emotional contagion in which an animal observes a conspecific experience painful electroshocks [] while we record multi- and single-unit activity using chronically implanted silicon probes in 17 rats. We explore whether some ACC locations and neurons are recruited during our social condition of shock observation (ShockObs; Figure 1 A; Video S1 ). We then record activity in two separate sessions while the observer himself experiences conditions thought to trigger pain (Laser) or fear (listening to a shock-conditioned sound, CS; Figure 1 B; Table 1 ). Following the tradition in the action-observation literature to classify mirror neurons based on their selectivity [], here we will define neurons broadly responding to the observation and experience of an emotion as emotional mirror neurons, and those that respond more narrowly to pain but not fear or fear but not pain as emotion-specific pain- or fear-mirror neurons. Here, we thus ask three questions: does the ACC contain (1) emotional mirror neurons, (2) emotion-specific mirror neurons, and (3) common coding? Thoroughly establishing specificity for an emotion would require testing neurons with a comprehensive battery of all emotions in the self and other, perfectly matched for salience and arousal. This will not be achieved in our experiment. Instead, we endeavor a step in that direction by contrasting the experience of two high-salience aversive states (pain and fear) in the self, and tentatively operationalize the terms pain- and fear-mirror neurons as those that distinguish between our pain (Laser) and fear (CS) conditions in the self.

(B) In the Laser condition, the implanted animal is alone, and a CO 2 laser (red beam) is shone on the rat’s paws or tail. Laser intensity is calibrated individually to trigger pain (HighLaser, thicker beam) or to be just below pain threshold (LowLaser, thinner beam). As a control condition, the laser is shone close to but without touching the animal (CtrlLaser). The LowShockObs and LowLaser conditions were added in the last 10/17 animals only.

(A) In the ShockObs condition, the silicon probe-implanted animal (obs) sits on a circular platform (bottom) while witnessing the demonstrator (demo; top) receive high- or low-intensity shocks (big and small lightning bolts). In the control condition (CtrlShockObs), the shock is delivered to a grid next to the demonstrator and does not trigger pain.

The selectivity of brain regions and neurons for a particular emotion is of particular interest. It has been argued that a vicarious response can only signal that someone else is in pain (as opposed to, for instance, in fear) if it has at least the following two features []. First, neural responses must be selective. If the same neuron responds to the experience of pain as much as to other salient emotions (e.g., fear), its firing cannot signal pain as different from these other emotions []. Second, the population of neurons should employ a common code to signal pain in the self and in others. If the brain reads out the pain of others from the vicarious ensemble activation of a subset of its own pain neurons, then a decoder able to decode pain levels of others from ensemble activity should be able to decode pain levels in the self from the same ensemble using the same rule []. Despite considerable efforts, fMRI experiments so far have failed to provide consistent evidence for either of these two criteria. The ACC is recruited by many salient stimuli beyond pain []. Studies show a decoder trained to distinguish pain from no-pain trials when observed in others can decode them when experienced in the self [] but decoders trained to distinguish different levels of pain in others fail to distinguish different levels of pain in the self []. That functional neuroimaging pools the activity of millions of neurons within each voxel may cause these failures.

Understanding how we share the affective states of others is important for understanding social interactions []. Neuroimaging shows that humans recruit their anterior cingulate cortex (ACC) both while experiencing pain and, vicariously, while witnessing pain in others []. This vicarious activity is stronger in more empathic individuals [] and reduced in psychopathy []. Reducing ACC activity using placebo or pharmacological analgesia alters empathy for pain []. These findings make the ACC a region of particular interest in the search for a neural mechanism of affect sharing. Some suggest these neuroimaging findings reflect the existence of mirror neurons, i.e., neurons responding during the experience of pain and the perception of other people’s pain []. That some ACC neurons respond to the observation and experience of pain is supported by reports of one such neuron in a human patient [] and by one report of neurons in the mouse ACC in which the immediate-early gene arc is more expressed following the experience of footshocks and witnessing another animal receive footshocks []. The functional properties of these neurons, however, remain unknown.

Finally, to test whether the ACC is necessary to trigger vicarious nocifensive behavior in the rat, we bilaterally injected muscimol or saline, into area 24 of two new small groups of observers ( Figure 5 A) and quantified their socially triggered freezing in response to a HighShockObs condition and to a CS playback in separate sessions. Histological reconstructions confirmed that our canulae were in area 24 and, considering an approximate radius of muscimol effect of 1 mm for the volume we injected (based on []; see red outline in Figure 5 A), our deactivations overlap with where we found pain-mirror neurons ( Figure S3 ). In line with previous observations in mice [], we found that although both groups showed increases in freezing in both HighShockObs and CS sessions relative to their baselines ( Figure 5 B; all one-tailed, paired t test, t > 5.6, all p < 0.001, with degrees of freedom [df] 5 and 7 for muscimol and saline, respectively), and freezing was similar in the saline group for HighShockObs and CS (t= 0.6, p = 0.55), the socially triggered freezing (Shock) was reduced in the muscimol compared to the saline group (t= 10.7, p < 0.001). This was not true in the non-social condition (CS; t= 0.17, p > 0.8). The necessity of the ACC for socially rather than non-socially triggered freezing was confirmed by a mixed ANOVA with 2 groups (Saline versus Muscimol) × 2 sessions (Shock versus CS) × 2 Epochs (baseline versus Shock or CS) that yielded a significant 3 way interaction (F= 17, p < 0.001).

(B) Whisker plot (median and quartiles) of the freezing levels during baseline (bl) or experimental periods (ShockObs or CS playback iconized as lightning bolts and loudspeakers) in the two groups of animals. p values refer to uncorrected, two-sample two-tailed t tests across the two groups. Note that the data from the ShockObs but not the CS condition are also used to explore how this affects the behavior of the demonstrator in [].

(A) Locations of the n = 6 muscimol (red) and n = 8 saline (black) injections on a sagittal view of the rat cingulate, based on the anatomical divisions in []. The red dashed line represents the likely spread of the muscimol based on a 1-mm radius [].

To further explore what stimulus may have triggered the neural response in the HighShockObs condition, we also computed spike-triggered average spectrograms, which revealed the broadband signal typical of pain squeaks to co-occur with moments of high spiking ( Figure 3 A6).

HighLaser triggered the well-described nocifensive reactions to a laser, including rapid paw retraction and licking and rapid turning around ( Figures S2 B and S2C; Video S1 ) [], but did not trigger squeaking similar to that in HighShockObs ( Figure S2 A). The response of pain-mirror neurons to HighShockObs and HighLaser ( Figures 3 A, 3B, and 3E) thus cannot be explained by hearing squeaking in both conditions, and must reflect a less trivial association of two physically different stimuli: one signaling the pain of another via exteroception and one signaling potential damage to the animal’s own body via nociceptive afferents. Behavioral responses to LowLaser were similar to those to CtrlLaser, and only included orienting, which could be explained by hearing the clicking of the button that delivered the laser ( Figures S2 B and S2C). Responses to the CS were characterized by freezing replacing the lying down and grooming that characterized baseline activity ( Figure S2 E). Freezing was not restricted to the actual playback of the CS but persisted during the interval between stimuli. Unlike the MUA response that decreased in the last compared to the first trials ( Figure S1 ), freezing increased slightly with time ( Figure S2 E).

What stimulus may have triggered the ACC response in the observers during the HighShock condition? Given that the shock was not delivered to the implanted animal, the stimulus must have originated from the demonstrator. Examining the behavior of the demonstrator during the 0- to 1-s interval of maximal ACC response revealed that jumping and squeaking were salient behaviors that were timed much as the ACC MUA response itself ( Figure 4 Video S1 ). This is visible in the spectrogram of the sound recording as a broadband signal, and in the behavior as a dramatic increase in jumping. The frequency of jumping and intensity of squeaking scaled with shock amplitude (HighShockObs > LowShockObs > CtrlShockObs; Figures 4 D and 4E) much like the MUA ( Figure 2 H) and spiking ( Figure 3 E) and temporarily interrupted the other behaviors (freezing and rearing). Although ultrasonic vocalizations around 22 kHz were also apparent following the administration of shocks, they were not specific to the 0- to 1-s window and thus cannot explain the timing of the ACC response. This makes the jumping and/or squeaking of the demonstrators seem the most likely trigger of the ACC response to HighShockObs. The observers’ actions in response to witnessing the shock included turning and walking toward the demonstrator (i.e., attention and proximity in Figures 4 D and 4E).

(F) Attention was quantified based on the angle α between observer head orientation and demonstrator with ± 30° considered maximal (=1) and 180 ± 30° considered minimal (=0). In the illustrated example, α = 70°, and the attention would be scored as 0.66.

(E) Same for High > LowShockObs for the 10 animals for which LowShockObs was tested. Tests are thresholded at p < 0.001, except for the n = 10 animal ethogram comparison in which no difference survives at p < 0.001.

(D) Random-effect comparison High > CtrlShockObs done by averaging all the trials per animal, and then using a matched-pair t test (n = 17 animals) pixel per pixel.

(A–C) Grand averaged shock-triggered audio spectrogram (top) and ethogram (bottom) obtained by averaging all trials and all animals for CtrlShockObs (A), LowShockObs (B) and HighShockObs (C). Note the broadband signal occurring in the 1 s post-stimulus. This includes the pain squeak and the rattling of the cage triggered by the jump. Peak sound-pressure levels during the squeaks in the HighShock condition were ∼87 dB.

A glmnet takes the spike counts from all 69 cells, and looks for a linear combination of spike counts from as few cells as possible to decode stimulus intensity. Examination of the regression weights evidenced that the 7 neurons the glmnet selected when trained on ShockObs did contain information about Laser intensity, whereas the 4 cells the glmnet selected when trained on Laser did not contain information about ShockObs intensity. This suggests an asymmetry in ACC representations, with those neurons providing the clearest ShockObs signals also carrying Laser intensity signals, but those providing the clearest Laser signals not necessarily also encoding ShockObs. To double check that within the mirror neurons, common coding operates in both directions, we replicated the analysis in both directions when feeding the glmnet only the 11 neurons for which we had 10 trials for the High, Low, and Ctrl conditions of ShockObs and Laser, and for which we had a significant response in both conditions (High > Ctrl). When training on ShockObs, Leave-one-out decoding of ShockObs worked as well as when considering all 69 cells (r = 0.6, t (28) = 4, p < 0.001), and decoding of Laser trials also worked as well as with all 69 cells (r = 0.67, t (28) = 4.9, p < 0.001). Training on Laser led to good decoding of leave-one-out laser trials (r = 0.52, t (28) = 3.2, p < 0.005) and to above-chance ShockObs decoding (r = 0.6, t (28) = 4, p < 0.001). This confirms that there is a population of neurons in the ACC that codes ShockObs and Laser in the same code but, considering the results from the 69 neurons, this common coding is not implemented in all neurons providing strong Laser intensity signals.

To explore the notion that the code the ACC uses to represent the distress of others is shared with that used to represent distress in the self—at least within a subpopulation of neurons—we used a decoding algorithm that can be applied to the spike count of the 69 neurons for which we have 10 trials of the High, Low, and Ctrl conditions for ShockObs and Laser. We chose to fit a generalized linear model via penalized maximum likelihood (glmnet). We first trained the algorithm to decode ShockObs spike counts, and found the resulting algorithm performs well on leave-one-out trials from the same condition ( Figure 3 D, green). To test common coding, the key question is: will the same algorithm decode Laser spike counts above chance without additional training? The answer is yes ( Figure 3 D, red), with a correlation between actual and decoded stimulus intensity of r = 0.66, t= 4.7, p < 0.001. This suggests that pain observation and pain experience do share a common code. An ANOVA across the 3 Laser conditions ( Figure 3 D, red; main effect of condition, F= 11, p < 0.001) showed that the two conditions that were calibrated not to induce nocifensive behavior (CtrlLaser and LowLaser) were decoded as of similar intensity (paired t test, p > 0.08), whereas the condition that triggered nocifensive behavior (HighLaser) was decoded as significantly more intense than either of the other two. Interestingly, training on Laser and testing on ShockObs trials did not lead to accurate cross-modal decoding: when the glmnet was trained on Laser spike counts, the leave-one-out decoding of the Laser trials worked well (r = 0.59, t= 3.88, p < 0.001); however, this decoder did not accurately decode the ShockObs trials (r = 0.13, t= 0.68, p = 0.49).

Histological reconstruction of the cells showed that our recordings were mainly in area 24 extending dorsally into M2 and anteriorly into caudal area 32 ( Figure S3 ). Exploring whether mirror cells with a particular property (pain or fear selectivity) are clustered, we tested whether their relative proportion differed across anterior-posterior coordinates or across the different cytoarchitectonic regions, but found no significant differences ( Figures S3 B and S3C). Mirror cells with different properties are intertwined with cells without mirror properties along the length of the explored region. If the spatial distribution of cells with these properties were similar in humans and rodents, the lack of specificity at the level of fMRI voxels [] may indeed have been the result of pooling the response of neurons with different selectivity within a voxel. To test whether selectivity is blurred at more macroscopic scales, we inspected whether the MUA (that pools activity over about 0.2 mm) shows less selectivity than the single neurons. Specifically, we used a χtest to compare the Venn diagrams obtained for MUA channels and single neurons ( Figure 2 F versus Figure 3 C). We found a trend toward a difference (χ(6) = 12.3, p = 0.0544), with selective mirror properties, i.e., fear- or pain-mirror neurons, indeed more frequent in single neurons (37% of channels but 49% of neurons) and unselective mirror neurons, i.e., responding to ShockObs, Laser, and CS, indeed more frequent in the MUA (12% of channels but 4% of cells). However, this trend did not reach significance, and the proportion of cells and channels showing mirror properties overall (be it selective or not) was very similar in both techniques (49% in MUA and 53% in single units). Future experiments may wish to explore local field potential (LFP) activity from the same electrodes to sample signals (1) from a larger area [] and (2) originating from events corresponding more closely to the blood-oxygen-level-dependent (BOLD) signal [] to further constrain the interpretation of fMRI experiments on emotional contagion.

A binomial distribution (59 trials at p = 0.05 each) indicates that finding 7 or more among the 59 socially responsive cells to respond to another condition is unexpected (p < 0.03), and finding 25 pain-selective mirror cells is extremely unlikely (p < 10 −14 ). We therefore found significant evidence for selective emotional mirror properties in the ACC, i.e., that neurons responding to the observation of pain also respond to the experience of pain (HighLaser) but not to other, non-painful salient stimuli (CS). That so few neurons respond to all three conditions (n = 3, below what could be expected by chance) points to the fact that the ACC may contain distinct “channels” of neurons separately mapping another animal’s response to a shock onto the witness’s representations of pain (n = 25) or fear (n = 11).

To explore selectivity, we asked how many of these emotional mirror neurons responded differentially to Laser and CS. Only 3 of these mirror cells responded to both HighLaser > CtrlLaser and CS > baseline, whereas all others responded to only one of the first-hand experiences. For the majority of the cells (n = 25), this was to HighLaser > CtrlLaser and not to CS > baseline. Figures 3 A and 3B illustrate two examples of such pain-mirror cells from different animals. In addition to a robust response to HighShockObs and HighLaser, cell A also shows a weaker transient response to CtrlLaser, a phenomenon also visible in the average MUA ( Figure 2 G) and which might reflect a response to the sound associated with laser delivery. To avoid this confound, we classify cells as pain responsive only if HighLaser > CtrlLaser. The selectivity of the ACC pain-mirror cells is further borne out by a direct comparison of spike counts for CS and HighLaser in the n = 25 + 3 cells that responded to HighShockObs > CtrlShockObs and HighLaser > CtrlLaser. For 23 of these 28 cells, HighLaser triggered significantly more spikes than the CS condition (Wilcoxon, p < 0.05). This provides the brain with the selectivity necessary to differentiate between states typically labeled as pain (HighLaser) and fear (CS) from the spike count of these neurons. Figure 3 E illustrates the average response pattern of these 23 selective pain-mirror neurons, 22 of which were also tested with the LowShockObs and LowLaser conditions. As for the MUA, we can see a nicely graded response for ShockObs, with High > Low > Ctrl in these neurons. The response to the Laser conditions shows a transient, low-latency response to Ctrl and Low conditions that could be triggered by the sound of the delivery system, but only the HighLaser response triggered a robust, slower, and longer-lasting response expected from nociceptive fibers. A smaller proportion of mirror neurons seemed selective for the fear-inducing CS, with 11 responding significantly to CS > Baseline but not HighLaser > CtrlLaser. Only 3 indiscriminately responded to both CS and HighLaser.

Particularly, 59 cells (81%) were socially triggered and responded to HighShockObs > CtrlShockObs. To identify emotional mirror neurons, we explored how many of these also responded to one of the conditions in which the observer himself experienced an emotion. This was true for 28/59 (47%) that also responded to HighLaser > CtrlLaser and for 14/59 (24%) that also responded to CS > Baseline. We thus found mirror properties at the single-cell level in 66% of the ShockObs-responsive neurons.

To determine whether the same cells responded in different conditions, we isolated single units from the recorded signals. Spike sorting identified 84 cells spread over 13 animals that could be isolated well and followed over all three experimental sessions. In the remaining 4 animals, low electrode impedance made single-cell isolation unreliable. Using the same analysis epochs as for the MUA, among these cells, we found 73 responsive cells that showed increased spike counts in at least one condition (HighShockObs > baseline, HighLaser > baseline, or CS > baseline, non-parametric Wilcoxon test, p < 0.05). Again, there was a significant number of cells that responded in more than one condition ( Figures 3 A–3C).

(D) Whisker plot (median and quartiles) of decoded stimulus intensity based on an algorithm trained on the ShockObs session, and used to decode either leave-one-out ShockObs (green) or Laser (red) spike counts. Dots represent outliers as standard with the function Boxplot in MATLAB (MathWorks, USA). Intensities were compared using one-tailed t tests corrected for multiple comparisons using fdr; ∗ p<0.05, ∗∗ p<0.01, ∗∗∗ p<0.001.

(B) The same as (A) for a second example cell from a different animal. (B6) The average spike shape in each session for cells shown in (A) and (B). For cell A, we also show the spike-triggered spectrogram in the ShockObs session (A6) evidencing the broadband signature of pain squeaks. The scale bar to the left of B3 applies to all spike-density functions.

In the last 10 animals, we added a lower intensity of ShockObs and Laser to our experimental design. The LowLaser intensity was chosen as a tighter control condition and involved a laser beam directed to the same body parts as in HighLaser but with an intensity reduced by 20%—an intensity at which no nocifensive behavior was apparent ( Figure S2 ). We suspect that this laser intensity induces a feeling of warmth in the body part but we have no behavioral readout to ascertain that any sensation was evoked, and this condition thus serves as an additional control condition. The LowShockObs condition was chosen to trigger nocifensive behavior in the demonstrator, but of lesser intensity than HighShockObs to examine whether the ACC response encodes the intensity of witnessed distress in a graded fashion. Figure 2 G shows the ACC responded vigorously to the Laser condition calibrated to produce nocifensive behavior, but not to the Laser condition calibrated not to produce such nocifensive behavior. The LowShockObs condition, on the other hand, did trigger noticeable but weaker responses both in the ACC ( Figure 2 H) and, as we will see later, in the behavior ( Figures 4 B and 4E).

The Venn diagram in Figure 2 F reveals overlap between channels responding when emotions are observed and experienced. To ensure that responses reflect another animal’s pain (HighShockObs) or the observer’s own pain (HighLaser) and not a conditioned response to the sound of the delivery system acquired during pre-exposure, for the ShockObs and Laser conditions, we compared the response in the experimental condition against their control (Ctrl) condition. Of the 313 responsive channels, 62% (193/313) showed a socially triggered response, i.e., HighShockObs > CtrlShockObs. Much like in the human ACC, many (71%) of the 193 channels that responded in that social condition also responded when first-hand affective experiences were triggered in the rat (HighLaser > CtrlLaser or CS > baseline) and will be labeled “mirror channels” hereafter. Most of these mirror channels showed selectivity in their response to the animal’s first-hand experience: of the 110 mirror channels responding to HighLaser > CtrlLaser, the majority (77) did not respond to the CS, and of the 60 mirror channels that responded to CS > baseline, 27 did not respond to HighLaser > CtrlLaser. Only 33 of the mirror channels responded to both first-hand conditions. Laser responses were more frequent than CS responses even among the first trials, where the effect of habituation was smaller than in later trials ( Figure S1 C). Figure S1 D finally shows that channels preferring the CS > Laser and those preferring the Laser > CS can co-exist in simultaneously recorded channels from individual animals.

With regard to our social condition, i.e., the ShockObs condition in which the other animal is the primary stimulus, many of the 313 responsive channels revealed robust responses to the HighShockObs, with a short latency and ∼1-s duration ( Figures 2 B, 2D, and 2H). With regard to the first-hand experiences, responses to the HighLaser, as described in the literature [], were strong, with a slower onset and lasting for several seconds ( Figures 2 A, 2C, and 2G). Responses to the CS were weaker ( Figures 2 E and 2G), and aligned to the beginning of the CS playback ( Figure S1 A). This was true despite the CS triggering robust defensive responses ( Figure S2 ). Comparing the response to the first and last 5 trials suggests some decreases in MUA magnitude with repeated presentation for CS and HighShockObs but not for HighLaser ( Figure S1 B). This impression is confirmed at the population level by paired t tests. Specifically, for each channel, we calculated the area under the z transformed average MUA of that channel in the experimental window, and compared this value across all 313 responsive channels in the first versus last 5 trials. This revealed a significant decrease (i.e., habituation) for HighShockObs, t= 5.1, p < 0.001, and CS, t= 3.2, p = 0.002, but not HighLaser t= −1.141, p = 0.25. For HighLaser, a Bayesian t test in JASP ( https://jasp-stats.org ) using a default one-tailed Cauchy prior provides very strong evidence for the null hypothesis of no habituation (BF= 32).

At the macroscopic scale, we first explored how many channels in the ACC show MUA that overlaps across conditions. We identified responsive channels as those that show MUA increases during at least one condition. We defined the baseline period as −1.2 to −0.2 s relative to any stimulus onset, and the stimulus response window as 0 to 1 s after stimulus onset for Shock and CS conditions. For the Laser condition, we used 0.3 to 1.3 s, because the laser depends on slower-conducting fibers []. Because stimulus-triggered deactivations are rare and more difficult to interpret, we focused on stimulus-triggered activations (i.e., stimulus responses larger than baseline), and thus used one-tailed statistics. We later also confirmed that deactivations were rare across the 425 channels we recorded over our 17 rats: only 2/425 showed deactivations following HighShockObs, 6/425 following HighLaser, and 3/425 following CS, each tested against their baseline using matched-pair, one-tailed t test at p < 0.01. In contrast, stimulus-triggered activations were observed across a majority of our channels: 313 (74%) showed increased MUA in at least one condition (matched-pair, one-tailed t test to identify stimulus-triggered activations, HighShockObs > Baseline, HighLaser > Baseline, or CS > Baseline, p < 0.01), and we then explored the time course of the MUA response to our conditions of interest ( Figure 2 ).

(H) Same as in (G) for the HighShockObs, CtrlShockObs, and LowShockObs conditions. The x axis for Laser and CS is shown over a longer period to illustrate the longer MUA response.

(G) Average of (A), (C), and (E) in all 313 channels, plus the LowLaser condition from the n = 194 channels acquired in the last 10/17 animals. The shading always represents the SEM.

(F) Venn diagram specifying the number of MUA channels that show specific combinations of significant responses. Each cell was tested at p < 0.01 using a t test comparing MUA in HighShockObs versus CtrlShockObs (green), HighLaser versus CtrlLaser (red), and CS versus baseline (black). Numbers indicate the number of channels that show significant activations in the respective test or intersection of tests.

(A–E) MUA of the 313 responsive MUA channels tested in the HighLaser (A), HighShockObs (B), CtrlLaser (C), CtrlShockObs (D), and CS (E) conditions. Each line shows the z transformed average MUA response of a channel. Z transformation was made relative to the mean and SD of the 3 s prior to each stimulus onset. Stimulus onset is shown as the dashed white line; the time axis for (A), (C), and (E) is shown in (G), and that for (B) and (D) is shown in (H). In (A) and (C), the channels are ordered in increasing average z score in the 0.3- to 1.3-s interval following stimulus onset based on the HighLaser condition, in (B) and (D) they are based on the HighShockObs, and in (E) they are based on CS.

Discussion

Our data show the rat ACC contains mirror-like multiunit and single unit activity with spiking increases during shock observation and first-hand experiences (Laser or CS). A decoding scheme trained to decode the intensity of another rat’s experience can decode the intensity of the rat’s own pain experience. Importantly, for the majority of multiunit channels and neurons, there was evidence for selectivity for the experience of laser-triggered pain over that of CS-triggered fear. Deactivating this region reduces socially triggered freezing without compromising freezing to non-social danger signals (CS).

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Keysers C. Repeated witnessing of conspecifics in pain: effects on emotional contagion. Although it is difficult to attribute human emotional labels to rodents [], CS is the prototypical procedure to trigger fear, whereas COheat lasers are a gold-standard method for inducing pain []. That many MUA channels and neurons responding to shock observation respond to the laser but not the CS suggests that shock observation may be predominantly mapped onto a representation of pain in the self. This dovetails with the fact that the behavioral signature most associated with the response, the squeak, is considered a highly specific pain signal []. The vicarious activation of ACC nociceptive neurons may then prime nocifensive behaviors in the observer, preparing it to cope with the same source of harm, including orienting toward the danger ( Figure 4 ) and elevated freezing ( Figure 5 B) often reported in such paradigms []. That an, albeit probably smaller, proportion of shock-responsive neurons preferentially respond to the CS suggests that the observer’s ACC may actually map the Shock observation onto a hybrid neural ensemble composed of a majority of pain and a minority of fear representations. That ACC deactivation compromised freezing to shock observation but not CS parallels the higher recruitment of the ACC to shock observation compared to CS.

An important question is to explore whether the ACC responses to shock observation are a cause for the observer’s emotional reaction to the distress of the other or rather a downstream representation of the observer’s reaction. That deactivation of the ACC impairs vicarious freezing suggests that it plays a causal role. Future experiments that selectively modulate activity in mirror neurons within the ACC rather than the ACC more generally will be key to addressing this question.

10 Zaki J.

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Keysers C.

Gazzola V. The anatomy of suffering: understanding the relationship between nociceptive and empathic pain. 10 Zaki J.

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Gazzola V. The anatomy of suffering: understanding the relationship between nociceptive and empathic pain. 23 Vogt B. Cingulate cortex and pain architecture. 37 Tovote P.

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Lüthi A. Neuronal circuits for fear and anxiety. 38 Giustino T.F.

Maren S. The role of the medial prefrontal cortex in the conditioning and extinction of fear. Our study has limitations that qualify our conclusions and invite future experiments. First, establishing that a neuron is selective for pain requires excluding that it responds to any other non-painful but equally salient emotion []. Showing that a number of our neurons respond to ShockObs and Laser but not, or less, to CS is but a first step in that direction. Future experiments in which a richer set of physiological parameters are collected (e.g., startle potentiation, heart-rate variability, pupil diameter) while animals are submitted to a wider range of stimuli, including non-painful conditions as salient as the painful conditions, are needed to gain a finer-grained understanding of the dimensions encoded in ACC mirror neurons []. That the CS and ShockObs conditions triggered similar levels of freezing in the muscimol experiment suggests they are matched along at least one indicator of negative affective relevance. Another relevant dimension meriting further investigation is the imminence of a stimulus: HighLaser represents an immediate nociceptive stimulus, whereas CS announces the likely arrival of a painful event in the future. This difference in imminence is perhaps intrinsic to the difference between pain and fear, but varying this dimension systematically could shed further light on the selectivity of ACC neurons. Contrasting our findings in area 24 (and, to a lesser extent, M2 and caudal area 32) with recordings and lesions in area 25 and more anterior parts of area 32 (also known as infralimbic and prelimbic [] and to be involved in fear conditioning to tones []) would sharpen our understanding of how selectivity for pain and fear coexist in the medial prefrontal cortex.

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Roelfsema P.R. Chronic multiunit recordings in behaving animals: advantages and limitations. 29 Stark E.

Abeles M. Predicting movement from multiunit activity. Second, the CS condition was collected a day after the ShockObs and Laser conditions for the animals to recover from the previous negative effect. Single cells could thus have drifted away from the electrodes overnight, creating a bias against the CS condition. This should apply less to the MUA data, known to be stable over time [], and that muscimol impaired freezing to ShockObs but not CS converges to suggest that losing cells over time is unlikely to entirely explain the scarcity of CS effects across all our measures.

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Cerliani L.

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Keysers C. Experience modulates vicarious freezing in rats: a model for empathy. 15 Carrillo M.

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Keysers C. Repeated witnessing of conspecifics in pain: effects on emotional contagion. 35 Han Y.

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et al. Cingulate dependent social risk assessment in rats. 14 Atsak P.

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Keysers C. Experience modulates vicarious freezing in rats: a model for empathy. 15 Carrillo M.

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Bruls R.

Han Y.

Heinemans M.

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Keysers C. Repeated witnessing of conspecifics in pain: effects on emotional contagion. 35 Han Y.

Bruls R.

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Jelinek N.

Heinemans M.

Bassez I.

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Pruis I.

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et al. Cingulate dependent social risk assessment in rats. 39 Herry C.

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Lüthi A. Switching on and off fear by distinct neuronal circuits. 35 Han Y.

Bruls R.

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Pentaraki V.

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Heinemans M.

Bassez I.

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et al. Cingulate dependent social risk assessment in rats. 14 Atsak P.

Orre M.

Bakker P.

Cerliani L.

Roozendaal B.

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Keysers C. Experience modulates vicarious freezing in rats: a model for empathy. 40 Keysers C.

Gazzola V. Hebbian learning and predictive mirror neurons for actions, sensations and emotions. 41 Keysers C.

Perrett D.I. Demystifying social cognition: a Hebbian perspective. 42 Church R.M. Emotional reactions of rats to the pain of others. Third, our animals showed unusually low freezing during the electrophysiological ShockObs condition compared to previous behavioral experiments and the present muscimol study []. Traditionally, we tested animals in the week following pre-exposure, in a two-compartment cage resembling that during pre-exposure and without tethering []. For electrophysiology, we introduced 2 additional weeks of habituation, placed the observer on a plastic cylinder to avoid electrical noise, and tethered the animal. This made the electrophysiological context more distinct from the initial pre-exposure and thereby reduced contextual danger cues. Such changes in context are known to reduce freezing in fear conditioning [], and we believe this to have reduced the propensity to freeze. That the ACC nevertheless encoded ShockObs vigorously is notable, but experiments that quantify ACC responses as a function of the remoteness (in time and contextual similarity) of pre-exposure will shed light onto what the ACC represents: if ACC responses decrease with increasing safety cues, they are more likely to represent the observer’s personal risk assessment []. If responses remain constant, they are more likely to represent the distress of the other. Varying the similarity between the noxious stimuli used during pre-exposure and testing would illuminate a similar question from a different angle: what exactly does the observer learn during pre-exposure? Would pre-exposure with Laser suffice to make the observer sensitive to seeing another animal experience footshocks? Must there be a tighter match between the bodily reactions produced during pre-exposure and observation? In a Hebbian learning model, we predict that to hear himself jump and squeak while in pain during pre-exposure is what allows pain representations in the cingulate to bind with sensory synaptic input representing the sound of squeaking and cage rattling []. These connections later recruit ACC neurons while hearing the demonstrator produce these sounds, a notion similar to auto-conditioning in the seminal work of Church []. If this prediction is true, Laser, which did not trigger squeaking, would not be as effective a pre-exposure stimulus for later ShockObs.

35 Han Y.

Bruls R.

Thomas R.M.

Pentaraki V.

Jelinek N.

Heinemans M.

Bassez I.

Verschooren S.

Pruis I.

van Lierde T.

et al. Cingulate dependent social risk assessment in rats. 1 de Waal F.B.M.

Preston S.D. Mammalian empathy: behavioural manifestations and neural basis. 43 Greene J.T. Altruistic behavior in the albino rat. 44 Ben-Ami Bartal I.

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Mason P. Empathy and pro-social behavior in rats. Finally, there is an important distinction between emotional contagion and empathy. Recruiting neurons involved in one’s own experience of pain while witnessing the pain of others could suffice to trigger emotional contagion—feeling the distress that the observed animal feels—and can prepare the observer to face the danger that afflicted the demonstrator []. This, however, does not provide evidence that the observer understands that this vicarious pain is experienced by a specific other animal—as empathy proper would require. This distinction is particularly relevant in relation to observations of pro-social behavior and targeted helping in rodents [], and invites future experiments that explore whether deactivating ACC mirror neurons influence the willingness of a rat to help another.