Inter-individual differences in heart rate variability are associated with inter-individual differences in mind-reading

In the present study, we investigated whether inter-individual differences in vagally-mediated cardiac activity (high frequency heart rate variability, HF-HRV) would be associated with inter-individual differences in mind-reading, a specific aspect of social cognition. To this end, we recorded resting state HF-HRV in 49 individuals before they completed the Reading the Mind in the Eyes Test, a test that required the identification of mental states on basis of subtle facial cues. As expected, inter-individual differences in HF-HRV were associated with inter-individual differences in mental state identification: Individuals with high HF-HRV were more accurate in the identification of positive but not negative states than individuals with low HF-HRV. Individuals with high HF-HRV may, thus, be more sensitive to positive states of others, which may increase the likelihood to detect cues that encourage approach and affiliative behavior in social contexts. Inter-individual differences in mental state identification may, thus, explain why individuals with high HF-HRV have been shown to be more successful in initiating and maintaining social relationships than individuals with low HF-HRV.

inter-individual differences in HRV would be associated with inter-individual differences regarding the identification of positive and negative states in the RMET.

Method
Participants. Before we recruited our participants, we performed a power analysis with G*Power 3 13 to determine the number of participants that we needed to detect meaningful associations between inter-individual differences in HRV and inter-individual differences in mental state identification. Previous studies investigating associations between inter-individual differences in HRV and inter-individual differences in social cognition revealed medium sized correlations (mean r = 0.35) between HRV and task performance 9,14 . These studies reported positive correlations indicating that task performance increased with increasing HRV. To detect a similar directed correlation (r = 0.35) with sufficient power (1-β = 80) and a conventional significance value (α = 0.05), 46 participants would be required at minimum. Taking potential drop-outs into account, we recruited 49 participants for our study from the university campus using flyers. In order to be included in the study, participants had to be aged between 18 and 35 years and to be native German speakers. Following established guidelines 15 , participants suffering from mental or physical health conditions and participants using other medication than oral contraceptives were excluded. Inclusion and exclusion of participants was determined on basis of an in-house interview assessing participants' physical and mental health as well as participants' utilization of physical and mental health care. The in-house interview was conducted by a trained graduate student in psychology (D.L.) under supervision of a clinical psychologist (A.L.), a clinical psychotherapist (A.O.H.) and a medical doctor (M.L.). Of the 49 participants that were included in the study, 7 did not provide valid data due to equipment dysfunction. Consequently, the data of 42 participants, 21 males and 21 females, were considered in the analyses (see Table 1).
All participants provided written-informed consent before taking part in the study and received 10 € after completion of the study. The study was approved by the ethics committee of the German Psychological Society (DGPs) and carried out in accordance with the Declaration of Helsinki.

Procedure.
After arriving at the laboratory, participants were asked to use the bathroom to control for the effects of bladder filling and gastric distension on HRV 16 . Participants were then seated in a comfortable chair in a sound-attenuated room (temperature: 22-23 °C). Following an acclimatization period of 5 min, a 5 min lasting electrocardiogram (ECG) was recorded with an Eindhoven Lead II set-up. In line with previous studies 9, 14 , participants were asked to breathe spontaneously and to keep their eyes open during the recording. Thereafter, participants performed the RMET 2 and completed the Brief Symptom Inventory 18 17 , a global measure of psychopathology.
Heart rate variability. An Eindhoven Lead II setup with two standard, electrolyte filled, Ag/AgCl electrodes (8 mm; Marquette Hellige, Freiburg, Germany) was used to record an ECG for 5 minutes. Online, the ECG signal was filtered with an 8 to 13 Hz band-pass filter, amplified with the factor 2000 and sampled at rate of 1000 Hz using a Coulbourn S75-01 system (Coulbourn Instruments, Whitehall, PA, USA). Offline, the ECG signal was down sampled to 400 Hz and further processed with ANSLAB 2.4 18 . Using ANSLAB 2.4, the ECG signal was visually inspected for artifacts (e.g., movement artifacts, physiological artifacts). Whenever necessary, the ECG signal was manually corrected via beat replacement instead of beat removal as recommend in recent guidelines 15 . Finally, Kubios HRV 2.2 19 was used to determine HRV following established guidelines 20 . Similarly as in previous studies 9, 14 , high frequency HRV (HF-HRV; 0.15-0.4 Hz) was estimated on basis of a Fast Fourier Transformation (Welch's periodogram: 256 s window with 50% overlap). In contrast to other indices of HRV, HF-HRV reflects parasympathetic rather than sympathetic induced changes in cardiac activity that are mediated by the vagus nerve 21 .

M (SD)
95% CI  24 . After determining the raw percentages of correctly identified positive, negative and neutral states, relative percentages of correctly identified positive and negative states were determined by subtracting the raw percentage of correctly identified neutral states from the raw percentages of correctly recognized positive and negative states, respectively. This subtraction method 25 , which is common in psychological studies [26][27][28][29] , was necessary to determine whether differences in mental state identification were specific for positive or negative as compared to neutral states. It also allowed the control of differences in mental state identification that were associated with the well-known ambiguity of neutral states 30-32 . Statistical Analysis. All statistical analyses were conducted using SPSS 22 (SPSS Inc., Chicago, IL, USA).
To investigate whether inter-individual differences in HRV would be associated with inter-individual differences in the identification of positive and negative states in the RMET, three sets of analyses were run. In each set of analyses, sex, age and psychopathology as assessed with the Brief Symptom Inventory 18 17 were used as covariates in partial correlations to control for factors that are known to affect HF-HRV 15 . In the first set of analyses, partial correlations were computed between HF-HRV and the difference between the percentage of correctly identified positive relative to neutral states and the percentage of correctly identified negative relative to neutral states. In the second set of analyses, partial correlations were computed between HF-HRV and the percentage of correctly identified positive relative to neutral states as well as between HF-HRV and the percentage of negative relative to neutral states. In the third set of analyses, the aforementioned partial correlations were compared with one another using Steiger's Z-Test 33 . Prior to all analyses, HF-HRV was log transformed (log 10) to account for deviations from normality distribution. The significance level for all analyses was set at p < 0.05 one-sided due to the hypothesis-driven nature of the respective analyses. To facilitate the interpretation of the respective findings, 95% confidence intervals (CI) and effect size measures (r, q) are reported 34 . Small effect sizes are indicated by r = 0.1 or q = 0.1, medium effect sizes are indicated by r = 0.3 or q = 0.3 and large effect sizes are indicated by r = 0.5 or q = 0.5.
Data availability. The data that was used for the aforementioned analyses are available from the corresponding author on reasonable request.

Results
The first set of analyses indicated that HF-HRV correlated with the difference between the relative percentages of correctly identified positive and negative states (r(37) = 0.295, p = 0.034; 95% CI [−0.01, 0.55]; see Fig. 1).
Although the size and direction of the correlation suggested that HF-HRV correlated more with the relative percentage of correctly identified positive than negative states, there was some ambiguity associated with the estimation of the corresponding correlation coefficient as indicated by the size of the respective confidence interval. However, the second set of analyses also indicated that HF-HRV correlated with the relative percentage of q = 0.565). Moreover, using raw instead of relative percentages of correctly identified states in the aforementioned analyses yielded a similar pattern of correlation coefficients (see Supplementary Results). Notably, the correlation coefficients describing the correlation between HF-HRV and the percentage of correctly identified positive states corresponded to medium or large effect sizes, whereas the correlation coefficients describing the correlation between HF-HRV and the percentage of correctly identified negative states corresponded to small effect sizes. HF-HRV was, thus, substantially and robustly correlated with the percentage of correctly identified positive states in a series of complementary analyses.

Discussion
In the present study, we investigated whether inter-individual differences in HRV would be associated with inter-individual differences regarding the identification of positive and negative states in the RMET. In accordance with our assumptions, we found an association between inter-individual differences in HRV and inter-individual differences in mental state identification during the processing of positive but not negative states. Individuals with high HRV were more accurate in the identification of positive but not negative states than individuals with low HRV, indicating an increased identification of positive states with increasing HRV. On basis of these findings, it may cautiously be speculated that inter-individual differences in HRV may be associated with inter-individual differences in mental state identification as well as with inter-individual differences in approach and avoidance behavior. Individuals with high HRV may be more sensitive to positive states of others' than individuals with low HRV. Individuals with high HRV may, thus, be more likely to detect cues that encourage approach and affiliation behavior, like, for example, a subtle smile, than individuals with low HRV. As a consequence, individuals with high HRV may be more likely to approach others than individuals with low HRV. Approaching others that are in a positive state may increase the likelihood of positive interactions, which may lead to a plethora of positive experiences in the approaching individual as well as in the approached individual. Accordingly, it has been shown that individuals with high HRV are more successful in initiating and maintaining social relationships than individuals with low HRV [10][11][12] , which has been found to be associated with feelings of well-being and connectedness 10,35,36 . In this respect it is interesting to note that individuals with low HRV have often been found among individuals with mental disorders that a characterized by marked deficits in social cognition and social interaction 7,8 . Inter-individual differences in HRV may, thus, account for inter-individual differences in social cognition and social behavior in healthy as well as in mentally-disordered individuals.
Regarding the neurobiological mechanisms mediating the association between inter-individual differences in HRV and inter-individual differences in mental state identification, it is noteworthy that a network of prefrontal and temporal brain regions has been shown to be engaged during mental state identification [37][38][39][40][41] . In particular, the prefrontal cortex and the amygdala have been reported to be crucial for the identification of mental states 38,41 . Accordingly, it has been found that individuals with functional and structural alterations in these brain regions show alterations in mental state identification 4,37,38,[41][42][43] , presumably because the interplay between the prefrontal cortex and the amygdala is disturbed in these individuals. Of note, inter-individual differences regarding functional and structural alterations in the prefrontal cortex and in the amygdala have been shown to be associated with inter-individual differences in HRV 44,45 . Moreover, inter-individual differences in HRV have even been considered to be a direct indicator of inter-individual differences regarding the interplay of the prefrontal cortex and the amygdala [46][47][48] . More precisely, an increase in HRV is thought to reflect an increase in prefrontal activity as well as an increase in prefrontal-amygdala connectivity. It may, thus, be possible that individuals with high HRV were more accurate in mental state identification than individuals with low HRV because they showed more prefrontal activity and prefrontal-amygdala connectivity during the processing of mental states.
Overall, our findings suggest that inter-individual differences in HRV may be associated with inter-individual differences in the identification of mental states, presumably due to inter-individual differences in prefrontal activity and prefrontal-amygdala connectivity during the processing of mental states. An increase in prefrontal activity and prefrontal-amygdala connectivity, which is reflected by an increase in HRV, may lead to an increased processing of positive as compared to negative states during encounters with others, thereby facilitating approach and affiliative behavior in social contexts. Recent theories regarding the neurobiological mechanisms mediating the association between inter-individual differences in HRV and inter-individual differences in social cognition and social interaction appear to be consistent with our assumptions [46][47][48] . Moreover, our assumptions are also consistent with recent findings regarding inter-individual differences in HRV and inter-individual differences in social cognition and social interaction 9,10,12,35,36 .
However, our assumptions should be treated with caution for several reasons. First and foremost, we employed a correlational study design that precludes any causal inferences about the direction of causality between inter-individual differences in HRV and inter-individual differences in mental state identification. Second, we assessed inter-individual differences in HRV and inter-individual differences in mental state identification but not inter-individual differences in approach and avoidance behavior. It is, thus, unclear whether inter-individual differences in HRV are in fact similarly associated with inter-individual differences in social behavior as with inter-individual differences in social cognition. Third, we did not assess inter-individual differences in prefrontal activity and prefrontal-amygdala connectivity, leaving open whether these differences in fact mediate the association between inter-individual differences in HRV and inter-individual differences in social cognition or social behavior. Fourth, our study sample consisted of healthy young adults, indicating that our assumptions regarding the association between inter-individual differences in HRV and inter-individual differences in social cognition and social behavior cannot be generalized to other study samples. Consequently, experimental rather than correlations studies are warranted that further test our assumptions, preferably by recording brain activity and cardiac activity in concert during tasks that affect both social cognition and social behavior in large samples of healthy and mentally-disordered individuals with different age ranges.