# Autonomic modulations to cardiac dynamics in response to affective touch: Differences between social touch and self-touch

Diego Candia-rivera, Rebecca Boehme, Paula Salamone

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Diego Candia-rivera, Rebecca Boehme, Paula Salamone. Autonomic modulations to cardiac dynamics in response to affective touch: Differences between social touch and self-touch. IEEE Transactions on Affective Computing, 2025, 16 (3), pp.1-11. 10.1109/TAFFC.2025.3548778. hal-04984753

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# Autonomic Modulations to Cardiac Dynamics in Response to Affective Touch: Differences Between Social Touch and Self-Touch

Diego Candia-Rivera ID, Rebecca Boehme ID, and Paula C. Salamone ID

**Abstract**—The autonomic nervous system plays a vital role in self-regulation and responding to environmental demands. Autonomic dynamics have been hypothesized to be involved in perceptual awareness and establishment and maintenance of the sense of a bodily self at a neural level. We hypothesized that the autonomic activity measured from cardiac dynamics could differentiate between social touch and self-touch. In our study, we used a newly developed method to analyze the temporal dynamics of cardiac sympathetic and parasympathetic activities during an ecologically valid affective touch experiment. We revealed that different types of touch conditions—social-touch, self-touch, and a control object-touch—resulted in a decrease in sympathetic activity. This decrease was more pronounced during social touch, as compared to the other conditions. Moreover, we quantified an increase in parasympathetic activity specifically during social touch, further distinguishing it from self-touch. Importantly, by combining the sympathetic and parasympathetic indices, we successfully differentiated social touch from the other experimental conditions, indicating that social touch exhibited the most substantial changes in cardiac autonomic indices. These findings may have important clinical implications as they provide insights into the neurophysiology of touch, relevant for aberrant affective touch processing in specific psychiatric disorders and for the comprehension of nociceptive touch.

**Index Terms**—Affective touch, heart-rate variability, social touch, self-awareness, brain-heart interaction.

## I. INTRODUCTION

EMOTION and stress regulation are key aspects of physiological stability. The intricate physiological mechanisms underlying emotions and their regulation not only affects

Received 25 March 2024; revised 22 December 2024; accepted 24 February 2025. Date of publication 6 March 2025; date of current version 15 September 2025. This work was supported in part by the Fredrik och Ingrid Thurings stiftelse, in part by the Lions Forskningsfond, and in part by the Swedish Research Council under Grant 2019-01873. Recommended for acceptance by G. Fortino. (Rebecca Boehme and Paula C. Salamone contributed equally to this work.) (Corresponding author: Diego Candia-Rivera.)

This work involved human subjects or animals in its research. Approval of all ethical and experimental procedures and protocols was granted by the Swedish National Ethics Board under Application No. DNR 2022-02110-01, and performed in line with the Declaration of Helsinki.

Diego Candia-Rivera is with the Paris Brain Institute (ICM), CNRS UMR7225, INRIA Paris, INSERM U1127, AP-HP Hôpital Pitié Salpêtrière, Sorbonne Université, 75013 Paris, France (e-mail: diego.candia.r@ug.uchile.cl).

Rebecca Boehme and Paula C. Salamone are with the Center for Social and Affective Neuroscience, Linköping University Hospital, 581 83 Linköping, Sweden.

This article has supplementary downloadable material available at https://doi.org/10.1109/TAFFC.2025.3548778, provided by the authors.

Digital Object Identifier 10.1109/TAFFC.2025.3548778

mental health but also shapes our affective processing and social interactions [1]. Two key mechanisms closely related to this regulation are allostasis and interoception. Allostasis refers to the process of anticipating stressors and achieving stability through physiological adaptations, while interoception refers to the communication within physiological systems, which can be assessed through the body's internal sensations [2]. The dynamic interplay between allostasis and interoception plays a crucial role in fostering bidirectional communication between our internal sensations and the body's adaptive responses [3]. In these complex physiological regulation mechanisms, the role of touch emerges as a fundamental factor, as it conveys information from the skin to the central nervous system mediated by the peripheral nervous system [2]. These interoceptive mechanisms may play a significant role in the emotional impact of various forms of touch, and ultimately influencing allostatic processes [4]. Here we refer to affective touch as the skin-to-skin touch performed at an optimal stroking speed that activates CT-fibers, resulting in a pleasant sensation [5], [6].

In broader terms, the impact of somatosensory stimuli on autonomic dynamics has been superficially explored [7], primarily through the assessment of heart rate variability (HRV). However, this exploration lacks a time-resolved approach which may allow for a comprehensive analysis of the physiological dynamics. HRV serves as a convenient proxy for analyzing autonomic dynamics, given that sympathetic and parasympathetic activations are reflected in alterations in noradrenergic and cholinergic mechanisms. These biochemical changes are subsequently reflected in the contraction rate of pacemaker cells [8]. For instance, thermoception can lead to dynamic changes in HRV from an increased sympathetic activity and decreased parasympathetic activity [9], as similarly occurs with nociception [10]. However, the relationship between touch and HRV might be more complex when there is the involvement of an affective component. At skin level, Aβ afferents mediate discriminative touch, while CT afferents contribute to affective touch, responding preferentially to caress-like stimuli—light pressure, skin temperature, and slow stroking [11], [12], [13]. While Aβ afferent-mediated signals are processed along the main somatosensory processing pathways, CTs are known to additionally activate the insular cortex [14]—a brain area suggested to be responsible for the perception of “how we feel” [15]. So far, evidence indicates that affective touch can increase HRV,
suggesting a parasympathetic modulation to cardiac dynamics and a sympathetic inhibition [16], [17], whereas sympathetic activations rather occur under the conditions of thermoception and nociception [18], [19]. Mental health conditions often co-occur with autonomic disruptions, such as those reported in major depressive disorder [20] or conditions involving dissociative symptoms [21]. These conditions are also linked to impairment in affective touch processing [22], [23]. Understanding the dynamics of autonomic function and affective touch could provide deeper insights into the physiological disruptions underlying mental health disorders.

The distinct contribution of interoceptive inputs to cognition has been hypothesized across various contexts. These contexts encompass regulatory and adaptive processes including fight-or-flight responses or social interactions [24], [25], as well as their potential role in fostering the essential first-person perspective required for perceptual awareness and self-other distinctions [26]. To enhance our understanding of the peripheral dynamics triggered by affective touch, we conducted an experiment involving social and self-produced touch. We aimed to examine the extent to which cardiac sympathetic and parasympathetic activities are differentially modulated under social and self-touch. To our best knowledge, the differences in the autonomic modulations to cardiac dynamics between social and self-touch have not yet been studied. This research gap is crucial for understanding the complex neurophysiology of affective touch, as the skin-brain axis directly connects with the autonomic nervous system influencing cardiac dynamics, but also endocrine and inflammatory regulation [27], which can influence social interactions [28]. The exact mechanisms underlying pleasant skin sensations are not fully understood yet, but different types of CT fibers are thought to respond depending on the type of touch [29]. These responses likely activate parallel pathways: a sympathetic inhibitory pathway projecting through the dorsal root ganglion to supraspinal structures [30] and a parasympathetic excitatory pathway traveling via the vagus nerve to the jugular ganglion [31], [32].

In this study, healthy adults underwent an experimental protocol involving three modalities of affective touch: social touch, self-touch, and object-mediated touch as a control measure [33]. Our first goal was to examine cardiac sympathetic and parasympathetic activities under our three touch conditions, as affective touch is expected to dynamically deactivate the sympathetic system and activate the parasympathetic system [34]. Our second goal was to explore differences between self-touch and social touch. We hypothesized distinct cardiac responses to self versus social touch, as self-other distinction is suggested to involve integrating interoceptive inputs [35], [36], [37]. Specifically, we anticipated that social touch would produce stronger effects than self or object touch, given reports linking social touch to higher HRV and lower heart rates [32], [38], [39], [40]. However, the majority of HRV measures lack specificity in identifying their sympathetic or parasympathetic origin, as they overlook the strong interdependence between HRV and heart rate [41]. To address this limitation, we employed a recently developed method that offers a robust, time-resolved estimation of cardiac sympathetic and parasympathetic indices

from RR time series, which incorporates parallel changes in both HRV and heart rate into the estimations [42]. This approach enabled us to dynamically quantify the cardiac sympathetic and parasympathetic changes at different latencies with respect to the touch onset, and the differences in these dynamics with respect to the different types of touch.

## II. MATERIALS AND METHODS

### A. Participants and Experimental Protocol

A total of 28 healthy adult volunteers participated in this study (16 females, mean age 29.04 years, SD = 5.16). Participants were required to be fluent in English, and had no current cardiac, sensory/motor, or affective/psychiatric conditions. Data acquisition was performed at the Center for Social and Affective Neuroscience (CSAN), Linköping, Sweden. All participants provided informed consent in accordance with the Helsinki Declaration and were compensated for their participation. The study was approved by the national ethics board (DNR 2022-02110-01).

To minimize confounds related to participants' cardiovascular status, they were instructed to avoid stimulants such as coffee, energy drinks, and smoking for at least 8 hours before the study. They were also encouraged to ensure they had a good night's sleep. This information was shared during the initial contact and reiterated with a reminder the day before the study. Participants were informed that if they did not meet these requirements, the session could be rescheduled without any issues.

The participants engaged in an established experimental task known as the self-other-touch paradigm [33] with modified timing to optimize data for the current research question. The task employed a randomized block design and encompassed three distinct conditions: social touch (skin-to-skin stroke on the left forearm by the female experimenter), self-touch (stroking of the participant's own left forearm), and object-touch (participant stroking a pillow). Before the task, participants were instructed to perform touch with light pressure and a slow pace (approximately 8 cm/s), meeting the criteria for affective touch [5], [6], [43]. Each condition lasted 180 seconds and was preceded by a resting period of approximately 60 seconds. For the self and object-touch condition, participants were instructed to gently stroke their left arm, mimicking the touch they would use when interacting with someone they like, using their right hand.

Instructions for each block of the task were presented on a screen. The instructions, provided in English, were displayed including the following prompts: "Social touch: Your arm will be touched by the experimenter", "Self-touch: Please stroke your arm"; "Object-touch: Please stroke the object"; Participants either received stimulation or performed the stimulation themselves, continuing for a duration of 180 seconds. The female experimenter (P.C.S), stationed adjacent to the participant replicated the participant's movements in the same area of the forearm as closely as possible. Participants performed the task with their eyes closed, therefore the experimenter informed them when the condition was over.

The ECG recordings were obtained using BIOPAC B-Alert. Two electrodes placed below the clavicles, corresponding to a modified Lead I bipolar configuration (right and left
infraclavicular placement). Recordings were performed with Acqknowledge software (Biopac) at 2000 Hz.

## B. ECG Preprocessing

Data analysis was performed using MATLAB 2022b. The ECG data were bandpass filtered with a Butterworth filter of order 4 between 0.5 and 45 Hz. The R-peaks from the ECG were identified using an automatized process, followed by an automated inspection of misdetections and manual correction if required. The procedure was based on Pan-Tompkins algorithm for detecting R-peaks [44]. For the correction of misdetection, all the detected peaks were visually inspected over the original ECG, along with the marks on ectopic heartbeats and the inter-beat intervals histogram.

## C. Computation of Cardiac Sympathetic and Parasympathetic Indices

Estimating sympathetic and parasympathetic activity from HRV poses a notable challenge due to the intricate interplay of these autonomic branches within the HRV series. HRV is traditionally studied in the frequency domain, i.e., by identifying and quantifying the amount of slow (<0.15 Hz) and fast (0.15–0.4 Hz) fluctuations in HRV on time [45]. However, the frequency domain approach has been challenged due to the difficulty of associating specific oscillations to either sympathetic or parasympathetic modulations and for not accounting for individual differences in these oscillations [46]. Therefore, untangling these sympathetic and parasympathetic contributions to HRV has prompted the development of alternatives to the frequency domain methods [47], [48].

In this study, a new approach based on Poincaré plot was used to estimate the sympathetic and parasympathetic modulations to HRV [42]. Poincaré plot is a method that depicts the fluctuations on the duration of consecutive inter beat intervals (IBI), accounting for potential nonlinearities in these fluctuations [49], as shown in Fig. 1. The Poincaré plot geometry has been used to characterize changes on HRV by quantifying the ratios of the ellipse formed from consecutive changes in IBIs, representing the short- and long-term fluctuations of HRV, respectively [50]. Importantly, this approach allows to quantify slow and fast fluctuations of HRV at an individual level, without relying on fixed frequency band delimitations. Notably, this method eliminates the need to resample the IBI series, demeaning or detrending, unlike traditional HRV approaches, such as spectral estimations.

We quantified three distinct features from Poincaré plot: First, the distance of the center of the ellipse to the origin cardiac cycle duration, (CCD), which represents the changes in the baseline heart rate that is increased by sympathetic and decreased by parasympathetic modulations. Second, the minor ratio of the ellipse (SD₁), which represents the fast fluctuations of HRV that are triggered by parasympathetic modulations. Third, the major ratio of the ellipse (SD₂), which represents the slow fluctuations of HRV that are triggered by sympathetic modulations [42], [50].

The time-varying fluctuations of the distance to the origin and the ellipse ratios were computed with a sliding-time window, as

<figure><img src="image_2.png" /><figcaption>Fig. 1. Example of a Poincaré plot. Inter beat intervals (IBIs) are plotted with respect to the next IBI duration. The ellipsoid formed contains three features extracted: the minor ratio (SD₁), the major ratio (SD₂), and the distance to the origin (CCD). CCD represents changes in baseline cardiac cycle duration that decreases by sympathetic and increases by parasympathetic modulations. SD₁ represents the fast fluctuations of HRV that are triggered by parasympathetic modulations. SD₂ represents the slow fluctuations of HRV that are triggered by sympathetic modulations.</figcaption></figure>

shown in (1), (2) and (3):

$$CCD(t) = \sqrt{mean(IBI_{i,...,n-1})^2 + mean(IBI_{i+1,...,n})^2} \quad (1)$$

$$SD_1(t) = \sqrt{\lambda_{\Omega_t}(1, 1)} \quad (2)$$

$$SD_2(t) = \sqrt{\lambda_{\Omega_t}(2, 2)} \quad (3)$$

where $\lambda_{\Omega_t}$ is the matrix with the eigenvalues of the covariance matrix of $IBI_{i,...,n-1}$ and $IBI_{i+1,...,n}$, with $\Omega_t: t - T \le t_i \le t$, and n is the length of IBI in the time window $\Omega_t$.

The distance to the origin $CCD_0$ and ellipse ratios $SD_{01}$ and $SD_{02}$ for the whole experimental duration are computed to re-center the time-resolved estimations of CCD, SD₁ and SD₂. Then, the Cardiac Parasympathetic Index (CPI) and the Cardiac Sympathetic Index (CSI), are computed as follows:

$$D(t) = \overline{CCD}(t) + CCD_0 \quad (4)$$

$$CPI(t) = k_p \cdot (\overline{SD_1}(t) + SD_{01}) + \tilde{D}(t) \quad (5)$$

$$CSI(t) = k_s \cdot (\overline{SD_2}(t) + SD_{02}) + D(t) \quad (6)$$

where $\overline{SD}_x$ is the demeaned $SD_x$ and $\tilde{D}$ is the flipped $D$ with respect the mean. The coefficients $k_p$ and $k_s$ define the weight of the fast and slow HRV oscillations, with respect the changes in the baseline heart rate. The values were defined as $k_p = 10$ and $k_s = 1$, as recommended in the original study [42]. Note that the weights of heart rate and HRV components represent the known effects of autonomic modulations on cardiac dynamics, where sympathetic modulations primarily influence baseline heart rate [51], but also slow HRV changes [52], and parasympathetic modulations are mainly associated to fast HRV changes [52].
<figure><img src="image_3.png" /><figcaption>Fig. 2. Time course of the changes in cardiac sympathetic (CSI) and parasympathetic indices (CPI) in response to social-touch, self-touch, object-touch (n=28). Time course represents the group median and shaded areas the median absolute deviation (MAD) of CSI and CPI.</figcaption></figure>

For a comprehensive description of the model, see [42]. The method was previously validated in different standard conditions where cardiac sympathetic and parasympathetic activities are modulated, including tilt-table and cold-pressor tests. The software can be gathered from https://github.com/diegocandiar/robust_hrv.

## D. Statistical Analysis

Within-subject statistical analyses between the three touch conditions were performed through nonparametric Wilcoxon signed-rank tests. The statistical testing was performed per autonomic index, in which the inputs correspond to averaged CSI or CPI in the intervals 0–60, 60–120 and 120–180 s during the different affective touch modalities. We chose 60-second intervals to capture oscillations at the lower bound of the low-frequency range, which can last up to 25 seconds [52]. In HRV studies, analyzing time windows shorter than 5 minutes is referred to as ultra-short HRV analysis. This approach has been shown to effectively capture short-term HRV changes in controlled settings [53]. Specifically, CSI and CPI have proven capable of detecting the expected changes under standard autonomic elicitation conditions, typically analyzed using longer time windows [42].

Further comparisons were performed between the experimental conditions, using IBI and frequency-domain features (LF and HF) [54] (see Supplementary Material, Table S1).

The significance level of p-values was corrected in accordance with the Bonferroni rule for the three possible paired comparisons, with an uncorrected statistical significance set to $\alpha = 0.05$. The samples were described group-wise using the medians $\pm$ median absolute deviation (MAD), where $MAD(X) = Median(|X - Median(X)|)$. The time-resolved autonomic indices were z-score normalized on time for the whole experimental recording, prior segmentation for statistical analyses.

Additionally, a multivariate analysis was included for ranking the contributions of cardiac autonomic dynamics at different latencies for the distinction of the different types of touch included in this study. The ranking computation was based on Minimum Redundancy Maximum Relevance (MRMR) scores

[55], in which a higher score indicates a higher relevance distinguishing between classes.

## III. RESULTS

We examined cardiac sympathetic and parasympathetic indices obtained from RR time series in a study involving healthy individuals undergoing an affective touch protocol. The time-resolved estimation of autonomic indices for each condition is presented in Fig. 2. In all three conditions, cardiac sympathetic activity decreased, and parasympathetic activity increased during the initial time window (0–60 s). As shown descriptively in Fig. 2 social vs self panel, notable group-level changes became more apparent within about 20 s.

We conducted a comparison of the three touch conditions at three specific intervals: 0–60 s, 60–120 s, and 120–180 s, to further describe the autonomic dynamics that allow the affective touch distinctions on time. Significant differences in sympathetic indices were observed in all three intervals when comparing social touch to self-touch and social touch to object touch (Fig. 3, Table I). However, there were no significant differences at any interval when comparing self-touch to object touch. Using a linear mixed model, we also found no effect related to the participants’ self-reported sex or the order in which each touch modality occurred (see Supplementary material, Table S2).

Similar to the sympathetic indices, we found significant changes in the cardiac parasympathetic indices across all three intervals when comparing social touch to self-touch and social touch to object touch. However, there were no significant differences at any interval when comparing self-touch to object touch (see Fig. 3, Table I). We found that cardiac sympathetic activity was consistently reduced under social touch, whereas cardiac parasympathetic activity tended to be higher in that condition. Notably, the differentiation between social touch and object touch became more pronounced in the later stages of the protocol.

Expanding upon these findings, we aimed to assess the distinguishability of the experimental conditions in a multivariate space. We conducted a feature ranking analysis using the MRMR algorithm to determine which sympathetic
<figure><img src="image_4.png" /><figcaption>Fig. 3. Paired comparisons of cardiac sympathetic and parasympathetic indices between social-touch, self-touch, object-touch (n=28). Each data point corresponds to one participant at the defined time interval. The comparisons were performed on 1-minute averages in the intervals 0-60, 60-120 and 120-180s. P-values correspond to the Wilcoxon signed-rank test (statistical tests shown in Table I). Significance is defined by the Bonferroni rule at =0.0166. A.U.: Arbitrary Units; n.s.: non-significant; \*p<0.0166; \*\*p<0.001; \*\*\*p<0.0001.</figcaption></figure>

or parasympathetic indices, and at what latency, were more effective in distinguishing the various types of touch encompassed within this study (Table II). The sympathetic (intervals 0–60 s and 60–120 s) and the later parasympathetic (120–180 s interval) modulations appeared among the three most relevant features in distinguishing between all possible paired comparisons. Based on the feature ranking for the distinctions of the three types of touch, we focused on the averaged sympathetic and parasympathetic indices within the aforementioned intervals to construct Fig. 4. As depicted, cardiac sympathetic and parasympathetic indices provide complementary information to distinguish between the touch conditions, with a more robust separability between social touch and both self and other touch. In this sense, social touch provides a greater modulation of

<table><caption>TABLE I
PAIRED TESTS BETWEEN SELF, SOCIAL, AND OBJECT TOUCH</caption><thead><tr><th colspan="4">Cardiac Sympathetic Index</th></tr><tr><th></th><th>Self vs Social</th><th>Social vs Object</th><th>Self vs Object</th></tr></thead><tbody><tr><td>0–60 s</td><td>Z=4.3493,<br>p&lt;0.0001</td><td>Z=3.3929,<br>p=0.0007</td><td>Z=1.7762,<br>p=0.0757</td></tr><tr><td>60–120 s</td><td>Z=3.6434,<br>p=0.0003</td><td>Z=3.7117,<br>p=0.0002</td><td>Z=0.2277,<br>p=0.8199</td></tr><tr><td>120–180 s</td><td>Z=4.0305,<br>p&lt;0.0001</td><td>Z=3.7117,<br>p=0.0002</td><td>Z=1.8673,<br>p=0.0619</td></tr></tbody><thead><tr><th colspan="4">Cardiac Parasympathetic Index</th></tr><tr><th></th><th>Self vs Social</th><th>Social vs Object</th><th>Self vs Object</th></tr></thead><tbody><tr><td>0–60 s</td><td>Z=2.6415,<br>p=0.0083</td><td>Z=2.5504,<br>p=0.0108</td><td>Z=0.0911,<br>p=0.9274</td></tr><tr><td>60–120 s</td><td>Z=2.6187,<br>p=0.0088</td><td>Z=3.1425,<br>p=0.0017</td><td>Z=0.6604,<br>p=0.5090</td></tr><tr><td>120–180 s</td><td>Z=2.4821,<br>p=0.0131</td><td>Z=3.3474,<br>p=0.0008</td><td>Z=1.3663,<br>p=0.1718</td></tr></tbody></table>

Paired Wilcoxon tests were performed on the average of cardiac sympathetic and parasympathetic indices within 0-60s, 60-120s, and 120-180s intervals, with respect to the touch onset. Significance is shown in shaded gray areas, and it was defined by the Bonferroni rule at α = 0.0166.

<table><caption>TABLE II
FEATURE RANKING BASED ON MINIMUM REDUNDANCY MAXIMUM RELEVANCE (MRMR) SCORE</caption><thead><tr><th rowspan="2">Feature ranking</th><th colspan="3">Feature (MRMR score)</th></tr><tr><th>Social vs self</th><th>Self vs object</th><th>Social vs object</th></tr></thead><tbody><tr><td>1</td><td>Sympathetic<br>0-60s<br>(0.3526)</td><td>Sympathetic<br>0-60s<br>(2.9e-15)</td><td>Sympathetic<br>60-120s<br>(0.2239)</td></tr><tr><td>2</td><td>Parasympathetic<br>120-180s<br>(0.1920)</td><td>Sympathetic<br>60-120s<br>(2.4e-15)</td><td>Parasympathetic<br>120-180s<br>(0.1574)</td></tr><tr><td>3</td><td>Sympathetic<br>60-120s<br>(0.1920)</td><td>Parasympathetic<br>120-180s<br>(2.4e-15)</td><td>Sympathetic<br>0-60s<br>(4.8e-15)</td></tr><tr><td>4</td><td>Sympathetic<br>120-180s<br>(0.1893)</td><td>Parasympathetic<br>0-60s<br>(2.4e-15)</td><td>Sympathetic<br>120-180s<br>(4e-15)</td></tr><tr><td>5</td><td>Parasympathetic<br>0-60s<br>(3.9e-15)</td><td>Parasympathetic<br>60-120s<br>(1.6e-28)</td><td>Parasympathetic<br>60-120s<br>(2.6e-15)</td></tr><tr><td>6</td><td>Parasympathetic<br>60-120s<br>(2.6e-15)</td><td>Sympathetic<br>120-180s<br>(1.2e-28)</td><td>Parasympathetic<br>0-60s<br>(6.9e-29)</td></tr></tbody></table>

The scores were computed for all possible comparisons between social, self, and object touch using as features the averages of cardiac sympathetic and parasympathetic indices within 0-60s, 60-120s, and 120-180s intervals.

cardiac parasympathetic activity while at the same time showing a greater reduction in cardiac sympathetic activity.

IV. DISCUSSION

This study is a pioneering effort in capturing time-resolved cardiac responses to different modalities of affective touch. Using a method that quantifies dynamic changes in cardiac rhythmicity over time [42], we moved beyond the traditional time-averaged approaches spanning a few minutes [17], [19], [32]. This approach allowed us to reveal the temporal dynamics of sympathetic and parasympathetic influences on cardiac activity during affective touch. Our results revealed that, overall, all touch conditions elicited a decrease in sympathetic activity. As expected, the sympathetic decrease was notably more pronounced during social touch as compared to the other conditions.
<figure><img src="image_5.png" /><figcaption>Fig. 4. Combined indices for the cardiac sympathetic index (CSI) and cardiac parasympathetic index (CPI), as taken from Fig. 3, in 3D scatter plots to distinguish self-touch, social-touch, object-touch (n=28). The CSI was considered in the intervals 0-60s and 60-120s, and CPI in the interval 120-180s, with respect to the touch onset. Those intervals represent the instances in which a major separability between the conditions occurred, as quantified in a multivariate analysis. The displayed ellipsoids are centered in the group median and their ratios correspond to the median absolute deviations per dimension.</figcaption></figure>

Moreover, we observed an increase in parasympathetic activity, specifically stronger during social touch, which furthered the differentiation from self-touch and object touch. Interestingly, as the protocol progressed, the distinction between parasympathetic responses to social touch and object touch became more prominent. It is important to mention that participants were relaxed in all conditions, with eyes closed, and even the object touch condition could elicit parasympathetic activation. However, this effect was considerably less pronounced than the social touch condition, and comparable to self-touch. These findings suggest that the autonomic effects are significantly influenced by the social component of touch. Remarkably, by combining the sympathetic and parasympathetic indices in a features' hyperplane, we were able to further differentiate the experimental conditions, with social touch exhibiting the most substantial modulations on cardiac autonomic dynamics. Self-touch and object-touch were not significantly different, which indicates that not only the involvement of CT-fibers is responsible for the effects on autonomic systems (since they are stimulated during self-ouch as well). Instead, the social component of touch seems to contribute something specific that evokes the observed autonomic effects. This fits well with previous brain imaging results that showed that social touch evokes a clearly different neural response as compared to self-touch [33].

Sympathetic activity might play a role in facilitating the functioning of tactile receptors, as suggested by findings that the inhibition of sympathetic activity enhances tactile sensitivity [43]. Our results are in line with this effect, which is thought to be triggered by the activation of CT-fibers, specialized receptors that respond to slow and gentle touch [16]. In comparison, the faster A-delta fibers in the skin are thought to be responsible for sympathetic activation during thermal and nociceptive stimuli [18]. Additional evidence indicates that sympathetic reactivity, as measured by changes in pupil diameter and skin conductance, is influenced by the velocity of stroking rather than touch itself [56], [57]. The observed effects on sympathetic indices may arise from ascending signaling from the skin to the brain via spinal cord pathways. Animal models have demonstrated that

inhibitory influences on sympathetic activity involve pathways ascending through the dorsolateral funiculus and sulcus areas of the spinal cord [58]. It is noteworthy that processing in the spinal cord also contributes to the modulation of the sense of body ownership [59] and the distinction between self-touch and social touch [33].

Our present and previous experimental evidence suggests that parasympathetic activations represent the affective component in touch. Cardiac deceleration modulated from parasympathetic inputs has been reported under affiliative contexts [38], [39], [40] and in infants [60]. Furthermore, the stimulation of CT-fibers within an optimal stroking velocity range produced an increased parasympathetic modulation to cardiac dynamics, which was sustained into the subsequent post-touch period [61]. The observed parasympathetic activity in our result indicates that social touch triggers additional physiological adjustments and involves active integration of interoceptive inputs. Previous studies have linked variations in parasympathetic tone to fluctuations in attention and emotional processing [62]. In fact, the differences in parasympathetic modulations to cardiac dynamics under emotion regulation tasks have demonstrated its ability to distinguish healthy individuals from those with certain pathologies [63], [64].

The sympathetic and parasympathetic dynamics have been previously associated with behavior in the polyvagal theory [24], which describes neural circuits involved in homeostatic regulation and adaptation. According to the polyvagal theory [24], the parasympathetic branch is primarily associated with promoting social engagement, as it correlates with reactivity, emotional expression, and self-regulation skills. Notably, parasympathetic activity has been found to promote emotional processing in response to audiovisual stimuli [65], which supports that subjective emotional experiences may require the ongoing integration of interoceptive inputs in the brain. The physiological circuits involved in social touch notably include endocrine responses triggered by the release of oxytocin following CT-fiber activation [27]. Oxytocin, known for its role in social bonding, promotes prosocial behaviors and supports emotional regulation
by reducing stress [28], [39], [40]. Therefore, it is important to mention that these mechanisms may help explain part of the physiological distinctions between self-touch and social touch.

Previous research links brain-heart mechanisms to cognitive processes like body ownership, perspective-taking, and consciousness [26], [66], [67], [68], [69], [70], [71]. These connections suggest that autonomic dynamics may influence the neural mechanisms distinguishing between social and self-produced touch, as the brain monitors changes in peripheral activity, including heart rhythms. For instance, in a follow-up study, we explored how brain connectivity patterns covary with cardiac activity, revealing distinct coupling patterns for social versus self-touch [72]. Tracking these covarying patterns of physiological dynamics could deepen our understanding of the pathways relating to affective touch.

In the framework of predictive coding, the integration of interoceptive inputs becomes essential for regulatory and anticipation processes [1], [73]. Somatosensory detection and tactile actions are closely linked to the muscle contraction phase of the cardiac cycle [74], [75], [76], and neural responses to heartbeats are also related to somatosensory detection [77], [78]. This suggests that interoceptive inputs are integrated during conscious somatosensory perception. Further supporting this idea, the insula—a brain region involved in interoceptive processing—plays a role in distinguishing between observing others’ somatosensory experiences and one’s own somatosensory experiences [79], and its damage disrupts affective touch perception [80]. Finally, the reported relationship of brain-heart interactions with self-other distinctions [36], [37], [81], [82] and emotion processing [37], [65], [83], [84], [85], [86] further supports the role of autonomic dynamics in the processing of affective stimuli. As interoceptive mechanisms are closely linked to various sensory modalities and processes of multisensory integration, future research could help to disentangle the specific physiological dynamics involved. Particularly in the scenario of observing touch, which is known to evoke distinct brain-level responses [79], [87], [88].

Our study has some limitations, particularly regarding the differences between receiving and performing touch. In the case of self-touch, it is challenging to disentangle the mechanisms of somatosensory processing from the touched arm and those related to the predictive model responsible for self-touch attenuation [33], [89], [90], [91]. Although participants were instructed to control for various factors that could influence their arousal levels and, consequently, their cardiovascular status (e.g., such as being indicated to not come with lack of sleep or stimulant intake), we acknowledge that there might be unknown potential confounders, e.g., because we are not able to determine whether whether participants performed the task under anxiety or stress. Differences between touch modalities may reflect variations in arousal, unpleasantness, boredom, or reduced engagement, rather than solely physiological distinctions between conditions themselves. Additionally, individual responses to the female experimenter performing social touch could introduce confounds, influenced by factors such as the participants’ sex, sexual orientation, social approachability, and level of engagement prior to the experiment [92], [93].

Understanding the physiological mechanisms underlying the processing of social touch holds significant relevance for various domains, including clinical conditions in which affective touch appears altered [94]. Disruptions in these pathways can lead to altered sensitivity and specificity of tactile receptors, resulting in the perception of tactile stimuli as uncomfortable or painful [43]. Enhancing our knowledge of the physiological aspects of social touch may offer insights for the treatment of pathological painful touch [95] and make further links with the neural mechanisms of nociceptors [96], [97]. By elucidating the relationship between autonomic activity and touch in the time domain, we can potentially uncover strategies for alleviating pain through touch-based interventions [98], [99], [100]. Overall, our findings have clinical relevance by highlighting the potential implications for the treatment of disrupted affective touch perception and processing.

## V. CONCLUSION

We revealed that social touch causes a greater modulation of autonomic activity as compared to self and object touch. We showed that the time-resolved analysis of these responses could enhance these distinctions by looking at different latencies. Our findings provide further insights into the neurophysiological dynamics of touch, which is relevant for investigating affective touch processing in healthy, neurodiverse, and neuropsychiatric populations.

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<figure><img src="image_6.png" /></figure>

Diego Candia-Rivera received the PhD degree in information engineering from the University of Pisa, Italy, in 2022. He is a researcher with the Paris Brain Institute, Sorbonne University, Paris. His research interests include the Development of Methods for studying brain-heart interactions and the understanding of the role of these interactions in consciousness. One of his significant research findings reveals that brain-heart interactions reflect the presence and levels of consciousness in severely brain-damaged patients. Furthermore, these interactions serve as the

catalyst for affective processing, shaping emotional arousal. He has performed research under the financial support from the European Commission's Marie Skłodowska-Curie Actions program and the French National Agency for Research.

<figure><img src="image_7.png" /></figure>

**Rebecca Boehme** is an associate professor with the Center for Social and Affective Neuroscience in Linköping, Sweden. Her research focuses on social interaction, interoception, and the self. Current projects aim at understanding how we establish a bodily self, how we connect with each other, and what happens to the self in different psychiatric and neurodiverse populations and during pharmacological interventions. Her research is funded by grants from the European Research Council, Vetenskapsrådet, Svenska Läkaresällskapet, Åke Wiberg Stiftelse, ALF and FORSS grants (Region Östergötland), and Lions Forskningsfond.

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**Paula C. Salamone** received the PhD degree in neuroscience from the National University of Cordoba in Argentina. She is a postdoctoral research fellow with the Center for Social and Affective Neuroscience in Linköping, Sweden. Her research focuses on interoception, affective processing, psychology, and the self, using behavioral, electrophysiology and neuroimaging techniques. Her studies focus on understanding brain-body interactions relevant for affective and social processing in neuropsychiatric and cardiac patients. She has received funding from the Lions Forskningsfond, Fredrik och Ingrid Thurings stiftelse (THS).