Social dialogue triggers biobehavioral synchrony of partners' endocrine response via sex-specific, hormone-specific, attachment-specific mechanisms

Abstract Social contact is known to impact the partners' physiology and behavior but the mechanisms underpinning such inter-partner influences are far from clear. Guided by the biobehavioral synchrony conceptual frame, we examined how social dialogue shapes the partners' multi-system endocrine response as mediated by behavioral synchrony. To address sex-specific, hormone-specific, attachment-specific mechanisms, we recruited 82 man–woman pairs (N = 164 participants) in three attachment groups; long-term couples (n = 29), best friends (n = 26), and ingroup strangers (n = 27). We used salivary measures of oxytocin (OT), cortisol (CT), testosterone (T), and secretory immuglobolinA (s-IgA), biomarker of the immune system, before and after a 30-min social dialogue. Dialogue increased oxytocin and reduced cortisol and testosterone. Cross-person cross-hormone influences indicated that dialogue carries distinct effects on women and men as mediated by social behavior and attachment status. Men's baseline stress-related biomarkers showed both direct hormone-to-hormone associations and, via attachment status and behavioral synchrony, impacted women's post-dialogue biomarkers of stress, affiliation, and immunity. In contrast, women's baseline stress biomarkers linked with men's stress response only through the mediating role of behavioral synchrony. As to affiliation biomarkers, men's initial OT impacted women's OT response only through behavioral synchrony, whereas women's baseline OT was directly related to men's post-dialogue OT levels. Findings pinpoint the neuroendocrine advantage of social dialogue, suggest that women are more sensitive to signs of men's initial stress and social status, and describe behavior-based mechanisms by which human attachments create a coupled biology toward greater well-being and resilience

Alterations in oxytocin and vasopressin in men with problematic pornography use: The role of empathy

Background Addictive behaviors share clinical, genetic, neurobiological and phenomenological parallels with substance addictions. Despite the prevalence of compulsive sexual behaviors, particularly problematic pornography use (PPU), how neuroendocrine systems relate to PPU is not well understood. Preclinical studies demonstrate alterations in oxytocin and arginine vasopressin (AVP) function in animal models of addiction, but no human study has tested their involvement in PPU. Method Participants included 122 males; 69 reported PPU, and 53 were demographically-matched participants without PPU. Plasma oxytocin and AVP levels and oxytocin-to-AVP balance were measured at baseline. Salivary oxytocin was assessed at baseline and in response to four videos depicting neutral/positive social encounters. Participants reported on empathy and psychiatric symptoms. Results Baseline plasma AVP levels were elevated in men with PPU, and the ratio of oxytocin-to-vasopressin suggested AVP dominance. Men with PPU reacted with greater oxytocin increases to presentation of neutral/positive social stimuli. Decreased empathic tendencies were found in men with PPU, and this reduced empathy mediated links between oxytocin and pornography-related hypersexuality. Structural equation modeling revealed three independent paths to pornography-related hypersexuality; two direct paths via increased AVP and higher psychiatric symptoms and one indirect path from oxytocin to pornography-related hypersexuality mediated by diminished empathy. Conclusions Findings are among the first to implicate neuropeptides sustaining mammalian attachment in the pathophysiology of pornography-related hypersexuality and describe a neurobiological mechanism by which oxytocin-AVP systems and psychiatric symptomatology may operate to reduce empathy and lead to pornography-related hypersexuality

Data for Synchronous Caregiving from Birth to Adulthood Tunes Humans' Social Brain

fMRI paradigm of empathy to different emotion

Technologically-assisted communication attenuates inter-brain synchrony

Funding Information: The study was supported by the Simms/Mann Foundation Chair to Ruth Feldman and by the Bezos Family Foundation. Publisher Copyright: © 2022 The AuthorsThe transition to technologically-assisted communication has permeated all facets of human social life; yet, its impact on the social brain is still unknown and the effects may be particularly intense during periods of developmental transitions. Applying a two-brain perspective, the current preregistered study utilized hyperscanning EEG to measure brain-to-brain synchrony in 62 mother-child pairs at the transition to adolescence (child age; M = 12.26, range 10–14) during live face-to-face interaction versus technologically-assisted remote communication. The live interaction elicited 9 significant cross-brain links between densely inter-connected frontal and temporal areas in the beta range [14–30 Hz]. Mother's right frontal region connected with the child's right and left frontal, temporal, and central regions, suggesting its regulatory role in organizing the two-brain dynamics. In contrast, the remote interaction elicited only 1 significant cross-brain-cross-hemisphere link, attenuating the robust right-to-right-brain connectivity during live social moments that communicates socio-affective signals. Furthermore, while the level of social behavior was comparable between the two interactions, brain-behavior associations emerged only during the live exchange. Mother-child right temporal-temporal synchrony linked with moments of shared gaze and the degree of child engagement and empathic behavior correlated with right frontal-frontal synchrony. Our findings indicate that human co-presence is underpinned by specific neurobiological processes that should be studied in depth. Much further research is needed to tease apart whether the "Zoom fatigue" experienced during technological communication may stem, in part, from overload on more limited inter-brain connections and to address the potential cost of social technology for brain maturation, particularly among youth.Peer reviewe

HyPyP: a Hyperscanning Python Pipeline for inter-brain connectivity analysis

International audienceThe bulk of social neuroscience takes a ‘stimulus-brain’ approach, typically comparing brain responses to different types of social stimuli, but most of the time in the absence of direct social interaction. Over the last two decades, a growing number of researchers have adopted a ‘brain-to-brain’ approach, exploring similarities between brain patterns across participants as a novel way to gain insight into the social brain. This methodological shift has facilitated the introduction of naturalistic social stimuli into the study design (e.g. movies) and, crucially, has spurred the development of new tools to directly study social interaction, both in controlled experimental settings and in more ecologically valid environments. Specifically, ‘hyperscanning’ setups, which allow the simultaneous recording of brain activity from two or more individuals during social tasks, has gained popularity in recent years. However, currently, there is no agreed-upon approach to carry out such ‘inter-brain connectivity analysis’, resulting in a scattered landscape of analysis techniques. To accommodate a growing demand to standardize analysis approaches in this fast-growing research field, we have developed Hyperscanning Python Pipeline, a comprehensive and easy open-source software package that allows (social) neuroscientists to carry-out and to interpret inter-brain connectivity analyses

easystats/parameters: parameters 0.21.2

Changes Minor improvements to factor analysis functions. The ci_digits argument of the print() method for model_parameters() now defaults to the same value of digits. model_parameters() for objects from package marginaleffects now also accepts the exponentiate argument. The print(), print_html(), print_md() and format() methods for model_parameters() get an include_reference argument, to add the reference category of categorical predictors to the parameters table. Bug fixes Fixed issue with wrong calculation of test-statistic and p-values in model_parameters() for fixest models. Fixed issue with wrong column header for glm models with family = binomial("identiy"). Minor fixes for dominance_analysis()