Krugers, H. J. | bioRxiv Science

bioRxiv2026

Dissociable Effects of Early and Adolescent Adversity on Emotional Contagion

BackgroundEarly-life adversity can alter emotional and social development and increase vulnerability to later life stress. We investigated how early adverse experiences (EAE) and later adverse experiences (LAE) shape adult emotional contagion (EC) responses in female and male rats. MethodsEAE was induced using the limited bedding and nesting model during the first postnatal week. LAE was induced via footshocks during adolescence. In adulthood, male and female rats underwent an EC test in which observers witnessed a conspecific receiving footshocks. ResultsAdolescence-footshock exposed observers showed cingulate cortex-associated increased immobility, proximity, and attention toward distressed conspecifics during adulthood, compared to adult-exposed and sham animals, both in male and female animals. While EAE did alter maternal care, pup stress physiology, and pup weight, we found evidence that it did not alter immobility during EC. However, female demonstrators paired with EAE observers showed increased immobility, linked to a reduced rate and lower frequency of the observers 50-kHz vocalizations. Mediation analysis revealed that a shift toward lower-frequency 50-kHz vocalizations specifically mediated this effect, suggesting a sex-specific pathway by which early adversity shapes social behavior. ConclusionsEarly and adolescent adversity influenced distinct aspects of emotional contagion: EAE mediated an observer-to-demonstrator emotional transfer during EC, while LAE impacted a demonstrator-to-observer transfer, with no evidence of additive effects. Our results highlight developmentally specific and sex-dependent mechanisms by which early and later adversity alter social-affective responses in adulthood.

neuroscience↗

bioRxiv2025

Coping strategy dynamics and resilience profiles after early life stress revealed by behavioral sequencing

Animal models can provide valuable insights into the mechanisms underlying stress-related disorders. Yet, significant translational challenges persist, as laboratory behavioral assays are often reductionistic, with limited attention to ethologically relevant behavioral diversity. Recent advances in high-throughput pose-estimation tools and computational ethology methods are addressing this limitation by enhancing the resolution and validity of behavioral phenotyping. In this context, it is known that early life stress (ELS) reshapes how animals handle subsequent threats later in life, but the fine-scale dynamics and ethological details of this shift remain elusive. To overcome this, we combined a deep-learning pose-estimation pipeline (DeepLabCut) with a supervised freezing classifier (SimBA) and an unsupervised behavioral motifs identification platform (keypoint MoSeq) to study in detail the diversity and dynamics of behavior in an auditory fear-conditioning (FC) paradigm in two independent cohorts of adult male mice that were exposed to ELS through the limited bedding and nesting (LBN) paradigm. We first validated the blunted freezing response after ELS in a supervised manner using SimBA. Next, keypoint MoSeq segmented the same pose-estimation data into ethologically meaningful motifs over time. When compared to control animals, ELS offspring showed an altered FC response, reduced behavioral entropy and limited diversity in their behavioral repertoire. Such response was characterized by longer active-behavior bouts and more recurrent transitions between states, indicating a more stereotyped and predictable response. Multidimensional scaling of time-binned behavioral vectors and distance metrics identified a resilient subpopulation within the ELS group that displayed a control-like behavioral profile, characterized by a steeper increase in freezing behavior during the FC task and a more diverse behavioral repertoire with reduced recurrence of stereotyped actions, less frequent and shorter active bouts and prolonged passive responses. Overall, our findings suggest that ELS shifts the balance between passive and active coping strategies and that resilience is marked by a less stereotypical yet more diverse and flexible behavioral response to a subsequent stressful demand. Finally, we further validated the unsupervised behavioral motifs with a predictive model that identified distinctive kinematic features of these responses, which could be used to build new behavioral classifiers that can be applied in other behavioral paradigms. These results demonstrate the potential of computational ethology to dissect complex behavioral patterns and improve our understanding of individual stress responses. By combining supervised and unsupervised behavioral analysis tools, we can deepen our understanding of the latent structure of stress behavior and identify objective markers of vulnerability and resilience.

neuroscience↗