RESUMO
Early life adversity (ELA) is a major risk factor for the development of pathology, including anxiety disorders. Neurodevelopmental and behavioral outcomes following ELA are multifaceted and are influenced heavily by the type of adversity experienced and sex of the individual experiencing ELA. It remains unclear what properties of ELA portend differential neurobiological risk and the basis of sex-differences for negative outcomes. Predictability of the postnatal environment has emerged as being a core feature supporting development, with the most salient signals deriving from parental care. Predictability of parental care may be a distinguishing feature of different forms of ELA, and the degree of predictability afforded by these manipulations may contribute to the diversity of outcomes observed across models. Further, questions remain as to whether differing levels of predictability may contribute to differential effects on neurodevelopment and expression of genes associated with risk for pathology. Here, we tested the hypothesis that changes in maternal behavior in mice would be contingent on the type of ELA experienced, directly comparing predictability of care in the limited bedding and nesting (LBN) and maternal separation (MS) paradigms. We then tested whether the predictability of the ELA environment altered the expression of corticotropin-releasing hormone (Crh), a sexually-dimorphic neuropeptide that regulates threat-related learning, in the amygdala of male and female mice. The LBN manipulation reliably increased the entropy of maternal care, a measure that indicates lower predictability between sequences of dam behavior. LBN and MS rearing similarly increased the frequency of nest sorties and licking of pups but had mixed effects on other aspects of dam-, pup-, and nest-related behaviors. Increased expression of Crh-related genes was observed in pups that experienced ELA, with gene expression measures showing a significant interaction with sex and type of ELA manipulation. Specifically, MS was associated with increased expression of Crh-related genes in males, but not females, and LBN primarily increased expression of these genes in females, but not males. The present study provides evidence for predictability as a distinguishing feature of models of ELA and demonstrates robust consequences of these differing experience on sex-differences in gene expression critically associated with stress responding and sex differences in risk for pathology.
RESUMO
For social robots to effectively engage in human-robot interaction (HRI), they need to be able to interpret human affective cues and to respond appropriately via display of their own emotional behavior. In this article, we present a novel multimodal emotional HRI architecture to promote natural and engaging bidirectional emotional communications between a social robot and a human user. User affect is detected using a unique combination of body language and vocal intonation, and multimodal classification is performed using a Bayesian Network. The Emotionally Expressive Robot utilizes the user's affect to determine its own emotional behavior via an innovative two-layer emotional model consisting of deliberative (hidden Markov model) and reactive (rule-based) layers. The proposed architecture has been implemented via a small humanoid robot to perform diet and fitness counseling during HRI. In order to evaluate the Emotionally Expressive Robot's effectiveness, a Neutral Robot that can detect user affects but lacks an emotional display, was also developed. A between-subjects HRI experiment was conducted with both types of robots. Extensive results have shown that both robots can effectively detect user affect during the real-time HRI. However, the Emotionally Expressive Robot can appropriately determine its own emotional response based on the situation at hand and, therefore, induce more user positive valence and less negative arousal than the Neutral Robot.