Epigenetic tuning of brain signal entropy in emergent human social behavior

Facing infant cuteness: How nurturing care motivation and oxytocin system gene methylation are associated with responses to baby schema features

Baby schema features are a specific set of physical features-including chubby cheeks, large, low-set eyes, and a large, round head-that have evolutionary adaptive value in their ability to trigger nurturant care. In this study among nulliparous women (N = 81; M age = 23.60, SD = 0.44), we examined how sensitivity to these baby schema features differs based on individual variations in nurturant care motivation and oxytocin system gene methylation. We integrated subjective ratings with measures of facial expressions and electroencephalography (EEG) in response to infant faces that were manipulated to contain more or less pronounced baby schema features. Linear mixed effects analyses demonstrated that infants with more pronounced baby schema features were rated as cuter and participants indicated greater motivation to take care of them. Furthermore, infants with more pronounced baby schema features elicited stronger smiling responses and enhanced P2 and LPP amplitudes compared to infants with less pronounced baby schema features. Importantly, individual differences significantly predicted baby schema effects. Specifically, women with low OXTR methylation and high nurturance motivation showed enhanced differentiation in automatic neurophysiological responses to infants with high and low levels of baby schema features. These findings highlight the importance of considering individual differences in continued research to further understand the complexities of sensitivity to child cues, including facial features, which will improve our understanding of the intricate neurobiological system that forms the basis of caregiving behavior.

Characterization of the internal working-life exposome using minimally and non-invasive sampling methods - a narrative review

During recent years, we are moving away from the 'one exposure, one disease'-approach in occupational settings and towards a more comprehensive approach, taking into account the totality of exposures during a life course by using an exposome approach. Taking an exposome approach however is accompanied by many challenges, one of which, for example, relates to the collection of biological samples. Methods used for sample collection in occupational exposome studies should ideally be minimally invasive, while at the same time sensitive, and enable meaningful repeated sampling in a large population and over a longer time period. This might be hampered in specific situations e.g., people working in remote areas, during pandemics or with flexible work hours. In these situations, using self-sampling techniques might offer a solution. Therefore, our aim was to identify existing self-sampling techniques and to evaluate the applicability of these techniques in an occupational exposome context by conducting a literature review. We here present an overview of current self-sampling methodologies used to characterize the internal exposome. In addition, the use of different biological matrices was evaluated and subdivided based on their level of invasiveness and applicability in an occupational exposome context. In conclusion, this review and the overview of self-sampling techniques presented herein can serve as a guide in the design of future (occupational) exposome studies while circumventing sample collection challenges associated with exposome studies.

The automated preprocessing pipe-line for the estimation of scale-wise entropy from EEG data (APPLESEED): Development and validation for use in pediatric populations

It is increasingly understood that moment-to-moment brain signal variability - traditionally modeled out of analyses as mere "noise" - serves a valuable functional role related to development, cognitive processing, and psychopathology. Multiscale entropy (MSE) - a measure of signal irregularity across temporal scales - is an increasingly popular analytic technique in human neuroscience calculated from time series such as electroencephalography (EEG) signals. MSE provides insight into the time-structure and (non)linearity of fluctuations in neural activity and network dynamics, capturing the brain's moment-to-moment complexity as it operates on multiple time scales. MSE is emerging as a powerful predictor of developmental processes and outcomes. However, differences in data preprocessing and MSE computation make it challenging to compare results across studies. Here, we (1) provide an introduction to MSE for developmental researchers, (2) demonstrate the effect of preprocessing procedures on scale-wise entropy estimates, and (3) establish a standardized EEG preprocessing and entropy estimation pipeline that adapts a critical modification to the original MSE algorithm, and generates reliable scale-wise entropy estimates capable of differentiating developmental stages and cognitive states. This novel pipeline - the Automated Preprocessing Pipe-Line for the Estimation of Scale-wise Entropy from EEG Data (APPLESEED) is fully automated, customizable, and freely available for download from https://github.com/mhpuglia/APPLESEED.

Oxytocin system gene methylation is associated with empathic responses towards children

Empathy is an essential component of sensitive caregiving behavior, which in turn is an important predictor of children's healthy social-emotional development. The oxytocin (OXT) system plays a key role in promoting sensitive parenting and empathy. In this study, we investigated how OXT system gene methylation was associated with empathic processes in nulliparous women (M age = 23.60, SD =0.44)-measuring both physiological facial muscle responses and ratings of compassion and positive affect to affective images depicting children. Linear mixed effects analyses demonstrated that lower methylation levels in the OXT and OXTR genes were related to enhanced empathic responses. The effect of OXT system gene methylation on empathic processes was partly qualified by an interaction with individual variations in women's care motivation. Our findings provide experimental evidence for an association between the methylation of OXT system genes and empathy.

Neuroimaging and DNA Methylation: An Innovative Approach to Study the Effects of Early Life Stress on Developmental Plasticity

DNA methylation plays a key role in neural cell fate and provides a molecular link between early life stress and later-life behavioral phenotypes. Here, studies that combine neuroimaging methods and DNA methylation analysis in pediatric population with a history of adverse experiences were systematically reviewed focusing on: targeted genes and neural correlates; statistical models used to examine the link between DNA methylation and neuroimaging data also considering early life stress and behavioral outcomes. We identified 8 studies that report associations between DNA methylation and brain structure/functions in infants, school age children and adolescents faced with early life stress condition (e.g., preterm birth, childhood maltreatment, low socioeconomic status, and less-than optimal caregiving). Results showed that several genes were investigated (e.g., OXTR, SLC6A4, FKBP5, and BDNF) and different neuroimaging techniques were performed (MRI and f-NIRS). Statistical model used ranged from correlational to more complex moderated mediation models. Most of the studies (n = 5) considered DNA methylation and neural correlates as mediators in the relationship between early life stress and behavioral phenotypes. Understanding what role DNA methylation and neural correlates play in interaction with early life stress and behavioral outcomes is crucial to promote theory-driven studies as the future direction of this research fields.

Correction to: Epigenetic tuning of brain signal entropy in emergent human social behavior

An amendment to this paper has been published and can be accessed via the original article.