Individual differences in processing speed and curiosity explain infant habituation and dishabituation performance.

Habituation and dishabituation are the most prevalent measures of infant cognitive functioning, and they have reliably been shown to predict later cognitive outcomes. Yet, the exact mechanisms underlying infant habituation and dishabituation are still unclear. To investigate them, we tested 106 8-month-old infants on a classic habituation task and a novel visual learning task. We used a hierarchical Bayesian model to identify individual differences in sustained attention, learning performance, processing speed and curiosity from the visual learning task. These factors were then related to habituation and dishabituation. We found that habituation time was related to individual differences in processing speed, while dishabituation was related to curiosity, but only for infants who did not habituate. These results offer novel insights in the mechanisms underlying habituation and serve as proof of concept for hierarchical models as an effective tool to measure individual differences in infant cognitive functioning. RESEARCH HIGHLIGHTS: We used a hierarchical Bayesian model to measure individual differences in infants' processing speed, learning performance, sustained attention, and curiosity. Faster processing speed was related to shorter habituation time. High curiosity was related to stronger dishabituation responses, but only for infants who did not habituate.

Eight-Month-Old Infants Meta-Learn by Downweighting Irrelevant Evidence.

Infants learn to navigate the complexity of the physical and social world at an outstanding pace, but how they accomplish this learning is still largely unknown. Recent advances in human and artificial intelligence research propose that a key feature to achieving quick and efficient learning is meta-learning, the ability to make use of prior experiences to learn how to learn better in the future. Here we show that 8-month-old infants successfully engage in meta-learning within very short timespans after being exposed to a new learning environment. We developed a Bayesian model that captures how infants attribute informativity to incoming events, and how this process is optimized by the meta-parameters of their hierarchical models over the task structure. We fitted the model with infants' gaze behavior during a learning task. Our results reveal how infants actively use past experiences to generate new inductive biases that allow future learning to proceed faster.

Predictive motor activation: Modulated by expectancy or predictability?

Predicting actions is a fundamental ability that helps us to comprehend what is happening in our environment and to interact with others. The motor system was previously identified as source of action predictions. Yet, which aspect of the statistical likelihood of upcoming actions the motor system is sensitive to remains an open question. This EEG study investigated how regularities in observed actions are reflected in the motor system and utilized to predict upcoming actions. Prior to measuring EEG, participants watched videos of action sequences with different transitional probabilities. After training, participants' brain activity over motor areas was measured using EEG while watching videos of action sequences with the same statistical structure. Focusing on the mu and beta frequency bands we tested whether activity of the motor system reflects the statistical likelihood of upcoming actions. We also explored two distinct aspects of the statistical structure that capture different prediction processes, expectancy and predictability. Expectancy describes participants' expectation of the most likely action, whereas predictability represents all possible actions and their relative probabilities. Results revealed that mu and beta oscillations play different roles during action prediction. While the mu rhythm reflected anticipatory activity without any link to the statistical structure, the beta rhythm was related to the expectancy of an action. Our findings support theories proposing that the motor system underlies action prediction, and they extend such theories by showing that multiple forms of statistical information are extracted when observing action sequences. This information is integrated in the prediction generated by the neural motor system of which action is going to happen next.

The Recognition of Cross-Cultural Emotional Faces Is Affected by Intensity and Ethnicity in a Japanese Sample.

Human faces convey a range of emotions and psychobiological signals that support social interactions. Multiple factors potentially mediate the facial expressions of emotions across cultures. To further determine the mechanisms underlying human emotion recognition in a complex and ecological environment, we hypothesized that both behavioral and neurophysiological measures would be influenced by stimuli ethnicity (Japanese, Caucasian) in the context of ambiguous emotional expressions (mid-happy, angry). We assessed the neurophysiological and behavioral responses of neurotypical Japanese adults (N = 27, 13 males) involved in a facial expression recognition task. Results uncover an interaction between universal and culturally-driven mechanisms. No differences in behavioral responses are found between male and female participants, male and female faces, and neutral Japanese versus Caucasian faces. However, Caucasian ambiguous emotional expressions which require more energy-consuming processing, as highlighted by neurophysiological results of the Arousal Index, were judged more accurately than Japanese ones. Additionally, a differential Frontal Asymmetry Index in neuronal activation, the signature of an approach versus avoidance response, is found in male participants according to the gender and emotional valence of the stimuli.

Dataset on genetic and physiological adults׳ responses to social distress.

Both expectations towards interactions with conspecifics, and genetic predispositions, affect adults׳ social behaviors. However, the underlying mechanisms remain largely unknown. Here, we report data to investigate the interaction between genetic factors, (oxytocin receptor (OXTR) and serotonin transporter (5-HTTLPR) polymorphisms), and adult interactional patterns in shaping physiological responses to social distress. During the presentation of distress vocalizations (cries of human female, infants and bonobos) we assessed participants׳ (N = 42 males) heart rate (HR) and peripheral nose temperature, which index state of arousal and readiness to action. Self-reported questionnaires were used to evaluate participants' interactional patterns towards peers (Attachment Style Questionnaire, Feeney et al., 1994[1]), and the quality of bond with intimate partners (Experiences in Close Relationships Scale, Fraley et al., 2000 [2]). To assess participants׳ genetic predispositions, the OXTR gene (regions rs53576, and rs2254298) and the 5-HTTLPR gene (region SLC6A4) were genotyped. The data set is made publicly available to enable critical or extended analyzes.