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Sensitivity to others’ emotional signals is an important factor for social interaction. While many studies of emotional reactivity focus on facial emotional expressions, signals such as pupil dilation which can indicate arousal, may also affect observers. For example, observers’ pupils dilate when viewing someone with dilated pupils, so-called pupillary contagion. Yet it is unclear how pupil size and emotional expression interact as signals. Further, examining individual differences in emotional reactivity to others can shed light on its mechanisms and potential outcomes. In the current study, adults’ (N = 453) pupil size was assessed while they viewed images of the eye region of individuals varying in emotional expression (neutral, happy, sad, fearful, angry) and pupil size (large, medium, small). Participants showed pupillary contagion regardless of the emotional expression. Individual differences in demographics (gender, age, socioeconomic status) and psychosocial factors (anxiety, depression, sleep problems) were also examined, yet the only factor related to pupillary contagion was socioeconomic status, with higher socioeconomic status predicting less pupillary contagion for emotionally-neutral stimuli. The results suggest that while pupillary contagion is a robust phenomenon, it can vary meaningfully across individuals.

Saccadic reaction time (SRT) is a widely used dependent variable in eye-tracking studies of human cognition and its disorders. SRTs are also frequently measured in studies with special populations, such as infants and young children, who are limited in their ability to follow verbal instructions and remain in a stable position over time. In this article, we describe a library of MATLAB routines (Mathworks, Natick, MA) that are designed to (1) enable completely automated implementation of SRT analysis for multiple data sets and (2) cope with the unique challenges of analyzing SRTs from eye-tracking data collected from poorly cooperating participants. The library includes preprocessing and SRT analysis routines. The preprocessing routines (i.e., moving median filter and interpolation) are designed to remove technical artifacts and missing samples from raw eye-tracking data. The SRTs are detected by a simple algorithm that identifies the last point of gaze in the area of interest, but, critically, the extracted SRTs are further subjected to a number of postanalysis verification checks to exclude values contaminated by artifacts. Example analyses of data from 5- to 11-month-old infants demonstrated that SRTs extracted with the proposed routines were in high agreement with SRTs obtained manually from video records, robust against potential sources of artifact, and exhibited moderate to high test-retest stability. We propose that the present library has wide utility in standardizing and automating SRT-based cognitive testing in various populations. The MATLAB routines are open source and can be downloaded from http://www.uta.fi/med/icl/methods.html .

BACKGROUND: Cross-species evidence suggests that genetic and experiential factors act early in development to establish individual emotional traits, but little is known about the mechanisms that emerge during this period to mediate long-term outcomes. Here, we tested the hypothesis that known genetic and environmental risk conditions may heighten infants' natural tendency to attend to threat-alerting stimuli, resulting in a cognitive bias that may contribute to emotional vulnerability. METHODS: Data from two samples of 5-7-month-old infants (N = 139) were used to examine whether established candidate variations in the serotonin-system genes, i.e., TPH2 SNP rs4570625 (-703 G/T) and HTR1A SNP rs6295 (-1019 G/C), and early rearing condition (maternal stress and depressive symptoms) are associated with alterations in infants' attention to facial expressions. Infants were tested with a paradigm that assesses the ability to disengage attention from a centrally presented stimulus (a nonface control stimulus or a neutral, happy, or fearful facial expression) toward the location of a new stimulus in the visual periphery (a geometric shape). RESULTS: TPH2 -703 T-carrier genotype (i.e., TT homozygotes and heterozygotes), presence of maternal stress and depressive symptoms, and a combination of the T-carrier genotype and maternal depressive symptoms were associated with a relatively greater difficulty disengaging attention from fearful facial expressions. No associations were found with infants' temperamental traits. CONCLUSIONS: Alterations in infants' natural attentional bias toward fearful facial expressions may emerge prior to the manifestation of emotional and social behaviors and provide a sensitive marker of early emotional development.

Biases in attention towards facial cues during infancy may have an important role in the development of social brain networks. The current study used a longitudinal design to examine the stability of infants' attentional biases towards facial expressions and to elucidate how these biases relate to emerging cortical sensitivity to facial expressions. Event-related potential (ERP) and attention disengagement data were acquired in response to the presentation of fearful, happy, neutral, and phase-scrambled face stimuli from the same infants at 5 and 7 months of age. The tendency to disengage from faces was highly consistent across both ages. However, the modulation of this behavior by fearful facial expressions was uncorrelated between 5 and 7 months. In the ERP data, fear-sensitive activity was observed over posterior scalp regions, starting at the latency of the N290 wave. The scalp distribution of this sensitivity to fear in ERPs was dissociable from the topography of face-sensitive modulation within the same latency range. While attentional bias scores were independent of co-registered ERPs, attention bias towards fearful faces at 5 months of age predicted the fear-sensitivity in ERPs at 7 months of age. The current results suggest that the attention bias towards fear could be involved in the developmental tuning of cortical networks for social signals of emotion.

Recording of event-related potentials (ERPs) is one of the best-suited technologies for examining brain function in human infants. Yet the existing software packages are not optimized for the unique requirements of analyzing artifact-prone ERP data from infants. We developed a new graphical user interface that enables an efficient implementation of a two-stage approach to the analysis of infant ERPs. In the first stage, video records of infant behavior are synchronized with ERPs at the level of individual trials to reject epochs with noncompliant behavior and other artifacts. In the second stage, the interface calls MATLAB and EEGLAB (Delorme & Makeig, Journal of Neuroscience Methods 134(1):9-21, 2004) functions for further preprocessing of the ERP signal itself (i.e., filtering, artifact removal, interpolation, and rereferencing). Finally, methods are included for data visualization and analysis by using bootstrapped group averages. Analyses of simulated and real EEG data demonstrated that the proposed approach can be effectively used to establish task compliance, remove various types of artifacts, and perform representative visualizations and statistical comparisons of ERPs. The interface is available for download from http://www.uta.fi/med/icl/methods/eeg.html in a format that is widely applicable to ERP studies with special populations and open for further editing by users.