Statistical analysis
Box plots were used to identify outliers. Values >3 box-lengths from the 75th percentile (box-length=interquartile range) were excluded.
Behavioral data (gender discrimination mean accuracy and mean RT) were analyzed using repeated-measures ANOVAs, with group (High vs Low Ns) as the between-subject variable and emotion (fearful, happy) and intensity of facial expression (high, medium, low) as the within-subjects variables. The eye-movement parameters were analyzed using repeated-measures ANOVAs, first over the whole face ROI with group (High vs Low Ns) as the between-subject variable and emotion (fearful, happy) and intensity of facial expression (high, medium, low) as the within-subjects variables. Ocular exploration over different face areas was analyzed, including the additional within-subjects variable of within-face ROIs (eyes, mouth) to the repeated-measures ANOVAs. The interpretation of significant interaction effects was aided by the use of post hoc analysis (Bonferroni) to compare between levels of the different factors and by use of simple main-effect analyses. Independent samples t-tests were performed to examine group differences in affect and personality ratings. Correlation analyses were run to check for relationships between eye-movement parameters and behavioral responses and affect ratings in the High Ns group. In order to simplify correlation analysis, eye-movement data were collapsed across different facial expression intensities.