Remembering unexpected beauty: Contributions of the ventral striatum to the processing of reward prediction errors regarding the facial attractiveness in face memory

The COVID-19 pandemic has led people to predict facial attractiveness from partially covered faces. Differences in the predicted and observed facial attractiveness (i.e., masked and unmasked faces, respectively) are defined as reward prediction error (RPE) in a social context. Cognitive neuroscience studies have elucidated the neural mechanisms underlying RPE-induced memory improvements in terms of monetary rewards. However, little is known about the mechanisms underlying RPE-induced memory modulation in terms of social rewards. To elucidate this, the present functional magnetic resonance imaging (fMRI) study investigated activity and functional connectivity during face encoding. In encoding trials, participants rated the predicted attractiveness of faces covered except for around the eyes (prediction phase) and then rated the observed attractiveness of these faces without any cover (outcome phase). The difference in ratings between these phases was defined as RPE in facial attractiveness, and RPE was categorized into positive RPE (increased RPE from the prediction to outcome phases), negative RPE (decreased RPE from the prediction to outcome phases), and non-RPE (no difference in RPE between the prediction and outcome phases). During retrieval, participants were presented with individual faces that had been seen and unseen in the encoding trials, and were required to judge whether or not each face had been seen in the encoding trials. Univariate activity in the ventral striatum (VS) exhibited a linear increase with increased RPE in facial attractiveness. In the multivariate pattern analysis (MVPA), activity patterns in the VS and surrounding areas (extended VS) significantly discriminated between positive/negative RPE and non-RPE. In the functional connectivity analysis, significant functional connectivity between the extended VS and the hippocampus was observed most frequently in positive RPE. Memory improvements by face-based RPE could be involved in functional networks between the extended VS (representing RPE) and the hippocampus, and the interaction could be modulated by RPE values in a social context.

Neural Mechanisms of Perceiving and Subsequently Recollecting Emotional Facial Expressions in Young and Older Adults

It is known that emotional facial expressions modulate the perception and subsequent recollection of faces and that aging alters these modulatory effects. Yet, the underlying neural mechanisms are not well understood, and they were the focus of the current fMRI study. We scanned healthy young and older adults while perceiving happy, neutral, or angry faces paired with names. Participants were then provided with the names of the faces and asked to recall the facial expression of each face. fMRI analyses focused on the fusiform face area (FFA), the posterior superior temporal sulcus (pSTS), the OFC, the amygdala, and the hippocampus (HC). Univariate activity, multivariate pattern (MVPA), and functional connectivity analyses were performed. The study yielded two main sets of findings. First, in pSTS and the amygdala, univariate activity and MVPA discrimination during the processing of facial expressions were similar in young and older adults, whereas in FFA and OFC, MVPA discriminated facial expressions less accurately in older than young adults. These findings suggest that facial expression representations in FFA and OFC reflect age-related dedifferentiation and positivity effect. Second, HC-OFC connectivity showed subsequent memory effects (SMEs) for happy expressions in both age groups, HC-FFA connectivity exhibited SMEs for happy and neutral expressions in young adults, and HC-pSTS interactions displayed SMEs for happy expressions in older adults. These results could be related to compensatory mechanisms and positivity effects in older adults. Taken together, the results clarify the effects of aging on the neural mechanisms in perceiving and encoding facial expressions.