Brain signal variability is reduced during self-face processing irrespective of emotional facial expressions: Evidence from multiscale entropy analysis.

Prior research shows that self-referential information (e.g., seeing one's own face) is prioritized in human cognition. However, the brain signal variability underlying self-processing remains scarcely treated in the literature. Additionally, less is known about whether the processing of self-referential visual content can be modulated by facial expressions of emotion, as these resemble more natural situations than neutral expressions. This study therefore investigated the brain signal variability underlying self-referential visual processing and its possible interaction with emotional facial expressions, as indexed by multiscale entropy analysis (MSE). This metric captures the temporal complexity or variability contained in neural patterns at varying timescales. Thirty-two participants were presented with distinctive facial identities (self, friend, and unknown) displaying different facial expressions (happy, neutral, and angry) and performed an identity recognition task. Our results showed that brain signal variability decreases in response to self-faces compared to other identities. Similarly, brain signal variability also decreases for friend faces relative to unknown faces. This reduction in complexity could be indicative of greater efficiency during the preferential processing of personally relevant stimuli. Furthermore, the data observed here show that self-processing is unaffected by facial expressions of emotion, suggesting an independent processing of identity from more dynamic facial information, particularly when the task demands are focused on identity recognition. These results provide novel evidence of the moment-to-moment brain signal variability involved in the identity of the self and others. The evidence presented here adds to a growing literature highlighting the relevance of neural variability for understanding brain-behavior relationships.