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Emotional congruency facilitates statistical learning

Year: 2020
Type: preprint
Abstract: Detecting regularities and extracting patterns is a vital skill that helps us to organize complex information in our environments. Statistical learning, a process through which we detect regularities by attending to the relationships between cues in our environment, contributes to knowledge acquisition across myriad domains. However, less is known about how emotional cues—specifically facial configurations of emotion—influence statistical learning. These cues pose challenges for statistical learning because they can vary both inter- and intra-individually and across contexts. Thus, the degree of congruence between the emotional and statistical information may diverge in important ways. In the current study, we tested two pre-registered aims to advance knowledge about emotional congruency and statistical learning: (1) We examined statistical learning of emotional information when compared to non-emotional information, and (2) We assessed how congruency influences regularity extraction. Using data from two independent samples (total N=671; 49% female, 50% male, 1% “other” or did not report gender; <1% American Indian or Alaskan Native; 14% Asian, 14% Black or African American, 5% Hispanic or Latinx; 4% Multiracial; 63% White), we demonstrated statistical learning across emotional cues similar to non-emotional cues (i.e., shapes). We also established that congruent cues facilitated statistical learning but found little evidence that incongruent information interfered with statistical learning. The results shed light on the application of a well-studied cognitive skill to the social domain and fill a knowledge gap about how cue congruency impacts statistical learning, including how we use emotional cues to make predictions in our social world.
DOI: 10.31234/osf.io/vsbgu
Language: English
Open Access status: green
OpenAlex ID: W3162565725
Cites: 41
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Related to: 10