The impact of emotional valence on generalization gradients

Alcalá, José A.; Martínez-Tomás, Celia; Urcelay, Gonzalo P; Hinojosa, José A

Abstract

Generalization enables individuals to respond to novel stimuli based on previous experiences. The degree to which organisms respond is determined by their physical resemblance to the original conditioned stimulus (CS+), with a stronger response elicited by more similar stimuli, resulting in similarity-based generalization gradients. Recent research showed that cognitive or conceptual dimensions also result in gradients similar to those observed with manipulations of physical dimensions. Such findings suggest that attributes beyond physical similarity play a role in shaping generalization gradients. However, despite its adaptive relevance for survival, there is no study exploring the effectiveness of affective dimensions in shaping generalization gradients. In two experiments (135 Spanish and 150 English participants, respectively), we used an online predictive learning task, in which different stimuli (words and Gabor patches) were paired with the presence - or absence - of a fictitious shock. After training, we assessed whether valence (i.e., hedonic experience) conveyed by words shape generalization gradients. In Experiment 1, the outcome expectancy decreased monotonically with variations in valence of Spanish words, mirroring the gradient obtained with the physical dimension (line orientation). In Experiment 2, conducted with English words, a similar gradient was observed when non-trained (i.e., generalization) words varied along the valence dimension, but not when words were of neutral valence. The consistency of these findings across two different languages strengthens the reliability and validity of the affective dimension as a determinant of generalization gradients. Furthermore, our data highlight the importance of considering the role of affective features in generalization responses, advancing the interplay between emotion, language, and learning. [Abstract copyright: © 2024. The Author(s).]

• Journal Article Type: Article
• Acceptance Date: Dec 26, 2023
• Online Publication Date: Jan 16, 2024
• Publication Date: Jan 16, 2024
• Deposit Date: Jun 11, 2024
• Publicly Available Date: Jun 12, 2024
• Print ISSN: 1069-9384
• Electronic ISSN: 1531-5320
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.3758/s13423-023-02450-8
• Keywords: Generalization gradients, Valence, Language, Predictive learning, Emotion
• Public URL: https://nottingham-repository.worktribe.com/output/30927660
• Publisher URL: https://link.springer.com/article/10.3758/s13423-023-02450-8