The Nature of Affect in the Structural Mere Exposure Effect

Иванчей, Иван; Asvarisch, Alexey

doi:10.2139/ssrn.3275988

Cited by 4 publications

(2 citation statements)

References 53 publications

(52 reference statements)

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“…Future studies could also investigate additional characteristics of the revealed EC effect, such as its automaticity or controllability. For instance, in affective-priming tasks, stimuli with emotional valence automatically enhance the detection of stimuli with the same valence (Fazio, Sanbonmatsu, Powell, & Kardes, 1986; Ivanchei & Asvarisch, 2018). Using the present paradigm, participants might undergo an affective-priming task in which primes could be new strings that follow the positive or the negative grammar.…”

Section: Discussionmentioning

confidence: 99%

Evaluative conditioning of artificial grammars: Evidence that subjectively-unconscious structures bias affective evaluations of novel stimuli.

Jurchiș¹,

Costea²,

Dienes³

et al. 2020

Journal of Experimental Psychology: General

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Evaluative conditioning (EC) refers to the acquisition of emotional valence by an initially-neutral stimulus (conditioned stimulus; CS), after being paired with an emotional stimulus (unconditioned stimulus; US). An important issue regards whether, when participants are unaware of the CS-US contingency, the affective valence can generalize to new stimuli that share similarities with the CS. Previous studies have shown that generalization of EC effects appears only when participants are aware of the contingencies, but we suggest that this is because (a) the contingencies typically used in these studies are salient and easy to detect consciously, and (b) the performance-based measures of awareness (so-called "objective measures"), typically used in these studies, tend to overestimate the amount of available conscious knowledge. We report a preregistered study in which participants (N = 217) were exposed to letter strings generated from two complex artificial grammars that are difficult to decipher consciously. Stimuli from one grammar were paired with positive USs, while those from the other grammar were paired with negative USs. Subsequently, participants evaluated new, previously-unseen, stimuli from the positively-conditioned grammar more positively than new stimuli from the negatively-conditioned grammar. Importantly, this effect appeared even when trial-by-trial subjective measures indicated lack of relevant conscious knowledge. We provide evidence for the generalization of EC effects even without subjective awareness of the structures that enable those generalizations.

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Section: Discussionmentioning

confidence: 99%

Evaluative conditioning of artificial grammars: Evidence that subjectively-unconscious structures bias affective evaluations of novel stimuli.

Jurchiș¹,

Costea²,

Dienes³

et al. 2020

Journal of Experimental Psychology: General

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“…Schematic expectations for music, according to the predictive-coding model, can unfold at multiple levels, whether they be stylistic (hip-hop, jazz), structural (melody, tonality), temporal (rhythm, meter), and/or acoustic (pitch, timbre) factors (Guo & Koelsch, 2016; Huron, 2006; Justus & Bharucha, 2001; Margulis, 2014). The predictive-coding model can account for the mere-exposure effect by positing that repeated exposure increases the efficiency of predictions (Ivanchei & Asvarisch, 2018), resulting in increased liking of stimuli that carry predictive value (Braem & Trapp, 2019).…”

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confidence: 99%

Generating New Musical Preferences From Multilevel Mapping of Predictions to Reward

Kathios,

Sachs,

Zhang

et al. 2023

Psychol Sci

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Much of what we know and love about music hinges on our ability to make successful predictions, which appears to be an intrinsically rewarding process. Yet the exact process by which learned predictions become pleasurable is unclear. Here we created novel melodies in an alternative scale different from any established musical culture to show how musical preference is generated de novo. Across nine studies ( n = 1,185), adult participants learned to like more frequently presented items that adhered to this rapidly learned structure, suggesting that exposure and prediction errors both affected self-report liking ratings. Learning trajectories varied by music-reward sensitivity but were similar for U.S. and Chinese participants. Furthermore, functional MRI activity in auditory areas reflected prediction errors, whereas functional connectivity between auditory and medial prefrontal regions reflected both exposure and prediction errors. Collectively, results support predictive coding as a cognitive mechanism by which new musical sounds become rewarding.

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