3 research outputs found
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Evaluative conditioning of artificial grammars: evidence that subjectively-unconscious structures bias affective evaluations of novel stimuli
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 ef-fects 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 “ob-jective 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, partici-pants 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 with-out subjective awareness of the structures that enable those generalizations
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Implicit learning of regularities followed by realistic body movements in virtual reality
The existence of implicit (unconscious) learning has been demonstrated in several laboratory paradigms. Researchers have also suggested that it plays a role in complex real-life human activities. For instance, in social situations, we may follow unconscious behaviour scripts or intuitively anticipate the reaction of familiar persons based on non-conscious cues. Still, it is difficult to make inferences about the involvement of implicit learning in realistic contexts, given that this phenomenon has been demonstrated, almost exclusively, using simple artificial stimuli (e.g., learning structured patterns of letters). In addition, recent analyses show that the amount of unconscious knowledge learned in these tasks has been overestimated by random measurement error. To overcome these limitations, we adapted the Artificial Grammar Learning (AGL) task, and exposed participants (N = 93), in virtual reality, to a realistic agent that executed combinations of boxing punches. Unknown to participants, the combinations were structured by a complex artificial grammar. In a subsequent test phase, participants accurately discriminated novel grammatical from non-grammatical combinations, showing they had acquired the grammar. For measuring awareness, we used trial-by-trial subjective scales, and an analytical method that accounts for the possible overestimation of unconscious knowledge due to regression to the mean. These methods conjointly showed strong evidence for implicit and for explicit learning. The present study is the first to show that humans can implicitly learn, in VR, knowledge regarding realistic body movements, and, further, that implicit knowledge extracted in AGL is robust when accounting for its possible inflation by random measurement error
Implicit and explicit learning of socio-emotional information in a dynamic interaction with a virtual avatar
Implicit learning (IL) deals with the non-conscious acquisition of structural regularities from the environment. IL is often deemed essential for acquiring regularities followed by social stimuli (e.g. other persons’ behavior), hence is hypothesized to play a role in typical social functioning. However, our understanding of how this process might operate in social contexts is limited for two main reasons. First, while IL is highly sensitive to the characteristics of the surface stimuli upon which it operates, most IL studies have used surface stimuli with limited social validity (e.g. letters, symbols, etc.). Second, while the social environment is dynamic (i.e. our behaviors and reactions influence those of our social partners and vice-versa), the bulk of IL research employed noninteractive paradigms. Using a novel task, we examine whether IL is involved in the acquisition of regularities from a dynamic interaction with a realistic real-life-like agent. Participants (N = 115) interacted with a cinematic avatar that displayed different facial expressions. Their task was to regulate the avatar’s expression to a specified level. Unbeknownst to them, an equation mediated the relationship between their responses and the avatar’s expressions. Learning occurred in the task, as participants gradually increased their ability to bring the avatar in the target state. Subjective measures of awareness revealed that participants acquired both implicit and explicit knowledge from the task. This is the first study to show that IL operates in interactive situations upon socially relevant surface stimuli, facilitating future investigations of the role that IL plays in (a)typical social functioning.SCOPUS: ar.jinfo:eu-repo/semantics/publishe