Investigating habits in humans with a symmetrical outcome-revaluation task.
Behav Res Methods
; 55(5): 2687-2705, 2023 08.
Article
em En
| MEDLINE
| ID: mdl-35867208
ABSTRACT
The translation of the outcome-devaluation paradigm to study habit in humans has yielded interesting insights but proven to be challenging. We present a novel, outcome-revaluation task with a symmetrical design, in the sense that half of the available outcomes are always valuable and the other half not-valuable. In the present studies, during the instrumental learning phase, participants learned to respond (Go) to certain stimuli to collect valuable outcomes (and points) while refraining to respond (NoGo) to stimuli signaling not-valuable outcomes. Half of the stimuli were short-trained, while the other half were long-trained. Subsequently, in the test phase, the signaled outcomes were either value-congruent with training (still-valuable and still-not-valuable), or value-incongruent (devalued and upvalued). The change in outcome value on value-incongruent trials meant that participants had to flexibly adjust their behavior. At the end of the training phase, participants completed the self-report behavioral automaticity index - providing an automaticity score for each stimulus-response association. We conducted two experiments using this task, that both provided evidence for stimulus-driven habits as reflected in poorer performance on devalued and upvalued trials relative to still-not-valuable trials and still-valuable trials, respectively. While self-reported automaticity increased with longer training, behavioral flexibility was not affected. After extended training (Experiment 2), higher levels of self-reported automaticity when responding to stimuli signaling valuable outcomes were related to more 'slips of action' when the associated outcome was subsequently devalued. We conclude that the symmetrical outcome-revaluation task provides a promising paradigm for the experimental investigation of habits in humans.
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01-internacional
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MEDLINE
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Condicionamento Operante
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Limite:
Humans
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article