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Working memory load dissociates contingency learning and item-specific proportion-congruent effects.

Giacomo SpinelliKesheni KrishnaJason R PerryStephen J Lupker
Published in: Journal of experimental psychology. Learning, memory, and cognition (2020)
A consistent finding in the Stroop literature is that congruency effects (i.e., the color-naming latency difference between words presented in incongruent vs. congruent colors) are larger for mostly-congruent items (e.g., the word RED presented most often in red) than for mostly-incongruent items (e.g., the word GREEN presented most often in yellow). This "item-specific proportion-congruent effect" might be produced by a conflict-adaptation process (e.g., fully focus attention to the color when the word GREEN appears) and/or by a more general learning mechanism of stimulus-response contingencies (e.g., respond "yellow" when the word GREEN appears). Under the assumption that limited-capacity resources are necessary for learning stimulus-response contingencies, we examined the contingency-learning account using both Stroop and nonconflict (i.e., noncolor words written in colors) versions of a color identification task while participants maintained a working memory (WM) load. Consistent with the contingency-learning account, WM load modulated people's ability to learn contingencies in the nonconflict task. In contrast, across 3 experiments, WM load did not affect the item-specific proportion-congruent effect in the Stroop task even though we employed a design (the "2-item set" design) in which contingency learning should be the dominant process. These results imply that the item-specific proportion-congruent effect is not merely a byproduct of contingency learning but a manifestation of reactive control, a mode of control engagement that may be especially useful when WM resources are scarce. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
Keyphrases
  • working memory
  • transcranial direct current stimulation
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  • systematic review
  • magnetic resonance imaging
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  • computed tomography
  • social media