Dissociable mechanisms underlying individual differences in visual working memory capacity

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Abstract

Individuals scoring relatively high on measures of working memory tend to be more proficient at controlling attention to minimize the effect of distracting information. It is currently unknown whether such superior attention control abilities are mediated by stronger suppression of irrelevant information, enhancement of relevant information, or both. Here we used steady-state visual evoked potentials (SSVEPs) with the Eriksen flanker task to track simultaneously the attention to relevant and irrelevant information by tagging target and distractors with different frequencies. This design allowed us to dissociate attentional biasing of perceptual processing (via SSVEPs) and stimulus processing in the frontal cognitive control network (via time-frequency analyses of EEG data). We show that while preparing for the upcoming stimulus, high- and low-WMC individuals use different strategies: High-WMC individuals show attentional suppression of the irrelevant stimuli, whereas low-WMC individuals demonstrate attentional enhancement of the relevant stimuli. Moreover, behavioral performance was predicted by trial-to-trial fluctuations in strength of distractor-suppression for high-WMC participants. We found no evidence for WMC-related differences in cognitive control network functioning, as measured by midfrontal theta-band power. Taken together, these findings suggest that early suppression of irrelevant information is a key underlying neural mechanism by which superior attention control abilities are implemented. (C) 2014 Elsevier Inc. All rights reserved.

Original languageEnglish
Pages (from-to)197-206
Number of pages10
JournalNeuroimage
Volume99
DOIs
Publication statusPublished - 1-Oct-2014

Keywords

  • DOWN SUPPRESSION DEFICIT
  • LATENT-VARIABLE APPROACH
  • COGNITIVE CONTROL
  • STROOP TASK
  • ATTENTIONAL CAPTURE
  • THETA OSCILLATIONS
  • FLUID INTELLIGENCE
  • NEURAL EFFICIENCY
  • RESPONSE CONFLICT
  • GOAL-NEGLECT

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