Journal
CEREBRAL CORTEX
Volume 26, Issue 1, Pages 166-179Publisher
OXFORD UNIV PRESS INC
DOI: 10.1093/cercor/bhu189
Keywords
attention; fMRI; intraparietal sulcus; multivariate voxel pattern analysis; verbal; visual; working memory
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Funding
- F.R.S.-FNRS (Fund for Scientific Research FNRS, Belgium) [1.5.056.10]
- Belgian Science Policy [PAI-IUAP P7/11]
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Recent studies suggest common neural substrates involved in verbal and visual working memory (WM), interpreted as reflecting shared attention-based, short-term retention mechanisms. We used a machine-learning approach to determine more directly the extent to which common neural patterns characterize retention in verbal WM and visual WM. Verbal WM was assessed via a standard delayed probe recognition task for letter sequences of variable length. Visual WM was assessed via a visual array WM task involving the maintenance of variable amounts of visual information in the focus of attention. We trained a classifier to distinguish neural activation patterns associated with high- and low-visual WM load and tested the ability of this classifier to predict verbal WM load (high-low) from their associated neural activation patterns, and vice versa. We observed significant between-task prediction of load effects during WM maintenance, in posterior parietal and superior frontal regions of the dorsal attention network; in contrast, between-task prediction in sensory processing cortices was restricted to the encoding stage. Furthermore, between-task prediction of load effects was strongest in those participants presenting the highest capacity for the visual WM task. This study provides novel evidence for common, attention-based neural patterns supporting verbal and visual WM.
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