Decoding working memory content from attentional biases

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作者
Emma Wu Dowd
John M. Pearson
Tobias Egner
机构
[1] Duke University,Department of Psychology & Neuroscience, Center for Cognitive Neuroscience, and Duke Institute for Brain Sciences
[2] The Ohio State University,Department of Psychology
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关键词
Working memory; Visual attention; Multivariate pattern classification; Attentional bias;
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摘要
What we are currently thinking influences where we attend. The finding that active maintenance of visual items in working memory (WM) biases attention toward memory-matching objects—even when WM content is irrelevant for attentional goals—suggests a tight link between WM and attention. To test whether this link is reliable enough to infer specific WM content from measures of attentional bias, we applied multivariate pattern classification techniques to response times from an unrelated visual search task during a WM delay. Single-trial WM content was successfully decoded from incidental attentional bias within an individual, highlighting the specificity and reliability of the WM-attention link. Furthermore, classifiers trained on a group of individuals predicted WM content in another, completely independent individual—implying a shared cognitive mechanism of memory-driven attentional bias. The existence of such classifiers demonstrates that memory-based attentional bias is both a robust and generalizable probe of WM.
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页码:1252 / 1260
页数:8
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