A neural model of retrospective attention in visual working memory.

Citation data:

Cognitive psychology, ISSN: 1095-5623, Vol: 100, Page: 43-52

Publication Year:
2018
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PMID:
29272732
DOI:
10.1016/j.cogpsych.2017.12.001
Author(s):
Bays, Paul M; Taylor, Robert
Publisher(s):
Elsevier BV
Tags:
Psychology; Social Sciences; Computer Science
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article description
An informative cue that directs attention to one of several items in working memory improves subsequent recall of that item. Here we examine the mechanism of this retro-cue effect using a model of short-term memory based on neural population coding. Our model describes recalled feature values as the output of an optimal decoding of spikes generated by a tuned population of neurons. This neural model provides a better account of human recall data than an influential model that assumes errors can be described as a mixture of normally distributed noise and random guesses. The retro-cue benefit is revealed to be consistent with a higher firing rate of the population encoding the cued versus uncued items, with no difference in tuning specificity. Additionally, a retro-cued item is less likely to be swapped with another item in memory, an effect that can also be explained by greater activity of the underlying population. These results provide a parsimonious account of the effects of retrospective attention on recall and demonstrate a principled method for investigating neural representations with behavioral tasks.