Abstract

The change detection task is a widely used paradigm to examine visual working memory processes. Participants memorize a set of items and then, try to detect changes in the set after a retention period. The negative slow wave (NSW) and contralateral delay activity (CDA) are event-related potentials in the EEG signal that are commonly used in change detection tasks to track working memory load, as both increase with the number of items maintained in working memory (set size). While the CDA was argued to more purely reflect the memory-specific neural activity than the NSW, it also requires a lateralized design and attention shifts prior to memoranda onset, imposing more restrictions on the task than the NSW. The present study proposes a novel change detection task in which both CDA and NSW can be measured at the same time. Memory items were presented bilaterally, but their distribution in the left and right hemifield varied, inducing a target imbalance or "net load." NSW increased with set size, whereas CDA increased with net load. In addition, a multivariate linear classifier was able to decode the set size and net load from the EEG signal. CDA, NSW, and decoding accuracy predicted an individual's working memory capacity. In line with the notion of a bilateral advantage in working memory, accuracy, and CDA data suggest that participants tended to encode items relatively balanced. In sum, this novel change detection task offers a basis to make use of converging neural measures of working memory in a comprehensive paradigm.

Full Text
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