Temporal Expectations Guide Dynamic Prioritization in Visual Working Memory through Attenuated α Oscillations

  • van Ede F
  • Niklaus M
  • Nobre A
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Abstract

Although working memory is generally considered a highly dynamic mnemonic store, popular laboratory tasks used to understand its psychologicalandneuralmechanisms(such aschangedetectionandcontinuousreproduction) oftenremain relatively “static,” involving the retention ofa set number ofitems throughout a shared delay interval. In the current study, we investigated visual workingmemoryin a more dynamic setting, and assessed the following: (1) whether internally guided temporal expectations can dynamically and reversibly prioritize individual mnemonic items at specific times at which they are deemedmost relevant; and (2) the neural substrates that support such dynamic prioritization. Participants encoded two differently colored oriented bars into visual working memory to retrieve the orientation of one bar with a precision judgment when subsequently probed. To test for the flexible temporal control to access and retrieve remembered items, we manipulated the probability for each ofthe two bars to be probed over time, and recorded EEG in healthy human volunteers. Temporal expectations had a profound influence on working memory performance, leading to faster access times as well as more accurate orientation reproductions for items that were probed at expected times. Furthermore, this dynamic prioritization was associated with the temporally specific attenuation of contralateral ␣ (8–14 Hz) oscillations that, moreover, predicted working memoryaccess times on a trial-by-trial basis.Weconclude that attentional prioritization in workingmemorycan be dynamically steered by internally guided temporal expectations, and is supported by the attenuation of␣oscillations in task-relevant sensory brain areas

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van Ede, F., Niklaus, M., & Nobre, A. C. (2017). Temporal Expectations Guide Dynamic Prioritization in Visual Working Memory through Attenuated α Oscillations. The Journal of Neuroscience, 37(2), 437–445. https://doi.org/10.1523/jneurosci.2272-16.2017

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