Attention Shifts and Latent Working Memories


Science  02 Dec 2016: Vol. 354, Issue 6316, pp. 1136-1139

Reactivation of latent working memories with transcranial magnetic stimulation

Nathan S. Rose,

Department of Psychiatry, University of Wisconsin, Madison, WI 53706, USA.

Department of Psychology, University of Notre Dame, Notre Dame, IN 46556, USA.

Neuroscience Training Program, University of Wisconsin, Madison, WI 53706, USA.

Coma Science Group, University of Liège, 4000 Liège, Belgium.

Department of Psychology, University of Wisconsin, Madison, WI 53706, USA.


The ability to hold information in working memory is fundamental for cognition. Contrary to the long-standing view that working memory depends on sustained, elevated activity, we present evidence suggesting that humans can hold information in working memory via “activity-silent” synaptic mechanisms. Using multivariate pattern analyses to decode brain activity patterns, we found that the active representation of an item in working memory drops to baseline when attention shifts away. A targeted pulse of transcranial magnetic stimulation produced a brief reemergence of the item in concurrently measured brain activity. This reactivation effect occurred and influenced memory performance only when the item was potentially relevant later in the trial, which suggests that the representation is dynamic and modifiable via cognitive control. The results support a synaptic theory of working memory.

The ability to mentally retain information in an accessible state, to manipulate it, and to use it to guide behavior is a critical building block for cognition. It has long been assumed that the neural basis for this working memory (WM) ability is elevated and persistent neuronal firing. This assumption has been called into question by recent proposals that information can be held in WM via synaptic mechanisms that do not require sustained, elevated brain activity.

Building on theoretical frameworks that information can be held in WM in one of several states of activation, we recorded neural activity while participants performed a multistep task in which two items were presented as memoranda for each trial. A cue indicated which item would be tested by the impending recognition memory probe, followed by the probe, then by a second cue, and then a second probe. There was equal probability following the first cue, but not the second, that the uncued item might be needed for an ensuing memory judgment. This procedure moves the uncued item into a different state than the cued item, which, by definition, is in the focus of attention. Cognitive theories refer to the intermediate state of this unattended memory item (UMI) as “activated long-term memory” (LTM)

For experiment 1, multivariate pattern analysis (MVPA) showed evidence for an active representation of the UMI that dropped to baseline levels. This suggests that information in WM (but outside of focal attention) can be maintained in a latent state via mechanisms other than sustained, elevated activity. Although a similar drop-to-baseline pattern is observed when participants are instructed to drop information from WM, here the UMI remained in WM because, when so instructed by the second cue, participants accurately reactivated it and used it to evaluate the final probe.

In three additional experiments, we tested the hypothesis that if a UMI is encoded in a distributed pattern of synaptic weights and held in a state that is more accessible than trial-irrelevant information, the readout from a nonspecific burst of activity filtered through this network might reveal this latent representation. This would be consistent with the idea that networks in the posterior cortex can be dynamically configured as matched filters to encode behaviorally relevant information.

Our results have important implications for the understanding of WM at many levels. They provide neural evidence for at least two levels of WM that are distinct from the default state of LTM representations. They are inconsistent with models positing just one level of WM storage. They also suggest that instead of “activated LTM,” a more apt label for the second level of WM would be “prioritized LTM.” Information can be held in WM in latent “activity-silent” traces. What might be the physiological bases of such representations? Computational models of WM have proposed that short-term synaptic plasticity could be the basis for the transient formation of weight-based networks that can represent information over short time periods.

Our results provide empirical evidence for the existence of a short-term plasticity mechanism that is likely to be fundamental to a wide range of cognitive functions involving attentional selection and may provide the building blocks for long-term potentiation mechanisms that support LTM. Therefore, our findings introduce a potential avenue for reactivating and strengthening representations that underlie many classes of high-level cognition.

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