Theoretical distinction between functional states in working memory and their corresponding neural states

Stokes, Mark G.; Muhle-Karbe, Paul S.; Myers, Norman

doi:10.1080/13506285.2020.1825141

Cited by 45 publications

(46 citation statements)

References 107 publications

(136 reference statements)

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“…Despite apparent similarities, TMS perturbations impact working memory performance [5,6,[42][43][44], while pinging does not [7,45] (see also chapter 4 of [46]). This suggested that these approaches could be interacting with fundamentally different neural mechanisms [7,47]. Indeed, we found through the reanalysis of the data of [6]…”

Section: Differential Mechanisms For Pinging-and Tms-induced Reactivationsmentioning

confidence: 78%

Pinging the brain with visual impulses reveals electrically active, not activity-silent, working memories

2021

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Persistently active neurons during mnemonic periods have been regarded as the mechanism underlying working memory maintenance. Alternatively, neuronal networks could instead store memories in fast synaptic changes, thus avoiding the biological cost of maintaining an active code through persistent neuronal firing. Such “activity-silent” codes have been proposed for specific conditions in which memories are maintained in a nonprioritized state, as for unattended but still relevant short-term memories. A hallmark of this “activity-silent” code is that these memories can be reactivated from silent, synaptic traces. Evidence for “activity-silent” working memory storage has come from human electroencephalography (EEG), in particular from the emergence of decodability (EEG reactivations) induced by visual impulses (termed pinging) during otherwise “silent” periods. Here, we reanalyze EEG data from such pinging studies. We find that the originally reported absence of memory decoding reflects weak statistical power, as decoding is possible based on more powered analyses or reanalysis using alpha power instead of raw voltage. This reveals that visual pinging EEG “reactivations” occur in the presence of an electrically active, not silent, code for unattended memories in these data. This crucial change in the evidence provided by this dataset prompts a reinterpretation of the mechanisms of EEG reactivations. We provide 2 possible explanations backed by computational models, and we discuss the relationship with TMS-induced EEG reactivations.

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Section: Differential Mechanisms For Pinging-and Tms-induced Reactivationsmentioning

confidence: 78%

Pinging the brain with visual impulses reveals electrically active, not activity-silent, working memories

2021

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“…Some have interpreted these results as consistent with the idea that whereas prioritized memory items (PMI) are held in an active state, UMIs may be maintained as “activity-silent” traces encoded in synaptic weights (Barak & Tsodyks, 2014; Stokes, 2015). Although this possibility remains a topic of vigorous debate (Christophel et al, 2018; Schneegans & Bays, 2017; Sprague et al, 2016; Stokes et al, 2020), the present report does not relate directly to this question. Instead, of primary relevance here are more recent empirical results suggesting that, rather than producing a decline to baseline, deprioritization may produce a representational transformation of an item into a different, but still active, format.…”

Section: Introductionmentioning

confidence: 58%

Priority-based transformations of stimulus representation in visual working memory

Wan

Menendez

Postle

2021

Preprint

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How does the brain prioritize among the contents of working memory to appropriately guide behavior? Using inverted encoding modeling (IEM), previous work (Wan et al., 2020) showed that unprioritized memory items (UMI) are actively represented in the brain but in a “flipped”, or opposite, format compared to prioritized memory items (PMI). To gain insight into the mechanisms underlying the UMI-to-PMI representational transformation, we trained recurrent neural networks (RNNs) with an LSTM architecture to perform a 2-back working memory task. Visualization of the LSTM hidden layer activity using Principle Component Analysis (PCA) revealed that the UMI representation is rotationally remapped to that of PMI, and this was quantified and confirmed via demixed PCA. The application of the same analyses to the EEG dataset of Wan et al. (2020) revealed similar rotational remapping between the UMI and PMI representations. These results identify rotational remapping as a candidate neural computation employed in the dynamic prioritization within contents of working memory.

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“…For example, Cowan (1995Cowan ( , 2005 proposed that representations stored in the passive state (also called the activated part of LTM) are likely to be forgotten due to decay over time and interference (e.g., perceptual interference, interference from other cognitive processes, and competition among memory representations). However, some researchers have proposed that memory representations in the passive state could be protected from decay and shielded from interaction with the current task to minimize interference from the currently prioritized cognition or activity-based representations (de Vries et al, 2020;Muhle-Karbe et al, 2021;Stokes, 2015;Stokes et al, 2020). Thus, the passive state could be regarded as being protective, preventing information loss of the VWM representations.…”

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confidence: 99%

The passive state: A protective mechanism for information in working memory tasks.

Zhang¹,

C²,

Sun³

et al. 2022

Journal of Experimental Psychology: Learning, Memory, and Cogni

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Memory representations can be stored in a passive state in a visual working memory (VWM) task. However, it remains unclear whether the representations stored in the passive state are prone to interference and decay. To explore this issue, we asked participants to successively remember two sets of memory items (M1 and M2) in three test manners: a combined test (both M1 and M2 are probed simultaneously), a backward test (probe M2 first and M1 second), or a forward test (probe M1 first and M2 second). We found that the contralateral delay activity (CDA) amplitude after the onset of M2 only tracked M2 independently of M1 in the two separate tests (Experiments 1-3), and the accuracy of M1 was well above chance. These results implied that the M1 representations had been transferred from the online state into the passive state after the onset of M2. Furthermore, the accuracy of M1 (two representations were transferred from the online state into the passive state and retrieved later) in the backward test was worse than M2 (2 representations in the online state throughout) in the backward test (Experiments 1-2), but was comparable to M1 (two representations were transferred from the online state into the passive state and retrieved first) in the forward test (Experiment 2). These results demonstrated that the memory representations were impaired during state switching. Importantly, once the representations had been stored in the passive state, they were robust with little memory loss during latent retention.

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Theoretical distinction between functional states in working memory and their corresponding neural states

Cited by 45 publications

References 107 publications

Pinging the brain with visual impulses reveals electrically active, not activity-silent, working memories

Pinging the brain with visual impulses reveals electrically active, not activity-silent, working memories

Priority-based transformations of stimulus representation in visual working memory

The passive state: A protective mechanism for information in working memory tasks.

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