Changing concepts of working memory

Ji, Wei; Husain, Masud; Bays, Paul M.

doi:10.1038/nn.3655

Cited by 935 publications

(931 citation statements)

References 99 publications

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“…It is also related to studies on visual working memory (50)(51)(52), especially the memory combination of categories and particulars (53). However, our study focuses on the integration of perceptual decoding and memory properties of low-and high-level features and the logical implications of this integration on decoding hierarchy whereas the previous studies do not.…”

Section: Discussionmentioning

confidence: 98%

Visual perception as retrospective Bayesian decoding from high- to low-level features

Ding

Cueva

Tsodyks

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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When a stimulus is presented, its encoding is known to progress from low-to high-level features. How these features are decoded to produce perception is less clear, and most models assume that decoding follows the same low-to high-level hierarchy of encoding. There are also theories arguing for global precedence, reversed hierarchy, or bidirectional processing, but they are descriptive without quantitative comparison with human perception. Moreover, observers often inspect different parts of a scene sequentially to form overall perception, suggesting that perceptual decoding requires working memory, yet few models consider how working-memory properties may affect decoding hierarchy. We probed decoding hierarchy by comparing absolute judgments of single orientations and relative/ordinal judgments between two sequentially presented orientations. We found that lower-level, absolute judgments failed to account for higher-level, relative/ordinal judgments. However, when ordinal judgment was used to retrospectively decode memory representations of absolute orientations, striking aspects of absolute judgments, including the correlation and forward/backward aftereffects between two reported orientations in a trial, were explained. We propose that the brain prioritizes decoding of higher-level features because they are more behaviorally relevant, and more invariant and categorical, and thus easier to specify and maintain in noisy working memory, and that more reliable higher-level decoding constrains less reliable lower-level decoding.Bayesian prior | interreport correlation | bidirectional tilt aftereffect | efficient coding | adaptation theory V isual stimuli evoke neuronal responses (a process termed encoding), which lead to our perceptual estimation of the stimuli (decoding). Experimental studies have firmly established that encoding is hierarchical, progressing from lower-level representations of simpler and less invariant features to higher-level representations of more complex and invariant features along visual pathways (1). Researchers have also studied decoding by using models to relate neuronal responses to perceptual estimation. Most models posit, explicitly or implicitly, that decoding follows the same low-to high-level hierarchy, often in the form of what we call the absolute-to-relative assumption (2-6). For example, these models may decode V1 responses to a line into a perceived orientation of, say 51.2°(or a distribution around it). Psychophysically, this is termed an absolute judgment. To determine the relationship between two lines, the models first decode each orientation separately and the two resulting absolute orientations are then compared. For instance, the two absolute orientations may be subtracted to obtain the angle between the lines (relative orientation), or the sign of the difference may be used to determine whether the second line is clockwise or counterclockwise from the first (ordinal orientation discrimination). Absolute orientation of a single line is a simpler, less invariant, lower-...

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Section: Discussionmentioning

confidence: 98%

Visual perception as retrospective Bayesian decoding from high- to low-level features

Ding

Cueva

Tsodyks

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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“…Instead, these results support the idea that responses proceed from integrative inference about the contents of working memory, an inference process slowed by context reinstatements that cause the intrusion of lure words into working memory. These reinstatements need not catastrophically interfere with maintenance; rather than occupying discrete "slots" in working memory, they may instead simply reduce the fidelity of the representation of the target set (Ma et al, 2014), leading to a slowed inference but not an incorrect response.…”

Section: Discussionmentioning

confidence: 99%

Refresh my memory: Episodic memory reinstatements intrude on working memory maintenance

Hoskin

Bornstein

Norman

et al. 2017

Preprint

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A fundamental question in memory research is how different forms of memory interact. Previous research has shown that when working memory (WM) is overloaded or maintenance is interrupted in short-term memory tasks, humans and animals can rely on episodic memory (EM) to support performance. Furthermore, episodic memory reactivation appears also to occur on its own (i.e., irrespective of demand), even during the short delays typically used in WM experiments. Based on these observations, we hypothesized that EM reinstatements would affect WM, even in the absence of any interference. Using novel behavioral and neural signatures of the effect of EM on WM, we show that EM introduces additional information into WM by reinstating incidental associations (context) present during initial encoding. The first two experiments establish that the influence of encoding context is evident both in errors (Experiment 1) and in slowing of responses (Experiment 2). Experiment 3 shows that fMRI evidence of EM reinstatement during the delay predicts response times on each trial. Modeling WM search using a Drift-Diffusion Model (DDM), we show that fits improve when trial drift rate varies with fMRI evidence for reinstatement during that trial's delay period. These results expose a previously hidden interaction between WM maintenance and EM replay, and raise new questions about the adaptive nature of the interplay between these mechanisms.

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“…Instead of the expected greater effect of foil proximity with greater load, proximity only influenced the d' measure of performance when memory load was low. I argued that the nature of the interaction between load and proximity would be able to help adjudicate between the competing accounts of working memory capacity: the slot model (Fukuda et al, 2010) and the flexible resource model (Ma et al, 2014). In particular, I argued that an effect of proximity at low load would provide support for the flexible resource allocation model while the lack of such an effect would support the slot model.…”

Section: Working Memory For Manual Gestures Discussionmentioning

confidence: 99%

Working memory for meaningless manual gestures.

Rudner

2015

Canadian Journal of Experimental Psychology / Revue canadienne

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Effects on working memory performance relating to item similarity have been linked to prior categorisation of representations in long-term memory. However, there is evidence from gesture processing that this link may not be obligatory. The present study investigated whether working memory for incidentally generated meaningless manual gestures is influenced by formational similarity and whether this effect is modulated by working-memory load. Results showed that formational similarity did lower performance, demonstrating that similarity effects are not dependent on prior categorisation. However, this effect was only found when working-memory load was low, supporting a flexible resource allocation model according to which it is the quality rather than quantity of working memory representations that determines performance. This interpretation is in line with proposals suggesting language modality specific allocation of resources in working memory.

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Changing concepts of working memory

Cited by 935 publications

References 99 publications

Visual perception as retrospective Bayesian decoding from high- to low-level features

Visual perception as retrospective Bayesian decoding from high- to low-level features

Refresh my memory: Episodic memory reinstatements intrude on working memory maintenance

Working memory for meaningless manual gestures.

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