Crowding in Visual Working Memory Reveals Its Spatial Resolution and the Nature of Its Representations

Tamber-Rosenau, Benjamin J.; Fintzi, Anat R.; Marois, René

doi:10.1177/0956797615592394

Cited by 27 publications

(37 citation statements)

References 30 publications

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“…Unless care is taken, increasing set size decreases the spacing between stimuli and increases the degree of crowding. Such crowding effects have also been shown in memory experiments (Tamber-Rosenau, Fintzi, & Marois, 2015). Another phenomena that can be confounded with set size is stimulus heterogeneity.…”

Section: Alternative Theories Of Change Detectionmentioning

confidence: 58%

“…Our second subgoal is to measure set-size effects that are purely attentional and not due to nonattentional phenomena such as crowding (Tamber-Rosenau et al, 2015), stimulus heterogeneity (Lin & Luck, 2009), and other configural phenomena between stimuli (Silvis & Shapiro, 2014). To do this, rather than manipulate set size, we manipulate the number of relevant stimuli using a 100% valid precue (e.g.…”

Section: Our Studymentioning

confidence: 99%

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Set-size effects in change detection depend on failures of retrieval and/or comparison and not on perception, encoding or storage

Moreland

Palmer

Boynton

2020

Preprint

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needs to be no more than 250 words (currently 250)Significance section needs to be no more than 100 words (currently 69) AbstractSet-size effects in change detection is often used to investigate the capacity limits of dividing attention. Such capacity limits have been attributed to a variety of processes including perception, memory encoding, memory storage, memory retrieval, comparison and decision.In this study, we investigated the locus of the effect of increasing set size from 1 to 2. To measure purely attentional effects and not other phenomena such as crowding, a precue was used to manipulate relevant set size and keep the display constant across conditions. The task was to detect a change in the orientation of 1 or 2 Gabor patterns. The locus of the capacity limits was determined by varying when observers were cued to the only stimulus that was relevant. We began by measuring the baseline set-size effect in an initial experiment. In the next experiment, a 100% valid postcue was added to test for an effect of decision. This postcue did not change the set-size effects. In the critical experiments, a 100% valid cue was provided during the retention interval between displays, or only one stimulus was presented in the second display (local recognition). For both of these conditions, there was little or no set-size effect. This pattern of results was found for both hard-to-discriminate stimuli typical of perception experiments and easy-to-discriminate stimuli typical of memory experiments.These results are consistent with capacity limits in memory retrieval, and/or comparison. For these set sizes, the results are not consistent with capacity limits in perception, memory encoding or memory storage. Set-Size Effects in Change Detection3 Significance SectionThe change detection paradigm is often used to demonstrate effects of divided attention. But it is not clear whether these effects are due to perception, memory, or judgment and decision. In this article, we present new evidence that the divided attention effect in change detection is due to limits in memory retrieval or comparison processes. These results are not consistent with limits in perception, memory encoding or memory storage.

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Section: Alternative Theories Of Change Detectionmentioning

confidence: 58%

Section: Our Studymentioning

confidence: 99%

Set-size effects in change detection depend on failures of retrieval and/or comparison and not on perception, encoding or storage

Moreland

Palmer

Boynton

2020

Preprint

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“…One possibility is that we did not observe an effect of proximity on WM precision because, when perceptual competition occurs between one item held in working memory and one item being displayed, the effects are more subtle and only the effect of proximity on P NT reaches significance. The fact that, with simultaneous presentation and a greater distance between stimuli, others have observed an effect of competition on P NT but not precision 21, 23 , supports the idea that the effect of competition on precision is somehow weaker. Alternatively, it is possible that the effect of proximity on P NT represents a different kind of competition to the effect of proximity on precision.…”

Section: Discussionmentioning

confidence: 69%

Competitive interactions affect working memory performance for both simultaneous and sequential stimulus presentation

Ahmad

Swan

Bowman

et al. 2017

Sci Rep

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Competition between simultaneously presented visual stimuli lengthens reaction time and reduces both the BOLD response and neural firing. In contrast, conditions of sequential presentation have been assumed to be free from competition. Here we manipulated the spatial proximity of stimuli (Near versus Far conditions) to examine the effects of simultaneous and sequential competition on different measures of working memory (WM) for colour. With simultaneous presentation, the measure of WM precision was significantly lower for Near items, and participants reported the colour of the wrong item more often. These effects were preserved when the second stimulus immediately followed the first, disappeared when they were separated by 500 ms, and were partly recovered (evident for our measure of mis-binding but not WM precision) when the task was altered to encourage participants to maintain the sequentially presented items together in WM. Our results show, for the first time, that competition affects the measure of WM precision, and challenge the assumption that sequential presentation removes competition.

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“…For our orientation experiment, the superiority of the hybrid model, with oblique effects included, suggests that there are other sources of trial-to-trial variability beyond just the oblique effect. There could be other stimulus-dependent effects arising from interactions among stimuli, such as ensemble coding effects (Brady & Alvarez, 2015a, 2015b; Johnson, Spencer, Luck, & Schoner, 2009), perceptual grouping effects (Woodman, Vecera, & Luck, 2003; Xu & Chun, 2007) and effects of visual crowding (Tamber-Rosenau, Fintzi, & Marois, 2015). For example, if some elements in a particular visual display can be perceptually grouped or “chunked” as a single unit for storage, this could alter the effective number of items that can be maintained in working memory, which in turn would lead to variability in VWM performance across displays containing the same physical number of items.…”

Section: Discussionmentioning

confidence: 99%

Accounting for stimulus-specific variation in precision reveals a discrete capacity limit in visual working memory.

Pratte¹,

Park²,

Rademaker³

et al. 2017

Journal of Experimental Psychology: Human Perception and Perfor

103

154

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If we view a visual scene that contains many objects, then momentarily close our eyes, some details persist while others seem to fade. Discrete models of visual working memory (VWM) assume that only a few items can be actively maintained in memory, beyond which pure guessing will emerge. Alternatively, continuous resource models assume that all items in a visual scene can be stored with some precision. Distinguishing between these competing models is challenging, however, as resource models that allow for stochastically variable precision (across items and trials) can produce error distributions that resemble random guessing behavior. Here, we evaluated the hypothesis that a major source of variability in VWM performance arises from systematic variation in precision across the stimuli themselves; such stimulus-specific variability can be incorporated into both discrete-capacity and variable-precision resource models. Participants viewed multiple oriented gratings, and then reported the orientation of a cued grating from memory. When modeling the overall distribution of VWM errors, we found that the variable-precision resource model outperformed the discrete model. However, VWM errors revealed a pronounced “oblique effect”, with larger errors for oblique than cardinal orientations. After this source of variability was incorporated into both models, we found that the discrete model provided a better account of VWM errors. Our results demonstrate that variable precision across the stimulus space can lead to an unwarranted advantage for resource models that assume stochastically variable precision. When these deterministic sources are adequately modeled, human working memory performance reveals evidence of a discrete capacity limit.

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Crowding in Visual Working Memory Reveals Its Spatial Resolution and the Nature of Its Representations

Cited by 27 publications

References 30 publications

Set-size effects in change detection depend on failures of retrieval and/or comparison and not on perception, encoding or storage

Set-size effects in change detection depend on failures of retrieval and/or comparison and not on perception, encoding or storage

Competitive interactions affect working memory performance for both simultaneous and sequential stimulus presentation

Accounting for stimulus-specific variation in precision reveals a discrete capacity limit in visual working memory.

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