To bind or not to bind, that's the wrong question: Features and objects coexist in visual short-term memory

Geigerman, Shriradha; Verhaeghen, Paul; Cerella, John

doi:10.1016/j.actpsy.2016.04.004

Cited by 7 publications

(8 citation statements)

References 25 publications

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“…This led the researchers to conclude that VSTM is limited in both the number of objects and their precision. Supporting this conclusion are findings indicating that although manipulation of task requirements of either integrated objects or separate features may affect the type of representation used, both separate features and integrated objects are represented (Cowan, Blume, & Saults, 2013;Geigerman, Verhaeghen, & Cerella, 2016;Oberauer & Eichenberger, 2013;Vergauwe & Cowan, 2015). Alvarez and Cavanagh (2004) have suggested defining object complexity as visual informational load, or visual details contained in an object, measured based on processing speed in a visual-search task.…”

Section: Capacity For Complex Objectsmentioning

confidence: 99%

A two-level hierarchical framework of visual short-term memory

Yatziv

Kessler

2018

Journal of Vision

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Over the last couple of decades, a vast amount of research has been dedicated to understanding the nature and the architecture of visual short-term memory (VSTM), the mechanism by which currently relevant visual information is maintained. According to discrete-capacity models, VSTM is constrained by a limited number of discrete representations held simultaneously. In contrast, shared-resource models regard VSTM as limited in resources, which can be distributed flexibly between varying numbers of representations; and a new interference model posits that capacity is limited by interference among items. In this article, we begin by reviewing benchmark findings regarding the debate over VSTM limitations, focusing on whether VSTM storage is all-or-none and on whether object complexity affects capacity. After that, we put forward a hybrid framework of VSTM architecture, arguing that this system is composed of a two-level hierarchy of memory stores, each containing a different set of representations: (1) perceptual memory, a resourcelike level containing analog automatically formed representations of visual stimuli in varying degrees of activation, and (2) visual working memory, in which a subset of three to four items from perceptual memory are bound to conceptual representations and to their locations, thus conveying discrete (digital/symbolic) information which appears quantized. While perceptual memory has a large capacity and is relatively nonselective, visual working memory is restricted in the number of items that can be maintained simultaneously, and its content is regulated by a gating mechanism.

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Section: Capacity For Complex Objectsmentioning

confidence: 99%

A two-level hierarchical framework of visual short-term memory

Yatziv

Kessler

2018

Journal of Vision

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“…As a temporary online platform, visual working memory (VWM) encodes, maintains, and extracts visual information in a task-driven process (Geigerman, Verhaeghen, and Cerella 2016;McCants, Katus, and Eimer 2020). Due to its profound relation with other cognitive functions (attention: Kong & Fougnie, 2019; long-term memory: Fukuda & Woodman, 2017;Hartshorne & Makovski, 2019; decision making: Schapiro, Josić, et al, 2022), the limited storage and flexible process of VWM have become a magnet for studies in past two decades (T. Gao et al 2011;X.…”

Section: Introductionmentioning

confidence: 99%

Dimension-Based Retro-Cue Benefit in Working Memory Does Not Require Unfocused Dimension Removal

Liu,

Guo,

Lin

et al. 2024

Preprint

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Attention guides flexibly allocation of limited visual working memory (VWM) resources among representations. Within the maintenance phase of VWM, previous researchers presented retro-cues orienting to a probed feature across all multifeature stimuli and found a stable feature-based retro-cue benefit: VWM performance for cued feature was better than no/neutral-cue baseline. Two accounts might explain the mechanism: the reconstruction account suggests for separation of integrated representations, weighting on focused feature representations and removing unfocused ones; nevertheless, the priority account supports reservation and rehearsal of integrated representations with a ready state for follow-up comparison on focused feature. One distinct point between these accounts is whether the unfocused feature is impaired in VWM storage. In the current study, we used coloured, oriented bars as memoranda and manipulated the number of retro-cues to investigate these accounts. Double-cue trials displayed two sequential retro-cues orienting to different features. The single cue and the second cue in the double-cue condition are valid. Experiment 1 adopted the change detection task and three cue type conditions (no-cue, single-cue, double-cue); and in the subsequent two experiments, we elevated task difficulties and decreased expectations on cue types respectively. Our results across three experiments showed a stable pattern: VWM for the refocused feature in double-cue trials was better than no/neutral-cue baseline but was not different from those for the focused feature in single-cue trials. These findings indicate the lack of attention shift cost for features in VWM, which demonstrates that the unfocused feature in VWM is not impaired, supporting for the priority account.

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“…An important aspect of the representational format in WM is whether visual features of an object are bound together to form an integrated representation [8][9][10] , or are maintained separately as flat sets and bound indirectly by a shared location [11][12][13][14][15] . WM is a system that prioritises task-relevant information, and representational states may be dynamic, holding both feature-based and object-based representations 16,17 . Furthermore, tasks can be designed to bias subjects towards maintaining either features or bound objects 18 .…”

Section: Introductionmentioning

confidence: 99%

“…feature-based and object-based representations 16,17 . Furthermore, tasks can be designed to bias subjects towards maintaining either features or bound objects 18 .…”

mentioning

confidence: 99%

Working memory as a representational template for reinforcement learning

Shibata,

Klar,

Fallon

et al. 2024

Preprint

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Working memory (WM) and reinforcement learning (RL) both influence decision-making, but how they interact to affect behaviour remains unclear. We assessed whether RL is influenced by the format of visual stimuli in WM, either feature-based or unified, object-based representations. In a pre-registered paradigm, participants learned stimulus-action combinations, mapping four stimuli onto two feature dimensions to one of two actions through probabilistic feedback. In parallel, participants retained the RL stimulus in WM and were asked to recall this stimulus after each trial. Crucially, the format of representation probed in WM was manipulated, with blocks encouraging either separate features or bound objects to be remembered. Incentivising a feature-based WM representation facilitated feature-based learning, shown by an improved choice strategy. This reveals a role of WM in providing sustained internal representations that are harnessed by RL, providing a framework by which these two cognitive processes cooperate.

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To bind or not to bind, that's the wrong question: Features and objects coexist in visual short-term memory

Cited by 7 publications

References 25 publications

A two-level hierarchical framework of visual short-term memory

A two-level hierarchical framework of visual short-term memory

Dimension-Based Retro-Cue Benefit in Working Memory Does Not Require Unfocused Dimension Removal

Working memory as a representational template for reinforcement learning

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