Academic journal article Memory & Cognition

Visual Working Memory Declines When More Features Must Be Remembered for Each Object

Academic journal article Memory & Cognition

Visual Working Memory Declines When More Features Must Be Remembered for Each Object

Article excerpt

Published online: 29 May 2013

© Psychonomic Society, Inc. 2013

Abstract The article reports three experiments investigating the limits of visual working memory capacity with a single-item probe change detection paradigm. Contrary to previous reports (e.g., Vogel, Woodman, & Luck, Journal of Experimental Psychology. Human Perception and Performance, 27, 92-114, 2001), increasing the number of features to be remembered for each object impaired change detection. The degree of impairment was not modulated by encoding duration, size of change, or the number of different levels on each feature dimension. Therefore, a larger number of features does not merely impair memory precision. The effect is unlikely to be due to encoding limitations, to verbal encoding of features, or to chunk learning of multifeature objects. The robust effect of number of features contradicts the view that the capacity of visual working memory can be described in terms of number of objects regardless of their characteristics. Visual working memory capacity is limited on at least three dimensions: the number of objects, the number of features per object, and the precision of memory for each feature.

Keywords Working memory * Visual working memory * Visual features * Capacity

(ProQuest: ... denotes formulae omitted.)

It has been claimed that performance of visual working memory (VWM) depends on the number of objects to be retained, but not on the number of features of each object (Luck & Vogel, 1997; Vogel, Woodman, & Luck, 2001). This empirical claim is important for theories arguing that the capacity of VWM can be measured in terms of the number of objects that can be maintained, such as the slot model (Luck & Vogel, 1997; Zhang & Luck, 2008) and the hypothesis of a "magical number" of chunks that can be held in WM (Cowan, 2001, 2005). These theories assume that integrated objects, including all their features, form the units of VWM, such that the capacity of VWM can be measiued as the number of objects that can be held simul- taneously, regardless of the complexity of the objects or the number of featiues that have to be retained for each object (Awh, Barton, & Vogel, 2007; Fukuda, Awh, & Vogel, 2010). If the number of features of an object matters for performance in VWM tasks, this notion of a "magical num- ber" of objects needs to be revised. Here, we show that the number of features that have to be remembered has a sub- stantial impact on performance in a standard VWM task, change detection.

In the change detection paradigm (Luck & Vogel, 1997; Wheeler & Treisman, 2002; Wilken & Ma, 2004), an array of visual objects (the memory array) is displayed simulta- neously, followed by a retention interval that exceeds the presumed diuation of visual sensory memory. After the retention interval, a second display (the probe array) is presented that contains either the same number of objects (full display) or a single object in the location of one of the memory objects (single-object display). The task is to de- termine whether any object (in the full-display condition) or the re-presented object (single-object display) has changed, relative to the memory array. Vogel et al. (2001) presented memory arrays in which each object had two featiues (color and orientation) or, in one experiment, even foiu featiues (color, orientation, size, and the presence or absence of a gap). In the single-feature condition, they asked participants to attend to one predetermined feature dimension (e.g., orientation), and a change could occiu only on that feature dimension (e.g., if there was a change, it was in the orientation of one object, while all other features remained constant between memory and probe array). In the conjunc- tion condition, participants were asked to attend to all fea- tures, and a change could occur in any feature. Change detection declined with the number of objects in the array but did not differ between single-feature and conjunction conditions. …

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