Models of verbal working memory capacity: What does it take to make them work?

Abstract

Theories of working memory (WM) capacity limits will be more useful when we know what aspects of performance are governed by the limits and what aspects are governed by other memory mechanisms. Whereas considerable progress has been made on models of WM capacity limits for visual arrays of separate objects, less progress has been made in understanding verbal materials, especially when words are mentally combined to form multi-word units or chunks. Toward a more comprehensive theory of capacity limits, we examine models of forced-choice recognition of words within printed lists, using materials designed to produce multi-word chunks in memory (e.g., leather brief case). Several simple models were tested against data from a variety of list lengths and potential chunk sizes, with test conditions that only imperfectly elicited the inter-word associations. According to the most successful model, participants retained about 3 chunks on average in a capacity-limited region of WM, with some chunks being only subsets of the presented associative information (e.g., leather brief case retained with leather as one chunk and brief case as another). The addition to the model of an activated long-term memory (LTM) component unlimited in capacity was needed. A fixed capacity limit appears critical to account for immediate verbal recognition and other forms of WM. We advance a model-based approach that allows capacity to be assessed despite other important processing contributions. Starting with a psychological-process model of WM capacity developed to understand visual arrays, we arrive at a more unified and complete model.

The impact of storage on processing: How is information maintained in working memory?

“…The mean spans for spatial locations in the two experiments with the spatial fit task and the parity task during retention interval were very close to each other (3.12 and 3.21, respectively) but lower than for letters. The small advantage in span for letters compared with spatial locations could result from the supplementary involvement of some longterm memory component, as suggested by Cowan, Rouder, Blume, and Saults (2012). Still, these values are very much in line with the work of Cowan (2001) demonstrating a limit at about three to four items in WM.…”

The maintenance of cross-domain associations in the episodic buffer.

“…According to this principle, it is very reasonable to accept that fewer objects than single features can be maintained. Our results concerning memory for cross-domain associations were more in line with Allen et al (2006) and Cowan et al (2012) for within-domain combinations and revealed a lower capacity for objects than single features. Cowan et al's idea of chunk decomposition could explain the results obtained in the present study and as such apply to the maintenance capacity limit of the episodic buffer.…”

“…About three "chunks" could be maintained, while these chunks were often incomplete. Cowan et al (2012) described this phenomenon as chunk decomposition. Chunks can fall apart in their different components and in that case occupy more than one slot within WM.…”

What limits working memory capacity?

“…Work along this line needs to flesh out in more detail how the resource limit is to be combined with the mechanisms of interference. (Baddeley et al, 1975;Schweickert & Boruff, 1986) Neo-Piagetian general resource model (Case et al, 1982) Feature model (Nairne, 1990) Limited-capacity trace-decay theory (Jensen, 1988;Salthouse, 1996) Multiple-resource model (Alloway et al, 2006;Logie, 2011) Interference model (Oberauer & Kliegl, 2001 Primacy model (Page & Norris, 1998) 3CAPS (Just & Carpenter, 1992) SOB (Lewandowsky & Farrell, 2008b) and SOB-CS (Oberauer, Lewandowsky, et al, 2012) Task-switching model (Towse & Hitch, 1995;Towse, Hitch, & Hutton, 2000) Slot model (Luck & Vogel, 2013;Cowan et al, 2012) Temporal-clustering-andsequencing model (Farrell, 2012) Computational phonological loop model (Burgess & Hitch, 1999 Resource models of visual WM Time-based resource-sharing model Camos et al, 2009) Note: Theories in the table were selected because they attribute the WM capacity limit unambiguously to decay, limited resources, or interference, respectively. Some theories of WM were not included because they combine two or three of the hypotheses, or make no clear assumptions about what causes the capacity limit.…”

“…(2) Alternatively, WM capacity has been characterized as a limited resource that needs to be shared by representations held available simultaneously and processes to be carried out at the same time (Case, Kurland, & Goldberg, 1982;Just & Carpenter, 1992;Ma, Husain, & Bays, 2014). This resource could be continuous or discrete, and the discrete variant is often referred to as a "slot model" (Cowan, Rouder, Blume, & Saults, 2012). (3) A third approach is to explain the limited capacity of WM WM Capacity 4 as arising from interference between representations that do not decay on their own and are not resource-limited (Nairne, 1990;Oberauer & Kliegl, 2006;Saito & Miyake, 2004).…”