What Makes Working Memory Spans So Predictive of High-Level Cognition?
Lépine, Raphaëlle, Barrouillet, Pierre, Camos, Valérie, Psychonomic Bulletin & Review
Working memory (WM) span tasks involving a complex activity performed concurrently with item retention have proven to be good predictors of high-level cognitive performance. The present study demonstrates that replacing these complex self-paced activities with simpler but computer-paced processes, such as reading successive letters, yields more predictive WM span measures. This finding suggests that WM span tasks evaluate a fundamental capacity that underpins complex as well as elementary cognitive processes. Moreover, the higher predictive power of computer-paced WM span tasks suggests that strategic factors do not contribute to the relationship between WM spans and high-level cognition.
The theoretical construct of working memory has played an increasingly important role in accounting for cognition, and especially for high-level cognition. Working memory (WM) usually refers to a cognitive system devoted to the simultaneous maintenance and treatment of information that is involved in the planning, coordination, and control of high-level cognitive processes (Baddeley & Hitch, 1974; Daneman & Carpenter, 1980). This central role in cognition led many authors to propose span tasks that aimed at assessing WM capacity in individuals. In contrast to traditional short-term memory span tasks, which require simple maintenance and recall of information such as digits, letters, or words, WM span tasks involve a processing component in addition to the maintenance of to-be-recalled items. For example, individuals are asked to read sentences while maintaining their final words (reading span; Daneman & Carpenter, 1980) or to solve arithmetic problems while maintaining words (operation span; Turner & Engle, 1989).
These WM span measures proved to reliably predict, better than short-term memory spans, performance in a wide range of complex activities such as reading comprehension (Daneman & Carpenter, 1980; Daneman & Merikle, 1996), complex learning (Shute, 1991), and reasoning (Barrouillet, 1996; Kyllonen & Christal, 1990). Moreover, it has been demonstrated that, in contrast to short-term memory, WM shows a strong connection to fluid intelligence (Engle, Tuholski, Laughlin, & Conway, 1999). In order to account for these relationships, it has been proposed that WM measures assess a fundamental capacity required by complex activities, which is conceived of as a capacity to control attention (Engle, Kane, & Tuholski, 1999) or to supervise and coordinate multiple-system functioning (Baddeley, 1990). Consequently, the activities included as processing components in WM span tasks are usually selected from those thought to require a high level of executive control (e.g., problem solving, reading comprehension, reasoning, mental calculation). The underlying idea is that more controlled and complex activities provide better WM span measures because complex activities tap the limited pool of cognitive resources sufficiently to disrupt maintenance and permit an accurate measure of WM capacity.
However, is the complexity of the processing component of WM span tasks necessary to disrupt maintenance and accurately assess WM capacity? Barrouillet, Bernardin, and Camos (2004) have recently shown that very simple activities included as processing components in WM span tasks have an equally detrimental effect on recall as do complex activities, provided that they are not self-paced but computer-paced. Remembering letters while solving running operations such as adding or subtracting 1 to or from digits, or even merely reading digits successively presented on a screen at a fast pace, was very difficult, and adult participants exhibited WM spans lower than 3 in these tasks. The authors accounted for this effect by proposing that simple but time-constrained activities capture a sufficient amount of attention to disrupt the maintenance of items to be recalled.
Nonetheless, the value of the WM span tasks is to predict performance on complex cognitive activities. …