Introduction

Working memory (WM) is the ability to maintain and manipulate information in the short term and in the context of concurrent processing or distraction (Baddeley & Hitch, 1974, 1994; Baddeley 2000, 2001). WM is closely related to attentional control, as it determines the information that is attended to and that which is filtered out (Westerberg et al., 2007). Further, working memory related areas of the brain (ie., frontal and parietal) overlap with those responsible for selective attention or top-down attention. It is thus no surprise that children with attention-deficit/hyperactivity disorder (ADHD) have well documented WM deficits (Martinussen et al., 2005) and disruption to the neural network in the front lobe (see Klingberg et al., 2010 for a review).

WM is regarded as a fundamental function, underlying other executive functions such as reasoning and goal-directed behavior like planning. Researchers have found associations between WM and general intellectual ability and WM is known to be a key predictor for academic attainment (Gathercole & Pickering, 2000; Alloway & Gathercole, 2006). Thus for populations with known WM deficits including but not limited to individuals with ADHD, brain injury, cancer, mild cognitive impairment, HIV and learning disabilities, low WM impairs cognition and daily functioning and has various implications over the developmental life course. Despite the abundance of literature on the function, importance and groups impacted by deficits in WM, there has been a dearth of knowledge concerning WM training and its impact. This void in the literature may reflect the long held belief that WM is a fixed trait.

In a 2004 study, Westerberg et al. found that visuo-spatial WM is a deficit structure in children with ADHD and that the gap in visuo-spatial WM deficit increases between typical and ADHD children over time. Thus, these researchers took on the challenge of developing WM training for children with ADHD based on features of a training regime previously used to induce cortical plasticity and enhance sensory discrimination (Buonomano & Merzenich, 1998; Tallal et al., 1996). In two separate studies in 2002 and 2005, Klingberg et al. tested this adaptive and computerized working memory training program, Cogmed, in children with ADHD. In this groundbreaking work, Klingberg et al. found that it was possible not only to train WM but also, that the training effects may transfer to other executive functions and behaviors.

Cogmed thus has it’s foundations in academic research. Since the initial findings of Klingberg et al. (2002, 2005), research has revealed that individuals of all ages have improved WM capacity in both the visuo-spatial and verbal domains after Cogmed. In some studies of children with ADHD, increased WM has also shown transfer to executive functions such as attention, inhibition and reasoning (Klingberg et al., 2002; 2005). Cogmed studies have investigated the impact of WM training from the most fundamental level of genetics (Brehmer et al., 2009) and biochemical functioning (McNab et al., 2009) to its impact on learning (Holmes et al., 2009) and behavioral expression (Klingberg et al., 2005).

Combined, the current body of Cogmed training literature refutes the long held belief that WM is static. The essence of these training studies point towards a compelling message: adaptive and sustained WM training is associated with training-induced plasticity in a common neural network for WM, which may remediate the limitations imposed on those with low WM capacity. The increased interest in and use of Cogmed in clinical, school and research settings worldwide is a testament to the growing acceptance of working memory training in the scientific community as well as a step forward in the field of evidence-based cognitive training. As Cogmed continues to evolve, both as a program and a business, research will play an integral role in processes of development, implementation, and integration with clinical assessments.

In order to convey the close relationship between the Cogmed program and it’s backing in academic research, it is essential to have an understanding of the findings to date. Beyond this introduction, Chapter 2 provides a summary of WM training by Torkel Klingberg, Professor of Cognitive Neuroscience at the Karolinska Institute in Stockholm, Sweden. In Chapter 3, key terms prevalent in the WM training literature are outlined and expounded on. Chapter 4 includes a timeline of the research findings to date with key take home messages.