Forget Me Not: A Brief Review of Working Memory Training

Forget Me Not: A Brief Review of Working Memory Training

Bradley W. Reynolds, MA

University of Tulsa

Working memory refers to a multifaceted, dynamic system of temporary information retention, manipulation, and modification (Baddeley & Hitch, 1974; Miller, 1956; Miller & Selfridge, 1950).  A “central executive” mechanism affords top-down control of attention to specific elements in memory, which are fed from two subservient systems processing both visual and auditory-verbal information (i.e., visuospatial sketch pad, phonological loop; Atkinson & Shiffrin, 1968; Baddeley, 1992; Beech, 1984; Farmer, Berman, & Fletcher, 1986).  Specifically, the location and synthesis of recent visual stimuli are maintained separately from spoken material, with integration of both components provided by the central executive (Baddeley, 1984; Vallar & Baddeley, 1984).  Retention capacity is finite, varying by the length of information “units” acquired (e.g., number sequences, syllables, word spans; Baddeley, Thomson, & Buchanan, 1975).  Given the salience of working memory among higher-order cognitive abilities (e.g., inhibition, mental flexibility, self-monitoring), researchers have recently attempted to modify if not enhance storage capacity (Evans & Brooks, 1981; Buschkuehl, Jaeggi, & Jonides, 2012; Jaeggi, Buschkuehl, Jonides, & Perrig, 2008).  Such efforts have culminated in the recent wave of “working memory training” programs, many of which claim to improve (1) working memory capacity, (2) working memory efficiency, (3) performance on attention and inhibition tasks, (4) performance on measures of fluid intelligence, or (5) enhance functional outcomes in various settings (Anguera et al., 2012; Buschkuehl, Hernandez-Garcia, Jaeggi, Bernard, & Jonides, 2014; Buschkuehl et al., 2012; Karbach & Verhaeghen, 2014; Shipstead, Redick, & Engle, 2012; Weicker, Villringer, & Thone-Otto, 2016).

Working memory training (WMT) varies markedly by program, though the core components identified in the research are relatively similar.  In modern WMT interventions, individuals are typically administered repeated sequences of either verbal-auditory or visual stimuli, sometimes simultaneously, and are required to recall various aspects (Buschkuehl et al., 2012; Weicker et al., 2016).  Programs may vary by their level of “adaptivity,” which essentially concerns whether trained tasks are altered in difficulty depending on the performance of the individual (Anguera et al., 2012).  These memory tasks are practiced multiple times a week, with total engagement in training typically ranging from as little as five to as many as 25 sessions (Bergman-Nutley & Klingberg, 2014; Buschkuehl et al., 2012; Dunning, Holmes, & Gathercole, 2013).  Importantly, this training format is generally consistent across the lifespan.  For example, considering the highly-researched CogMed program, individuals in preschool through older adulthood are typically trained for the same duration and at a similar rate across homogeneous working memory domains (e.g., verbal, non-verbal, letter sequences, numerical sequences, spatial-object arrangements; Brehmer, Westerberg, Backman, 2012; CogMed, 2016; Egeland, Aarlien, & Saunes, 2013; Klingberg et al., 2005; van Dongen-Boomsma, Vollebregt, Buitelaar, & Slaats-Willemse, 2014; Wayne, Hamilton, Huyck, & Johnsrude, 2016).  The only difference among age groups appears to be length per training session and type of stimuli provided (e.g., colorful shapes, animated objects, simple numbers/shapes); young children are typically required to complete shorter modules each day (CogMed, 2016).  Ostensibly, WMT improves overall working memory on measures that are relatively similar to the over-practiced task (Lange & Suß, 2015).  However, the allure posed by many training programs is that it “transfers” or confers benefits to other cognitive domains, most notably attention, executive functioning, and visuospatial processing (Au et al., 2015; Bechk, Hanson, Puffenberger, L. Benninger, & W. Benninger, 2010; Heinzel et al., 2016; Jaeggi et al., 2008, 2014; Uttal et al., 2013).  Whether these transfer effects are legitimate, as well as robust to idiosyncratic factors (e.g., age, cognitive functioning, setting), remains a target for future research and will be discussed further in this review (Melby-Lervg & Hulme, 2016; Redick et al., 2013).

The mechanisms of WMT, from both cognitive and neuroanatomical perspectives, have recently been dissected in the literature.  WMT is thought to target one’s ability to maintain as well as “update” information in temporary storage (i.e., enhance the central executive; Weicker et al., 2016).  Consequently, attentional control is improved due to this increased processing efficiency (Buschkuehl et al., 2014; Kundu, Sutterer, Emrich, & Postle, 2013; Lilienthal, Tamez, Shelton, Myerson, & Hale, 2013).  Practice over time appears to augment the underlying neural connections associated with working memory, which can be coalesced into more general anatomical regions (Buschkuehl et al., 2012; Thompson, Waskom, & Gabrieli, 2016).  These principally include, but are not entirely limited to, the dorsolateral prefrontal cortex (dlPFC), medial frontal cortex (MFC), inferior and posterior parietal cortex, occipital lobe, anterior cingulate cortex (ACC), and cerebellum (Borst & Anderson, 2013; Buschkuehl et al., 2014; Daniel, Katz, & Robinson, 2016; Ekman, Fiebach, Melzer, Tittgemeyer, & Derrfus, 2016; Heinzel et al., 2016; Kundu et al., 2013; Kuper et al., 2016; Nee et al., 2013).  Collectively, WMT is thought to bolster the efficiency of neural transmission between frontal-parietal and parietal-occipital circuits (Buschkuehl et al., 2014; Kundu et al., 2013; Heinzel et al., 2014; Stevens, Gaynor, Bessette, & Pearlson, 2016).  This may result in reduced activation of the prefrontal system, with less activity translating to increased efficiency of the network in attending to visual and verbal material (Vermejj et al., 2016).  Altogether, neuroscience and neuropsychology have identified the processes which contribute to functional change among WMT participants.  These mechanisms have recently been studied within populations that may most benefit from enhanced cognitive functioning, namely school-aged children and the elderly.

Middle-late childhood and early adolescence are associated with rapid changes in working memory (Thaler et al., 2013).  Relevant to this age range, working memory is thought to be implicated throughout the course of many childhood disorders, including attention-deficit hyperactivity disorder (ADHD) and various learning disorders (Alloway, Bibile, & Lau, 2013; Beck et al., 2010; Dunning et al., 2013; Martinussen, Hayden, Hogg-Johnson, Tannock, 2005; Pejinenborgh, Hurks, Aldenkamp, Vles, Hendricksen, 2016; Yu, Li, Y. Liu, An, & X. Liu, 2015).  As such, several researchers have attempted to assess WMT benefits in children, both with and without developmental disorders (Danielsson, Zottarel, Palmgyist, & Lanfranchi, 2015; Pejinenborgh et al., 2016; Shipstead et al., 2012).  Among healthy youth, recent studies have found at least modest immediate and long-term improvements in working memory efficiency and capacity (Dunning et al., 2013; Randall & Tyldesley, 2016; Shipstead et al., 2012).  This effect appears to assume a dose-response relationship, where increases in total practice time correspond to additional improvements in cognitive performance (Bergman-Nutley & Klingberg, 2014).  However, transfer effects to non-working memory tasks, as well as to functional improvements (e.g., classroom behaviors), remain inconsistent.  Highlighting this ambiguity, several investigations have yielded no association between adaptive WMT and reading achievement, mathematics achievement, or increased classroom-appropriate behavior (Banales, Kohnen, & McArthur, 2015; Dunning et al., 2013; Hitchcock & Westwell, 2016).  Conversely, multiple studies have noted at least small improvements in mathematics-related abilities (Bergman-Nutley and Klingberg, 2014; Passolunghi & Costa, 2016; Soderqvist & Nutley, 2015; Studer-Luethi, Bauer, & Perrig, 2016).  Reading ability likewise may be enhanced in healthy youth following WMT (Loosli, Buschkuehl, Perrig, & Jaeggi, 2012; Soderqvist & Nutley, 2015; Studer-Luethi, Bauer, & Perrig, 2016).  Together, this inconclusive pattern of results requires further investigation to ascertain the transfer effects of WMT among this population.

Children with ADHD and learning disabilities (LD) have received considerable attention over the last several years with respect to WMT outcomes (Martin, Hayden, Hogg-Johnson, & Tannock, 2005).  Researchers have suggested that ADHD symptoms may be attenuated by WMT, specifically in increasing attention modulation, mental control, and more broadly executive functioning (Alderson et al., 2015; Barkley, 1997; Beck et al., 2010; Castellanos, Sonuga-Barke, Milham, Tannock, 2006; Yu et al., 2015).  Specifically, working memory dysfunction corresponds with an inability to retain outcomes associated with recent behavioral responses (Barkley, 1997).  In turn, individuals are unable to evaluate these experiences and effectively modify future actions in response to the environment (Barkley, 1997).  Consequently, suboptimal working memory translates to poor behavioral maintenance and frequent disruption of goal orientation (i.e., loss of focus on task goals; Barkley, 1997; Holmes et al., 2014).  Individuals with ADHD display frequent shifting to irrelevant stimuli in the classroom setting, and thus are unable to acquire the necessary material for effective learning (Holmes et al., 2010, 2014).  Collectively, clinical deficits in attention and working memory are associated with an increased risk of being held back, enlisted in special education coursework, as well as lower reading and mathematics achievement (Fried, 2016).

Similarly, working memory and attentional processing are associated with achievement among youth with learning disabilities (Dahlin, 2011; Maehler & Schuchardt, 2016; Melby, Lyster, & Hulme, 2012).  Working memory contributes uniquely to reading and mathematics ability.  Verbal working memory is implicated in the retention and manipulation of phonemes (i.e., letter sounds; Cartwright, 2012).   This may manifest in deficits in reading as well as spelling competency (Brandenburg et al., 2015).  When individuals are unable to effectively decode verbal information, reading comprehension is likewise compromised (Swanson, 2003).  Altogether, poor reading fluency increases working memory demand, which in turn prevents efficient evaluation and analysis of verbal content (Sesma, Mahone, Levine, Eason, & Cutting, 2009).  Conversely, mathematics achievement appears dependent on spatial working memory.  This process allows for the manipulation of numerical information in visual space; when relevant mathematic stimuli are not retained over a short duration, the ability to solve word problems is impacted (Passolunghi & Mammarella, 2011).  In general, working memory is intimately related to the development of mathematical knowledge at an early age (Passolunghi, Vercelloni, & Schadee, 2007).

As was the case with typically developing children, the benefits (i.e., transfer effects) of WMT remain inconclusive.  Concerning individuals with ADHD, a recent randomized controlled trial (RCT) found that while working memory ability may have improved, there were no clear benefits conferred to secondary outcomes (e.g., ADHD symptoms, cognitive functioning, overall mental well-being; Dongen-Boomsma, Vollebregt, Buitelaar, & Slaats-Willemse, 2014).  While this singular effect of improved working memory has been replicated in other samples, at least one study did demonstrate reductions in daily inattentiveness (Chacko et al., 2014; Spencer-Smith & Klingberg, 2015).  In the context of learning disabilities, transfer effects are likewise difficult to determine.  Danielsson and colleagues (2015) conducted a meta-analysis of 10 studies assessing LD and WMT; these authors identified a small effect of combined verbal and visual WMT on working memory, but were unable to determine transfer to other cognitive domains given the dearth of research on the topic.  An RCT of adolescents with LD or ADHD found similar results, supporting benefits for working memory alone (Gray et al., 2012).  Conversely, a more recent review of 13 controlled studies by Peijnenborgh et al. (2016) noted that LD individuals evidence immediate improvements in reading ability following training.  In summary, the benefits of WMT for this clinical population tend to be circumscribed to the working memory domain, with poorly understood effects on secondary outcomes (Shipstead et al., 2012).

Older adults, particularly those suffering from mild cognitive impairment (MCI), may benefit from cognitive enhancement techniques such as WMT (Hyer et al., 2016; Vermeij, Claassen, Dautzenberg, & Kessels, 2016).  Similar to the developmental disorder population, WMT is thought to support growth in attention control and inhibition for older adults (Borella, Carretti, Zanoni, Zavagnin, & De Beni, 2013; Brehmer et al., 2011).  To investigate these mechanisms, Karbach and Verhaeghan (2014) conducted a large meta-analysis on all WMT studies of adults (63-87 years of age).  These authors found support for modest transfer effects to other working memory tasks, with significant but small improvements across other cognitive domains.  Even adults in senesce display plasticity in improving cognitive functioning (Borella et al., 2013; Carretti, Borella, Zavagnin, & Beni, 2013; Lange & Suß, 2015).  A recent RCT investigating the potential transfer effects of adaptive WMT for older adults achieved comparable results; WMT enhanced both working memory as well visual-construction and visual-spatial skills (Stepankova et al., 2014).  Pragmatically, the benefits of WMT have been observed in elderly clinical populations.  Specifically, two recent studies have demonstrated immediate and long-term transfer effects across working memory tasks among individuals with MCI (Hyer et al., 2016; Vermeij, Claassen, Dautzenberg, & Kessels, 2016).  Improvements in functional outcomes were also noted (Hyer et al., 2016).  Collectively, research on the elderly suggests more consistent transfer effects beyond the working memory domain.  These encouraging findings indicate that rehabilitation of cognitive deficits in older age may be possible through structured WMT (Stepankova et al., 2014).

Studies considering older adults imply that age does not moderate the effect of WMT.  Specifically, multiple studies have addressed whether older adults benefit as substantially as individuals in middle adulthood, even childhood.  At least two meta-analyses have found no differences in both working memory or transfer effects across the lifespan following WMT (Karbach & Verhaeghen, 2014; Melby-Lervag & Hulme, 2013).  While youth tend to demonstrate slightly higher scores on near and far transfer tasks, this discrepancy has consistently been observed as non-significant (Karbach & Verhaeghen, 2014).  However, this conclusion should be interpreted cautiously.  Publication bias, inconsistent use of transfer measures, and relatively few studies addressing the elderly all hinder accurate interpretation (Melby-Lervag & Hulme, 2013).

As previously mentioned, the benefits of WMT through transfer effects generally remain unclarified in the literature (Melby-Lervag & Hulme, 2016).  Following review of recent developments in WMT, it remains pertinent to address present pitfalls in this area of study.  The most contentious discussion has centered on whether improvements in working memory contribute to enhanced fluid intelligence (Au et al., 2015; Harrison et al., 2013; Jaeggi et al., 2008).  The proposed theory or pathway linking WMT to fluid intelligence is somewhat convoluted.  In review, working memory is thought to contribute to executive control, which allows for the modification of stimuli in “mental space” (Burgess, Gray, Conway, & Braver, 2011; Kane & Engle, 2002).  In turn, working memory allows for the inhibition of competing or irrelevant processes in order to maximize retention of target information (Oelhafen et al., 2013; Schwarb, Nail, & Schumacher, 2016).  Thus, when visual stimuli are presented, an intact working memory system provides the basis for appropriate attention and acquisition of relevant input.  Visual and spatial information, when repeatedly confronted through training, may consequently influence visual-spatial reasoning (Uttal et al., 2013).  Visual-spatial synthesis, abstraction, and reasoning are all secondary abilities assumed under fluid intelligence (Jaeggi et al., 2008).  While a few studies have identified an association between WMT and fluid ability, the conclusion that training provides direct improvements to intellectual functioning remains anything but assured (Chooi & Thompson, 2012; Stephenson & Halpern, 2013; Jaeggi et al., 2008, 2014).

Researchers that have succeeded in linking WMT to fluid intelligence have done so with major limitations.  For example, Stephenson and Halpern (2013) revealed that WMT training must contain a visual-spatial component to confer improvements on fluid measures.  Practice with auditory-verbal stimuli may not provide such benefits.  When transfer effects to intellectual functioning have been documented, they are rarely consistent with respect to level of influence (i.e., whether WMT improved individual visual-spatial measure performance or composite fluid intelligence; Colom et al., 2013; Jaeggi et al., 2014).  On this conundrum, Jaeggi and colleagues (2014) revealed that while a composite of visual-spatial functioning was significantly associated with WMT, improvements on independent visual-spatial tests were not observed.  Conversely, other studies have identified transfer effects on individual measures, but not toward higher-order indices of fluid intelligence (Chooi & Thompson, 2012; Colom et al., 2013; Dahlin, 2011; Stephenson & Halpern, 2013).  While these findings suggest the potential for WMT to exert influence on intelligence, a sizeable body of research argues otherwise.

Among most studies investigating transfer effects in WMT, heterogeneity of both study design and participant characteristics hinders the clarity of conclusions (e.g., lack of control group, confounding use of repeated testing on transfer measures; Melby-Lervag & Hulme, 2016; Shipstead et al., 2012).  Illuminating this inconsistency, Au et al. (2015) found that the impact of WMT was markedly stronger depending on whether a passive control group was used, and whether the study was done outside the United States.  Even when studies are well-controlled, evidence suggesting even a small association between WMT and fluid intellect is tenuous at best.  Redick and colleagues (2013) conducted a rigorous RCT comparing adaptive visual-spatial WMT to groups receiving either visual search practice or no intervention.  Results from this study identified an absence of any benefit for WMT on fluid intelligence, multi-tasking, and processing efficiency across all groups.  Interestingly, Redick et al. revealed that the adaptive WMT sample reported subjective benefits to their cognitive functioning, despite an absence of any objective effects.  Similarly, Harrison et al. (2013) conducted a study on visual-spatial and verbal WMT among young adults with active controls to assess fluid intelligence transfer effects.  Much like the entirety of research reviewed in this paper, working memory was immediately improved.  However, while visual-spatial sequencing was enhanced, there were no significant differences between participant groups.  Additionally, performance on fluid reasoning tasks did not increase for either group.  These results collectively suggest that (1) improved visual-spatial processing may not be specific to structured WMT, and (2) any form of active memory enhancement will not reliably translate to improvements in fluid ability (Harrison et al., 2013; Redick et al., 2013).

While further investigation on the influence of WMT on fluid intelligence is warranted, it is important to emphasize other directions for future research and theory.  In order to better measure working memory as a distinct ability, it has been suggested that the construct be broken down into smaller components (Gibson et al., 2011, 2013).  Specifically, working memory can be demarcated by more than a visual-verbal dichotomy.  According to Gibson and colleagues (2011), working memory includes a maintenance and retrieval function, which in turn impact how well recent information is retained and modified.  From this model, Gibson et al. (2013) have suggested that WMT may demonstrate more robust influence on cognitive functioning if designed to target these novel facets.  Thus, specification of working memory from alternative frameworks may provide new methods for constructing and evaluating WMT.

While the neuroanatomical correlates of working memory are well understood, their specificity is still somewhat lacking.  As reviewed previously, there are distinct networks within predominantly the frontal and parietal cortices, but also the occipital lobe, which allow for successful acquisition and storage of recent information (Kundu et al., 2013; Thompson et al., 2016).  However, while several functions have been ascribed to particular regions, these functions remain vaguely defined and often overlap within multiple cortical and subcortical areas (Daniel et al., 2016; Ekman et al., 2016; Nee et al., 2013).  Given recent advancements in neuroscience technology, these anatomic ambiguities will likely be resolved in the next few years.  In the meantime, research on WMT must assess the manner in which programs beneficially alter brain structure and composition (Buschkuehl et al., 2014; Metzler-Baddeley, Caeyenberghs, Foley, & Jones, 2016).

Finally, investigation of WMT in at-risk groups such as children with ADHD and LD should continue.  Results achieved across the past few years of research are anything but consistent, specifically in clarifying the presence of beneficial transfer effects to real-world behaviors (Dunning et al., 2013).  For example, the association between functional outcomes (e.g., classroom activity) and learning disabilities has not yet been addressed in a satisfactory manner (Danielsson et al., 2015).  ADHD interventions utilizing WMT have been studied, but results are problematically inconclusive (Beck et al., 2010; Gray et al., 2012).  Additionally, the field might benefit from further research on individuals with down syndrome.  Of the limited studies available, initial results suggest that WMT may provide lasting improvements to visual-spatial memory among this cognitively limited population (Bennett, Holmes, & Buckley, 2013).

Working memory training research appears to still be in a nascent stage.  General improvements in working memory capacity have been observed, specifically on measures similar to the over-practiced task used in training (i.e., near transfer effects).  However, the claims of far-reaching influence on other cognitive domains and achievement remain contentious (i.e., far transfer effects; Au et al., 2015; Melby-Lervag & Hulme, 2016; Peijnenborgh et al., 2016; Shipstead et al., 2012; Weicker et al., 2016).  Specific populations, such as elderly adults with and without cognitive impairment, have benefitted more consistently from these transfer effects (Karbach & Verhaeghen, 2014).  As such, future investigations must continue to better define WMT as well as validate touted mechanisms of transference.


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