Training General Intelligence

Many attempts have been made to improve general intelligence, often referred to as G. G is principally composed of crystalline intelligence (Gc), acquired knowledge, and fluid intelligence (Gf), ability to reason and problem solving based on the information available in the environment and on Gc. Gf is a strong predictor of academic and career success. Training interventions attempting to target Gf have resulted in task specific effects, that is, those trained demonstrate improved performance on measures of fluid intelligence with no transfer effects observed. Studies that do report transfer effects typically use testing tasks that bear a close similarity to the tasks participants have been trained on, raising questions of whether transfer has truly been demonstrated (Cassidy, Roche, and Hayes, 2011; Bergman Nutley et al., 2011).

Some of the most robust findings of the beneficial effects of cognitive training have been demonstrated for elderly participants (Willis et al., 2006). The effect may be specific to this group due to the protective effects of neural stimulations against the cognitive and neural decline associated with old age. Additionally, these effects may also be the result of the reengagement of underutilised neural mechanisms or simple reflect an up-regulation in activity levels generally. Importantly, these training effects are reported to have a positive impact on the performance of daily activities.

Training improvements reported in the literature include processing speed, working memory, selective attention, and composite measures of cognitive functioning and executive function (see Kueider, et al., 2012, and Kelly et al., 2014 for a review).

A range of training interventions target a broad array of cognitive functions; e.g. sustained attention, selective attention, task switching and inhibition. Wass,

Porayska-Pomsta, and Johnson (2011) used an eye-tracker administered battery of training tasks using a gaze-contingent interface targeting attentional control in typically developing infants. They report that training for one hour and a quarter led to improved cognitive flexibility, sustained attention, and to a reduction in saccadic reaction time latencies. Rueda et al. (2005) trained 4 and 6 year olds for 5 days over a 2 to 3 week period with tasks targeting object tracking, anticipation, stimulus discrimination, conflict resolution and inhibitory control. They report some transfer to

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reasoning tasks but no performance improvements on the Attention Network Test (Fan et al., 2002) or temperament scale ratings. They note changes to the anterior cingulate EEG activity associated with improvements. Those participants who were initially the poorest at attention tasks showed the most benefits, which suggests that this effect may reflect regression to the mean. Studies using adapted computerised versions of dimensional card sorting tasks compare the effects of training children, young adults and older adults. They report transfer to fluid intelligence and other executive tasks across all age groups (Karbach and Kray, 2009, Kerns et al., 1999 and Kloo and Perner, 2003).

Recently there have been studies attempting to train working memory (WM). A number of studies report improved WM after a period of training (Jaeggi et al., 2008; Klingberg et al. 2002; Oberauer, 2006; Olesen, Westerberg, & Klingberg, 2004; Salminen, Strobach, & Schubert, 2012). There is some debate as to whether this training is improving WM capacity or speeding up attentional processes within WM. An exciting aspect of this research is that WM improvements have been reported to transfer to executive function abilities. It has been proposed that WM and attentional processes share a capacity system, a shared resource pool. Thus, increased WM efficiency leads to a greater availability of resources for other

cognitive functions. Oberauer (2006) suggests that WM training specifically on the n- back task leads to a speed up in attentional processes within WM, rather than to a pure increase in WM capacity.

Salminen, Strobach, & Schubert (2012) conducted a similar WM intervention study using a dual N-back training task with a typically developing university sample. The aim of the study was to identify transfer effects from WM training to different aspects of executive functioning, namely WM updating, coordination of dual

discrimination task performance, task switching, and attention switching. No control intervention was used. 9 of the 18 controls completed the post test, while 13 of the 20 participants who took part in the training completed the post-test After the dual N-back training improvements were seen for visual spatial WM updating, and task switching and attentional processing. There was no transfer seen for the dual-task situation or to reasoning skills. While suggestive this is a small sample with a high attrition rate.

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A study by Jaeggi and colleagues (2008) examined the impact of WM training (N- back) on fluid general intelligence (Gf). They propose that WM and Gf share a common capacity constrain referred to as binding, that is, the maintenance of a number of items or interrelations in the cognitive system. Participants were assessed on a matrix reasoning task, then received training for 8 days (N=16), 12 days (N – 22), 17 days (N = 16), or 19 days (N=15) on a dual N back task, before repeating the assessment on the matrix reasoning assessment task. After controlling for individual differences and improvements in WM with a digit span task they found Gf improvements. Importantly Gf improvements were dose dependent, that is, more training resulted in greater improvements. Irrespective of whether the dual N-back task can be classed as a WM task, these results are promising and suggestive of the potential to make cognitive gains with training. Replication, controlling for

participant-experimenter interactions, and experimenter blinding are needed. Thompson et al. (2013) and others subsequently failed to reproduce this result. A recent meta-analysis of 20 studies examining the effects of N-back training on Gf suggested a small but significant positive effect (Au et al., 2014).

An intervention delivered to adults with dyslexia targeting the ability to convert visual letters to sound demonstrated an improvement in reading performance but also a normalisation of activity in regions associated with reading, the boundary between temporal and parietal lobes (Eden et al, 2004). A meta-analysis by Barquero, Davis, and Cutting (2014) examining reading interventions and neural activation concludes that performance can be improved as a result of interventions and that improvements are accompanied by neural activation changes in regions associated with reading.

Chapman and Mudar (2014) discuss an intervention targeting top-down cognition. The ‘Gist’ reasoning training purportedly targets strategic attention, integrated reasoning, and innovation. This training targets the acquisition of strategies to ’facilitate cognitive control and depth of encoding to facilitate knowledge acquisition and creation’ (Chapman and Mudar, 2014). In contrast to interventions attempting to enhance cognitive functions, this training holds intuitive appeal as it seeks to enhance the utilisation of the cognitive functions already in place. While the results

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thus far are promising well controlled independent replication is needed with demonstrable functional improvements in everyday activities.

Numerous cognitive training programmes have been marketed in recent years directly to the public, in some cases, making grandiose claims about the benefits of cognitive training. A consensus statement was recently released by leading

academics in the field in reaction to the claims by advertisers (Kooij et al., 2010). The statement rebuts claims that there is scientific support that such cognitive training programmes, or “brain games” as they are known enhance neural functioning such that cognitive performance in everyday life improves, or that cognitive decline, slowing, or disease in old age are reduced. It goes on to say advertisers frequently exaggerate and at times mislead the public with the claims made. While it is possible that cognitive training may lead to improvements in everyday functioning at present more research is needed. The effects thus far are small, narrow, and fleeting, and due to a publication bias positive effects are likely to be overrepresented.