Cognitive Training in the Elderly: Bottlenecks and New Avenues

Nahid Zokaei, Christopher MacKellar, GiedrėČepukaitytė,

Eva Zita Patai, and Anna Christina Nobre Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/29/9/1473/1786573/jocn_a_01080.pdf by MIT Libraries user on 17 May 2021

Abstract ■ Development of measures to preserve cognitive function or lack of consensus on a comprehensive assessment protocol. We even reverse cognitive decline in the ever-growing elderly pop- propose that the success of training-based therapeutics will rely Downloaded from http://direct.mit.edu/jocn/article-pdf/29/9/1473/1952866/jocn_a_01080.pdf by guest on 01 October 2021 ulation is the focus of many research and commercial efforts. on targeting specific cognitive functions, informed by compre- One such measure gaining in popularity is the development hensive and sensitive batteries that can provide a “fingerprint” of computer-based interventions that “exercise” cognitive func- of an individual’s abilities. Instead of expecting a panacea from tions. Computer-based cognitive training has the potential to be training regimens, focused and personalized training interven- specific and flexible, accommodates feedback, and is highly ac- tions that accommodate individual differences should be cessible. As in most budding fields, there are still considerable developed to redress specific patterns of deficits in cognitive inconsistencies across methodologies and results, as well as a rehabilitation, both in healthy aging and in disease. ■

INTRODUCTION population is therefore a primary focus of research Over the last century, the fields of medicine and health efforts. care have had tremendous success, increasing life expec- In the last decade, interest has been growing for devel- tancy to an average age of approximately 80 years (www. oping computer-based cognitive training interventions cdc.gov/nchs/fastats/life-expectancy.htm). Although phys- that can preserve or even improve cognition both in ical health has resulted in prolonged lifespan, preserva- the medical sector and the technology industry. These tion of cognitive health has remained a fundamental provide an alternative to pharmacological treatments challenge. Normal aging, as well as disorders associated and could be used independently or in combination with with the old age (e.g., ), have been associated medication. Cognitive training is characterized by several with considerable decline in fundamental cognitive abili- features, which make it a highly promising lifestyle-based ties, such as , working , long-term mem- intervention that could dramatically improve the mental ory, decision-making, and task switching, to name just a life in older adults and in patients. Numerous enterprises few (e.g., Stark, Stevenson, Wu, Rutledge, & Stark, 2015; are sprouting to develop training tasks that exercise Brockmole & Logie, 2013; Chowdhury et al., 2013; Peich, cognitive abilities in an analogous fashion to using phys- Husain, & Bays, 2013; Stark, Yassa, Lacy, & Stark, 2013; ical exercises for improving physical fitness and health. Zanto, Sekuler, Dube, & Gazzaley, 2013; Chowdhury, This review will take stock of the state of play on the em- Guitart-Masip, Bunzeck, Dolan, & Düzel, 2012; Smyth & pirical research that supports the development of cogni- Shanks, 2011; Zanto et al., 2011; Brockmole, Parra, Della tive training in the elderly population. We will comment Sala, & Logie, 2008; Gazzaley, Cooney, Rissman, & on success and limitations and propose key factors that D’Esposito, 2005). Importantly, cognitive decline impacts need to be considered for the field to advance. the quality of life by adversely affecting activities of daily living such as driving, shopping, or taking medication (Maki et al., 2014; Bárrios et al., 2013; Teng, Tassniyom, ADVANTAGES OF COMPUTER- & Lu, 2012; Wadley, Okonkwo, Crowe, & Ross-Meadows, BASED TRAINING 2008) as well as compromising social interactions and relations (e.g., Davies et al., 2010; Frank et al., 2006). De- There are a number of key aspects that, if well imple- veloping approaches to preserve healthy cognitive func- mented, can set computer-based cognitive training apart tion and improve the quality of life of the elderly from other medical interventions. Should they prove effective, they have the potential to transform our approach to preservation of cognitive health during normal University of Oxford aging and in disease.

© 2017 Massachusetts Institute of Technology Journal of Cognitive 29:9, pp. 1473–1482 doi:10.1162/jocn_a_01080 First, computer-based training can be directed to a spe- tive data. Peretz and colleagues (2011) successfully imple- cific cognitive function and thereby selectively trigger mented personalized cognitive training using the plasticity or changes in efficiency in the specific neural “CogFit” personal coach. The time spent playing the systems that support the trained cognitive function. Al- training tasks for each participant was determined by per- though arguably not to the same extent as in younger in- formance in a battery of baseline cognitive tests. Com- dividuals, the aging brain retains the capacity for plasticity pared with a group of individuals playing conventional (Li et al., 2008; Craik & Bialystok, 2006; Li, Brehmer, video games (e.g., Tetris, Puzzled, or Snake), personal-

Shing, Werkle-Bergner, & Lindenberger, 2006), and thus, ized cognitive training yielded superior training benefits. Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/29/9/1473/1786573/jocn_a_01080.pdf by MIT Libraries user on 17 May 2021 it is possible to drive plasticity and improvements in effi- Similarly, one can incorporate immediate quantitative ciency in selective neural systems. The natural and inher- feedback, modifying the task demands as the training ent ability of cognitive training to target specific neural evolves to optimize the regimen for each individual. Al- systems is in contrast to pharmacological medications, though in principle it is possible to regulate dosage in which tend to act in a diffuse manner in the brain to in- pharmacological treatments, obtaining accurate and fluence chemicals involved in widespread neurotransmit- quantitative feedback to guide dosing can be highly chal- ter or neuromodulator systems linked to a deficit or lenging. In other words, cognitive training tasks can Downloaded from http://direct.mit.edu/jocn/article-pdf/29/9/1473/1952866/jocn_a_01080.pdf by guest on 01 October 2021 disorder. Typically, any given neurotransmitter or neuro- change flexibly based on the participant’s performance modulator is involved in many neural systems and cogni- to ensure maximum gain. This homeostatic dynamic ad- tive functions. As a consequence, treatment effects often justment based on continual feedback is referred to as a entail other, unplanned and potentially undesirable side closed-loop system (Mishra & Gazzaley, 2015). A few effects. Cognitive interventions therefore naturally pro- studies have indeed shown benefits of closed-loop train- vide a superior level of specificity and neural targeting, ing tasks that adjust parameters adaptively according to which pharmacological treatments struggle to achieve. participants’ performance (e.g., Mishra, de Villers-Sidani, An example of the neural specific cognitive training Merzenich, & Gazzaley, 2014; Anguera et al., 2013; Smith comes from a recent study that trained the ability to sup- et al., 2009; Mahncke et al., 2006). For example, Anguera press distraction in older human participants and rats, a and colleagues (2013) trained older participants on a function often reported to be impaired in the elderly custom-designed adaptive multitasking video game, (Mishra, de Villers-Sidani, Merzenich, & Gazzaley, 2014). NeuroRacer, designed to enhance the ability of individ- The task involved identifying target tones presented in- uals to multitask effectively in the context of driving while frequently among other distracting tones. In the main having to respond appropriately to attention-grabbing distractor suppression training task, distractors became transient events. The difficulty of the task in the adaptive progressively more similar to the target tone in frequency. group was modified after each run according to partici- The task required increasingly refined perceptual dis- pant’s performance and ensured continuous challenge crimination and specifically focused adaptive training in and high level of engagement and motivation. The results the ability to recognize and ignore distractors. With task showed a reduction in multitasking costs, as well as en- progression, the distractor became increasingly more hanced performance in tasks that measured attention similar to the target stimuli. As a stringent control, a dif- and working memory following training. Training bene- ferent group of participants was also required to discrimi- fits were observed only in the multitasking adaptive nate targets amidst distracting tones in a similar training group compared with a group of individuals performing environment. In contrast to the previous group, the adap- each of the tasks in isolation. However, it is important to tive aspect of the task focused on recognizing and selec- note that, because of the nature of the control task, ting the target stimuli. Over the task, the target became participants who performed the multitasking procedure progressively more similar to the distractors. Of these had twice as many trials per task as both groups trained closely matched tasks, only the distractor suppression for the same amount of hours. Considering this limita- training was found to redress the intended deficit specifi- tion, these findings require replication and extension of cally, as measured by a decrease in proportion of incorrect training-specific findings. distractor responses. Behavioral improvement was accom- Aside from the scientific benefits of computer-based panied by changes at the neural level in both humans and cognitive training, there are also practical aspects that rats. There was diminished neuronal firing to distractors in make such interventions highly desirable. Cognitive train- the rat auditory cortex and attenuated early event-related ingtaskscanbedesignedtobehighlyimmersiveand auditory potentials to distractor tones in humans. entertaining. Hence, participants can remain highly moti- A related benefit of brain training interventions is that vated to engage regularly in the training regimen. Fur- they can be personalized to accommodate individual dif- thermore, training tasks are highly accessible, delivered ferences. It is possible to tailor a training regimen to tar- on common and portable digital platforms—computers, get and train specific abilities based on the cognitive tablets, smartphones—to an increasingly technology-savvy profile or “fingerprint” of the participant. This contrasts population of elderly individuals. When it comes to the with pharmacological treatments, in which both the type elderly, this allows for cognitive interventions that can and dosage of medication are typically based on norma- reach individuals in their homes or on the go with minimal

1474 Journal of Volume 29, Number 9 disruption to their daily lives. Lastly, computer-based (Karbach & Verhaeghen, 2014; Melby-Lervåg & Hulme, training is inexpensive, especially when compared with 2013). Similarly, Baniqued et al. (2014) found that train- long-term pharmaceutical treatments. ing on video games that place high demands on atten- tional abilities (e.g., Sushi Go Round) for 15 hr resulted in enhanced divided attention compared with playing IS COMPUTER-BASED COGNITIVE other forms of video games. RT improvements have also TRAINING EFFECTIVE? been reported following training in tasks that require fast

There are a number of studies pointing to the effective- pace responses (Ballesteros et al., 2014; Edwards et al., Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/29/9/1473/1786573/jocn_a_01080.pdf by MIT Libraries user on 17 May 2021 ness of computer-based training interventions in the 2005; Goldstein et al., 1997). elderly. Studies commonly use existing video games that The evidence for far transfer, however, is much more are not originally designed to improve cognition (e.g., scarce with, at best, small effect sizes (Karbach & Verhaeghen, Medal of Honor, Tetris, or Pac Man), a combination of 2014). In fact evidence for far transfer in older participants cognitive tasks taken from commercial packages (e.g., is so rare that some have reported them as “almost entirely Nintendo Brain training or Brain Age; e.g., Clemenson absent” (Noack, Lövdén, Schmiedek, & Lindenberger,

& Stark, 2015; Bozoki, Radovanovic, Winn, Heeter, & 2009). One of the few studies reporting evidence for far Downloaded from http://direct.mit.edu/jocn/article-pdf/29/9/1473/1952866/jocn_a_01080.pdf by guest on 01 October 2021 Anthony, 2013; Maillot, Perrot, & Hartley, 2012; McDougall transfer comes from the NeuroRacer game training multi- & House, 2012; Nouchi et al., 2012; Stern et al., 2011; tasking, resulting in improved RTs in a sustained attention Cassavaugh & Kramer, 2009; Basak, Boot, Voss, & Kramer, task as well as improved performance in a working memory 2008), or tailored games designed specifically for training task with or without distraction (Anguera et al., 2013). such as the NeuroRacer (e.g., Mishra et al., 2014; Anguera But why is there such limited evidence of far transfer? et al., 2013). Training regimens vary widely in terms of the Theoretically, far transfer refers to improvement in tasks choice of tasks, as well as in the duration and schedule of that have no overlap with the trained cognitive function. training, the nature of control groups, and the pre- and Considering that cognitive training drives plasticity in posttraining assessment batteries. Furthermore, different neural systems that support a specific function, it would studies measure the same cognitive function in their as- not be expected that cognitive functions that rely primar- sessment battery (e.g., working memory) using different ily on other neural systems should benefit. If we take tasks. Together, these differences complicate the assess- physical exercise as a simple analogy, muscles that are ment of the effectiveness of cognitive training. Neverthe- not involved in a specific exercise will not benefit from less, after controlling for some of these differences, a that specific activity. Thus, measuring the effectiveness meta-analysis of 20 training studies in the older participants of training in terms of far transfer may not be theoretically revealed that training older adults with computer-based sensible. tasks does improve several cognitive functions that decline Furthermore, what gets labeled as far transfer in any with aging, such as memory, attention, RT, and executive given study can often be based on arbitrary or crude cri- function especially in the older age range (Toril, Reales, & teria. For example, one may label a long-term memory Ballesteros, 2014). task as a far transfer following attention training, assum- The effectiveness of cognitive training is usually as- ing that these two cognitive functions have very little in sessed by looking at changes in performance in untrained common in terms of both function and neural substrate. cognitive tasks, otherwise known as “transfer.” Transfer However, as our understanding of the neural mecha- can occur to tasks that are close in function and tap into nisms supporting various cognitive functions evolves, the same underlying cognitive processes as in the train- the boundaries between tasks do not mirror a similar dis- ing, known as “near transfer.” For example, if participants tinction between their neuronal underpinnings. For ex- were trained on an n-back working memory task, another ample, training in the NeuroRacer resulted in an type of working memory task such as operation span increase in midline frontal theta power that has also been would be an example of near transfer. Alternatively, train- implicated in other cognitive functions and may reflect a ing can result in generalized improvement on tasks bear- general change in processes related to cognitive control ing little overlap to the task being trained, that is, “far that can play a role within many task contexts (e.g., transfer.” Examples of far transfer would be working Mitchell, McNaughton, Flanagan, & Kirk, 2008). Therefore, memory training resulting in improvements on a lan- what a few studies have labeled as far transfer may reflect guage or reasoning task (for more information on the some functional and neural overlap to the training concept of transfer, please refer to Klahr & Chen, 2011; regimen. Zelinski, 2009). Instead of focusing on the generality of training regi- There is some evidence supporting near transfer fol- mens, measured through far transfer, we propose that lowing cognitive interventions in older participants. A the effectiveness of training in the future should instead recent meta-analysis on the effectiveness of working highlight the specificity. Training interventions have the memory and executive function training reported a small potential to accommodate individual differences in base- to medium effect size for near transfer, that is, transfer to line cognitive abilities; one can optimally target tasks that other working memory and executive function measures require improvement based on an individual’s cognitive

Zokaei et al. 1475 fingerprint. In fact, few studies have shown that cognitive tervention. The importance of a well-matched control training may be more effective in individuals with low group becomes more significant because it has been baseline ability (e.g., Whitlock, McLaughlin, & Allaire, shown that cognitive training can be achieved through a 2012). Flexibility in personalized training interventions placebo effect, using only suggestive flyers, in young is thus the future of cognitive rehabilitation, both in individuals (Foroughi, Monfort, Paczynski, McKnight, & healthy aging and in disease. Greenwood, 2016). Unfortunately, however, many studies In addition, it may be possible to enhance the effec- in the elderly have not employed well-matched control

tiveness of training by considering other factors that groups, hindering interpretation of their findings. A well- Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/29/9/1473/1786573/jocn_a_01080.pdf by MIT Libraries user on 17 May 2021 may interact with training such as personality traits or matched control group should minimally match the exper- motivation levels. For example, it has been shown in imental training group in demographics, expectations younger participants that those who believe in malleabil- about the treatment, motivation levels, time of engage- ity of intelligence and cognition show greater improve- ment, challenge, and level of progression. ment following training than those who do not (Jaeggi, On one extreme, a few studies have neglected to Buschkuehl, Shah, & Jonides, 2014). Although not di- include any control group (e.g., Ackerman, Kanfer, & rectly related to motivation, such beliefs can influence Calderwood, 2010; Cassavaugh & Kramer, 2009). The Downloaded from http://direct.mit.edu/jocn/article-pdf/29/9/1473/1952866/jocn_a_01080.pdf by guest on 01 October 2021 the motivation levels of participants when undergoing absence of a control group in these studies means it is im- cognitive training. Furthermore, there are also few studies possible to determine whether the observed effects are examining the effect of different personality traits on cog- specific to the training regimen, a product of test–retest nitive training. For example, openness to experience has effects on the outcome measures or results of motivational been positively related to increased training gains (Double or social factors to name just a few. & Birney, 2016), with less consistent findings for other To control for test–retest effects, many studies have personality traits (Thompson et al., 2013; Studer-Luethi, employed a passive or no-contact control group (e.g., Jaeggi, Buschkuehl, & Perrig, 2012). Future studies should Belchior et al., 2013; Sosa, 2012; see Boot, Simons, thus not only focus on baseline individual cognitive abilities Stothart, & Stutts, 2013, for discussion). This involves a but also examine the effects of other factors that have been group of participants who perform the pre- and postas- shown, to some extent, to interact with training gains. This sessment battery, but who do not participate in any train- should also include studies that combine noninvasive neu- ing nor have any contact with the experimenter. roimaging techniques, such as fMRI, which have shown Although these designs control for practice effects on changes in resting-state functional connectivity in various the assessment battery, the level of social interaction with neural networks following training (e.g., Cao et al., 2016; the investigators is not matched between the groups. Strenziok et al., 2014; Kirchhoff, Anderson, Barch, & This is problematic, specifically because social interac- Jacoby, 2012). Baseline differences in connectivity and tions have been shown to have protective effect against anatomy may also contribute to both the effectiveness and age-related cognitive decline (Glei et al., 2005; Zunzunegui, the magnitude of cognitive training gain. Alvarado, Del Ser, & Otero, 2003). Moreover, any change in cognitive abilities following training in this design does not control the Hawthorne effect—the change in behavior due METHODOLOGICAL LIMITATIONS to participants’ awareness of being observed (Noland, 1959; Most published studies suggest some positive improve- Roethlisberger, Dickson, Wright, & Pforzheimer, 1939). ments after training. However, the progress in our under- Furthermore, differences in motivational levels may be at standing of brain training tools has been constrained by play, and it is well recognized that heightened motivation the lack of a standardized methodological protocol. In- can significantly enhance performance in multiple domains consistent methodologies employed by different studies (e.g., Pessoa, 2009). make comparison of different training tasks challenging More recently, the importance of employing active and preventing us from identifying the most reliably control groups has been recognized. Individuals in active effective components of a training regimen. There are a control groups undergo a training regimen that is well few methodological inconsistencies, explained below, matched to the experimental training intervention in as which, once addressed, will enhance future advancement many features as possible, for example, in duration, in- of this field. tensity, and frequency of training sessions, as well as in- teraction with researchers, except for the critical factor being manipulated. Although more studies are using ac- Control Groups tive control groups, they often are not well matched to The addition of well-matched control groups is an essential the training regimen. For example, Ballesteros et al. methodological component of training studies, because (2014) compared performance between a group of indi- most cognitive training studies involve between-group viduals trained on “Lumosity” brain training tasks against designs. They are used as a benchmark to measure the an active control group who met in the lab to discuss effectiveness of the training and allow us to isolate and topics of general interest. The computer-based training interpret the causes of any improvement by the in- regimen resulted in improved attention, memory, and

1476 Journal of Cognitive Neuroscience Volume 29, Number 9 processing speed compared with the control group—not evaluate training using large number of tasks, increasing surprising considering that the control group engaged in the probability of a false positive. Instead, the assessment activities unrelated to these cognitive processes. One battery should include sensitive tasks that are specific to promising approach is to assess the effects of adaptive cog- the trained cognitive functions as well as tasks that are nitive training against performance of individuals training hypothesized to have minimal overlap with the trained on a nonadaptive version of the same training task. cognitive functions. Developing a core, common compre- Another, possibly optimal approach is to use closely re- hensive, and sensitive cognitive battery for assessing cogni-

lated tasks with adaptive elements that specifically target tive training in different studies would be of great utility. Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/29/9/1473/1786573/jocn_a_01080.pdf by MIT Libraries user on 17 May 2021 different cognitive functions (A and B). The “training” and “control” groups become relative to one another. They Compliance should share training environments that are maximally sim- ilar. The efficacy of training can subsequently be verified In addition to scientific methodological limitations, a few using a double dissociation methodology, wherein partici- other practical factors can undermine the effective appli- pants in which the adaptive element of the task focused on cation of brain training. One such factor is low compli- function A should show transfer to tasks that share function ance. Training studies in the elderly have been plagued Downloaded from http://direct.mit.edu/jocn/article-pdf/29/9/1473/1952866/jocn_a_01080.pdf by guest on 01 October 2021 A, but not function B. In contrast, participants with adap- with issues of poor adherence to training schedules. tive training in B should show transfer on tasks that share For example, in a large-scale study by Owen and function B, but not A. The study by Mishra et al. (2014) ap- colleagues (2010), only 11,430 out of the initial 52,617 proximated this approach. They targeted either distractor participants completed a minimum of two 10-min train- or target discrimination by focusing the adaptive aspects of ing sessions during a 6-week training period. To ensure the training to challenge each process independently. In high compliance, future studies should also focus and ex- such a design, each training regimen acts as an active con- pand on quality of the tasks, creating more engaging and trol group for the other group while controlling for all the easily accessible training regimens. For example, desired factors mentioned. although action-based and first-person shooter games have yielded promising findings of training in various cognitive functions in younger participants (e.g., Bejjanki Standardized Assessment Battery et al., 2014; Green & Bavelier, 2012), 10 of 16 elderly in- A comprehensive and standardized sensitive battery of dividuals reported that they did not wish to engage in pre- and posttraining tasks is another essential methodo- such a training task and 50% of those that did claimed logical component of training studies. So far, a wide and that they did not enjoy the experience (McKay & Maki, unsystematic range of different cognitive and neuropsy- 2010). This highlights the importance that training regi- chological tasks has been used to assess the efficiency mens should be tailored to the preferences of older indi- of training tasks. Some studies have adopted standard- viduals. For example, a nonviolent, strategy video game ized neuropsychological tests, which are often used to di- such as Rise of Nations has been employed successfully agnose impairments in patient populations (e.g., Lee in training in older individuals (Basak et al., 2008). et al., 2013; Smith et al., 2009). Other studies have used Moreover, one other factor that may improve compli- a combination of publicly available assessment batteries ance is employing personalized training regimens, target- including the CogState (Bozoki et al., 2013), NexAde ing an individual’s cognitive ability that requires (Peretz et al., 2011) or elements of the WAIS (McDougall improvement. This will possibly motivate participants to & House, 2012; Drew & Waters, 1986). Still others have engage in training, as it will be beneficial to each partic- quantified the effectiveness of training according to the ipant, especially in studies that adapt a double dissocia- functional outcomes measures of daily living, such as the tion methodology (see Control Groups section). Everyday Problems Test, Activities of Daily Living (Willis Although these are possible solutions to tackle the et al., 2006; Ball et al., 2002), and Tests of Everyday Coping compliance problem, in some cases large sample sizes and Independent Living (Oswald, Gunzelmann, Rupprecht, are required to examine, for example, the effect of per- & Hagen, 2006). sonality traits on effectiveness of training. To tackle such These types of tasks have different degrees of sensitiv- questions and overcome poor adherence to training ity and specificity. Some may be too blunt to detect schedules, studies will benefit from collaborations with changes in healthy populations (Elkana et al., 2015). Stan- the technology industry, which will help with both access dard neuropsychological tasks and tasks of daily living to large number of willing participants and designing also often combine many cognitive functions (Wasserman engaging and accessible training tasks. & Wasserman, 2012), making it hard to pinpoint the specif- ic pattern of functions that have been modified. Moreover, UPGRADING COGNITIVE TRAINING the number and variety of tests used assessment batteries that differ dramatically. At one extreme, some studies use a Going forward, the field of cognitive training should very limited set of tests and thus may miss training effects focus first on addressing the aforementioned method- that are actually present. On the other hand, some studies ological shortcomings. This includes the addition of

Zokaei et al. 1477 well-controlled control groups and training procedures as et al., 2008). Although such training regimens would well as the development of a core assessment battery. The not be easily adaptable to accommodate individual differ- assessment battery should involve sensitive and specific ences, they have been shown to demonstrate consistent tasks that tap into both related and unrelated functions training benefits. The secret to the success of these train- to the training, going beyond what is afforded by standard ings may rely not only on their feature of taxing multiple neuropsychological tasks. Developing such a battery will cognitive functions but also on the specific type of func- require the development of novel measures and bench- tions that adapt with successful task performance, namely

marking against standardized tests. Furthermore, such a attention and cognitive control. Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/29/9/1473/1786573/jocn_a_01080.pdf by MIT Libraries user on 17 May 2021 battery should ideally contain separate subgroups, each tar- Cognitive functions related to attention and other geting a group of closely related cognitive functions, similar aspects of cognitive control are not unitary, isolated to commonly used neuropsychological measures (e.g., domains but rather support and interact heavily with Addenbrooke’s Cognitive Assessment, ACE). This will allow other cognitive domains (e.g., Mok, Myers, Wallis, & Nobre, researchers to select tasks that are closely related to the 2016; Kuo, Stokes, & Nobre, 2012; Rohenkohl, Cravo, Wyart, question at hand, minimizing the negative effects of fatigue & Nobre, 2012; Stokes, Atherton, Patai, & Nobre, 2012). and lack of motivation that can follow long assessment ses- As such, they can be of as providing an important Downloaded from http://direct.mit.edu/jocn/article-pdf/29/9/1473/1952866/jocn_a_01080.pdf by guest on 01 October 2021 sions. Moreover, gamification of cognitive tests will appeal scaffold for organizing and optimizing cognition across to the ever-growing technology-savvy older population, the board. Hence, a training regimen that focuses on these allowing for a more accessibleandenjoyablecognitive functions will not only have a specific effect on these fingerprinting of participants. Although there have been functions alone but also have an impact on many other many attempts at creating such battery (e.g., CANTAB or cognitive tasks. UFOV), the commercialized nature of such attempts limits Therefore, a complementary approach to training sin- the accessibility and flexibility of these batteries. gle cognitive functions in isolation is to train these scaf- Moreover, alongside in-depth cognitive assessment, folding functions, such as sustaining and focusing measures of daily living should also be included, ideally attention, resisting distraction, and task switching. Taking in conjunction with low-friction measures of cognitive this even further, training could also target the coopera- performance in real life. These measures will become in- tion between cognitive functions to allow for a synergistic creasingly available as scientific research forges links with enhancement of cognition. Thus, to bolster a specific the digital technology industry to use wearable devices to function, a training task should first target that specific gain performance measures on important and relevant function, through engaging, motivating, dynamic, and variables such as mobility and the extent of social inter- adaptive training. In complement, and equally impor- actions, as well as physiological measures, such as heart tantly, it should promote cooperation of that function rate variability and sleep quality. with other domains. For example, working memory train- The nature of the cognitive training tasks should also ing should not only focus on increasing its capacity to be considered carefully. Often, tasks that have been used encode and maintain greater number of items. It should successfully to investigate the psychological and neural also train the ability to protect memory representations mechanisms of cognition are adapted or deployed for from distractors and to prioritize flexibly the items that cognitive training. These, however, rarely provide effec- are in memory. tive tools for training, resulting in weak transfer effects In addition, it may be possible to boost the effects of at best. This is the case if single tasks have been used cognitive training by combining it with physical training in isolation or if multiple tasks have been used in parallel (see Hötting & Röder, 2013, for a review). Physical exer- (Ballesteros et al., 2014; Boot et al., 2013; Bozoki et al., cise influences synaptic plasticity, cell proliferation, and 2013; McDougall & House, 2012; van Muijden, Band, & vascularization and is related to gray and white matter Hommel, 2012; Peretz et al., 2011; Dahlin, Neely, Larsson, volumes in older adults (e.g., Sexton et al., 2016; Erickson, Bäckman, & Nyberg, 2008). Gildengers, & Butters, 2013). Furthermore, a meta-analysis An alternative approach has been to use training tasks of 18 physical training studies with older adults has re- that employ and coordinate multiple cognitive functions vealed that physical fitness has a “robust” effect on cogni- simultaneously. These tasks tend to come from more im- tion in the elderly (Colcombe & Kramer, 2003). Therefore, mersive gaming contexts rather than experimental task physical and cognitive training may interact so that designs. This was demonstrated in one study that trained together they are more beneficial than the added effects participants in a highly multifactorial game, which taxed of each type of training in isolation. A flurry of studies have divided attention, executive function, and, importantly, started investigating whether combined cognitive and their effective coordination (Basak et al., 2008). This physical training confers an additional advantage to cogni- study and others employing similar training tasks that tive functions in the elderly (e.g., Zheng et al., 2015; Shah combine many cognitive domains such as navigation in et al., 2014; Maillot et al., 2012). However, only a few have a rich virtual reality environment, tracking of multiple ob- directly compared combined cognitive-physical training to jects, attention-switching or goal-directed plans provide cognitive-only training interventions in the elderly (e.g., effective training (e.g., Belchior et al., 2013; Basak Oswald et al., 2006; Rahe et al., 2015; Smiley-Oyen, Lowry,

1478 Journal of Cognitive Neuroscience Volume 29, Number 9 Francois, Kohut, & Ekkekakis, 2008). With the availability of Reprint requests should be sent to Nahid Zokaei, Oxford Centre recent technologies such as Nintendo Wii and Xbox Kinect for Activity, Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, United Kingdom, or via e-mail: nahid. (home-based gaming consoles), future studies can more [email protected]. easily test the effectiveness of cognitive and physical training. As our understanding of the mechanisms of cognitive REFERENCES training grows and our methodology to apply and assess Ackerman, P. L., Kanfer, R., & Calderwood, C. (2010). Use it or interventions is refined, it will become possible to apply Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/29/9/1473/1786573/jocn_a_01080.pdf by MIT Libraries user on 17 May 2021 tailored cognitive training interventions in patient popu- lose it? Wii brain exercise practice and reading for domain knowledge. Psychology and Aging, 25, 753–766. lations. Although many studies have examined the effect Anguera, J. A., Boccanfuso, J., Rintoul, J. L., Al-Hashimi, O., of training in patients with, for example, mild cognitive Faraji, F., Janowich, J., et al. (2013). Video game training impairment (e.g., Vermeij et al., 2016; Reijnders, van enhances cognitive control in older adults. Nature, 501, Heugten, & van Boxtel, 2013; Gates, Sachdev, Fiatarone 97–101. Singh, & Valenzuela, 2011; Li et al., 2011), brain injury Ball, K., Berch, D. B., Helmers, K. F., Jobe, J. B., Leveck, M. D., Marsiske, M., et al. (2002). Effects of cognitive training (e.g., Dymowski, Ponsford, & Willmott, 2016; Lindeløv interventions with older adults: A randomized controlled Downloaded from http://direct.mit.edu/jocn/article-pdf/29/9/1473/1952866/jocn_a_01080.pdf by guest on 01 October 2021 et al., 2016), stroke (Wentink et al., 2016; Gamito et al., trial. JAMA, 288, 2271–2281. 2015), or Alzheimer’s disease (Kim et al., 2016; Sitzer, Ballesteros, S., Prieto, A., Mayas, J., Toril, P., Pita, C., Ponce de Twamley, & Jeste, 2006), very few were able to demon- León, L., et al. (2014). Brain training with non-action video strate clear training benefits. At present, the methodolog- games enhances aspects of cognition in older adults: A randomized controlled trial. Frontiers in Aging Neuroscience, ical limitations that plague training tasks in studies of 6, 277. healthy elderly volunteers also extend to studies involv- Baniqued, P. L., Kranz, M. B., Voss, M. W., Lee, H., Cosman, ing patient population. Often problems are further exac- J. D., Severson, J., et al. (2014). Cognitive training with casual erbated with regard to the choice of training tasks, video games: Points to consider. Frontiers in Psychology, because not all tasks used for the healthy elderly individ- 4, 1010. Bárrios, H., Narciso, S., Guerreiro, M., Maroco, J., Logsdon, R., uals can be performed by individuals with clinical symp- & de Mendonça, A. (2013). Quality of life in patients with toms, such as motor problems in the case of Parkinson’s mild cognitive impairment. Aging & Mental Health, 17, disease or severe memory problems in the case of 287–292. Alzheimer’s disease. Basak, C., Boot, W. R., Voss, M. W., & Kramer, A. F. (2008). Can training in a real-time strategy video game attenuate cognitive decline in older adults? Psychology and Aging, 23, 765–777. Conclusion Bejjanki, V. R., Zhang, R., Li, R., Pouget, A., Green, C. S., Lu, Z.-L., et al. (2014). Action video game play facilitates the Computer-based training is still a young and emerging development of better perceptual templates. Proceedings of field. Unsurprisingly, there are many lessons to be the National Academy of Sciences, U.S.A., 111, 16961–16966. learned before the field matures. The importance and Belchior, P., Marsiske, M., Sisco, S. M., Yam, A., Bavelier, D., Ball, K., et al. (2013). Video game training to improve cost posed by cognitive decline in the elderly; the enor- selective visual attention in older adults. Computers in mous impact that a simple lifestyle-based intervention Human Behavior, 29, 1318–1324. can have on the lives of individuals as well as on the Boot, W. R., Simons, D. J., Stothart, C., & Stutts, C. (2013). The burden to society; and the inherent features that enable pervasive problem with placebos in psychology why active cognitive training to be readily accessible, targeted, control groups are not sufficient to rule out placebo effects. Perspectives on Psychological Science, 8, 445–454. personalized, and flexible all argue for continued invest- Bozoki, A., Radovanovic, M., Winn, B., Heeter, C., & Anthony, ment in developing this line of research. The enterprise J. C. (2013). Effects of a computer-based cognitive exercise will benefit significantly from building collaborative part- program on age-related cognitive decline. Archives of nerships between academic research and the information Gerontology and Geriatrics, 57, 1–7. and technology industry to enable rapid innovation of Brockmole, J. R., & Logie, R. H. (2013). Age-related change in visual working memory: A study of 55,753 participants aged platforms and applications that are accessible to and en- 8–75. Frontiers in Psychology, 4, 12. gage the general public. We are optimistic that method- Brockmole, J. R., Parra, M. A., Della Sala, S., & Logie, R. H. ological and conceptual breakthroughs on the horizon (2008). Do binding deficits account for age-related decline in will enable cognitive training to realize its full potential visual working memory? Psychonomic Bulletin & Review, – to transform cognitive rehabilitation in both normal and 15, 543 547. Cao, W., Cao, X., Hou, C., Li, T., Cheng, Y., Jiang, L., et al. abnormal aging. (2016). Effects of cognitive training on resting-state functional connectivity of default mode, salience, and central executive Acknowledgments networks. Frontiers in Aging Neuroscience, 8, 70. Cassavaugh, N. D., & Kramer, A. F. (2009). Transfer of This work was supported by the Wellcome Trust (A. C. N., computer-based training to simulated driving in older adults. 104571/Z/14/Z), the British Academy (N. Z., pf150057), and the Applied Ergonomics, 40, 943–952. National Institute for Health Research (NIHR) Oxford Biomedical Chowdhury, R., Guitart-Masip, M., Bunzeck, N., Dolan, R. J., Research Centre based at Oxford University Hospitals NHS & Düzel, E. (2012). Dopamine modulates episodic memory Foundation Trust Oxford University. persistence in old age. Journal of Neuroscience, 32, 14193–14204.

Zokaei et al. 1479 Chowdhury, R., Guitart-Masip, M., Lambert, C., Dayan, P., Huys, activities helps preserve cognitive function: An analysis of a Q., Düzel, E., et al. (2013). Dopamine restores reward prediction longitudinal, population-based study of the elderly. errors in old age. Nature Neuroscience, 16, 648–653. International Journal of Epidemiology, 34, 864–871. Clemenson, G. D., & Stark, C. E. L. (2015). Virtual environmental Goldstein, P., Cajko, L., Oosterbroek, M., Michielsen, M., Van enrichment through video games improves hippocampal- Houten, O., & Salverda, F. (1997). Video games and the associated memory. Journal of Neuroscience, 35, elderly. Social Behavior and Personality, 25, 345–352. 16116–16125. Green, C. S., & Bavelier, D. (2012). , attentional control Colcombe, S., & Kramer, A. F. (2003). Fitness effects on the and action video games. Current Biology, 22, R197–R206. cognitive function of older adults: A meta-analytic study. Hötting, K., & Röder, B. (2013). Beneficial effects of physical Psychological Science, 14, 125–130. exercise on neuroplasticity and cognition. Neuroscience and Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/29/9/1473/1786573/jocn_a_01080.pdf by MIT Libraries user on 17 May 2021 Craik, F. I. M., & Bialystok, E. (2006). Cognition through the Biobehavioral Reviews, 37, 2243–2257. lifespan: Mechanisms of change. Trends in Cognitive Jaeggi, S. M., Buschkuehl, M., Shah, P., & Jonides, J. (2014). The Sciences, 10, 131–138. role of individual differences in cognitive training and Dahlin, E., Neely, A. S., Larsson, A., Bäckman, L., & Nyberg, L. transfer. Memory & Cognition, 42, 464–480. (2008). Transfer of learning after updating training mediated Karbach, J., & Verhaeghen, P. (2014). Making working memory by the striatum. Science, 320, 1510–1512. work: A meta-analysis of executive-control and working Davies, H. D., Newkirk, L. A., Pitts, C. B., Coughlin, C. A., memory training in older adults. Psychological Science, Sridhar, S. B., Zeiss, L. M., et al. (2010). The impact of 25, 2027–2037. Downloaded from http://direct.mit.edu/jocn/article-pdf/29/9/1473/1952866/jocn_a_01080.pdf by guest on 01 October 2021 and mild memory impairment (MMI) on intimacy Kim, M.-J., Han, C.-W., Min, K.-Y., Cho, C.-Y., Lee, C.-W., Ogawa, and sexuality in spousal relationships. International Y., et al. (2016). Physical exercise with multicomponent Psychogeriatrics, 22, 618–628. cognitive intervention for older adults with Alzheimer’s Double, K. S., & Birney, D. P. (2016). The effects of personality disease: A 6-month randomized controlled trial. Dementia and metacognitive beliefs on cognitive training adherence and Geriatric Cognitive Disorders Extra, 6, 222–232. and performance. Personality and Individual Differences, Kirchhoff, B. A., Anderson, B. A., Barch, D. M., & Jacoby, L. L. 102, 7–12. (2012). Cognitive and neural effects of semantic encoding Drew, B., & Waters, J. (1986). Video games: Utilization of a strategy training in older adults. Cerebral Cortex, 22, 788–799. novel strategy to improve perceptual motor skills and Klahr, D., & Chen, Z. (2011). Finding one’s place in transfer cognitive functioning in the non-institutionalized elderly. space. Child Development Perspectives, 5, 196–204. Cognitive Rehabilitation, 4, 26–31. Kuo, B.-C., Stokes, M. G., & Nobre, A. C. (2012). Attention Dymowski, A. R., Ponsford, J. L., & Willmott, C. (2016). modulates maintenance of representations in visual short- Cognitive training approaches to remediate attention and term memory. Journal of Cognitive Neuroscience, 24, 51–60. executive dysfunction after : Lee, T.-S., Goh, S. J. A., Quek, S. Y., Phillips, R., Guan, C., A single-case series. Neuropsychological Rehabilitation, Cheung, Y. B., et al. (2013). A brain-computer interface based 26, 866–894. cognitive training system for healthy elderly: A randomized Edwards, J. D., Wadley, V. G., Vance, D. E., Wood, K., Roenker, control pilot study for usability and preliminary efficacy. PLoS D. L., & Ball, K. K. (2005). The impact of speed of processing One, 8, e79419. training on cognitive and everyday performance. Aging & Li, H., Li, J., Li, N., Li, B., Wang, P., & Zhou, T. (2011). Cognitive Mental Health, 9, 262–271. intervention for persons with mild cognitive impairment: Elkana, O., Eisikovits, O. R., Oren, N., Betzale, V., Giladi, N., & A meta-analysis. Ageing Research Reviews, 10, 285–296. Ash, E. L. (2015). Sensitivity of neuropsychological tests to Li, S.-C., Brehmer, Y., Shing, Y. L., Werkle-Bergner, M., & identify cognitive decline in highly educated elderly Lindenberger, U. (2006). Neuromodulation of associative and individuals: 12 Months follow up. Journal of Alzheimer’s organizational plasticity across the life span: Empirical Disease, 49, 607–616. evidence and neurocomputational modeling. Neuroscience Erickson, K. I., Gildengers, A. G., & Butters, M. A. (2013). and Biobehavioral Reviews, 30, 775–790. Physical activity and brain plasticity in late adulthood. Li, S.-C., Schmiedek, F., Huxhold, O., Röcke, C., Smith, J., & Dialogues in Clinical Neuroscience, 15, 99–108. Lindenberger, U. (2008). Working memory plasticity in old Foroughi, C. K., Monfort, S. S., Paczynski, M., McKnight, P. E., & age: Practice gain, transfer, and maintenance. Psychology and Greenwood, P. M. (2016). Placebo effects in cognitive Aging, 23, 731–742. training. Proceedings of the National Academy of Sciences, Lindeløv, J. K., Dall, J. O., Kristensen, C. D., Aagesen, M. H., U.S.A., 113, 7470–7474. Olsen, S. A., Snuggerud, T. R., et al. (2016). Training and Frank, L., Lloyd, A., Flynn, J. A., Kleinman, L., Matza, L. S., transfer effects of n-back training for brain-injured and Margolis, M. K., et al. (2006). Impact of cognitive impairment healthy subjects. Neuropsychological Rehabilitation, on mild dementia patients and mild cognitive impairment 26, 895–909. patients and their informants. International Mahncke, H. W., Connor, B. B., Appelman, J., Ahsanuddin, Psychogeriatrics, 18, 151–162. O. N., Hardy, J. L., Wood, R. A., et al. (2006). Memory Gamito, P., Oliveira, J., Coelho, C., Morais, D., Lopes, P., enhancement in healthy older adults using a brain plasticity- Pacheco, J., et al. (2015). Cognitive training on stroke based training program: A randomized, controlled study. patients via virtual reality-based serious games. Disability Proceedings of the National Academy of Sciences, U.S.A., and Rehabilitation, 2, 1–4. 103, 12523–12528. Gates, N. J., Sachdev, P. S., Fiatarone Singh, M. A., & Valenzuela, Maillot, P., Perrot, A., & Hartley, A. (2012). Effects of interactive M. (2011). Cognitive and memory training in adults at risk of physical-activity video-game training on physical and cognitive dementia: A systematic review. BMC Geriatrics, 11, 55. function in older adults. Psychology and Aging, 27, 589–600. Gazzaley, A., Cooney, J. W., Rissman, J., & D’Esposito, M. Maki, Y., Yamaguchi, T., Yamagami, T., Murai, T., Hachisuka, K., (2005). Top–down suppression deficit underlies working Miyamae, F., et al. (2014). The impact of subjective memory memory impairment in normal aging. Nature Neuroscience, complaints on quality of life in community-dwelling older 8, 1298–1300. adults. Psychogeriatrics, 14, 175–181. Glei, D. A., Landau, D. A., Goldman, N., Chuang, Y.-L., McDougall, S., & House, B. (2012). Brain training in older Rodríguez, G., & Weinstein, M. (2005). Participating in social adults: Evidence of transfer to memory span performance

1480 Journal of Cognitive Neuroscience Volume 29, Number 9 and pseudo-Matthew effects. , Development, studies examining the relationship between physical fitness and Cognition. Section B, Aging, Neuropsychology and and activity and the white matter of the ageing brain. Cognition, 19, 195–221. Neuroimage, 131, 81–90. McKay, S. M., & Maki, B. E. (2010). Attitudes of older adults Shah, T., Verdile, G., Sohrabi, H., Campbell, A., Putland, E., toward shooter video games: An initial study to select an Cheetham, C., et al. (2014). A combination of physical activity acceptable game for training visual processing. Gerontechnology, and computerized brain training improves verbal memory 9, 5–17. and increases cerebral glucose metabolism in the elderly. Melby-Lervåg, M., & Hulme, C. (2013). Is working memory Translational Psychiatry, 4, e487. training effective? A meta-analytic review. Developmental Sitzer, D. I., Twamley, E. W., & Jeste, D. V. (2006). Cognitive Psychology, 49, 270–291. training in Alzheimer’s disease: A meta-analysis of the Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/29/9/1473/1786573/jocn_a_01080.pdf by MIT Libraries user on 17 May 2021 Mishra, J., de Villers-Sidani, E., Merzenich, M., & Gazzaley, A. literature. Acta Psychiatrica Scandinavica, 114, 75–90. (2014). Adaptive training diminishes distractibility in aging Smiley-Oyen, A. L., Lowry, K. A., Francois, S. J., Kohut, M. L., & across species. Neuron, 84, 1091–1103. Ekkekakis, P. (2008). Exercise, fitness, and neurocognitive Mishra, J., & Gazzaley, A. (2015). Closed-loop cognition: The function in older adults: The “selective improvement” and next frontier arrives. Trends in Cognitive Sciences, 19, “cardiovascular fitness” hypotheses. Annals of Behavioral 242–243. Medicine: A Publication of the Society of Behavioral Mitchell, D. J., McNaughton, N., Flanagan, D., & Kirk, I. J. Medicine, 36, 280–291. (2008). Frontal-midline theta from the perspective of Smith, G. E., Housen, P., Yaffe, K., Ruff, R., Kennison, R. F., Downloaded from http://direct.mit.edu/jocn/article-pdf/29/9/1473/1952866/jocn_a_01080.pdf by guest on 01 October 2021 hippocampal “theta.” Progress in Neurobiology, 86, 156–185. Mahncke, H. W., et al. (2009). A cognitive training program Mok, R. M., Myers, N. E., Wallis, G., & Nobre, A. C. (2016). based on principles of brain plasticity: Results from the Behavioral and neural markers of flexible attention over Improvement in Memory with Plasticity-based Adaptive working memory in aging. Cerebral Cortex, 26, 1831–1842. Cognitive Training (IMPACT) study. Journal of the American Noack, H., Lövdén, M., Schmiedek, F., & Lindenberger, U. Geriatrics Society, 57, 594–603. (2009). Cognitive plasticity in adulthood and old age: Smyth, A. C., & Shanks, D. R. (2011). Aging and implicit Gauging the generality of cognitive intervention effects. learning: Explorations in contextual cuing. Psychology and Restorative Neurology and Neuroscience, 27, 435–453. Aging, 26, 127–132. Noland, E. W. (1959). Landsberger’s Hawthorne revisited. Sosa, G. (2012). The impact of a video game intervention on the Ithaca. Social Forces, 37, 361–364. cognitive functioning, self-efficacy, self-esteem, and video Nouchi, R., Taki, Y., Takeuchi, H., Hashizume, H., Akitsuki, Y., game attitudes of older adults. CGU Theses & Dissertations. Shigemune, Y., et al. (2012). Brain training game improves doi:10.5642/cguetd/19. and processing speed in the elderly: A Stark, S. M., Stevenson, R., Wu, C., Rutledge, S., & Stark, C. E. L. randomized controlled trial. PLoS One, 7, e29676. (2015). Stability of age-related deficits in the mnemonic Oswald, W. D., Gunzelmann, T., Rupprecht, R., & Hagen, B. similarity task across task variations. Behavioral (2006). Differential effects of single versus combined Neuroscience, 129, 257–268. cognitive and physical training with older adults: The SimA Stark, S. M., Yassa, M. A., Lacy, J. W., & Stark, C. E. L. (2013). study in a 5-year perspective. European Journal of Ageing, 3, A task to assess behavioral pattern separation (BPS) in 179–192. humans: Data from healthy aging and mild cognitive Owen, A. M., Hampshire, A., Grahn, J. A., Stenton, R., Dajani, S., impairment. Neuropsychologia, 51, 2442–2449. Burns, A. S., et al. (2010). Putting brain training to the test. Stern, Y., Blumen, H. M., Rich, L. W., Richards, A., Herzberg, G., Nature, 465, 775–778. & Gopher, D. (2011). Space Fortress game training and Peich, M.-C., Husain, M., & Bays, P. M. (2013). Age-related executive control in older adults: A pilot intervention. decline of precision and binding in visual working memory. Neuropsychology, Development, and Cognition. Section B, Psychology and Aging, 28, 729–743. Aging, Neuropsychology and Cognition, 18, 653–677. Peretz, C., Korczyn, A. D., Shatil, E., Aharonson, V., Birnboim, Stokes, M. G., Atherton, K., Patai, E. Z., & Nobre, A. C. (2012). S., & Giladi, N. (2011). Computer-based, personalized Long-term memory prepares neural activity for . cognitive training versus classical computer games: A Proceedings of the National Academy of Sciences, U.S.A., randomized double-blind prospective trial of cognitive 109, E360–E367. stimulation. Neuroepidemiology, 36, 91–99. Strenziok, M., Parasuraman, R., Clarke, E., Cisler, D. S., Pessoa, L. (2009). How do emotion and motivation direct Thompson, J. C., & Greenwood, P. M. (2014). executive control? Trends in Cognitive Sciences, 13, 160–166. Neurocognitive enhancement in older adults: Comparison Rahe, J., Petrelli, A., Kaesberg, S., Fink, G., Kessler, J., & Kalbe, of three cognitive training tasks to test a hypothesis of E. (2015). Effects of cognitive training with additional physical training transfer in brain connectivity. Neuroimage, 85, activity compared to pure cognitive training in healthy older 1027–1039. adults. Clinical Interventions in Aging, 10, 297–310. Studer-Luethi, B., Jaeggi, S. M., Buschkuehl, M., & Perrig, W. J. Reijnders, J., van Heugten, C., & van Boxtel, M. (2013). (2012). Influence of neuroticism and conscientiousness on Cognitive interventions in healthy older adults and people working memory training outcome. Personality and with mild cognitive impairment: A systematic review. Ageing Individual Differences, 53, 44–49. Research Reviews, 12, 263–275. Teng, E., Tassniyom, K., & Lu, P. H. (2012). Reduced quality-of- Roethlisberger, F. J., Dickson, W. J., Wright, H. A., & life ratings in mild cognitive impairment: Analyses of subject Pforzheimer, C. H. (1939). Management and the worker: An and informant responses. The American Journal of Geriatric account of a research program conducted by the Western Psychiatry, 20, 1016–1025. Electric Company, Hawthorne works, Chicago. Cambridge, Thompson, T. W., Waskom, M. L., Garel, K.-L. A., Cardenas- MA: Press. Iniguez, C., Reynolds, G. O., Winter, R., et al. (2013). Failure Rohenkohl, G., Cravo, A. M., Wyart, V., & Nobre, A. C. (2012). of working memory training to enhance cognition or Temporal expectation improves the quality of sensory intelligence. PLoS One, 8, e63614. information. Journal of Neuroscience, 32, 8424–8428. Toril, P., Reales, J. M., & Ballesteros, S. (2014). Video game Sexton, C. E., Betts, J. F., Demnitz, N., Dawes, H., Ebmeier, training enhances cognition of older adults: A meta-analytic K. P., & Johansen-Berg, H. (2016). A systematic review of MRI study. Psychology and Aging, 29, 706–716.

Zokaei et al. 1481 van Muijden, J., Band, G. P. H., & Hommel, B. (2012). Online a multi-modal, attentionally demanding game-based games training aging : Limited transfer to cognitive intervention for older adults. Computers in Human control functions. Frontiers in Human Neuroscience, 6, 221. Behavior, 28, 1091–1096. Vermeij, A., Kessels, R. P. C., Heskamp, L., Simons, E. M. F., Willis, S. L., Tennstedt, S. L., Marsiske, M., Ball, K., Elias, J., Dautzenberg, P. L. J., & Claassen, J. A. H. R. (2016). Prefrontal Koepke, K. M., et al. (2006). Long-term effects of cognitive activation may predict working memory training gain in training on everyday functional outcomes in older adults. normal aging and mild cognitive impairment. Brain Imaging JAMA, 296, 2805–2814. and Behavior, 26, 783–809. Zanto, T. P., Pan, P., Liu, H., Bollinger, J., Nobre, A. C., & Wadley, V. G., Okonkwo, O., Crowe, M., & Ross-Meadows, L. A. Gazzaley, A. (2011). Age-related changes in orienting (2008). Mild cognitive impairment and everyday function: attention in time. Journal of Neuroscience, 31, 12461–12470. Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/29/9/1473/1786573/jocn_a_01080.pdf by MIT Libraries user on 17 May 2021 Evidence of reduced speed in performing instrumental Zanto, T. P., Sekuler, R., Dube, C., & Gazzaley, A. (2013). activities of daily living. The American Journal of Geriatric Age-related changes in expectation-based modulation of Psychiatry, 16, 416–424. motion detectability. PLoS One, 8, e69766. Wasserman, T., & Wasserman, L. D. (2012). The sensitivity and Zelinski, E. M. (2009). Far transfer in cognitive training of older specificity of neuropsychological tests in the diagnosis of adults. Restorative Neurology and Neuroscience, 27, 455–471. attention deficit hyperactivity disorder. Applied Zheng, Z., Zhu, X., Yin, S., Wang, B., Niu, Y., Huang, X., et al. Neuropsychology: Child, 1, 90–99. (2015). Combined cognitive-psychological-physical Wentink, M. M., Berger, M. A. M., de Kloet, A. J., Meesters, J., intervention induces reorganization of intrinsic functional brain Downloaded from http://direct.mit.edu/jocn/article-pdf/29/9/1473/1952866/jocn_a_01080.pdf by guest on 01 October 2021 Band, G. P. H., Wolterbeek, R., et al. (2016). The effects architecture in older adults. Neural Plasticity, 2015, 713104. of an 8-week computer-based brain training programme Zunzunegui, M.-V., Alvarado, B. E., Del Ser, T., & Otero, A. on cognitive functioning, QoL and self-efficacy after (2003). Social networks, social integration, and social stroke. Neuropsychological Rehabilitation, 26, engagement determine cognitive decline in community- 847–865. dwelling Spanish older adults. The Journals of Gerontology, Whitlock, L. A., McLaughlin, A. C., & Allaire, J. C. (2012). Series B, Psychological Sciences and Social Sciences, 58, Individual differences in response to cognitive training: Using S93–S100.

1482 Journal of Cognitive Neuroscience Volume 29, Number 9