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This suggests that additional training could lead to larger gains. While it is unlikely that the linear relation holds indefinitely i. In addition to the enhanced performance observed in the cognitive training group on the neuropsychological measures of cognitive function, participants in this group also self-reported experiencing benefits that were significantly greater than those reported by participants in the active control.
These participant-reported improvements were particularly strong on questions related to the ability to concentrate. These results suggest that participants in the treatment group experienced benefits from the training in their everyday lives. Crossword puzzles were chosen as the active control because they are commonly believed to be a cognitively stimulating activity that is good for brain health [ 31 , 32 ].
This is important because it has been suggested that belief in the efficacy of a training intervention could affect effort and performance on testing outcomes [ 47 ].
While not as large as the gains seen in the treatment group, participants in the crosswords control group also showed improvements in cognitive performance. Without a no-contact control group in this study, it is not possible to conclusively determine whether these improvements in the active control condition were due to practice effects, placebo effects, real treatment effects, or some combination of these.
Further study will be needed to better understand the benefits of crossword puzzles for maintenance and enhancement of cognition. It is worth noting that participants in the crosswords group improved slightly more than the cognitive training group on a measure of grammatical reasoning.
There are several reasons why the treatment program might have outperformed crossword puzzles in enhancing cognitive function. First, the cognitive training program is specifically targeted to core cognitive functions.
This distinguishes the treatment from crossword puzzles, which are not designed with the goal of cognitive enhancement. Another central feature of the cognitive training program studied here is that it is progressively challenging —that is, many of the tasks explicitly increase in difficulty as the individual improves, while others encourage the individual to perform at threshold by rewarding increasingly faster and more accurate performance see S1 Appendix.
This follows a long-established tenet in the psychological literature, that learning conditions are optimized when the task is challenging, but not prohibitively difficult [ 48 , 49 ]. Task variety and novelty are also potentially important.
In the case of crossword puzzles, participants are primarily involved in vocabulary retrieval, challenging a more limited set of neural pathways. In the cognitive training program studied here, participants are challenged to engage with a variety of cognitive tasks that challenge different neural processing systems and do so in different ways.
This variety limits the opportunity to solve the tasks with a single task-specific strategy, thus encouraging the learning of new strategies and the development of new neural connections. We noted that there have been several studies that have reported not finding benefits from cognitive training.
The only other similarly powered study that did not find positive results is a study that recruited 11, participants through a BBC television show and collected data online [ 17 ]. The authors concluded that brain training had no measureable benefits. Several key aspects of that study differ from the one presented here.
First, neither of the two treatment conditions they used had been studied empirically prior to that experiment. As we demonstrate in this study, not all cognitively stimulating activities are equally effective for enhancing cognition, and it is possible that other programs not examined in their study are more effective.
Also, the average amount of training exposure in the BBC study was less than half of that in this study. This is an important distinction as results of this study indicate that amount of training is related to the magnitude of gains in cognitive performance Fig 4.
Our results represent statistically significant improvements in cognitive processes through training. This study included a sufficiently large number of participants and enough training to reliably detect these effects.
As has been noted previously [ 50 ], most cognitive training studies that have shown null results have not been powered in such a way that either a positive or a null outcome would be informative, and often include quite short training periods.
In the broader context of factors influencing cognitive processes i. Further research will be needed to understand how the current effects extrapolate over much longer training periods. In this study, There was little difference in dropout rates between the two groups, and supplemental analyses S1 File that equated the engagement characteristics of completers from both groups demonstrated that these differences in dropout between the two groups could not explain the results.
This study utilized an entirely online design. The online methodology is ecologically valid, since most users in the real world experience the program at home or in some other personal environment outside a laboratory or clinic. In traditional laboratory-based training studies, participants experience considerable contact with study personnel.
Contact with study personnel may lead to lower rates of loss to follow up. However, this personal interaction introduces a variable that could affect the results and is not reflective of how most normal, healthy adults use these programs.
A possible limitation of the current study is that it does not isolate specific mechanisms. For example, adaptive difficulty may play an important role in driving the transfer of training [ 51 ].
Many of the tasks in the cognitive training program were explicitly adaptive i. The two conditions differed on other dimensions as well.
The cognitive training program incorporated a variety of tasks that targeted specific cognitive functions, while the crosswords condition did not. Future research is needed to more fully elucidate the relative contributions of particular components of activities that lead to improvements in cognitive performance.
Future studies could also extend the cognitive domains tested. Our neuropsychological assessment battery was relatively comprehensive across a variety of domains, but not every possible dimension of cognition was addressed. For example, this battery did not include any assessment explicitly targeting learning e.
Research on training to improve cognitive skills is not complete, and there remain many open questions. The ability to efficiently collect large data sets in controlled experiments over the Internet may prove crucial to answering the open questions related to cognitive training in the future.
The first supplementary analysis is an ANCOVA analysis that includes participants assigned to the control group who engaged in some cognitive training during the study period. The second supplementary analysis describes how engagement time is estimated in the two conditions and provides a paired-matching analysis that controls for the total time spent engaging with the two conditions.
The third supplementary analysis includes an outlier removal procedure. We would like to acknowledge the efforts of all the dedicated people who have worked to create Lumosity. We would like to thank Kacey Ballard Corrado and Tyler Hinman for their work to facilitate the creation of the crossword puzzles system that was used as the control condition.
We would also like to thank Sylvia Bunge, Murali Doraiswamy, Jerri Edwards, Amit Etkin, Anett Gyurak, Christine Hooker, Joseph Ventura, and Mike Walker for their thoughtful comments on the manuscript. Conceived and designed the experiments: JLH FF RAN MET DAS MS. Performed the experiments: JLH FF DAS MS.
Analyzed the data: DAS KK. Wrote the paper: JLH RAN MET DAS KK FF MS. Browse Subject Areas? Click through the PLOS taxonomy to find articles in your field.
Article Authors Metrics Comments Media Coverage Reader Comments Figures. Abstract Background A variety of studies have demonstrated gains in cognitive ability following cognitive training interventions.
Methods The present study evaluated an online cognitive training program comprised of 49 exercises targeting a variety of cognitive capacities. Conclusion Taken together, these results indicate that a varied training program composed of a number of tasks targeted to different cognitive functions can show transfer to a wide range of untrained measures of cognitive performance.
Trial Registration ClinicalTrials. gov NCT Greenlee, University of Regensburg, GERMANY Received: March 4, ; Accepted: July 8, ; Published: September 2, Copyright: © Hardy et al.
This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Data Availability: The study data for the statistical comparisons of outcomes for cognitive training relative to crosswords are in a CSV file in Supporting Information.
Introduction Recent evidence suggests that engaging in cognitively challenging activities can positively impact brain function, with studies demonstrating behavioral [ 1 , 2 ], physiological [ 3 , 4 ], and real-world functional [ 5 , 6 ] gains.
Methods Ethics statement Participants provided informed consent by clicking a dialogue box on a digital consent form prior to participation in the study.
Trial registration The study was registered on ClinicalTrials. Participants Participants were recruited from the Lumosity website www. Download: PPT. Table 1. Demographic information for fully evaluable participants. Treatment and control groups All participants were instructed to log into the website and do one session per day of their activity cognitive training for the treatment group or crossword puzzles for the control group , 5 days a week for 10 weeks.
Cognitive training treatment. Crossword puzzles control. Outcome measures Outcomes were assessed using a battery of seven neuropsychological tests, as well as a participant-reported outcomes survey.
Neuropsychological assessment battery. Assessment scaling procedure. Participant-reported outcomes. Results Primary outcome measure Our primary hypothesis was that the treatment program would lead to greater improvements in aggregate cognitive performance compared to the active control, as measured by the neuropsychological assessment battery.
Fig 2. Change in composite score Grand Index for the cognitive training treatment and crossword puzzle control conditions. Table 2. Neuropsychological assessment baseline means, change scores, and effect sizes.
Individual assessments Based on the significant main effect on our primary outcome measure, we performed secondary analyses consisting of additional ANCOVA models for each assessment.
Effects of amount of engagement If the cognitive training treatment was more effective than playing crossword puzzles for improving cognitive abilities, we may observe a larger effect of active days of study engagement for the treatment condition compared to the control condition. Fig 4. Change in composite score Grand Index by number of active days in treatment and control conditions.
Participant-reported outcomes Of the 4, participants included in the analyses above, 4, Discussion The findings of this study are consistent with the extant literature on cognitive training that shows that progressively challenging, targeted cognitive training can be an effective tool for improving core cognitive abilities including speed of processing [ 13 ], working memory [ 46 ], and fluid reasoning [ 10 ].
Supporting Information. S1 CONSORT Checklist. Completed CONSORT checklist of information to include when reporting a randomized trial. s PDF. S1 Appendix. Descriptions of each of the cognitive training tasks used in this study. s DOCX.
S2 Appendix. A more thorough description of the seven neuropsychological assessments used to measure cognitive performance at pre-test and post-test. S1 Dataset. The study data for the statistical comparisons of outcomes for cognitive training relative to crosswords.
s CSV. S2 Dataset. A description of the data columns in S1 Dataset. S1 File. Additional Analyses. S1 Protocol. The IRB-approved study protocol. Acknowledgments We would like to acknowledge the efforts of all the dedicated people who have worked to create Lumosity. Author Contributions Conceived and designed the experiments: JLH FF RAN MET DAS MS.
References 1. Green CS, Bavelier D. Action video game modifies visual selective attention. Smith GE, Housen P, Yaffe K, Ruff R, Kennison RF, Mahncke HW, et al. A cognitive training program based on principles of brain plasticity: results from the Improvement in Memory with Plasticity-based Adaptive Cognitive Training IMPACT study.
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Neurobiol Aging. Anguera JA, Boccanfuso J, Rintoul JL, Al-Hashimi O, Faraji F, Janowich J, et al. Video game training enhances cognitive control in older adults. Ball K, Edwards JD, Ross LA, McGwin G Jr.
Cognitive training decreases motor vehicle collision involvement of older drivers. Wolinsky FD, Unverzagt FW, Smith DM, Jones R, Stoddard A, Tennstedt SL.
The ACTIVE cognitive training trial and health-related quality of life: protection that lasts for 5 years. J Gerontol A Biol Sci Med Sci. Woollett K, Maguire EA. Acquiring "the Knowledge" of London's layout drives structural brain changes.
Curr Biol. Munte TF, Altenmuller E, Jancke L. The musician's brain as a model of neuroplasticity. Nat Rev Neurosci.
Mackey AP, Whitaker KJ, Bunge SA. Experience-dependent plasticity in white matter microstructure: reasoning training alters structural connectivity.
When then evaluated the progress of the processing speed, the increase in game difficulty throughout the sessions must be taken into account.
The time course of the processing speed over the sessions, adjusted for difficulty levels and the total duration of the training, are presented in Fig. The results of the mixed models are presented in Table 4. For Word Pairs we observed an decrease in the processing speed in all age groups.
For Square Numbers , Unique and Rush Back there was a statistically significant increase for all participant age groups, however as for the score, the increase of the processing speed is more marked for younger participants.
This study aimed to determine the efficacy of a cognitive training performed using CMG in real-life use on cognitive performance in older adults. First, we compared the baseline game scores per age group and observed that outcomes are sensitive to age-related cognitive changes, which is in line with the results of a previous study, where we showed that CMG scores are correlated with the cognitive abilities of older adults with and without cognitive impairments When investigating the scores of the CMG, we observed statistically significant linear decreases with the increasing age of the participants, and conversely, a significant decrease in processing speed.
These results are in accordance with neuropsychological and physiological data: aging is indeed related to a decrease in cognitive function 17 and an increase in reaction time This observation supports that our outcomes are sensitive to age-related changes in cognitive function. The literature also supports that basic numerical skills are preserved in healthy aging 19 and that deficits may be associated with MCI The age-related differences in baseline scores we observed in Square Numbers are therefore probably not related to a decrease of numerical skills but may be explained by slowed reaction times and inhibiting abilities, both of which are known to be affected by aging Our study did not measure inhibitory processes directly, but Must Sort may be considered an indirect measure of inhibitory response.
In Must Sort , we observed a linear decrease in scores as well as an decrease in processing speed with increasing participant age, both results are consistent with the aforementioned study 21 and could explain why we observed age-dependent differences in baseline Square Numbers scores.
Though the changes in different cognitive abilities over the lifespan are relatively well-documented 22 , 23 , there is less evidence on the plasticity of these different cognitive functions across the lifespan 23 , 24 , Furthermore, it has not yet been established whether all cognitive functions can be trained or the extent to which progress can be achieved in healthy subjects of different ages These are both important questions in the field of cognitive training.
Neuroplasticity is the ability of the brain to modify its structure and function for example under conditions of learning or compensation. We studied a healthy population and therefore the observed improvements are most likely due to training-induced plasticity rather than compensation.
Previous studies have shown neuroimaging and neurotransmitter changes after cognitive training of working memory in healthy people 27 , 28 , 29 , that could ultimately lead to an increase of cognitive reserve However, it is possible given the age of the subjects that this may be a compensatory mechanism.
For example the scaffolding theory of aging and cognition provides a theoretical model for the causes and the consequences of age-related compensatory neural activity According to this theory, scaffolding is conceptualized as the recruitment of additional circuitry that shores up declining brain function that has become inefficient.
Despite the age-related alteration in different important brain structures i. Cognitive training or sustained engagement in challenging novel tasks like CMGs could enhance the development of scaffolding and as a result, confer protection and improvement in cognitive functions We observed a clear linear trend for the analysis of the initial score, the same tendency was found for the time course of the scores, where all progress were smaller with increasing age.
Those results confirm that even if the age-related cognitive decline is inevitable, lifelong trajectories of brain and cognitive functions are variable and stay plastic throughout the lifespan For the next part of discussion, we will address the effect of training on each cognitive domain see Table 5 for the different cognitive abilities trained by the CMG in turn.
Note that each CMG may train different cognitive abilities but for the sake of this discussion, we define the main component of cognition for each CMG. The processing speed increases during the first 50 sessions then remain stable while the score of the games is continuously increasing, this seems to indicate that the speed is no longer decreasing but the participants are able to perform more complex tasks.
The results of the present study are consistent with these results and extend them to older adults. We observed an increase in Word Pairs scores throughout the sessions in every age group. This increase was greater for the younger participants.
Word processing and literacy engagement along adulthood enable to maintain an efficient lexical processing 37 , which is reflected by the evolution of the scores observed in the current study indicating that semantic learning abilities are preserved even at advanced ages.
However, concerning the processing speed, even after adjusting for the difficulty level, we observed an increase in all age groups during the training. Word Pairs and Babble Bot are the only two CMG using retrieval from long-term memory. Participants tended to recall common, more easily accessible items before unique, less accessible items, and this pattern was more prominent in older adults The words to pair become more difficult and less common as the training progresses, which may explain why, despite the adjustment, the time needed to associate these words increases significantly in the different age groups.
It has been demonstrated that older adults experience more difficulties in task switching, coupled with infrequent and unexpected transitions from one task set to another Despite the highest costs to task shifting performance 40 , we observed that older participants were able to train this function, as exhibited by their significant improvements in processing speed.
One potential mechanism that could explain this is a shift in cognitive control. Previous neuroimaging studies have indeed shown that older adults may switch from a proactive e. In the Must Sort , reactive control strategy is the most used mechanism. With regard to visual attention, it is widely accepted that aging is associated with the deterioration of vision and field of view 42 , and with a decrease in selective attention We observed that the time needed to find the unique object decreased in all age groups over time, which may indicate that this CMG is able to improve selective attention in older adults, or at least improve response speed, which is a good indicator of cognitive function These results are in line with a previous study that showed that processing speed training improves selective attention in older adults Similarly to other CMGs, scores and reaction time of Rush Back , which mainly trains working memory, were improved in all age groups with a slower progression in the older groups.
It has been demonstrated that older adults can improve their working memory after a specific training In another study the investigators analyzed the effect of a session training program using an n -back task program same principle as the Rush Back where the subjects must remember the previous card in younger, middle-aged and older adults The authors found that age exerted independent effects on training gains and asymptotic performance: older adults tended to show less improvement in scores than younger adults 47 , which is also consistent with our findings.
There are three main limitations in this study: the first is that we did not have access to any information about the background of the participants: it is well-known that several factors influence cognitive function and the risk of dementia such as genetic risk factors 48 , as well as non-genetic risk factors including lifestyle-related factors 49 , for example education level, smoking history, history of hypertension, dyslipidemia, physical activity, body mass index, or concomitant pathologies such as stroke 50 , cardiovascular disease 51 , diabetes 52 , or chronic respiratory disease Gender is also postulated to influence some cognitive functions such as vocabulary capacity Due to the fact that we did not have access to this background information, we cannot establish whether the effects observed in the current study were influenced by any of these factors.
Most probably, subjects playing with this kind of app are cognitively healthy and quite comfortable with mobile devices. The second limitation is the choice of the outcomes, namely, the scores of the CMG and the processing speed data obtained within the games.
Furthermore, both of the scores of the CMG and processing speed have been shown to be good indicators of cognitive function 16 , In a recent study examining the effects of cognitive training on cognitive performance of healthy adults, the authors found that there was a transfer effect between the trained abilities and the instruments used only when the tests were similar to the trained situation near effects.
If the tests differed too much from the training tasks far effects no training effect was observed However, some studies did show a transfer to general cognitive function as tested byneuropsychological batteries for multiple cognitive domains 11 , 16 and also demonstrated a protective effect in patients with MCI Those beneficial effects could be related to the multi-domains, novel and continuously challenging self-adaptative stimulation provided by most cognitive training apps, which has been shown to be superior to the routine mental activities of everyday life These challenging and unusual stimuli induce changes in brain activity and connectivity in areas that are known to be affected by aging and neurodegenerative diseases.
Those changes may help counteract age- and disease-related alterations and help to explain cognitive benefits and transfers, once their link with cognitive improvements has been clearly established 33 , Finally, the study suffers a selection bias, since the participants were all users of this app and were therefore most probably familiar with the use of smartphones and current technology.
This has two consequences: first, older people who are less familiar with mobile technology might find this app less usable and therefore the adherence may be lower. Secondly, a recent study underlined the importance of digital devices use in delaying cognitive decline in the older adults 58 , thus the participants of this study may have already been benefiting from this phenomenon and thus functioning at a higher cognitive level than those who do not regularly use mobile technology.
Despite these limitations, the results of this study support that even at old age above 80 years old , participants are able to use CMG and to train and improve cognition through CMG. Although technological devices and medical-related apps cannot single-handedly improve cognitive decline, in the absence of effective, low-cost, and accessible treatments for cognitive and motivational deficits, these brain training apps could be greatly beneficial to public health.
One salient aspect of the games is that they could be combined with automated evaluation and assessment of cognitive function 16 , In this context, the presented method could be an interesting complementary tool due to its potential to become widely available thanks to the growing use of mobile technology.
Another positive aspect is that the cognitive training and follow-up with games on mobile can be also proposed to patients with limited mobility, or living to far to come on a regular basis to specialized centers 60 , and in lockdown during the COVID pandemic 61 , While cognitive training app games have been shown to improve memory in older people with mild cognitive impairment 63 , further studies are needed to determine if technologies, such as apps, can decrease dementia risk in healthy subjects or slow down the progression of the disease in patients suffering from cognitive impairment and if there is a transfer to the activities of daily living.
We can, also, speculate that since psychomotor slowing associated with aging has an important negative effect on multi-tasking activities of daily living, improving the processing speed could have a positive effect on the quality of life of the participants We carried out a retrospective observational study in which we obtained anonymized CMG results of healthy participants.
This study was approved by The Cambridge Psychology Research Ethics Committee Pre. The scores of the CMG, automatically recorded by the application, were then analysed anonymously for each of the five age groups provided: 60—64, 65—69, 70—74, 75—79, and 80 years or older.
The number of participants varied in each CMG and in the different age groups Table 1. In this study, we used a set of seven individual short CMG provided by Peak brain training www. net , London—UK to analyze changes in-game scores and processing speed over the course of sessions of CMG one session is defined as the completion of one level of the CMG.
The games are organized by categories based on the main cognitive functions on which they focus. Screenshots of the games are presented in Fig. The difficulty level of each CMG is adapted automatically according to the previous performance of the participant i.
The number of stimuli and the intersimulus intervals depend on the CMG and the difficulty level The CMG were played on smartphones or tablets and the scores of training sessions were analyzed.
No particular instructions were given to the participants about the frequency or the duration of each training session, the total duration needed to achieve the sessions of training for the different CMG is presented in Supplementary Table S1.
Screenshots of the 7 CMG used in this study. A Square Numbers, B Memory Sweep, C Word Pair, D Babble Bots, E Must Sort, F Unique, G Rush Back.
Instructions and main cognitive abilities trained of each CMG are presented in Table 5. The primary outcome was the scores obtained in the seven CMG for the different age groups.
Several cognitive sub-functions are usually assessed during standard cognitive evaluations: attention, memory, fluency, language, and visuospatial abilities Table 5 To have a complete overview of the cognition, those different sub-functions need to be assessed individually; the scores of the CMG are used as a proxy of the main sub-cognitive abilities challenged in each game.
As a second primary outcome, we computed the processing speed based on the reaction time for the speed-dependent CMG exceptions were Memory Sweep and Word Pairs Details of the computations are presented in Table 4.
Processing speed is considered as a good indicator of general cognitive performance 19 and has been proposed as a predictor of frailty risk among people in old age 67 , Firstly, the first session scores of the different age groups were compared using one-way analysis of variance ANOVA or Kruskal—Wallis tests, depending the distribution of the data, to determine if age had an influence on the initial scores.
Omega-squared analyses or epsilon-squared non-normally distributed tests were computed to estimate the effect size Post-hoc tests for linear trends were performed last. We then analysed each CMG using a separate mixed model with random slope age and intercept with the scores from each session treated as repeated measures adjusted for the total duration of the training for each participant.
Fixed effects of age group, session 1 to , and the interaction between age group and session were specified, and the estimated baseline measures were constrained to be identical in the age groups by subtracting the mean values of the first session for each age group in all the sessions.
This approach is equivalent to adjusting for baseline and permitting the relationship between baseline and follow-up scores to differ at each session. Likelihood-ratio tests were used to test the significance of the random effects model and linear mixed model with interaction.
For the processing speed, we applied a separate mixed model for the different CMG with random slope age and intercept with the processing speed from each session treated as repeated measures, adjusted for the difficulty levels reached and the total duration of the training for each participant.
Statistical analyses were performed at an overall significance level of 0. The data that support the findings of this study are available from the corresponding author upon reasonable request. Google Scholar. World Health Organization.
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Cappelletti, M. Number skills are maintained in healthy ageing. Vogel, A. Differences in quantitative methods for measuring subjective cognitive decline—Results from a prospective memory clinic study. CogniFit does not offer any medical diagnosis or treatment of any medical disease or condition.
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For Cognitive function improvement courses information about PLOS Subject Areas, improvemsnt here. A Cognitive function improvement courses of studies have demonstrated gains in Effective weight loss supplements ability imprvement cognitive training interventions. However, other studies have not shown such gains, and questions remain regarding the efficacy of specific cognitive training interventions. Cognitive training research often involves programs made up of just one or a few exercises, targeting limited and specific cognitive endpoints. In addition, cognitive training studies typically involve small samples that may be insufficient for reliable measurement of change.
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