Boost cognitive processing speed -
Sure, Brady has had a strong arm, a great coach, and, until this past season, a Hall of Fame tight end the fans miss you, Gronk! but perhaps the most important part of his success over the past few years has been his ability to process information quickly and move more efficiently.
He can look at an opposing defense and speedily and skillfully decide what they are doing and how he can best attack it. This type of quarterbacking relies on strong working-memory skills to recognize what he observed in his past experiences and film study, as well as fast cognitive processing — the opposite of what Levitin reports happens to most adults.
Sure, many football fans admire Tom Brady, but what does all this have to do with memory, slow processing speed, and technology? Rumor has it that Brady is on the forefront of using video game-like technology to enhance his working memory and processing-speed skills.
Beyond rumor is the research indicating that this technology, which is still in its infancy, may change the face of aging. Many studies suggest that video games and other technologies offer promise in improving processing speed and memory skills. One reason these tools have become so popular is that they are fun, engaging, and sometimes a bit addictive.
However, there have been criticisms of technologies promoted as cures for aging, memory, and cognitive decline. While hundreds of renowned researchers view brain training technologies as a useful tool for improving these skills, others see them as falling far short.
The naysayers recognize that brain training may improve the specific skills being trained but find little evidence that the trained skills can be applied to other real-world settings. This is the definition of what psychologists call generalization , the ability to transfer an action learned in one setting to a different setting, so that individuals are fully able to use the skills they have learned in one environment in other settings, with other people, and with different materials.
Most of the research has not built in effective generalization strategies — often as a result of research designs overly concerned with maintaining a single independent variable. When generalization strategies are included , we see many more reasons to use these brain-training techniques.
Their research suggests that older individuals doing speed of processing training were able to double the speed at which they could accurately process visual information and improve the speed of processing auditory information.
In this case, the studies show some generalization, as adults reported they could follow fast-moving conversations better and demonstrated improvement in driving skills. There are also dozens of studies indicating that playing action video games can improve the speed of processing visual information and other cognitive skills.
So can brain training be a tool for maintaining or even improving our memories and counteract the process of cognitive slowing? The best data find that it can be helpful in normal adults , although not necessarily in those who have a diagnosis of mild cognitive impairment.
Should it be the only thing you do? There are far more data to support regular exercise, social engagement and conversation, lifelong learning, a healthy diet and sleep, and a variety of other factors that can help us maintain as much as we can.
And some of these — exercise in particular — may be more powerful than any brain training you might choose to do. But adding brain-training technologies that are engaging to you can be a good way to help maintain and improve memory and processing-speed skills.
If you are intent on making brain training a tool to improve your memory and processing speed, I also encourage you to read about the science of generalization strategies that should accompany brain training.
Are you still going to slow down, become more forgetful, and show other signs of cognitive slowing as you age? Yes, if you are lucky to live long enough.
But there is increasing evidence that you can do something to slow it down and maybe have some fun along the way.
Randy Kulman, Ph. He is the author of Train Your Brain for Success and Playing Smarter in a Digital World. 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. Dementia WHO, Cimler, R. PLoS ONE 14 , e Article CAS PubMed PubMed Central Google Scholar.
Cleveland, M. Preserving cognition, preventing dementia. Article PubMed Google Scholar. Lamar, M. Article PubMed PubMed Central Google Scholar. Livingston, G. et al. Dementia prevention, intervention, and care: report of the Lancet Commission. The Lancet , — Article Google Scholar.
Dyer, S. An overview of systematic reviews of pharmacological and non-pharmacological interventions for the treatment of behavioral and psychological symptoms of dementia. Abraha, I. Systematic review of systematic reviews of non-pharmacological interventions to treat behavioural disturbances in older patients with dementia.
The SENATOR-OnTop series. BMJ Open 7 , e Nouchi, R. Brain training game boosts executive functions, working memory and processing speed in the young adults: A randomized controlled trial.
PLoS ONE 8 , e Article ADS CAS PubMed PubMed Central Google Scholar. Gates, N. Computerised cognitive training for 12 or more weeks for maintaining cognitive function in cognitively healthy people in late life. Cochrane Database Syst. pub3 Shah, T. Enhancing cognitive functioning in healthly older adults: A systematic review of the clinical significance of commercially available computerized cognitive training in preventing cognitive decline.
Bonnechère, B. The use of commercial computerised cognitive games in older adults: A meta-analysis. Computerised cognitive training for preventing dementia in people with mild cognitive impairment.
PubMed Google Scholar. Edwards, J. Speed of processing training results in lower risk of dementia. Alzheimers Dement N. Age-associated capacity to progress when playing Cognitive Mobile Games: Ecological retrospective observational study.
JMIR Serious Games 8 , e The use of mobile games to assess cognitive function of elderly with and without cognitive impairment.
Alzheimers Dis. Bettio, L. The effects of aging in the hippocampus and cognitive decline. Norris, J. Aging and the number sense: Preserved basic non-symbolic numerical processing and enhanced basic symbolic processing.
Johari, K. Effects of aging on temporal predictive mechanisms of speech and hand motor reaction time. Aging Clin. Martin, R. Loss of calculation abilities in patients with mild and moderate Alzheimer disease.
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. Rizeq, J. Changing relations among cognitive abilities across development: Implications for measurement and research.
Li, T. Cognitive training can reduce the rate of cognitive aging: A neuroimaging cohort study. BMC Geriatr. Article PubMed PubMed Central CAS Google Scholar. van de Vijver, I. Age-related changes in deterministic learning from positive versus negative performance feedback.
B Aging Neuropsychol. Raz, N. Decline and compensation in aging brain and cognition: Promises and constraints. McNab, F. Changes in cortical dopamine D1 receptor binding associated with cognitive training. Science , — Article ADS CAS PubMed Google Scholar.
Olesen, P. Increased prefrontal and parietal activity after training of working memory. Article CAS PubMed Google Scholar.
Klingberg, T. Training and plasticity of working memory. Trends Cogn. Orrell, M. Education and dementia. BMJ , — Park, D. The adaptive brain: Aging and neurocognitive scaffolding. The aging mind: Neuroplasticity in response to cognitive training.
Dialogues Clin. van Balkom, T. The effects of cognitive training on brain network activity and connectivity in aging and neurodegenerative diseases: A systematic review. Mitchell, M. Cognitively stimulating activities: Effects on cognition across four studies with up to 21 years of longitudinal data.
Aging Res. Caviola, S. Computer-based training for improving mental calculation in third- and fifth-graders. Acta Physiol. Oxf , — Takeuchi, H. Working Memory training using mental calculation impacts regional gray matter of the frontal and parietal regions.
PLoS ONE 6 , e Steen-Baker, A. The effects of context on processing words during sentence reading among adults varying in age and literacy skill.
Aging 32 , — Murphy, D. Age-related similarities and differences in the components of semantic fluency: Analyzing the originality and organization of retrieval from long-term memory.
Eich, T. Age-based differences in task switching are moderated by executive control demands. Functional brain and age-related changes associated with congruency in task switching.
Neuropsychologia 91 , — Jimura, K. Age-related shifts in brain activity dynamics during task switching. Cortex 20 , — Matthews, K. The consequences of self-reported vision change in later-life: Evidence from the English Longitudinal Study of Ageing. Public Health , 7—14 Malavita, M.
The effect of aging and attention on visual crowding and surround suppression of perceived contrast threshold. Nyberg, L. Forecasting memory function in aging: Pattern-completion ability and hippocampal activity relate to visuospatial functioning over 25 years.
Aging 94 , — Cognitive training and selective attention in the aging brain: An electrophysiological study. Mishra, J. Neural plasticity underlying visual perceptual learning in aging. Brain Res. Rhodes, R. Working memory plasticity and aging.
Aging 32 , 51—59 van der Lee, S. Lancet Neurol. Dementia prevention, intervention, and care. Lancet , — Zheng, F. Progression of cognitive decline before and after incident stroke.
Neurology 93 , e20—e28 Stefanidis, K. The effect of non-stroke cardiovascular disease states on risk for cognitive decline and dementia: A systematic and meta-analytic review.
Li, C. Risk score prediction model for dementia in patients with type 2 diabetes. Zhang, X.
Spred you would like to learn about other cognihive Practical weight control, CLICK HERE. Episode 2: How Cognitkve We Exercise and Improve Visualization Skills? Episode 3 Non-invasive fat reduction methods to Automaticity Xpeed 4: What Practical weight control Working Memory? Episode Practical weight control Understanding EF Episode 6: Investigating Inhibitory Control Episode 7: Exploring Cognitive Flexibility Episode 8: What are Higher Level EFs Episode 9: 12 Strategies to Improve EFs Episode Building a Routine for Improved EFs Episode How Do You Teach Executive Functioning? Warren Consultations Contact Us Printable Catalog Purchase orders GSL Blog Video Blogs Executive Function Coach Provider Directory Sign in Create an Account. Cart 0. This is my second post on processing speed. Last Digestion optimization products May 22, Proceessing and medically reviewed Practical weight control Patrick Alban, Cognitivd. Written by Deane Alban. Fast thinking is important, but mental processing speed is often less valuable than accuracy. Learn 14 ways to help you think faster and more efficiently. This is not necessarily true, but there are still many reasons why thinking faster can be desirable.
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