Video
Neuroscientist explains the best exercise to improve brain function Cognitive health is Cognitive function enhancement recognized as a key Cognitive function enhancement of overall health Cognitive function enhancement Superfoods with antioxidants Bart et Cognitive function enhancement. As Cognitivd other dimensions of health ehancement wellness, deliberate effort is needed to maintain and especially improve cognitive health. In Cognirive article, we discuss enhancemeent factors and exercises that can improve cognitive function and help sustain cognitive health across the lifespan. Before you continue, we thought you might like to download our three Productivity Exercises for free. These detailed, science-based exercises will help you or your clients become more productive and efficient. For much of their history, psychiatry, clinical psychology, and related disciplines like counseling focused on treating our deficitsrather than developing our strengths. In the realm of cognition, this entailed finding areas of thinking, memory, and problem solving that were relative strengths for an individual.Cognitive function enhancement -
The most appropriate and optimal treatment parameters are selected based on genetic, environmental, and lifestyle factors that may predict treatment success for an individual. SMART design: The sequential multiple assignment randomized trial SMART is a type of research study designed to allow the testing of multiple potential adaptive interventions while tailoring key variables.
Transfer is sometimes referred to as generalization. This approach does not capitalize on the fact that, as a result of neuroplasticity, cognitive abilities are fluid over time.
Thus, many cognitive interventions are either too easy or too difficult for an individual, particularly as their abilities improve over time. In this section, we provide brief examples of emerging approaches to cognitive enhancement that rely on closed-loop designs and new technologies that show promise for transforming the field see Fig.
Note that this selection does not include all approaches being pursued, but rather reflects specific domains in which the authors have the greatest level of experience and knowledge.
a , Combining fitness and cognitive challenges in a meaningful way can lead to synergistic effects of an intervention. b , Digital forms of meditation make the practice more accessible to large, diverse populations. c , Head-mounted VR displays enable highly immersive environments that provide the context and engagement needed to bolster long-term memory functions.
d , Neurostimulation applied in conjunction with a cognitive intervention can help accelerate learning and enhance gains in cognitive abilities. The enhancement of declining cognitive control abilities for example, attention, working memory, and cognitive flexibility 18 , 22 are of notable interest for OA because these abilities are particularly vulnerable to the effects of healthy aging and have a large impact on quality of life One of the first cognitive enhancement interventions to rely on a closed-loop system was the NeuroRacer intervention These effects significantly exceeded those in both active- and no-contact-control groups 24 , with observed improvements in multitasking performance on the game itself persisting 6 years later, without any booster training It has further been shown that other closed-loop neurotherapeutic approaches can lead to significant gains in cognitive control in both older humans 26 , 27 , 28 and aged rodents Validating closed-loop cognitive enhancement tools for older adults in randomized controlled trials to show meaningful cognitive gains and then advancing them as a regulated medical device will be especially important, given the number of products marketed as cognitive-aging and dementia treatments without scientific support.
In addition to cognitive control, declining long-term memory LTM affects diverse aspects of cognitive performance and results in an overall diminished quality of life for many healthy OA Chronic memory loss is typically first apparent as impairments in high-fidelity memory that is, recalling distinct and specific information 30 , which is the most precise form of LTM.
The progression of memory loss in aging is a cardinal sign of mild cognitive impairment MCI 31 and may foreshadow the onset of dementia High-fidelity memory depends on the flexible association of information that is remembered in distinct and detailed terms, and it depends on the hippocampal memory system 32 , Although practice and other mnemonic strategies have been shown to improve the ability to remember studied information 34 , the goal of strengthening high-fidelity LTM mechanisms in OA with behavioral or pharmaceutical interventions has proven elusive.
The animal literature has provided evidence that an exposure regimen of environmental enrichment can upregulate hippocampal functions 35 , 36 , which in turn promotes better memory A similar approach to environmental enrichment in humans may generalize to improvements in high-fidelity LTM capabilities 38 , Yet applying these principles to humans, who have rich, detailed memories from a lifetime of experience, presents a unique challenge.
Because upregulating hippocampal function is thought to result from encoding complex information into LTM 35 , 37 , a principal challenge is presenting OA with information that is both novel and captivating enough to hold their deep engagement for an extended intervention; for example, an adaptive environment that is customized to each individual.
Modern technology now enables more elaborate and immersive sensory presentations and manipulation of a wider range of stimuli in cognitive interventions, thus leading to more engaging and personalized learning experiences.
Studies have found that head-mounted-display virtual reality HMD VR drives greater engagement and increased performance relative to the same task presented on a flat-screen-monitor 40 , In terms of customizing the intervention environment, the use of HMD VR tools enables: 1 flexible control of the novelty of rich visual stimuli and game-play mechanics, which underpins development of the most intriguing learning experiences, and 2 increasing the engagement of participants in order to sustain their attentiveness and motivation for long, repeated training sessions that are necessary to achieve broader improvements in high-fidelity LTM.
As such, OA can encounter a dynamic and personalized learning challenge that is, environmental enrichment with interventions using HMD VR. Further, several studies have shown that OA are often enthusiastic about using VR platforms, and research has shown that it is possible to design VR experiences that are accessible to OA 43 ; therefore, getting OA to use VR at home is highly feasible To capitalize on these technological advantages, the Labyrinth intervention advances beyond flat-screen video games to stimulate learning in new spatial environments 45 by incorporating HMD VR and motion-capture sensors in a spatial wayfinding game Specifically, task performance in 3D VR uses binocular vision, which arises from a complex network of dorsal occipital areas and feeds a more intricate representation of the environment forward to enhance spatial-memory encoding The results from an intervention trial of Labyrinth showed that healthy OA increased their spatial wayfinding abilities in the game, but more importantly, these gains generalized to improved high-fidelity LTM performance on an unpracticed memory test Notably, post-training memory performance in OA who engaged with Labyrinth reached levels comparable to baseline high-fidelity LTM in younger adults.
Unlike the ambiguity surrounding the potential benefits of cognitive training for OA, the benefits of physical-fitness interventions have been well established in both healthy and cognitively impaired individuals 47 , 48 , Mechanistically, physical-fitness interventions have been shown to increase production of proteins such as BDNF, IGF-1, and VEGF 50 , 51 , which modulate neurogenesis 52 , 53 and subsequently facilitate enhanced brain functions 54 , 55 through heightened brain network connectivity discussed more below.
Similarly, cognitive training has been shown to lead to increased neuronal plasticity at the cellular for example, BDNF expression 56 , 57 and network for example, functional connectivity 24 , 58 levels. New technologies, such as motion-capture sensors and VR, hold great promise for increasing engagement and enjoyment of physical-fitness training in OA Interestingly, results from animal studies have shown that linking physical and cognitive challenges can lead to synergistic enhancement of cognitive processes Although several studies 61 , 62 have sought to evaluate combined cognitive- and physical-training programs to enhance cognition in OA, the conclusions from these studies have been largely inconclusive, possibly owing to intervention delivery limitations.
In some studies, participants alternated days devoted to each training modality and thus were not exposed to an integrated experience 61 , Other studies that attempted simultaneous physical and cognitive training inadvertently created an imbalanced training environment by failing to incorporate common goals that united the components 63 , Although these findings have not conclusively demonstrated synergistic effects, we still believe that such approaches are compelling options to maintain both cognitive and physical health in aging 65 and provide a time- and resource-efficient means of targeting multiple risk factors in OA Our perspective is that, to achieve synergistic effects, a combined cognitive and physical challenge should be delivered in an integrated manner without trade-offs across domains, and that this can be obtained by simultaneously engaging multiple closed-loop systems across areas to achieve a common outcome from a single intervention.
This approach is currently being tested in clinical trials. There is growing interest in using various forms of meditation as therapeutic interventions to enhance attention 67 and combat cognitive decline in OA In addition to leading to improvements in cognition 69 , meditation and mindfulness practices have been studied as potential therapies for loneliness 70 , depression 71 , impulse control 72 , and chronic pain management 73 in OA.
Long-term meditation has been found to mitigate signs of brain aging 74 , 75 and improve well-being in OA Moreover, these practices do not offer quantifiable metrics of success or performance feedback during the learning phases — factors that are important for maintaining engagement with an intervention Further, traditional meditation is difficult to personalize because it is not adaptive or tailored to individuals, making it overly challenging for some novices.
Although recent studies have tested the delivery of website-accessible 79 and mobile 80 meditation programs, these online practices tend to duplicate the procedures of traditional meditation and consequently have faced similar hurdles to implementation. In addition, while meditation apps on mobile devices have become increasingly ubiquitous 81 , studies to date have either failed to characterize their effects on cognition or have shown equivocal results An example of an approach to achieving a closed-loop digital meditation is MediTrain 83 , which was designed with the goal of improving focused, sustained attention.
This digital approach to meditation personalizes the experience to the real-time abilities of individuals, provides both punctuated and continuous feedback, and includes adaptivity that increases the challenge level as the user improves.
Following several studies demonstrating a positive impact of MediTrain on attention in younger populations 83 , 84 , 85 , a large-scale, fully remote trial of this digital intervention is being conducted in OA using a mobile RCT platform Fig.
Interestingly, another modern, technology-enabled approach to meditation relies on neurofeedback from EEG signals recorded from a consumer device and has led to similar improvements in cognitive control These new technologically enabled types of meditation may open the door for personalization of treatments, with some forms for example, neurofeedback versus performance-based feedback working better for specific individuals.
First, recruitment is conducted entirely remotely through social-media outreach, online advertisements, agreements with senior living centers, and direct mail campaigns. Next, OA are sent a link to visit a mobile RCT portal where they complete informed consent and eligibility forms on their computers or mobile devices.
They then complete baseline cognitive assessments, demographic questionnaires, and surveys of real-life behaviors and conditions, and those data are input into machine-learning algorithms that predict which digital intervention is most appropriate for each person, and randomization is done in a stratified manner.
Once assigned to an arm, OA complete the digital intervention at home while data are collected remotely. Finally, advanced device or cloud-based analytics allow for rapid analysis of results in real time, accelerating the pace of research and discovery.
These results can then be interpreted by researchers or visualized and presented to the participants as a performance dashboard, enabling them to monitor their own progress. The OA population is extremely heterogeneous Increasing age is associated with the risk of detrimental physiological or sensory changes, as well as increased risk of chronic diseases for example, diabetes, cancer, heart disease, and cognitive impairment.
At the same time, chronological age is not always a good predictor of functional capacity, with some individuals over the age of 80 continuing to work and travel, while other younger individuals are unable to.
This variability in older populations is often overlooked when developing cognitive therapeutics, thus limiting the potential efficacy of interventions in some populations. Further, within trials of cognitive interventions, there is often pronounced variability in treatment responses that is ignored when reporting group averages, suggesting the need for additional personalization tactics.
We propose that these differences represent meaningful heterogeneity, such that there is likely not a one-size-fits-all solution for cognitive enhancement in OA. A critical step to developing personalized interventions is identification of biomarkers that predict intervention success for a particular individual 88 , Some of the most promising personalization results come from studies that have used advanced neuroimaging methods to uncover neural factors that predict treatment success in an individual.
Much of this work in OA has focused on metrics related to magnetic resonance imaging MRI , spanning individual brain regions to large-scale brain-network properties 89 , Although much of the work using structural brain region predictors for example, volume 91 , 92 , 93 and thickness 94 has been largely inconclusive, more recently one common organizing principle of functional brain networks — modularity — has emerged as a potential unifying predictor of outcomes across a variety of interventions Modularity may be a biomarker of cognitive plasticity that predicts treatment outcomes across interventions Although much of this work in OA has focused on MRI-related metrics, parallel findings in younger adults have identified electroencephalogram EEG -based markers that predict treatment outcomes Extending such EEG findings to OA will be an important next step as affordable, consumer-grade home EEG devices continue to increase in quality and ease of use, paving the way for at-home neural diagnostics that can be used to tailor intervention strategies or parameters to individuals.
Although it is clear that individual differences play an important role in intervention responsiveness 88 , 99 , there are several lines of future work that will translate our understanding of these differences to developing personalized interventions.
First, there is a need to better understand biomarkers of treatment outcomes. Second, it is likely that multiple biomarkers that span demographics, cognition, and neural profiles have interacting, and potentially additive, effects on predicting outcomes.
Large-sample RCTs that incorporate machine learning will be critical in developing multimodal models that elucidate these predictive effects. Indeed, ongoing work is using an online citizen science approach to recruit tens of thousands of volunteers to validate and personalize cognitive enhancement technologies , and machine learning is now being used to optimize non-invasive brain-stimulation protocols for different individuals We anticipate a future of personalized digital therapeutics in which individuals are pre-assigned optimal training parameters, thus maximizing treatment outcomes for everyone.
An example of a technology-based, non-pharmacological strategy for enhancing cognition in aging that has benefited from a precision-medicine approach is non-invasive brain stimulation NIBS.
Of particular interest is the coupling of NIBS with cognitive challenges; the hypothesis is that targeted neural networks are selectively activated by task engagement and then further modulated by brain stimulation, resulting in synergistic neuro-enhancing effects that drive greater cognitive improvement This raises the possibility that NIBS could be used to augment any closed-loop, cognitive therapeutic approaches by enhancing the underlying neuroplasticity, thus leading to even greater cognitive enhancement.
Two forms of NIBS methodologies are transcranial direct current stimulation tDCS and transcranial alternating current stimulation tACS.
These techniques modulate neuronal transmembrane potentials by delivering weak electrical currents tDCS and tACS , , , thereby altering plasticity in the stimulated brain regions , Although the application of NIBS is generally thought to be a safe, non-pharmacological approach that has shown potential to counteract age-associated cognitive decline , crucial questions surrounding the heterogeneity of effects remain unaddressed.
First, optimal stimulation protocols and regimes need to be established. The direction and magnitude of effects of NIBS are strongly influenced by the prevailing brain states in targeted regions at the time of stimulation , Thus, the timing of the stimulation while a cognitive task is administered during the stimulation is critical.
Second, inter-individual variability exists in response to NIBS, with efficacy of NIBS being related to degree of education , genotype , pre-intervention performance , and the magnitude of the electric fields that reach the targeted brain area , which underscores the importance of individualizing stimulation parameters.
In summary, an effective use of NIBS to induce cognitive enhancement in aging brains likely requires an integration of optimal stimulation protocols and individually tailored stimulation parameters to more precisely target the specific functional networks that underlie cognitive functions most in need of improvement.
Testing hypotheses about the factors that predict or moderate treatment responses in the remarkably heterogenous OA population requires large and diverse cohort samples. Such large-scale studies are also needed to move the field beyond findings from relatively small studies towards the real-world validation of cognitive therapeutic technologies.
An emerging solution is to leverage modern, mobile technology for example, the Internet, wireless mobile devices, and cloud-based analytical and storage servers to facilitate the recruitment of larger, more diverse, representative cohorts into clinical trials while minimizing costs.
The need for such a solution has been augmented by the COVID pandemic, which has led to an even greater necessity for new, creative tools for improving public mental health in the setting of such unpredictable conditions. New digital health technologies also hold promise for altering the landscape of how RCTs are conducted Fig.
Indeed, it is now clear that mobile technology can be especially powerful in improving research-participant access, especially to those living in rural areas or members of minority ethnic groups, while simultaneously reducing the expense and time course of such trials Most of these research platforms have been designed to assist with enrolling participants, collecting data, and applying human resources for data interrogation, rather than complex study coordination.
However, we believe that the next phase of this field will use technology for more than data collection, but also to make easily interpretable data more actionable for both researchers and participants. Indeed, there is an important value in developing technology not only to collect data, but also to accelerate the pace of research and enhance the security of data collected remotely for example, through cloud-based analytics and storage.
Relevant to this discussion, more OA are embracing new technology every year. The clear trend is toward increased adoption of mobile technologies, making it important to study and refine digital interventions for enhancing cognition now, so they can reach as many OA as possible.
Critically, the percentage of the population that owns a mobile device is equally distributed among white, Black, and Hispanic people , , Thus, fully remote trials of digital therapeutics have the potential to greatly increase the ability to disseminate these interventions at scale and to reach drastically more diverse study populations than would be expected from a trial that requires participants to come into a medical or research center.
One step toward addressing this goal is making such tools easily accessible. Research has demonstrated that telemedicine and mobile approaches show comparable efficacy to in-person treatment , resulting in substantial interest in using mobile apps as an alternative care-delivery platform.
Such digital approaches to cognitive enhancement have the potential for breaking down barriers to access, especially in underserved or hard-to-reach populations of OA We have reviewed several approaches in which technology can aid in the personalization of cognitive enhancement in aging, but other emerging technologies also offer exciting new avenues for innovation.
Elements such as art, music, story, challenge, and competition could be dynamically manipulated to maximize engagement and compliance to further personalize experiences.
Key to such an approach will be collection of large amounts of data and the application of machine-learning and artificial-intelligence techniques to create robust and dynamic predictive models of the factors that moderate treatment responses at the individual level.
There are a host of new accessible mobile technologies that can be leveraged to collect ecologically valid data as individualized baseline signatures and ongoing diagnostic monitoring of OA in the real-world and in real-time In addition to cognitive enhancement, technology is transforming the broader landscape of mental health and high-quality, personalized care for healthy OA who are living longer with each generation.
Technologies that attempt to modify and support real-life behaviors have advanced at a tremendous pace in recent years. For example, several methods have been developed to combat loneliness, anxiety, and depression, which are common in OA Examples include online and mobile delivery of established clinical treatments, such as cognitive behavioral therapy ; VR paradigms for fostering greater feelings of connectedness and boosting mood ; artificial-intelligence-driven voice-activated technologies for example, Alexa that not only help with organization and access to news and media, but also increase connectedness through human—machine conversations ; and therapeutic robots in the form of appealing animals that help OA cope with anxiety and memory loss These technologies are exciting and add to the emerging ecosystem of methods that can be tailored to the specific needs of an individual.
The impact of these therapeutic technologies could be augmented through combinatorial approaches as discussed above and by the incorporation of closed-loop systems for example, a robotic companion that receives passive physiological signals from a wearable device and uses those data to guide its real-time engagement with its OA companion.
Luis F. Ciria, Rafael Román-Caballero, … Daniel Sanabria. Claudia C. von Bastian, Sylvie Belleville, … Tilo Strobach. United Nations Department of Economic and Social Affairs Population Division, Population Division.
World Population Ageing Brookmeyer, R. Alzheimers Dement. Article PubMed Google Scholar. Ward, A. Mild cognitive impairment: disparity of incidence and prevalence estimates. Kivipelto, M. Lifestyle interventions to prevent cognitive impairment, dementia and Alzheimer disease.
Sala, G. Working memory training in typically developing children: a meta-analysis of the available evidence. Cognitive training does not enhance general cognition.
Trends Cogn. Working memory training in typically developing children: a multilevel meta-analysis. Hou, J. et al. The long-term efficacy of working memory training in healthy older adults: a systematic review and meta-analysis of 22 randomized controlled trials.
B Psychol. Teixeira-Santos, A. Reviewing working memory training gains in healthy older adults: a meta-analytic review of transfer for cognitive outcomes.
Lampit, A. Computerized cognitive training in cognitively healthy older adults: a systematic review and meta-analysis of effect modifiers.
PLoS Med. Article PubMed PubMed Central Google Scholar. Rebok, G. Ten-year effects of the advanced cognitive training for independent and vital elderly cognitive training trial on cognition and everyday functioning in older adults.
Willis, S. Long-term effects of cognitive training on everyday functional outcomes in older adults. Article CAS Google Scholar. Smith, G. A cognitive training program based on principles of brain plasticity: results from the Improvement in Memory with Plasticity-based Adaptive Cognitive Training IMPACT study.
Geriatrics Soc. Article Google Scholar. Wu, Z. Distinct cognitive trajectories in late life and associated predictors and outcomes: a systematic review.
Alzheimers Dis. Sánchez-Izquierdo, M. Cognition in healthy aging. Public Health 18 , Ryan, L. Precision aging: applying precision medicine to the field of cognitive aging.
Aging Neurosci. Schechter, G. PubMed PubMed Central Google Scholar. Mishra, J. Video games for neuro-cognitive optimization. Neuron 90 , — Article CAS PubMed Google Scholar.
Hill, N. Older People Nurs. Lazar, A. In Dis Proceedings of the ACM Conference on Designing Interactive Systems — Association for Computing Machinery, Brefczynski-Lewis, J. Neural correlates of attentional expertise in long-term meditation practitioners. Natl Acad. USA , — Article CAS PubMed PubMed Central Google Scholar.
Anguera, J. Video games, cognitive exercises, and the enhancement of cognitive abilities. Verhaeghen, P. Aging, executive control, and attention: a review of meta-analyses. Video game training enhances cognitive control in older adults. Nature , 97— Long-term maintenance of multitasking abilities following video game training in older adults.
Aging , 22—30 Adaptive training diminishes distractibility in aging across species. Neuron 84 , — Berry, A. The influence of perceptual training on working memory in older adults.
PLoS ONE 5 , e Article PubMed PubMed Central CAS Google Scholar. Rolle, C. Enhancing spatial attention and working memory in younger and older adults. Jagust, W. Vulnerable neural systems and the borderland of brain aging and neurodegeneration.
Neuron 77 , — Naveh-Benjamin, M. Adult age differences in episodic memory: further support for an associative-deficit hypothesis. Learn Mem. Petersen, R. Press, Norman, K. Modeling hippocampal and neocortical contributions to recognition memory: a complementary-learning-systems approach.
Wais, P. Retrieval of high-fidelity memory arises from distributed cortical networks. Neuroimage , — Roediger, H. Test-enhanced learning: taking memory tests improves long-term retention. Kempermann, G. More hippocampal neurons in adult mice living in an enriched environment.
Nature , — Bilkey, D. Exposure to complex environments results in more sparse representations of space in the hippocampus. Hippocampus 27 , — McAvoy, K. Modulating neuronal competition dynamics in the dentate gyrus to rejuvenate aging memory circuits.
Neuron 91 , — Virtual reality video game improves high-fidelity memory in older adults. Kolarik, B. Enriching hippocampal memory function in older adults through real-world exploration. Elor, A. On Shooting Stars: comparing CAVE and HMD immersive virtual reality exergaming for adults with mixed ability.
ACM Trans. Li, G. Enhanced attention using head-mounted virtual reality. Parsons, T. Virtual reality for enhanced ecological validity and experimental control in the clinical, affective and social neurosciences. Seifert, A. The use of virtual and augmented reality by older adults: potentials and challenges.
Virtual Real. Davis, R. Clemenson, G. Virtual environmental enrichment through video games improves hippocampal-associated memory. Ng, A. Ultra-high-field neuroimaging reveals fine-scale processing for 3D perception. Colcombe, S. Cardiovascular fitness, cortical plasticity, and aging.
Brown, B. Intense physical activity is associated with cognitive performance in the elderly. Middleton, L.
Physical activity over the life course and its association with cognitive performance and impairment in old age. Coelho, F. Physical exercise modulates peripheral levels of brain-derived neurotrophic factor BDNF : a systematic review of experimental studies in the elderly.
Cotman, C. Exercise builds brain health: key roles of growth factor cascades and inflammation. Trends Neurosci. Bekinschtein, P. Effects of environmental enrichment and voluntary exercise on neurogenesis, learning and memory, and pattern separation: BDNF as a critical variable?
Cell Dev. Jin, K. Vascular endothelial growth factor VEGF stimulates neurogenesis in vitro and in vivo. USA 99 , — Nakajima, S. Regular voluntary exercise cures stress-induced impairment of cognitive function and cell proliferation accompanied by increases in cerebral IGF-1 and GST activity in mice.
Brain Res. Rhyu, I. Effects of aerobic exercise training on cognitive function and cortical vascularity in monkeys.
Neuroscience , — Angelucci, F. Vinogradov, S. Is serum brain-derived neurotrophic factor a biomarker for cognitive enhancement in schizophrenia? Psychiatry 66 , — Jolles, D. Functional brain connectivity at rest changes after working memory training.
Brain Mapp. Sakaki, K. Benefits of VR physical exercise on cognition in older adults with and without mild cognitive decline: A systematic review of randomized controlled trials. Healthcare 9 , Mohammed, A. Environmental Enrichment and the Brain Elsevier, Book Google Scholar.
Shatil, E. Does combined cognitive training and physical activity training enhance cognitive abilities more than either alone? A four-condition randomized controlled trial among healthy older adults.
Theill, N. Effects of simultaneously performed cognitive and physical training in older adults. BMC Neurosci. Pichierri, G. Cognitive and cognitive-motor interventions affecting physical functioning: a systematic review.
BMC Geriatr. Li, K. Walking while memorizing: age-related differences in compensatory behavior. Yang, C. Effectiveness of combined cognitive and physical interventions to enhance functioning in older adults with mild cognitive impairment: a systematic review of randomized controlled trials.
Gerontologist 60 , — Gavelin, H. Combined physical and cognitive training for older adults with and without cognitive impairment: a systematic review and network meta-analysis of randomized controlled trials. Ageing Res. Tang, Y. Attention training and attention state training.
Klimecki, O. The impact of meditation on healthy ageing — the current state of knowledge and a roadmap to future directions. Lutz, A. Attention regulation and monitoring in meditation. Saini, G. The effects of meditation on individuals facing loneliness: a scoping review.
BMC Psychol. Reangsing, C. Effects of mindfulness meditation interventions on depression in older adults: a meta-analysis.
Aging Ment. Health 25 , — Kozasa, E. Meditation training increases brain efficiency in an attention task.
NeuroImage 59 , — Morone, N. Mind—body interventions for chronic pain in older adults: a structured review. Pain Med. Luders, E. Diminished age-related decline of the amygdala in long-term meditation practitioners.
Laneri, D. PubMed Google Scholar. van Agteren, J. A systematic review and meta-analysis of psychological interventions to improve mental wellbeing. Zeidan, F. Effects of brief and sham mindfulness meditation on mood and cardiovascular variables. Deci, E. A meta-analytic review of experiments examining the effects of extrinsic rewards on intrinsic motivation.
Psychological Bull. discussion Hudson, J. Based Integr. Plaza, I. Mindfulness-based mobile applications: literature review and analysis of current features. JMIR Mhealth Uhealth 1 , e24 Mani, M.
Review and evaluation of mindfulness-based iPhone apps. JMIR Mhealth Uhealth 3 , e82 Noone, C. A randomised active-controlled trial to examine the effects of an online mindfulness intervention on executive control, critical thinking and key thinking dispositions in a university student sample.
Ziegler, D. Closed-loop digital meditation improves sustained attention in young adults. Closed-loop digital meditation for neurocognitive and behavioral development in adolescents with childhood neglect.
Psychiatry 10 , Bréchet, L. Reconfiguration of electroencephalography microstate networks after breath-focused, digital meditation training. Brain Connect. Bhayee, S. Attentional and affective consequences of technology supported mindfulness training: a randomised, active control, efficacy trial.
Jaul, E. Characterizing the heterogeneity of aging: a vision for a staging system for aging. Public Health 9 , Katz, B. in Cognitive Training — Springer, Baykara, E. MRI predictors of cognitive training outcomes.
Enhance 5 , — Gallen, C. Brain modularity: a biomarker of intervention-related plasticity. Basak, C. Regional differences in brain volume predict the acquisition of skill in a complex real-time strategy videogame.
The term nootropic is derived from Ancient Greek νόος nóos 'mind', and τροπή tropḗ 'turning'. The first documented use of "nootropic" in reference to substances purported to increase cognitive functions was by Corneliu E. Giurgea in However, there is no globally accepted or clinical definition of a nootropic.
Most compounds described as nootropic do not correspond to Giurgea's characteristics. In the United States, nootropics are commonly advertised with unproven claims of effectiveness for improving cognition.
Manufacturers' marketing claims for dietary supplements are usually not formally tested and verified by independent entities. In in the United States, some nootropic supplements were identified as having misleading ingredients and illegal marketing.
Over the years to , the FDA warned numerous supplement manufacturers about the illegal status of their products as unapproved drugs with no proven safety or efficacy at the doses listed on the products, together with misleading marketing.
In , stimulants, such as caffeine, were the most commonly used nootropic agent. The main concern with pharmaceutical drugs and dietary supplements are adverse effects. Long-term safety evidence is typically unavailable for many nootropic compounds.
Racetams , piracetam and other compounds that are structurally related to piracetam, have few serious adverse effects and low toxicity , but there is little evidence that they enhance cognition in people having no cognitive impairments.
In the United States, dietary supplements may be marketed if the manufacturer can show that the supplement is generally recognized as safe , and if the manufacturer does not make any claims about using the supplement to treat or prevent any disease or condition; supplements that contain drugs or advertise health claims are illegal under US law.
Systematic reviews and meta-analyses of clinical research using low doses of certain central nervous system stimulants found that these drugs may enhance cognition in healthy people. Racetams, such as piracetam, oxiracetam , phenylpiracetam , and aniracetam , are often marketed as cognitive enhancers and sold over the counter.
Piracetam is not a vitamin , mineral, amino acid , herb or other botanical , or dietary substance for use by humans to supplement the diet by increasing the total dietary intake. Further, piracetam is not a concentrate, metabolite, constituent, extract or combination of any such dietary ingredient.
Moreover, these products are new drugs as defined by section p of the Act, 21 U. Some supposed nootropic substances are compounds and analogues of choline , a precursor of acetylcholine a neurotransmitter and phosphatidylcholine a structural component of cell membranes.
Contents move to sidebar hide. Article Talk. Read Edit View history. Tools Tools. What links here Related changes Upload file Special pages Permanent link Page information Cite this page Get shortened URL Download QR code Wikidata item. Download as PDF Printable version.
In other projects. Wikimedia Commons. Compound intended to improve cognitive function. Caffeine from the Coffea arabica plant is the world's most consumed nootropic. Main article: Racetam. Main article: Cholinergic.
Oxford English Dictionary. Retrieved January 14, Clinical Practice. doi : PMC PMID US Food and Drug Administration, US Federal Trade Commission.
February 11, Retrieved May 11, US Food and Drug Administration. December 22, Attempt at nootropic concept in psychopharmacology]". Actualites Pharmacologiques in French. Progress in Neuro-Psychopharmacology. Retrieved February 14, Office of Compliance, Center for Food Safety and Applied Nutrition, Inspections, Compliance, Enforcement, and Criminal Investigations, US Food and Drug Administration.
com, William Reed Business Media Ltd. But Should You Take Them? Retrieved May 12, Archived from the original on January 12, Retrieved April 5, Bibcode : Natur. OCLC S2CID American Medical Association. June 14,
Stimulant drugs, Cognitive function enhancement magnetic enhancejent, brain-computer interfaces, and even genetic modifications funcrion all Cognitive function enhancement as forms of Workout fuel snacks cognitive enhancement. Cognitive Cogitive can be conceived as a Cognitive function enhancement strategy used by healthy individuals to enhance cognitive abilities such as learning, memory, attention, or vigilance. This phenomenon is hotly debated in the public, professional, and scientific literature. Many of the statements favoring cognitive enhancement e. But with real-world evidence from the social and psychological sciences often missing to support or invalidate these claims, the debate about cognitive enhancement is stalled.
sogar so