A cognitively rich and physically active lifestyle can be very beneficial for brain health and cognitive performance. Underlying these effects is one of the most important properties of the brain: brain plasticity, or neuroplasticity, is the brain’s capacity to adapt based on life experiences and it’s what allows us to learn and become more skilled with practice.
Brain plasticity acts at a functional level by adjusting the functional properties of existing neurons and synapses through molecular changes, and at a structural level through changes in neuronal morphology, neuronal connections, glial cells, and other dynamic adjustments in cellular structures. To learn about some of the main mechanisms of brain plasticity check out this article.
The plastic capacity of the brain declines significantly with age—that’s why children are such great learners and adults take increasingly longer as they get older. But a significant degree of plasticity remains throughout life. Mentally and physically stimulating activities tap into this plastic capacity of the brain to promote functional and structural adaptations that support cognitive performance.
In this capacity of the brain to adapt in response to life experiences, there’s a clear opportunity for cognitive enhancement. So let’s see how we may harness neuroplasticity to improve cognitive performance.
How Novel Activities Support Neuroplasticty
What better way to stimulate our mind than to learn new things? Learning is, by its very nature, a plasticity process. At the very least, learning changes the strength of synapses in the neural circuits that encode the memories we form as we acquire new knowledge or develop new skills. But as we progress in our practice and proficiency, plastic adaptations often extend to the structural level. Learning a new skill or engaging in cognitively demanding tasks can therefore be a gateway into the brain’s neuroplastic potential.
Brain plasticity is a neurohacking opportunity.
Taking up a musical instrument can be a great way to do so because it stimulates different aspects of cognition by combining motor and sensory auditory training. Studies with professional musicians showed that their brains have greater gray matter volumes in motor and auditory regions compared to amateur musicians and non-musicians . Although most professional musicians start learning at a young age, when the brain is more plastic, and practice extensively throughout life, similar adaptations can also take place when skills are acquired later in life (though probably not to the same extent).
In adult non-musicians, short-term musical training (a simple task of learning to play a musical sequence on the piano) was shown to induce functional plasticity in the auditory cortex [2,3] and even structural plasticity in the auditory-motor network . Importantly, the plastic changes induced by musical training were shown to contribute to an enhancement of other aspects of cognitive performance. Musically naïve older adults (61-85 years old) who received a 4-month musical instrument training improved memory performance on a verbal recall test and showed changes in neural functional connectivity between specific brain areas indicative of improved neural efficiency . In another study with older adults, musical training enhanced neural encoding of speech .
Similar effects have been observed while learning other motor skills. For example, young adults who learned how to juggle for three months showed gray matter expansions in brain areas associated with the processing and storage of complex visual motion . Importantly, in a later similar study with older adults, although the older volunteers did not achieve the same skill level as the younger participants, structural adaptations were only slightly smaller, revealing that their brain retained significant structural plasticity. Interestingly, unlike the younger volunteers, the older individuals also showed increases in gray matter in the hippocampus, which has key roles in learning and memory, and in the nucleus accumbens, which is a neural interface between the limbic and motor systems that participates in turning reward information into motivated action . This may mean that the reward of learning something new may also contribute to an enhancement of neuroplasticity.
Playing video games is another interesting example because it requires and trains not only complex motor skills, but also complex cognitive skills. Young adults who played a game involving 3D-space navigation (Super Mario 64, nothing too fancy!) over a period of 2 months showed significant gray matter increases in brain areas crucial for spatial navigation, strategic planning, working memory, and motor performance . In other studies, as few as 10 to 20 hours of video game playing was shown to improve performance on attention-demanding and perceptual tasks, and on tasks that require executive control [10–12].
These are all examples of predominantly motor skills, but other types of learning with a predominant cognitive component can also drive functional and structural brain changes and cognitive benefits.
Learning a second language may increase gray matter density, even in aged individuals.
Learning a new language is a classic example (and now that we can do it through an app on our phone, easy to take up). Learning a second language, even in late adulthood, was shown to increase gray matter density in regions associated with language processing, to increase cortical thickness, and to support white matter integrity .
Sign language may be a particularly good option because it also incorporates motor and visual elements. In a study with hearing adults, after just 3 months of learning sign language, major changes were observed in neural activity patterns within the language network and visuospatial and motion-sensitive regions. Functional coupling between specific brain regions progressed as proficiency increased and an increase in gray matter volume was detected in a region of the cerebral cortex associated with language processing .
Just a few months of learning sign language may change neural activity patterns within the language network and visuospatial and motion-sensitive brain regions.
Cognitive training methods have also been shown to induce plastic changes in the brain. In one study with middle-aged and elderly healthy volunteers, memory training using the Method of Loci increased cortical thickness in specific brain areas that correlated with improvements in memory performance . The Method of Loci, or Memory Palace, is a mnemonic device that helps to memorize information by placing each item to be remembered in a logical order in a familiar spatial environment, such as rooms in a building, for example (loci is the latin word for places).
In another study, a group of younger (aged 20–31 years) and older (aged 65–80 years) adults received, over a period of about 6 months, a total of one hundred and one 1-h sessions of cognitive training with a set of working memory, episodic memory, and perceptual speed tasks. In both age groups, changes were observed in white matter in the corpus callosum (the bundle of nerve fibers that connects the two cerebral hemispheres), along with improved cognitive performance in the trained tasks. Although cognitive performance improvements were more substantial in younger adults, structural changes were of similar magnitude in both younger and older adults .
What these examples show is that learning and memory experiences may leave lasting changes in brain function and structure that underlie not only improved performance in the skills being trained, but also in many other aspects of cognition.
Focusing on mastering a specific skill or refining skills you already have is great, but trying new things really gives it an extra kick. That’s because novelty is processed differently by the brain and is more stimulating than familiar stimuli [17,18]. Novelty elicits strong responses in several brain areas, stimulates many different neuromodulatory systems, and affects different aspects of cognition; it enhances attention and arousal, leading to enhanced motivation and learning . Animal studies have shown that exploration of a novel environment can increase hippocampal synaptic plasticity and memory encoding . This enhanced responsiveness to novelty may be an evolutionary adaptation of the brain that allowed us to quickly take in a novel environment in order to more quickly adapt and survive.
Novelty elicits strong responses in the brain and stimulates the brain’s neuromodulatory systems.
So, even if you’re not proactively learning something new, you may be stimulating neuroplasticity simply by traveling to a new place or taking new routes to work, for example.
Sleep Supports Learning and Memory Through Neuroplasticity
Among its many functions, sleep is essential for learning and the consolidation of memory . These memory-supporting effects of sleep are likely linked to roles on neuroplasticity, as sleep can influence long-term potentiation (LTP) and the expression of genes associated with building new synapses and strengthening existing synapses in the cortex and hippocampus [22,23].
A number of studies have associated sleep patterns with learning and memory performance in humans. For example, recall of face-location associations was better following a 12-h interval containing sleep than following an equal period of wakefulness . Importantly, sleep was found to be particularly supportive of memory if it occurred shortly after learning . Sleep within 3 h after learning vocabulary was more effective than sleep delayed by more than 10h . Similarly, word recall after 24 h was better when sleep took place immediately after learning than after a day of wakefulness .
Sleep is essential for learning and memory consolidation.
On the other hand, individuals with poor sleep exhibit decreased sleep-dependent memory consolidation, regarded as an indicator for poorer neural plasticity [27,28]. Poor sleep was also associated with reduced gray matter in subregions of the prefrontal cortex (PFC) [29,30] and smaller hippocampal volume [31,32].
So, a good way to learn better and make better use of the plasticity-promoting effects of new learning experiences is to try to learn closer to bedtime and to take care of your sleep. Check out our article on the neuroscience of sleep to learn how to get more of it.
Physical Activity Stimulates Both Body and Mind
Exercise and physical activity in general are an essential part of a healthy lifestyle. It’s well documented that aerobic exercise is beneficial for pretty much every system in the human body. Exercise improves cardiovascular and metabolic health, immune signaling, endocrine signaling, mitochondrial function, cell energy production, and antioxidant defenses, all of which support healthy brain function either directly and indirectly [33,34].
Exercise supports the brain from the molecular to the structural level—it influences neurotransmitter levels and neuronal communication, activates signaling pathways and molecules that drive positive cellular adaptations in the brain, improves cerebral blood flow and metabolism, and supports healthy neuronal and glial function and morphology [35–41]. One of the most influential molecules produced in response to exercise is a growth factor called brain-derived neurotrophic factor (BDNF). Among its many actions in the brain, BDNF acts as a facilitator of neuroplasticity [42–44]. Through this set of adaptations, exercise has the potential to support plasticity. And indeed, that seems to be the case.
Animal studies have shown that exercise may enhance the magnitude of LTP, which is one of the key mechanisms of functional synaptic plasticity underlying learning and memory . In human studies, exercise was shown to stimulate neuroplastic adaptations in individuals of all ages—it increased excitability in the cerebral cortex, stimulated cortical and hippocampal activity, and supported functional connectivity in the cortex and hippocampus [46–52].
At a structural level, greater aerobic physical activity and fitness were associated with increases in gray matter volume in the cortex, improvements in hippocampal microstructure and integrity, and increases in hippocampal volume in adults of all ages [38,39,53–56]. This structural support is particularly important because it may help to offset brain atrophy, one of the main consequences of brain aging, by helping to maintain and even increase both gray matter and white matter volumes in older adults [56–59].
The hippocampus, which has a key role in cognitive function, is one of the structures most affected by age-related atrophy. Exercise may help not only to delay its structural decline, but also to actually increase hippocampal volume, as has been shown in a few studies in older individuals [38,55,60,61]. In one study, older adults involved in long-term aerobic exercise showed a 2% increase in hippocampal volume over the course of one year, whereas controls who underwent one year of only stretching exercises exhibited a 1.4% decrease . These numbers may not seem like much, but a 2% increase in hippocampal volume actually corresponds to reversing age-related losses by 1 to 2 years.
Importantly, these plastic adaptations promoted by exercise manifest as improved cognitive capacities . Studies showed that functional brain adaptations associated with better aerobic fitness correlated with improved memory  and that, in parallel with the increase in hippocampal volume, spatial memory performance was also enhanced by exercise . Aerobic exercise a few hours after learning influenced hippocampal processing during memory retrieval and improved associative memory . Additionally, exercise also benefits mental health and stress responses [64,65], which, as we’ll see, may also contribute to an improvement in neuroplasticity and cognitive function.
Exercise creates a favorable physiological environment for adaptive neuroplasticity.
Chronic Stress May Hinder Brain Plasticity
That chronic stress can wreak havoc on our health is well known. Stress is as bad for the brain as it is for the heart and neuroplasticity seems to be among its victims.
Stress can influence health at a systemic level via endocrine signaling. Through the activation of the hypothalamic-pituitary axis (HPA), stress hormones secreted into the bloodstream modulate cellular signaling pathways that influence cell and tissue function. When produced in excessive amounts, stress hormones may trigger maladaptive responses in the body and brain.
In a context of chronic stress, excessive hormone production can have a detrimental impact on brain function and on many aspects of cognitive performance, including attention, learning, memory, and emotion processing, for example . This effect is partially associated with plastic alterations in the brain as chronic stress and excessive stress hormone levels have been associated with functional and structural modifications in brain regions with important roles in cognitive and emotional processing such as the amygdala, the hippocampus, and the prefrontal cortex [67–73].
In humans, chronic stress and high cortisol levels were linked to memory impairments and decreases in hippocampal volume and cortical thickness [71–73]. In animals, chronic exposure to elevated levels of stress hormones was linked to altered dendritic morphology, dendritic atrophy, neuronal loss, and reduced volume of the hippocampus . A marked reduction of spine density and spine dynamics in the motor cortex was also observed in animals subjected to chronic social stress . Interestingly, cognitive training was shown to reverse structural changes associated with chronic stress .
Interestingly, a different type of detrimental response to stress has been observed in the amygdala, which has an important role in emotional responses. In neurons of the amygdala, repeated stress and increased stress hormone levels increased dendritic branching and spine density, an effect that was associated with increased anxiety-like behaviors [68,69]. So, in this case, although stress promoted morphological adaptations in neurons, plasticity was actually recruited to reinforce and facilitate maladaptive affective responses.
However, there seems to be a difference between acute and chronic stress. In studies evaluating the cognitive effects of different levels of stress hormones, an hormetic dose-response has been observed: there were beneficial effects at lower hormone levels for working memory  and emotional memory  that became detrimental after a certain dose threshold. Other studies have shown a positive effect of mild acute psychological stress on the response speed in an attention task , and on alertness and attentional control in selective attention processes, for example . It is possible that such effects may be due to a modulation of plasticity, as acute stress was shown to transiently increase serum BDNF levels in humans [79,80]. In an animal study, brief acute stress was shown to reinforce hippocampal LTP .
Given the great variability observed across studies on the effects of acute stress, this needs to be taken with a grain of salt. Effects differed depending on the amount, type, and duration of stress, with abundant examples of detrimental cognitive effects. Still, brief periods of stress may be cognitively stimulating for some people or in specific conditions—it may be the reason why some people work well under occasional pressure.
Meditation and Relaxation Practices May Counter The Effects of Stress
Meditation is a mind and body practice that supports mental, emotional, and physical well-being. It can bring calmness and a sense of balance, promote mental and physical relaxation, help to reduce feelings of stress, and support sleep. By doing so, meditation may provide a number of health benefits, including for the brain. Among the mechanisms that support brain health and cognitive function, a reduction of stress hormone production seems particularly relevant [82–84], as it may counter the damaging effects of stress on cognitive performance and neuroplasticity.
Several studies have consistently reported structural brain changes associated with mindfulness meditation in brain regions that are known to support awareness, attention, and emotional regulation and that are adversely affected by mood disorders . An association has been reported between structural changes and functional activation in emotional and cognitive regions of the brain of meditators, such as the prefrontal cortex, insula, hippocampus, and amygdala .
Meditation is a well-studied example, but it’s likely that any practice or activity that promotes relaxation may, to some extent, have similar benefits. Obviously, what’s relaxing for one person, may be stressful for another. The point is, finding something soothing may help to clear the brain from the clutter of stress and create space for cognitive growth.
Healthy Diets Nurture Brain Plasticity
Diet is tremendously important for brain function not only because it provides the fuel that supports the high energetic demand of the brain, but also because it provides many of the ingredients that are required for neuroplasticity signaling, adaptive brain functions, and building new cellular structures.
Diet can influence a number of cellular processes and structures essential for the viability of neuroplasticity mechanisms, including cellular metabolism and mitochondrial health. Unhealthy dietary patterns can have a negative impact on these processes, usually leading to an increase in oxidative stress, which can, for example, damage neural membranes and constrain the many neuronal processes that rely on membrane properties, including synaptic communication and neuronal firing. These are all essential for the plastic capacity of the brain.
A few examples of unhealthy dietary patterns with a negative impact on neuroplasticity can be found in animal studies: a high-fat diet induced oxidative stress and hampered insulin sensitivity, synaptic plasticity, blood-brain barrier integrity, and cerebral blood flow ; a high-calorie diet caused long-term memory impairments via reduced synaptic plasticity ; a high-fat and refined sugar diet reduced hippocampal BDNF levels, synaptic plasticity, and learning capacity ; a palatable diet rich in simple sugars was shown to impair memory and reduce hippocampal BDNF and other neuroplasticity markers ; a high-salt diet increased oxidative stress, impaired short-term and long-term memory, inhibited LTP in the hippocampus, and decreased the expression of BDNF and synaptic proteins .
Conversely, a diet rich in vitamins, minerals, healthy fats, complex carbohydrates, and neuroprotective polyphenols—of which the Mediterranean diet is a prime example—may support healthy brain function, and consequently, support the neuroplastic capacity of the brain .
Cognitive benefits may also be obtained from caloric restriction and intermittent or periodic fasting, known to activate a number of pro-longevity signaling pathways and to support mitochondrial function and cellular metabolism . In animals, caloric restriction improved learning [94,95], enhanced hippocampal synaptic plasticity, hippocampal BDNF levels, and dendritic spine density [96,97], prevented age-related deficits in synaptic plasticity [98,99], enhanced hippocampal neurogenesis, and supported long-term memory consolidation . Likewise, in humans, caloric restriction improved memory performance in healthy elderly subjects .
A Healthy and Stimulating Lifestyle Supports Neuroplasticity
There are so many other things that may support neuroplasticity… the limit is that of imagination. Research on brain plasticity is plentiful and shows that plasticity can be harnessed to support cognition. In the big picture, the brain-as-a-muscle analogy is one that works very well here: if you work out your brain, it becomes stronger, if you don’t use it, it atrophies. Nourish your brain with mental stimulation, physical activity, sleep, relaxation, healthy food, novelty, and fun and it will flourish.
C. Gaser, G. Schlaug, Ann. N. Y. Acad. Sci. 999 (2003) 514–517.
C. Lappe, S.C. Herholz, L.J. Trainor, C. Pantev, J. Neurosci. 28 (2008) 9632–9639.
C. Pantev, C. Lappe, S.C. Herholz, L. Trainor, Ann. N. Y. Acad. Sci. 1169 (2009) 143–150.
Q. Li, X. Wang, S. Wang, Y. Xie, X. Li, Y. Xie, S. Li, Hum. Brain Mapp. 39 (2018) 2098–2110.
X. Guo, M. Yamashita, M. Suzuki, C. Ohsawa, K. Asano, N. Abe, T. Soshi, K. Sekiyama, Hum. Brain Mapp. 42 (2021) 1359–1375.
D. Fleming, S. Belleville, I. Peretz, G. West, B.R. Zendel, Brain Cogn. 136 (2019) 103592.
B. Draganski, C. Gaser, V. Busch, G. Schuierer, U. Bogdahn, A. May, Nature 427 (2004) 311–312.
G.J. Mogenson, D.L. Jones, C.Y. Yim, Prog. Neurobiol. 14 (1980) 69–97.
S. Kühn, T. Gleich, R.C. Lorenz, U. Lindenberger, J. Gallinat, Mol. Psychiatry 19 (2014) 265–271.
C.S. Green, D. Bavelier, Nature 423 (2003) 534–537.
C.S. Green, D. Bavelier, Cognition 101 (2006) 217–245.
C. Basak, W.R. Boot, M.W. Voss, A.F. Kramer, Psychol. Aging 23 (2008) 765–777.
P. Li, J. Legault, K.A. Litcofsky, Cortex 58 (2014) 301–324.
A. Banaszkiewicz, J. Matuszewski, Ł. Bola, M. Szczepanik, B. Kossowski, P. Rutkowski, M. Szwed, K. Emmorey, K. Jednoróg, A. Marchewka, Hum. Brain Mapp. 42 (2021) 384–397.
A. Engvig, A.M. Fjell, L.T. Westlye, T. Moberget, Ø. Sundseth, V.A. Larsen, K.B. Walhovd, Neuroimage 52 (2010) 1667–1676.
M. Lövdén, N.C. Bodammer, S. Kühn, J. Kaufmann, H. Schütze, C. Tempelmann, H.-J. Heinze, E. Düzel, F. Schmiedek, U. Lindenberger, Neuropsychologia 48 (2010) 3878–3883.
C. Hawco, M. Lepage, Front. Hum. Neurosci. 8 (2014) 699.
E. Tulving, H.J. Markowitsch, F.E. Craik, R. Habib, S. Houle, Cereb. Cortex 6 (1996) 71–79.
J. Schomaker, M. Meeter, Neurosci. Biobehav. Rev. 55 (2015) 268–279.
C.D. Davis, F.L. Jones, B.E. Derrick, J. Neurosci. 24 (2004) 6497–6506.
B. Rasch, J. Born, Physiol. Rev. 93 (2013) 681–766.
R. Huber, M.F. Ghilardi, M. Massimini, G. Tononi, Nature 430 (2004) 78–81.
C. Cirelli, C.M. Gutierrez, G. Tononi, Neuron 41 (2004) 35–43.
L.M. Talamini, I.L.C. Nieuwenhuis, A. Takashima, O. Jensen, Learn. Mem. 15 (2008) 233–237.
S. Gais, B. Lucas, J. Born, Learn. Mem. 13 (2006) 259–262.
J.D. Payne, M.A. Tucker, J.M. Ellenbogen, E.J. Wamsley, M.P. Walker, D.L. Schacter, R. Stickgold, PLoS One 7 (2012) e33079.
J. Backhaus, K. Junghanns, J. Born, K. Hohaus, F. Faasch, F. Hohagen, Biol. Psychiatry 60 (2006) 1324–1330.
C. Nissen, C. Kloepfer, B. Feige, H. Piosczyk, K. Spiegelhalder, U. Voderholzer, D. Riemann, J. Sleep Res. 20 (2011) 129–136.
E.Y. Joo, H.J. Noh, J.-S. Kim, D.L. Koo, D. Kim, K.J. Hwang, J.Y. Kim, S.T. Kim, M.R. Kim, S.B. Hong, Sleep 36 (2013) 999–1007.
E. Altena, H. Vrenken, Y.D. Van Der Werf, O.A. van den Heuvel, E.J.W. Van Someren, Biol. Psychiatry 67 (2010) 182–185.
D. Riemann, U. Voderholzer, K. Spiegelhalder, M. Hornyak, D.J. Buysse, C. Nissen, J. Hennig, M.L. Perlis, L.T. van Elst, B. Feige, Sleep 30 (2007) 955–958.
E.Y. Joo, H. Kim, S. Suh, S.B. Hong, Sleep 37 (2014) 1189–1198.
G.N. Ruegsegger, F.W. Booth, Cold Spring Harb. Perspect. Med. 8 (2018).
A. Rebelo-Marques, A. De Sousa Lages, R. Andrade, C.F. Ribeiro, A. Mota-Pinto, F. Carrilho, J. Espregueira-Mendes, Front. Endocrinol. 9 (2018) 258.
R.J. Maddock, G.A. Casazza, D.H. Fernandez, M.I. Maddock, J. Neurosci. 36 (2016) 2449–2457.
D.D. Church, J.R. Hoffman, G.T. Mangine, A.R. Jajtner, J.R. Townsend, K.S. Beyer, R. Wang, M.B. La Monica, D.H. Fukuda, J.R. Stout, J. Appl. Physiol. 121 (2016) 123–128.
S. Vaughan, M. Wallis, D. Polit, M. Steele, D. Shum, N. Morris, Age Ageing 43 (2014) 623–629.
M.M. Kleemeyer, S. Kühn, J. Prindle, N.C. Bodammer, L. Brechtel, A. Garthe, G. Kempermann, S. Schaefer, U. Lindenberger, Neuroimage 131 (2016) 155–161.
L. Den Ouden, A. Kandola, C. Suo, J. Hendrikse, R.J.S. Costa, M.J. Watt, V. Lorenzetti, Y. Chye, L. Parkes, K. Sabaroedin, M. Yücel, Brain Plast 4 (2018) 211–216.
D. Moore, P.D. Loprinzi, Eur. J. Neurosci. 54 (2021) 6960–6971.
M.W. Voss, C. Vivar, A.F. Kramer, H. van Praag, Trends Cogn. Sci. 17 (2013) 525–544.
C.W. Cotman, N.C. Berchtold, L.-A. Christie, Trends Neurosci. 30 (2007) 464–472.
M. Miranda, J.F. Morici, M.B. Zanoni, P. Bekinschtein, Front. Cell. Neurosci. 13 (2019) 363.
K.L. Szuhany, M. Bugatti, M.W. Otto, J. Psychiatr. Res. 60 (2015) 56–64.
W.C. Abraham, O.D. Jones, D.L. Glanzman, NPJ Sci Learn 4 (2019) 9.
A.M. Singh, J.L. Neva, W.R. Staines, Exp. Brain Res. 232 (2014) 3675–3685.
A.M. Hendy, J.W. Andrushko, P.A. Della Gatta, W.-P. Teo, Front. Psychol. 13 (2022) 814633.
N. Hashimoto, M. Yokogawa, H. Kojima, S. Tanaka, T. Nakagawa, J. Phys. Therapy Sci. 30 (2018) 1257–1261.
T. Demirakca, V. Cardinale, S. Dehn, M. Ruf, G. Ende, Neural Plast. 2016 (2016) 8240894.
M.W. Voss, K.I. Erickson, R.S. Prakash, L. Chaddock, E. Malkowski, H. Alves, J.S. Kim, K.S. Morris, S.M. White, T.R. Wójcicki, L. Hu, A. Szabo, E. Klamm, E. McAuley, A.F. Kramer, Neuropsychologia 48 (2010) 1394–1406.
K. Suwabe, K. Byun, K. Hyodo, Z.M. Reagh, J.M. Roberts, A. Matsushita, K. Saotome, G. Ochi, T. Fukuie, K. Suzuki, Y. Sankai, M.A. Yassa, H. Soya, Proc. Natl. Acad. Sci. U. S. A. 115 (2018) 10487–10492.
J. Won, D.D. Callow, G.S. Pena, L.S. Jordan, N.A. Arnold-Nedimala, K.A. Nielson, J.C. Smith, J. Alzheimers. Dis. 82 (2021) 1015–1031.
K.I. Erickson, M.W. Voss, R.S. Prakash, C. Basak, A. Szabo, L. Chaddock, J.S. Kim, S. Heo, H. Alves, S.M. White, T.R. Wojcicki, E. Mailey, V.J. Vieira, S.A. Martin, B.D. Pence, J.A. Woods, E. McAuley, A.F. Kramer,
Proc. Natl. Acad. Sci. U. S. A. 108 (2011) 3017–3022.
A.G. Thomas, A. Dennis, P.A. Bandettini, H. Johansen-Berg, Front. Psychol. 3 (2012) 86.
K.I. Erickson, R.S. Prakash, M.W. Voss, L. Chaddock, L. Hu, K.S. Morris, S.M. White, T.R. Wójcicki, E. McAuley, A.F. Kramer, Hippocampus 19 (2009) 1030–1039.
K. Wittfeld, C. Jochem, M. Dörr, U. Schminke, S. Gläser, M. Bahls, M.R.P. Markus, S.B. Felix, M.F. Leitzmann, R. Ewert, R. Bülow, H. Völzke, D. Janowitz, S.E. Baumeister, H.J. Grabe, Mayo Clin. Proc. 95 (2020) 44–56.
S.J. Colcombe, A.F. Kramer, K.I. Erickson, P. Scalf, E. McAuley, N.J. Cohen, A. Webb, G.J. Jerome, D.X. Marquez, S. Elavsky, Proc. Natl. Acad. Sci. U. S. A. 101 (2004) 3316–3321.
J.R. Best, B.K. Chiu, C. Liang Hsu, L.S. Nagamatsu, T. Liu-Ambrose, J. Int. Neuropsychol. Soc. 21 (2015) 745–756.
S. Colcombe, A.F. Kramer, Psychol. Sci. 14 (2003) 125–130.
Y.S. Kim, S.K. Shin, S.B. Hong, H.J. Kim, Exp. Gerontol. 97 (2017) 22–28.
C. Rosano, J. Guralnik, M. Pahor, N.W. Glynn, A.B. Newman, T.S. Ibrahim, K. Erickson, R. Cohen, C.E. Shaaban, R.L. MacCloud, H.J. Aizenstein, Am. J. Geriatr. Psychiatry 25 (2017) 209–217.
C. Vorkapic, S. Leal, H. Alves, M. Douglas, A. Britto, E.H.M. Dantas, Arq. Neuropsiquiatr. 79 (2021) 536–550.
E.V. van Dongen, I.H.P. Kersten, I.C. Wagner, R.G.M. Morris, G. Fernández, Curr. Biol. 26 (2016) 1722–1727.
H.E. Webb, D.S. Rosalky, S.E. Tangsilsat, K.A. McLeod, E.O. Acevedo, B. Wax, Med. Sci. Sports Exerc. 45 (2013) 379–386.
K. Mikkelsen, L. Stojanovska, M. Polenakovic, M. Bosevski, V. Apostolopoulos, Maturitas 106 (2017) 48–56.
S.J. Lupien, R.-P. Juster, C. Raymond, M.-F. Marin, Front. Neuroendocrinol. 49 (2018) 91–105.
J. Radley, D. Morilak, V. Viau, S. Campeau, Neurosci. Biobehav. Rev. 58 (2015) 79–91.
R. Mitra, S. Jadhav, B.S. McEwen, A. Vyas, S. Chattarji, Proc. Natl. Acad. Sci. U. S. A. 102 (2005) 9371–9376.
A. Vyas, R. Mitra, B.S. Shankaranarayana Rao, S. Chattarji, J. Neurosci. 22 (2002) 6810–6818.
A.-K. Gellner, A. Sitter, M. Rackiewicz, M. Sylvester, A. Philipsen, A. Zimmer, V. Stein, Transl. Psychiatry 12 (2022) 91.
S.J. Lupien, M. de Leon, S. de Santi, A. Convit, C. Tarshish, N.P. Nair, M. Thakur, B.S. McEwen, R.L. Hauger, M.J. Meaney, Nat. Neurosci. 1 (1998) 69–73.
P.J. Gianaros, J.R. Jennings, L.K. Sheu, P.J. Greer, L.H. Kuller, K.A. Matthews, Neuroimage 35 (2007) 795–803.
W.S. Kremen, R.C. O’Brien, M.S. Panizzon, E. Prom-Wormley, L.J. Eaves, S.A. Eisen, L.T. Eyler, R.L. Hauger, C. Fennema-Notestine, B. Fischl, M.D. Grant, D.H. Hellhammer, A.J. Jak, K.C. Jacobson, T.L. Jernigan, S.J. Lupien, M.J. Lyons, S.P. Mendoza, M.C. Neale, L.J. Seidman, H.W. Thermenos, M.T. Tsuang, A.M. Dale, C.E. Franz, Neuroimage 53 (2010) 1093–1102.
C. Sandi, H.A. Davies, M.I. Cordero, J.J. Rodriguez, V.I. Popov, M.G. Stewart, Eur. J. Neurosci. 17 (2003) 2447–2456.
S.J. Lupien, C.J. Gillin, R.L. Hauger, Behav. Neurosci. 113 (1999) 420–430.
H.C. Abercrombie, N.H. Kalin, M.E. Thurow, M.A. Rosenkranz, R.J. Davidson, Behav. Neurosci. 117 (2003) 505–516.
G.S. Shields, A.M. Rivers, M.M. Ramey, B.C. Trainor, A.P. Yonelinas, Psychoneuroendocrinology 108 (2019) 78–86.
M. Qi, H. Gao, Psychophysiology 57 (2020) e13521.
R. Linz, L.M.C. Puhlmann, F. Apostolakou, E. Mantzou, I. Papassotiriou, G.P. Chrousos, V. Engert, T. Singer, Neuropsychopharmacology 44 (2019) 1797–1804.
R. Hermann, A. Schaller, D. Lay, W. Bloch, C. Albus, K. Petrowski, Stress 24 (2021) 442–449.
T. Ahmed, J.U. Frey, V. Korz, J. Neurosci. 26 (2006) 3951–3958.
A. Chiesa, A. Serretti, J. Altern. Complement. Med. 15 (2009) 593–600.
J.D. Creswell, L.E. Pacilio, E.K. Lindsay, K.W. Brown, Psychoneuroendocrinology 44 (2014) 1–12.
R. Jevning, A.F. Wilson, J.M. Davidson, Horm. Behav. 10 (1978) 54–60.
K.C.R. Fox, S. Nijeboer, M.L. Dixon, J.L. Floman, M. Ellamil, S.P. Rumak, P. Sedlmeier, K. Christoff, Neurosci. Biobehav. Rev. 43 (2014) 48–73.
Y.-Y. Tang, B.K. Hölzel, M.I. Posner, Nat. Rev. Neurosci. 16 (2015) 213–225.
S. Sharma, Physiol. Behav. 240 (2021) 113528.
S.L. Paulo, C. Miranda-Lourenço, R.F. Belo, R.S. Rodrigues, J. Fonseca-Gomes, S.R. Tanqueiro, V. Geraldes, I. Rocha, A.M. Sebastião, S. Xapelli, M.J. Diógenes, Curr. Issues Mol. Biol. 43 (2021) 2305–2319.
R. Molteni, R.J. Barnard, Z. Ying, C.K. Roberts, F. Gómez-Pinilla, Neuroscience 112 (2002) 803–814.
V. Altermann Torre, A.G. Machado, N. de Sá Couto-Pereira, D. Mar Arcego, A. Dos Santos Vieira, P.S.V. Salerno, E. Dos Santos Garcia, C. Lazzaretti, A.P. Toniazzo, F. Nedel, C. Noschang, F. Schmitz, A.T.S. Wyse, C.ΩDalmaz, R. Krolow, Int. J. Dev. Neurosci. (2020).
Q. Ge, Z. Wang, Y. Wu, Q. Huo, Z. Qian, Z. Tian, W. Ren, X. Zhang, J. Han, Mol. Nutr. Food Res. 61 (2017).
G.C. Román, R.E. Jackson, R. Gadhia, A.N. Román, J. Reis, Rev. Neurol. 175 (2019) 724–741.
V.D. Longo, M. Di Tano, M.P. Mattson, N. Guidi, Nat Aging 1 (2021) 47–59.
L. Ma, R. Wang, W. Dong, Z. Zhao, Exp. Gerontol. 102 (2018) 28–35.
L. Ma, Z. Zhao, R. Wang, X. Zhang, J. Zhang, W. Dong, B. Xu, J. Zhang, Neurol. Sci. 35 (2014) 1381–1386.
G. Talani, V. Licheri, F. Biggio, V. Locci, M.C. Mostallino, P.P. Secci, V. Melis, L. Dazzi, G. Carta, S. Banni, G. Biggio, E. Sanna, Neuropsychopharmacology 41 (2016) 1308–1318.
A.M. Stranahan, K. Lee, B. Martin, S. Maudsley, E. Golden, R.G. Cutler, M.P. Mattson, Hippocampus 19 (2009) 951–961.
K. Eckles-Smith, D. Clayton, P. Bickford, M.D. Browning, Brain Res. Mol. Brain Res. 78 (2000) 154–162.
N. Hori, I. Hirotsu, P.J. Davis, D.O. Carpenter, Neuroreport 3 (1992) 1085–1088.
G.P. Dias, T. Murphy, D. Stangl, S. Ahmet, B. Morisse, A. Nix, L.J. Aimone, J.B. Aimone, M. Kuro-O, F.H. Gage, S. Thuret, Mol. Psychiatry 26 (2021) 6365–6379.
A.V. Witte, M. Fobker, R. Gellner, S. Knecht, A. Flöel, Proc. Natl. Acad. Sci. U. S. A. 106 (2009) 1255–1260.
Tagged with :