Relevant bibliographies by topics / Brain – Aging

Academic literature on the topic 'Brain – Aging'

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Published: 4 June 2021
Last updated: 31 July 2024

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Journal articles on the topic "Brain – Aging"

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Selkoe, Dennis J. "Aging Brain, Aging Mind." Scientific American 267, no. 3 (September 1992): 134–42. http://dx.doi.org/10.1038/scientificamerican0992-134.

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&NA;, &NA;. "BRAIN AGING." Journal of Wound, Ostomy and Continence Nursing 12, no. 6 (November 1985): 28A. http://dx.doi.org/10.1097/00152192-198511000-00020.

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Cherdak, M. A. "Brain Aging." Problems of Geroscience, no. 2 (December 18, 2023): 71–79. http://dx.doi.org/10.37586/2949-4745-2-2023-71-79.

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Brain aging is part of the aging of the whole body, largely determining the success of general aging and the quality of life of an older person. Brain aging is a complex multifactorial process that occurs throughout a human’s life, which includes changes at subcellular, tissue, and organ levels as well as at physiological level, mediating changes in neurophysiological (cognitive) functions. The review provides up-to-date data on morphological and physiological changes observed during natural aging; various phenotypes of brain aging are discussed, including both pathologically accelerated and «supernormal» aging; questions of the division between the norm and pathology are raised in the context of changes observed during brain aging; the factors both accelerating and decelerating the aging processes of the brain are considered along with linkage of natural aging with neurodegenerative and cerebrovascular diseases.
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Cherdak, M. A. "Brain Aging." Advances in Gerontology 13, no. 2 (June 2023): 70–77. http://dx.doi.org/10.1134/s2079057024600198.

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Wu, Zhou, Janchun Yu, Aiqin Zhu, and Hiroshi Nakanishi. "Nutrients, Microglia Aging, and Brain Aging." Oxidative Medicine and Cellular Longevity 2016 (2016): 1–9. http://dx.doi.org/10.1155/2016/7498528.

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As the life expectancy continues to increase, the cognitive decline associated with Alzheimer’s disease (AD) becomes a big major issue in the world. After cellular activation upon systemic inflammation, microglia, the resident immune cells in the brain, start to release proinflammatory mediators to trigger neuroinflammation. We have found that chronic systemic inflammatory challenges induce differential age-dependent microglial responses, which are in line with the impairment of learning and memory, even in middle-aged animals. We thus raise the concept of “microglia aging.” This concept is based on the fact that microglia are the key contributor to the acceleration of cognitive decline, which is the major sign of brain aging. On the other hand, inflammation induces oxidative stress and DNA damage, which leads to the overproduction of reactive oxygen species by the numerous types of cells, including macrophages and microglia. Oxidative stress-damaged cells successively produce larger amounts of inflammatory mediators to promote microglia aging. Nutrients are necessary for maintaining general health, including the health of brain. The intake of antioxidant nutrients reduces both systemic inflammation and neuroinflammation and thus reduces cognitive decline during aging. We herein review our microglia aging concept and discuss systemic inflammation and microglia aging. We propose that a nutritional approach to controlling microglia aging will open a new window for healthy brain aging.
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Otomo, Eiichi. "Aging of brain." JOURNAL OF THE STOMATOLOGICAL SOCIETY,JAPAN 56, no. 2 (1989): 215–21. http://dx.doi.org/10.5357/koubyou.56.215.

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Villeda, Saul. "Healthy Brain Aging." Innovation in Aging 5, Supplement_1 (December 1, 2021): 196. http://dx.doi.org/10.1093/geroni/igab046.753.

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Yankner, Bruce A., Tao Lu, and Patrick Loerch. "The Aging Brain." Annual Review of Pathology: Mechanisms of Disease 3, no. 1 (February 2008): 41–66. http://dx.doi.org/10.1146/annurev.pathmechdis.2.010506.092044.

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Stern, P., P. J. Hines, and J. Travis. "The Aging Brain." Science 346, no. 6209 (October 30, 2014): 566–67. http://dx.doi.org/10.1126/science.346.6209.566.

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Brody, H. "The aging brain." Acta Neurologica Scandinavica 85, S137 (March 1992): 40–44. http://dx.doi.org/10.1111/j.1600-0404.1992.tb05037.x.

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Dissertations / Theses on the topic "Brain – Aging"

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Tam, Man-kin Helena, and 譚敏堅. "Cognitive functioning of the aging brain." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hdl.handle.net/10722/209669.

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This thesis contains two studies which examined the cognitive functioning of the aging brain. Specifically, age-related changes in processing speed and its remediation via cognitive training were studied. In study 1, younger adults (n = 34) and older adults (n = 39) were recruited to investigate the age-related differences in the relationships between processing speed and general cognitive status (GCS). Their performance in GCS (as measured by The Montreal Cognitive Assessment, Hong Kong Version), cognitive processing speed (as measured by Processing Speed Index, Wechsler Adult Intelligence Scale), cognitive inhibition (as measured by Stroop Color-Word Test), and divided attention (as measured by Color Trails Test) was examined. Current findings indicated that processing speed predicted GCS in older but not younger adults. In older adults, processing speed as a predictor accounted for an additional 13% of variance in GCS. This study further verified the relationship between processing speed and prefrontal abilities, including verbal fluency, cognitive inhibition and divided attention in aging. Findings revealed that despite the abovementioned prefrontal abilities were significantly correlated with processing speed, verbal fluency had remained the strongest predictor, accounting for 21% of variance in processing speed in older adults. Based on findings in study 1, it was anticipated that training cognitive skills including processing speed and prefrontal abilities in older adults would improve cognitive functioning in general. Therefore, in study 2, elderly people at risk of progressive cognitive decline (n = 70) were recruited to investigate the training effect of computerized cognitive training programs that aimed to improve cognitive processing speed, cognitive inhibition and divided attention. Findings indicated that cognitive processing speed and divided attention improved post-training. Results obtained from the two studies implied potential intervention through training cognitive processing speed in elderly people at risk of progressive cognitive decline. Future studies should focus on training specific effect and examining the optimal effect by modification of the training paradigms, particularly the design of the contents and level of difficulty.
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Elobeid, Adila. "Altered proteins in the aging brain." Doctoral thesis, Uppsala universitet, Institutionen för immunologi, genetik och patologi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-277214.

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The classification of neurodegenerative disorders is based on the major component of the protein aggregates in the brain. The most common altered proteins associated with neurodegeneration are Hyperphosphorylated tau (HPt), beta amyloid (Aβ), alpha-synclein (αS) and transactive response DNA binding protein 43 (TDP43). In this study we assessed the incidence and the neuroanatomical distribution of proteins associated with neurodegeneration in the brain tissue of cognitively unimpaired subjects. We demonstrated the early involvement of the Locus Coeruleus (LC) with HPt pathology in cognitively unimpaired mid aged subjects, a finding which supports the notion that LC is an initiation site of HPt pathology. This may suggest that development of clinical assessment techniques and radiological investigations reflecting early LC alterations may help in identifying subjects with early stages of neurodegeneration. Furthermore, we studied a large cohort of cognitively unimpaired subjects with age at death ≥50 years and we applied the National Institute on Aging –Alzheimer’s disease (AD) Association (NIA-AA) guidelines for the assessment of AD related neuropathological changes. Interestingly, a considerable percentage of the subjects were classified as having an intermediate level of AD pathology. We also showed that the altered proteins;  HPt , Aβ, αS, and TDP43 are frequently seen in the brain of cognitively unimpaired subjects with age at death ≥50 years, the incidence of these proteins increased significantly with age. This finding suggests that neurodegeneration has to be extensive to cause functional disturbance and clinical symptoms. Moreover, we investigated the correlation between AD related pathology in cortical biopsies, the AD / cerebrospinal fluid (CSF) biomarkers and the Mini Mental State examination (MMSE) scores in a cohort of idiopathic Normal Pressure Hydrocephalus (iNPH) patients. We demonstrated that AD/ CSF biomarkers and MMSE scores reflect AD pathology in the cortical biopsies obtained from iNPH patients.  In conclusion, this study shows that the altered proteins associated with neurodegeneration are frequently seen in the brain tissue of cognitively unimpaired aged subjects. This fact should be considered while developing diagnostic biomarkers for identification of subjects at early stages of the disease, in order to introduce therapeutic intervention prior to the occurrence of significant cognitive impairment.
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Bajaj, Sahil, Anna Alkozei, Natalie S. Dailey, and William D. S. Killgore. "Brain Aging: Uncovering Cortical Characteristics of Healthy Aging in Young Adults." FRONTIERS MEDIA SA, 2017. http://hdl.handle.net/10150/626429.

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Despite extensive research in the field of aging neuroscience, it still remains unclear whether age related cortical changes can be detected in different functional networks of younger adults and whether these networks respond identically to healthy aging. We collected high-resolution brain anatomical data from 56 young healthy adults (mean age = 30.8 +/- 8.1 years, 29 males). We performed whole brain parcellation into seven functional networks, including visual, somatomotor, dorsal attention, ventral attention, limbic, frontoparietal and default mode networks. We estimated intracranial volume (ICV) and averaged cortical thickness (CT), cortical surface area (CSA) and cortical volume (CV) over each hemisphere as well as for each network. Averaged cortical measures over each hemisphere, especially CT and CV, were significantly lower in older individuals compared to younger ones (one-way ANOVA, p < 0.05, corrected for multiple comparisons). There were negative correlations between age and averaged CT and CV over each hemisphere (p < 0.05, corrected for multiple comparisons) as well as between age and ICV (p = 0.05). Network level analysis showed that age was negatively correlated with CT for all functional networks (p < 0.05, corrected for multiple comparisons), apart from the limbic network. While age was unrelated to CSA, it was negatively correlated with CV across several functional networks (p < 0.05, corrected for multiple comparisons). We also showed positive associations between CV and CT and between CV and CSA for all networks (p < 0.05, corrected for multiple comparisons). We interpret the lack of association between age and CT of the limbic network as evidence that the limbic system may be particularly resistant to age-related declines during this period of life, whereas the significant age-related declines in averaged CT over each hemisphere as well as in all other six networks suggests that CT may serve as a reliable biomarker to capture the effect of normal aging. Due to the simultaneous dependence of CV on CT and CSA, CV was unable to identify such effects of normal aging consistently for the other six networks, but there were negative associations observed between age and averaged CV over each hemisphere as well as between age and ICV. Our findings suggest that the identification of early cortical changes within various functional networks during normal aging might be useful for predicting the effect of aging on the efficiency of functional performance even during early adulthood.
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Jonasson, Lars. "Aerobic fitness and healthy brain aging : cognition, brain structure, and dopamine." Doctoral thesis, Umeå universitet, Diagnostisk radiologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-139056.

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Background: Performing aerobic exercise and maintaining high levels of aerobic fitness may have positive effects on both brain structure and function in older adults. Despite decades of research however, there is still a rather poor understanding of the neurocognitive mechanisms explaining the positive effects of aerobic exercise on cognition. Changes in prefrontal gray matter as well as dopaminergic neurotransmission in striatum are both candidate neurocognitive mechanisms. The main aims of this thesis are: 1. To investigate the effects of aerobic exercise and fitness on cognition and magnetic resonance imaging (MRI) derived gray matter volumes using data from a 6 month physical exercise intervention in older adults (Study I). 2. To simulate the effect of atrophy in longitudinal positron emission tomography (PET) which could pose a challenge to interpreting changes in longitudinal PET imaging (Study II). 3. To study the influence of aerobic exercise and fitness on the dopamine D2-receptor (D2R) system in striatum using [11C]raclopride PET as a potential mechanism for improved cognition (Study III). Results: In Study I, aerobic exercise was found to improve cognitive performance in a broad, rather than domain-specific sense. Moreover, aerobic fitness was related to prefrontal cortical thickness, and improved aerobic fitness over 6 months was related to increased hippocampal volume. In Study II, we identified areas in the striatum vulnerable to the effect of shrinkage, which should be considered in longitudinal PET imaging. Finally, in Study III, the effect of being aerobically fit, and improving fitness levels was found to impact dopaminergic neurotransmission in the striatum, which in turn mediated fitness-induced improvements in working memory updating performance. Conclusion: The findings in this thesis provide novel evidence regarding the neurocognitive mechanisms of aerobic exercise-induced improvements in cognition, and impacts the interpretation of longitudinal PET imaging. Performing aerobic exercise and staying aerobically fit at an older age have positive effects on cognition and brain systems important for memory and cognition. Specifically, fitness-induced changes to the dopaminergic system stands out as one novel neurocognitive mechanism explaining the positive effects of aerobic fitness on working-memory performance in healthy older adults.
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Fox, Geoffrey Arthur. "Effects of aging on functions of the prefrontal cortex." Access electronically, 2004. http://www.library.uow.edu.au/adt-NWU/public/adt-NWU20050112.155754/index.html.

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Robinson, Amy Ann. "Quantification of brain-derived neurotrophic factor expression in the aging monkey brain." Thesis, Boston University, 2013. https://hdl.handle.net/2144/11035.

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Thesis (Ph.D.)--Boston University
While early studies of normal aging largely focused on the loss of neurons as a basis of cognitive aging, current studies of both aging humans and the rhesus monkey model of normal aging demonstrate that forebrain neurons are largely preserved. Instead, MRI and electron microscopic analyses show that age-related changes in the white matter are good predictors of cognitive impairment. White matter changes include an increase in damaged myelin sheaths as well as a loss of myelinated fibers. To explore potential causes of the white matter alterations, the expression of genes related to myelination and axonal survival were examined revealing age-related alterations in the expression of 9 genes in grey matter and 7 in subcortical white matter of the inferior parietal lobule (IPL). Four were selected for further analysis. Of these, brain-derived neurotrophic factor (BDNF) had a statistically significant decrease in expression in the cortical grey matter of the IPL at both the level of gene expression and of protein expression. In 27 male and female rhesus monkeys ranging from young to old, the precursor form of BDNF (proBDNF) was significantly decreased while the mature form was preserved. In order to understand the localization of the age-related decline in proBDNF, immunohistochemical reactivity was quantified in the IPL and in the hippocampus. In the IPL there was a significant decrease in total immunohistochemical reactivity. Further analysis showed that there was an increase in the number of proBDNF positive somata while there was no change in the smaller extrasomal puncta. This increase in cell bodies expressing proBDNF despite the age-related decrease in total proBDNF immunohistochemical density suggests disruption of post-translational processing and/or transport out into the processes. In contrast to the IPL, there was no change in proBDNF density in the hippocampus with age. However, in the hippocampus but not the IPL, proBDNF immunohistochemical reactivity was sexually dimorphic with higher levels in the female monkeys compared to males. While the significance of the change in proBDNF levels for myelin damage is unclear, alteration in this neurotrophin may play a role in the axon loss that accompanies myelin degradation.
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Higaki, Sayuri. "Molecular aspects of brain aging in female macaques." 京都大学 (Kyoto University), 2012. http://hdl.handle.net/2433/157838.

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Klein, Martin. "Cognitive aging, attention, and mild traumatic brain injury." Maastricht : Maastricht : Neuropsych Publishers ; University Library, Maastricht University [Host], 1997. http://arno.unimaas.nl/show.cgi?fid=5810.

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Halfmann, Kameko Mae. "Emotion and decision-making in the aging brain." Diss., University of Iowa, 2015. https://ir.uiowa.edu/etd/1617.

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Natural aging leads to substantial brain changes. These biological changes can, and often do, precede changes in affect, cognition, and behavior. Even subtle changes, for example in affective experience, can create problematic outcomes in day-to-day emotion regulation and decision-making. For example, poor emotion regulation may lead an individual to fall prey to an emotionally potent scam. Similarly, an overly positive individual may not fully attend to or consider potentially negative future outcomes when faced with a decision. This work characterizes changes in affect across the lifespan, and how affect corresponds to brain function, as indexed by the blood oxygen dependent signal, during tasks taxing emotion regulation and decision-making functions. I predicted that age would correlate with greater positive relative to negative emotions and with a more global (i.e., less specific and less complex) representation of emotions. The former predicted pattern indicates increased "affective optimization" and the latter indicates reduced "affective complexity." I predicted that affective optimization and complexity would correlate with brain function during emotion regulation and decision-making. I used time-based experience sampling, self-reported affect, implicit measures of affect, and performance based measures of affect to determine the associations between age and affective optimization and complexity. Results show that age negatively correlates with affective complexity. Specifically, older age was associated with less negative affect complexity, less positive emotion regulation, less affective awareness. Also, older age corresponded to lower levels of negative affect, as indexed by their experiences and an implicit measure of affect. Next, I examined emotion regulation using a cognitive reappraisal task. I found that older age was associated with less successful reappraisal of negative and positive affect. I also found individual differences in the ventromedial prefrontal cortex among older adults during emotion regulation. Lastly, I examined decision-making patterns using an intertemporal choice task. I found that younger adults’ experienced affect aligned more closely with their decision patterns. Among older adults, affective acceptance correlated with individual differences in the striatum and insula. Taken together, these results support the idea that lower levels of affective competence, rather than higher levels, characterize older age. Also, individual differences in affect parallel individual differences in brain function in the somatic marker circuitry. This suggests possible deficits in interpreting visceral information important to emotion regulation and decision-making. The findings from this work will be important for understanding why some older adults are more susceptible to scams, fraud, and decision-making problems.
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Huang, Jing [Verfasser]. "Differential Aging effects on visuomotor control : evidence for an adaptive aging brain / Jing Huang." Gießen : Universitätsbibliothek, 2019. http://d-nb.info/1174938846/34.

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Books on the topic "Brain – Aging"

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Whalley, Lawrence J. The aging brain. New York, NY: Columbia University Press, 2001.

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Gaitz, Charles M., ed. Aging and the Brain. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4684-8503-5.

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D, Terry Robert, and Fondation Princesse Liliane, eds. Aging and the brain. New York: Raven Press, 1988.

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William, Jagust, and D'Esposito Mark, eds. Imaging the aging brain. New York: Oxford University Press, 2009.

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de Vellis, Jean. Neuroglia in the Aging Brain. New Jersey: Humana Press, 2001. http://dx.doi.org/10.1385/1592591051.

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Thakur, Mahendra K., and Suresh I. S. Rattan, eds. Brain Aging and Therapeutic Interventions. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-5237-5.

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Guido, Filogamo, and Conference on Recent Advances in Neurobiology : Plasticity and Regeneration (1995 : Aosta, Italy), eds. Brain plasticity: Development and aging. New York: Plenum Press, 1997.

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Zhang, Zhanjun, ed. Cognitive Aging and Brain Health. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1627-6.

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J, De Leon Mony, Snider Donald A, Federoff Howard, and New York Academy of Sciences, eds. Imaging and the aging brain. Boston: Blackwell Pub. on behalf of the New York Academy of Sciences, 2007.

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1945-, Wang E., and Snyder D. Stephen, eds. Handbook of the aging brain. San Diego: Academic Press, 1998.

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Book chapters on the topic "Brain – Aging"

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Taki, Yasuyuki. "Brain Aging Using Large Brain MRI Database." In Aging Mechanisms, 291–302. Tokyo: Springer Japan, 2015. http://dx.doi.org/10.1007/978-4-431-55763-0_17.

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Weis, Serge, Michael Sonnberger, Andreas Dunzinger, Eva Voglmayr, Martin Aichholzer, Raimund Kleiser, and Peter Strasser. "Normal Aging Brain." In Imaging Brain Diseases, 871–95. Vienna: Springer Vienna, 2019. http://dx.doi.org/10.1007/978-3-7091-1544-2_31.

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Cutler, Neal R. "The Aging Brain." In Drug Studies in the Elderly, 151–64. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4684-1253-6_8.

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La Rue, Asenath. "The Aging Brain." In Critical Issues in Neuropsychology, 25–46. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4757-9119-8_2.

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Baloh, Robert W. "The Aging Brain." In Exercise and the Brain, 109–28. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-13924-6_6.

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Magnoni, M. S., S. Govoni, F. Battaini, and M. Trabucchi. "The Aging Brain." In Cell to Cell Signals in Plants and Animals, 243–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-76470-7_17.

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Kern, M. J. "Brain Aging in Insects." In Insect Aging, 90–105. Berlin, Heidelberg: Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/978-3-642-70853-4_7.

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Gajdusek, D. Carleton, and C. Joseph Gibbs. "Brain Amyloidoses." In Biomedical Advances in Aging, 3–24. Boston, MA: Springer US, 1990. http://dx.doi.org/10.1007/978-1-4613-0513-2_1.

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Cohadon, F., and P. Desbordes. "Brain Edema, Brain Water, and Aging." In Brain Edema, 331–35. Berlin, Heidelberg: Springer Berlin Heidelberg, 1985. http://dx.doi.org/10.1007/978-3-642-70696-7_51.

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Morović, Sandra, and Vida Demarin. "Arterial Stiffness and Aging." In Mind and Brain, 129–35. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38606-1_11.

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Conference papers on the topic "Brain – Aging"

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GANGULI, MARY. "BRAIN AGING: THREATS AND OPPORTUNITIES." In Proceedings of the 45th Session of the International Seminars on Nuclear War and Planetary Emergencies. WORLD SCIENTIFIC, 2013. http://dx.doi.org/10.1142/9789814531788_0034.

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Lindenberger, Ulman. "Human Cognitive Aging: Maintenance Versus Dedifferentiation." In 2020 8th International Winter Conference on Brain-Computer Interface (BCI). IEEE, 2020. http://dx.doi.org/10.1109/bci48061.2020.9061660.

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Klinger-König, J., S. Frenzel, K. Wittfeld, S. Van der Auwera, G. Homuth, A. Hannemann, R. Bülow, H. Völzke, and HJ Grabe. "Cortisol, aging and the influence on brain age." In Abstracts of the 2nd Symposium of the Arbeitsgemeinschaft für Neuropsychopharmakologie und Pharmakopsychiatrie (AGNP) and Deutsche Gesellschaft für Biologische Psychiatrie (DGBP). Georg Thieme Verlag KG, 2020. http://dx.doi.org/10.1055/s-0039-3403001.

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FUKUDA, HIROSHI, YASUYUKI TAKI, KAI WU, KAZUNORI SATO, RYOI GOTO, KENTARO INOUE, KEN OKADA, and RYUTA KAWASHIMA. "DEVELOPMENT AND AGING OF THE HUMAN BRAIN STUDIED WITH BRAIN MAGNETIC RESONANCE IMAGE." In Proceedings of the Tohoku University Global Centre of Excellence Programme. IMPERIAL COLLEGE PRESS, 2012. http://dx.doi.org/10.1142/9781848169067_0022.

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Alam, Saadia Binte, Ryosuke Nakano, Naotake Kamiura, and Syoji Kobashi. "Morphological changes of aging brain structure in MRI analysis." In 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Advanced Intelligent Systems (ISIS). IEEE, 2014. http://dx.doi.org/10.1109/scis-isis.2014.7044901.

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Cai, DaXuan, XuFeng Yao, Gan Huang, ZhiQiang Wang, Ping Li, and Gang Huang. "Evaluation of human brain aging via diffusion structural characteristics." In 2017 4th International Conference on Systems and Informatics (ICSAI). IEEE, 2017. http://dx.doi.org/10.1109/icsai.2017.8248469.

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Sidhu, Abhijot S., Talal H. Shahid, Kauê T. N. Duarte, Rachel J. Sharkey, Cheryl R. McCreary, Bradley G. Goodyear, and Richard Frayne. "Default Mode Network Segregation Decreases in Healthy Brain Aging." In 2023 19th International Symposium on Medical Information Processing and Analysis (SIPAIM). IEEE, 2023. http://dx.doi.org/10.1109/sipaim56729.2023.10373545.

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Lóss, Juliana da Conceição Sampaio, Cristina de Fátima de Oliveira Brum Augusto de Souza, and Rosalee Santos Crespo Istoe. "Neurosciences and aging: determinants of healthy aging." In XIII Congresso Paulista de Neurologia. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1516-3180.102.

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Introduction: Neuroscience is an area of knowledge that has been an important ally in the study, prevention and understanding of brain mechanisms and their influence on neurodegenerative diseases. In this tuning fork, the neuroscience of aging is concerned with studying important aspects in the life of the elderly, so that it becomes valuable to study the determinants of healthy aging. The present study aims to understand the aspects that involve healthy aging and how neuroscience can beneficially influence the aging process. Method: This research is a bibliographic review, of a qualitative nature, where the analysis of articles and authors was sought in the Scielo, Pubmed, Redalic databases. The study is justified because population aging is a reality where there is a forecast that, in 2025, Brazil will be the sixth country in the world in population of people over 60 years of age. Results: Through this study it was possible to understand that the determinants of health in aging are related to important factors such as the presence of diabetes, high blood pressure, the practice of regular physical activities, mental illness, healthy lifestyle, social interaction, leisure, and volunteer work. Conclusion: Neuroscience demonstrates relevant advances, as it considers the brain’s ability to restructure, recover damaged parts, develop and create new connections in aging. Knowing these factors can mean a long-term and quality- of-life future for the elderly with the prevention of diseases present in this phase of life.
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Borowski, Bret, Clifford R. Jack, Michael W. Weiner, Paul M. Thompson, Artemis Zavaliangos-Petropulu, Talia M. Nir, Sophia I. Thomopoulos, Neda Jahanshad, Robert I. Reid, and Matthew A. Bernstein. "Ranking diffusion tensor measures of brain aging and Alzheimer’s disease." In 14th International Symposium on Medical Information Processing and Analysis, edited by Eduardo Romero, Natasha Lepore, and Jorge Brieva. SPIE, 2018. http://dx.doi.org/10.1117/12.2506694.

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Samadani, Ali-Akbar, and Z. Moussavi. "The effect of aging on human brain spatial processing performance." In 2012 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2012. http://dx.doi.org/10.1109/embc.2012.6347548.

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Reports on the topic "Brain – Aging"

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Wisniewski, Thomas. Characterization of the Pathological and Biochemical Markers that Correlate to the Clinical Features of Autism: The Neuropathological Markers of Abnormal Brain Development and Aging in Autism. Fort Belvoir, VA: Defense Technical Information Center, October 2010. http://dx.doi.org/10.21236/ada540024.

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Debunking Myths About the Aging Brain: Infographic. Global Council on Brain Health, July 2017. http://dx.doi.org/10.26419/pia.00001.003.

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Debunking Myths About the Aging Brain: Infographic [Chinese]. Global Council on Brain Health, July 2017. http://dx.doi.org/10.26419/pia.00001.011.

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Debunking Myths About the Aging Brain: Infographic [Arabic]. Global Council on Brain Health, July 2017. http://dx.doi.org/10.26419/pia.00001.012.

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Healthy Aging Requires You to Challenge Your Brain: Infographic. Global Council on Brain Health, July 2017. http://dx.doi.org/10.26419/pia.00001.002.

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Healthy Aging Requires You to Challenge Your Brain: Infographic [Chinese]. Global Council on Brain Health, July 2017. http://dx.doi.org/10.26419/pia.00001.007.

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Healthy Aging Requires You to Challenge Your Brain: Infographic [Arabic]. Global Council on Brain Health, July 2017. http://dx.doi.org/10.26419/pia.00001.008.

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Sleep is Vital to the Aging Brain, Including Cognitive Function: Infographic. Global Council on Brain Health, January 2017. http://dx.doi.org/10.26419/pia.00014.002.

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Sleep is Vital to the Aging Brain, Including Cognitive Function: Infographic [Chinese]. Global Council on Brain Health, January 2017. http://dx.doi.org/10.26419/pia.00014.005.

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Sleep is Vital to the Aging Brain, Including Cognitive Function: Infographic [Arabic]. Global Council on Brain Health, January 2017. http://dx.doi.org/10.26419/pia.00014.006.

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