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Brain reserve

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Brain reserve may be defined as the brain's resilience; that is, the ability of the brain to cope with damage caused by traumatic injuries, cerebrovascular accidents, or neurodegenerative diseases (NDs). It is largely determined by neuroanatomical and neurophysiological properties such as brain volume, cerebral metabolism[1], lesion loads[2] [3] and patterns of structural connectivity[4]. These properties are subjected to much individual variability[5], entailing differential functional and behavioural outcomes for a given neuropathology. Indeed, people with high brain reserve are thought to have a lower probability of experiencing functional impairment following brain insult.

Brain Reserve Capacity

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Brain reserve capacity (BRC) is the extent to which one’s brain can maintain its functions despite damage. In other words, it is the amount of brain reserve available to one’s brain. Satz (1993)[6] introduced this construct in the frame of the threshold model of brain reserve. According to this model, BRC is determined by structural and functional parameters such as brain size and total synapse count. These parameters moderate the outcomes of neuropathology, containing its effects on cognition, affection and behaviour. However, their capacity as moderators is limited: once brain reserve is depleted to a threshold value, clinical signs become observable.[6]

This model may account for individual differences in the clinical manifestations of neuropathology. Indeed, two patients with different BRCs may experience different degrees of severity of the same pathology, as the latter may deplete brain reserve above threshold in a patient, but not in another.[6] Thus, the pathology will have more clinical manifestations in the patient with lower BRC, and less clinical manifestations in the one with higher BRC. It follows that brain reserve is a resilience factor for brain insults such as traumatic injuries, cerebrovascular accidents and neurodegenerative diseases, as well as for aging[7].

Studies on Alzheimer’s populations provide examples of brain reserve as a predictor of the clinical manifestations of NDs. The first – and perhaps most famous – example dates back to 1988, when Katzman and colleagues[8] reported the presence of biomarkers of Alzheimer’s disease in the post-mortem brain of volunteers that showed no signs of pathology during life. Interestingly, these brains weighed above average and included almost double the number of large neocortical pyramidal neurons as compared to the brains of volunteers showing signs of Alzheimer’s disease during late stages of their lives. Subsequent studies replicated this result, finding an association between high pre-morbid brain volume and delayed onset of clinical manifestations of pathology[9][10].

Brain Reserve versus Cognitive Reserve

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As described above, the Brain Reserve Hypothesis (BRH) ascribes different levels of resilience to physical variables such as brain volume and synapse count. To this extent, the BRH is a passive hypothesis[11]. Indeed, it explains resilience in terms of pre-existing physical factors, implying that the outcome of brain insult is entirely pre-determined when brain damage kicks in[12].

On the other hand, the Cognitive Reserve Hypothesis (CRH) suggests that the brain actively attempts to cope with damage by using known cognitive processes or enlisting compensatory strategies[11]. It considers active remediation, implying that the outcomes of brain insult may be influenced by post-traumatic experiences. Nonetheless, the CRH does not rule out the contribution of brain reserve. Indeed, cognitive functioning entails the recruitment of functional brain networks, implying a role for brain reserve. To this extent, cognitive and brain reserve are complementary, with the former describing the resilience of the mind (functional) and the latter describing the resilience of the brain (structural)[11]. The two cannot be thought of as distinct and independent. Indeed, cognitive processes are clearly implemented at a neural level, so that cognitive reserve needs brain reserve and brain reserve leads to cognitive reserve[13].

Brain plasticity has been proposed as a reserve mechanism at both the neural and cognitive levels[12]. Indeed, the structural and functional brain changes promoted by plasticity may contribute to resilience by creating new structural and functional connections when the old ones are damaged by pathology.

Main indexes of brain reserve

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Measurement is a major concern in brain reserve research. Indeed, the brain reserve construct is multidimensional and considering parameters that can only be measured post-mortem or indirectly. New lines of evidence [14][15][16][17] suggest that advanced brain networks analysis could provide more accurate measures of the relation between structural and functional brain properties as compared to traditionally measured variables such as whole brain volume or cerebral metabolism.

  • Brain size

A 1997 study found that Alzheimer's disease affecting large brains did not entail a clinically relevant dementia. Another study reported head circumference to be independently associated with a reduced risk of Alzheimer's disease. However, this result failed replication in several occasions. This is thought to be because head circumference and other approximations are indirect measures[10].

  • Number of neuronal connections

The number of synapses is a measure of the computational power of a brain, i.e. the number and complexity of the operations it can carry out. It follows that a brain with a high synapse count is less likely to fall into neurocognitive degeneration than a brain with a low synapse count (cf. threshold model of brain reserve[6])[18].

  • Cerebral Metabolism

Cerebral metabolism is linked to the consumption of resources and blood flow associated with brain activity[19]. As the state of health of cells varies according to the rate and type of metabolic processes, metabolism affects brain reserve by determining whether - and to what extent - nervous cells proliferate.

Genetic component of cognitive reserve

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Evidence from a twin study [20] indicates a genetic contribution to cognitive functions. Heritability estimates have been found to be high for general cognitive functions but low for memory itself[20]. Adjusting for the effects of education, 79% of executive function can be explained by genetic contribution[21]. Finally, a study combining twin and adoption studies found all cognitive functions to be heritable. Speed of processing had the highest heritability in this particular study[22].

Brain reserve and education

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Notably, brain reserve is associated with the level of education, so that people with higher schooling cope better with brain damage. In fact, functional imaging studies (18F-FDG-PET imaging) show that patients with Alzheimer's disease who received higher education show less severe pathology, controlling for disease severity[23]. Therefore, schooling seems to provide brain reserve against neurodegeneration.

On the structural side, education has been found to promote synaptic growth, i.e. increase brain reserve[24]. On the functional side, it increases cognitive reserve through the development of a variety of cognitive strategies[25][26].

See also

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References

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  1. ^ Cohen, A. D.; Price, J. C.; Weissfeld, L. A.; James, J.; Rosario, B. L.; Bi, W.; Nebes, R. D.; Saxton, J. A.; Snitz, B. E. (2009-11-25). "Basal Cerebral Metabolism May Modulate the Cognitive Effects of A in Mild Cognitive Impairment: An Example of Brain Reserve". Journal of Neuroscience. 29 (47): 14770–14778. doi:10.1523/jneurosci.3669-09.2009. ISSN 0270-6474. PMC 2810461. PMID 19940172.
  2. ^ Cader, S.; Johansen-Berg, H.; Wylezinska, M.; Palace, J.; Behrens, T.E.; Smith, S.; Matthews, P.M. (2007). "Discordant white matter N-acetylasparate and diffusion MRI measures suggest that chronic metabolic dysfunction contributes to axonal pathology in multiple sclerosis". NeuroImage. 36 (1): 19–27. doi:10.1016/j.neuroimage.2007.02.036. ISSN 1053-8119. PMID 17398118. S2CID 13953754.
  3. ^ Cader, Sarah; Cifelli, Alberto; Abu-Omar, Yasir; Palace, Jacqueline; Matthews, Paul M. (2005-10-26). "Reduced brain functional reserve and altered functional connectivity in patients with multiple sclerosis". Brain. 129 (2): 527–537. doi:10.1093/brain/awh670. ISSN 1460-2156. PMID 16251214.
  4. ^ Alstott, Jeffrey; Breakspear, Michael; Hagmann, Patric; Cammoun, Leila; Sporns, Olaf (2009-06-12). "Modeling the Impact of Lesions in the Human Brain". PLOS Computational Biology. 5 (6): e1000408. doi:10.1371/journal.pcbi.1000408. ISSN 1553-7358. PMC 2688028. PMID 19521503.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  5. ^ Fisher, Aaron J.; Medaglia, John D.; Jeronimus, Bertus F. (2018-06-18). "Lack of group-to-individual generalizability is a threat to human subjects research". Proceedings of the National Academy of Sciences. 115 (27): E6106–E6115. doi:10.1073/pnas.1711978115. ISSN 0027-8424. PMC 6142277. PMID 29915059.
  6. ^ a b c d Satz, Paul (1993). "Brain reserve capacity on symptom onset after brain injury: A formulation and review of evidence for threshold theory". Neuropsychology. 7 (3): 273–295. doi:10.1037//0894-4105.7.3.273. ISSN 0894-4105.
  7. ^ STERN, YAAKOV (2002). "What is cognitive reserve? Theory and research application of the reserve concept". Journal of the International Neuropsychological Society. 8 (3): 448–460. doi:10.1017/s1355617702813248. ISSN 1355-6177. PMID 11939702. S2CID 9902333.
  8. ^ Katzman, Robert; Terry, Robert; DeTeresa, Richard; Brown, Theodore; Davies, Peter; Fuld, Paula; Renbing, Xiong; Peck, Arthur (1988). "Clinical, pathological, and neurochemical changes in dementia: A subgroup with preserved mental status and numerous neocortical plaques". Annals of Neurology. 23 (2): 138–144. doi:10.1002/ana.410230206. ISSN 0364-5134. PMID 2897823. S2CID 31389744.
  9. ^ Schofield, Peter W. (1995-01-01). "The Age at Onset of Alzheimer's Disease and an Intracranial Area Measurement". Archives of Neurology. 52 (1): 95–98. doi:10.1001/archneur.1995.00540250103019. ISSN 0003-9942. PMID 7826282.
  10. ^ a b Mori, E.; Hirono, N.; Yamashita, H.; Imamura, T.; Ikejiri, Y.; Ikeda, M.; Kitagaki, H.; Shimomura, T.; Yoneda, Y. (1997). "Premorbid brain size as a determinant of reserve capacity against intellectual decline in Alzheimer's disease". American Journal of Psychiatry. 154 (1): 18–24. doi:10.1176/ajp.154.1.18. ISSN 0002-953X. PMID 8988953.
  11. ^ a b c Nucci, Massimo; Mapelli, Daniela; Mondini, Sara (2011). "Cognitive Reserve Index Questionnaire". PsycTESTS Dataset. doi:10.1037/t53917-000. Retrieved 2019-05-08.
  12. ^ a b Fratiglioni, Laura; Wang, Hui-Xin (2007-08-24). "Brain Reserve Hypothesis in Dementia". Journal of Alzheimer's Disease. 12 (1): 11–22. doi:10.3233/jad-2007-12103. ISSN 1875-8908. PMID 17851191.
  13. ^ Stern, Yaakov (2009). "Cognitive reserve☆". Neuropsychologia. 47 (10): 2015–2028. doi:10.1016/j.neuropsychologia.2009.03.004. ISSN 0028-3932. PMC 2739591. PMID 19467352.
  14. ^ Honey, C. J.; Sporns, O.; Cammoun, L.; Gigandet, X.; Thiran, J. P.; Meuli, R.; Hagmann, P. (2009-02-02). "Predicting human resting-state functional connectivity from structural connectivity". Proceedings of the National Academy of Sciences. 106 (6): 2035–2040. doi:10.1073/pnas.0811168106. ISSN 0027-8424. PMC 2634800. PMID 19188601.
  15. ^ Honey, Christopher J.; Thivierge, Jean-Philippe; Sporns, Olaf (2010). "Can structure predict function in the human brain?". NeuroImage. 52 (3): 766–776. doi:10.1016/j.neuroimage.2010.01.071. ISSN 1053-8119. PMID 20116438. S2CID 11324632.
  16. ^ Medaglia, John D.; Lynall, Mary-Ellen; Bassett, Danielle S. (2015). "Cognitive Network Neuroscience". Journal of Cognitive Neuroscience. 27 (8): 1471–1491. doi:10.1162/jocn_a_00810. ISSN 0898-929X. PMC 4854276. PMID 25803596.
  17. ^ Wen, Wei; He, Yong; Sachdev, Perminder (2011). "Structural brain networks and neuropsychiatric disorders". Current Opinion in Psychiatry. 24 (3): 219–225. doi:10.1097/yco.0b013e32834591f8. ISSN 0951-7367. PMID 21430538. S2CID 34520674.
  18. ^ Terry, Robert D.; Masliah, Eliezer; Salmon, David P.; Butters, Nelson; DeTeresa, Richard; Hill, Robert; Hansen, Lawrence A.; Katzman, Robert (1991). "Physical basis of cognitive alterations in Alzheimer's disease: Synapse loss is the major correlate of cognitive impairment". Annals of Neurology. 30 (4): 572–580. doi:10.1002/ana.410300410. ISSN 0364-5134. PMID 1789684. S2CID 38412183.
  19. ^ "Neurovascular coupling". Scholarpedia.
  20. ^ a b Ando, Juko; Ono, Yutaka; Wright, Margaret J. (2001). "Genetic structure of spatial and verbal working memory". Behavior Genetics. 31 (6): 615–624. doi:10.1023/a:1013353613591. ISSN 0001-8244. PMID 11838538. S2CID 39136550.
  21. ^ Swan, G. E.; Carmelli, D. (2002-03-01). "Evidence for Genetic Mediation of Executive Control: A Study of Aging Male Twins". The Journals of Gerontology Series B: Psychological Sciences and Social Sciences. 57 (2): P133–P143. doi:10.1093/geronb/57.2.p133. ISSN 1079-5014. PMID 11867661.
  22. ^ Plomin, R.; Pedersen, N. L.; Lichtenstein, P.; McClearn, G. E. (1994). "Variability and stability in cognitive abilities are largely genetic later in life". Behavior Genetics. 24 (3): 207–215. doi:10.1007/bf01067188. ISSN 0001-8244. PMID 7945151. S2CID 6503298.
  23. ^ Perneczky, R (2006-05-18). "Schooling mediates brain reserve in Alzheimer's disease: findings of fluoro-deoxy-glucose-positron emission tomography". Journal of Neurology, Neurosurgery & Psychiatry. 77 (9): 1060–1063. doi:10.1136/jnnp.2006.094714. ISSN 0022-3050. PMC 2077756. PMID 16709580.
  24. ^ Katzman, R. (1993-01-01). "Education and the prevalence of dementia and Alzheimer's disease". Neurology. 43 (1, Part 1): 13–20. doi:10.1212/wnl.43.1_part_1.13. ISSN 0028-3878. PMID 8423876. S2CID 42469859.
  25. ^ STERN, YAAKOV (2002). "What is cognitive reserve? Theory and research application of the reserve concept". Journal of the International Neuropsychological Society. 8 (3): 448–460. doi:10.1017/s1355617702813248. ISSN 1355-6177. PMID 11939702. S2CID 9902333.
  26. ^ Manly, Jennifer J.; Byrd, Desiree; Touradji, Pegah; Sanchez, Danurys; Stern, Yaakov (2004). "Literacy and cognitive change among ethnically diverse elders". International Journal of Psychology. 39 (1): 47–60. doi:10.1080/00207590344000286. ISSN 0020-7594.
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