1) Brief summary:
The article focuses on research that was done regarding the effects of aging of the brain and its relationship with interactions of the brain's network. The researchers believed that there would be a positive correlation between the increased interactions among these brain networks and the healthy aging of cognitive functions. Generative models were used in order to overcome the challenges related to natural changes in the brain related to aging as well as the flexibility of neural activity. The study found that aging does in fact influence the cognitive capacities of adults. As people grow older, the capacity of their mental processes are largely dependent on a variety of factors.
2) Background and perspective:
It is necessary to understand the relationship that this research has with previous analysis that has been done on the cognitive capacity of the mind in regards to aging. The study “Age-Related Decrease Of Functional Connectivity Additional To Gray Matter Atrophy In A Network For Movement Initiation” provides insight into the basic effects that aging can have on the brain. It demonstrates that this can result in an atrophy of physical matter, resulting in a loss of basic cognitive capacity. “Healthy aging is accompanied by a decrease in cognitive and motor capacities” (Hoffstaedter et al. 1). This demonstrates that even a perfectly healthy mind suffers a basic loss in capacity as it ages. For this reason, there is a need to account for this when taking part in future studies. Furthermore, there is a growing amount of data that suggests the relationship between loss of brain tissue during this natural aging process and the mechanical abilities of the brain as well. Evidence suggests that “reduction of gray matter (GM) density and decrease of resting-state functional connectivity (FC)” can result in “deteriorating movement coordination and motor speed with aging” (Hoffstaedter et al. 2). This demonstrates that, despite illness or disease, the mental capacities of an individual during the aging process will diminish in both cognitive capacity and mechanical ability.
The research carried out in “Brain Network Local Interconnectivity Loss In Aging Apoe-4 Allele Carriers” presents further evidence of the connection between aging and loss of cognitive functions. The study looks at the connection between old age and carriers of APOE-4, an allele that is thought to have a significant role in the onset of Alzheimer's disease. The contributing effects of both of these factors are accounted for in the analysis in order to determine whether having the allele in combination with aging actually has an effect on neural brain connectivity. The study indicates that these elements “have been shown to exhibit earlier signs of cognitive decline with aging” (Brown et al. 4). The analysis of the data suggests an strong correlation between these factors. This is important due to the physiological context of the issue and the underlying challenges associated with isolating the specific variables that should be focused on in the future. The study ultimately demonstrated that those that carried the allele “showed a significantly more negative relationship between local interconnectivity and age than noncarriers” (Brown et al. 30). This indicates a strong connection between carriers of the allele and more dramatic losses in cognitive capabilities at old age.
In applying this background to the current study it is evident that a wider perspective can be achieved regarding the capacity of the brain to withstand aging and the underlying biological or genetic factors that can influence this. The analysis of “Extrinsic and Intrinsic Brain Network Connectivity Maintains Cognition across the Lifespan Despite Accelerated Decay of Regional Brain Activation” demonstrates that there can be drastic changes to the “strength of effective connectivity, within and between large scale functional networks” with research suggesting that these factors have ultimately “changed over the healthy adult lifespan” (Tsvetanov et al. 3122). Through analysis of this research it is evident that there is a strong correlation between declining cognitive processes and age that is strongly influenced by the size and level of brain inter-connectivity. The study ultimately concludes that “Effective connectivity was significantly related to the effect of age on cognition” which, demonstrates that mental capacity of older adults can be seen to have “relied more strongly on a good connectivity profile between and within large scale networks” (Tsvetanov et al. 3124). This presents strong foundations for the relationship between mental decline resulting from aging and the interconnectivity of brain synapses.
3) Methods and results:
The research utilizes quantitative methods in order to gather observable and objective data regarding the processes of mental stagnation. This is due to the fact that the researchers need an “iterative process whereby evidence is evaluated” (Rajasekar, Philominathan, and Chinnathambi 9). This was established using a population based sample, which consisted of roughly the same amount of males and females. Through the use of psychological tests that examined brain activity throughout its various areas in order to create a cognitive map that could help to determine both the speed at which these areas were able to process as well as the level of intelligence that they exerted. This was based on the use of generative models, which were able to randomly apply specific perimeters to the problem in order to overcome the limitations of the study. The study used imaging data in order to take a snapshot of these various areas and the level of activity that they indicated was going on at any specific point in time. The participants were first screened in order to normalize the survey so that there could be an accurate measurement of the desired information. The study then employed methods in order to test the basic level of interactivity between these various areas of the brain. They then used a specific form of measurement in order to get an idea of the weight, or size, of each of these areas and its relative importance for normal cognitive functioning. This was able to effectively provide the researchers of a basic idea of the relationship between the connectivity of the brain in these individuals and their ages. The study ultimately resulted in findings that indicate a strong correlation between activity in the brain, neural networks, and aging. This essentially confirms “the importance of these interactions for cognitive function in healthy adults across the lifespan” (Tsvetanov et al. 3122). The use of the specific methodologies of the study indicate the need to separate specific brain functions from one another in order to better understand the relationship of networks in specific areas.
4) Your analysis of the results:
The data that was obtained through the research methods seems to indicate that the author's results were accurate. Through the establishment of a method through which the various areas of the brain could be objectively measured and assessed for cognitive functioning presents an essential element of importance to their conclusions. They were able to overcome the limitations of natural aging and disease through the use of “generative models to dissociate neural from vascular components of the fMRI signal” (Tsvetanov et al. 3125). This allowed the study to gain an understanding of the limitations of the mind in an unbiased fashion and was able to provide the researchers with the basis necessary for further research. This was necessary due to the fact that the brain can “change dynamically and in a context-sensitive fashion” (Friston and Price, 2001). Future research should focus on specific degenerative disorders such as Alzheimer's disease and the level of control that methods are able to utilize in accounting for any associated changes.
Works Cited
Brown, Jesse A., Terashima, Kevin H., Burggren, Alison C., Ercoli, Linda M., Miller, Karen J., Small, Gary W., and Bookheimer, Susan Y. Brain network local interconnectivity loss in aging APOE-4 allele carriers. Proceedings of the National Academy of Sciences, vol. 108 no. 51, 20760-20765. 2011. Print.
Friston, Karl J. and Price, Cathy J. Dynamic Representations And Generative Models Of Brain Function. Brain Research Bulletin, Vol. 54, No. 3, pp. 275–285, 2001. Print.
Hoffstaedter, F., Grefkes, C., Roski, C., Caspers, C., Zilles, K., and Eickhoff, S.B. Age-Related Decrease Of Functional Connectivity Additional To Gray Matter Atrophy In A Network For Movement Initiation. Brain Structure Functions. 2014. Print.
Rajasekar, S., Philominathan, P. and Chinnathambi, V. Research Methodology. Research in Science. 2013. Print.
Tsvetanov, Kamen A, Henson, Richard N.A., Tyler, Lorraine K., Razi, Adeel, Geerligs, Linda, Ham, Timothy E., Rowe, James B. Extrinsic and Intrinsic Brain Network Connectivity Maintains Cognition across the Lifespan Despite Accelerated Decay of Regional Brain Activation. The Journal of Neuroscience, 36(11): 3115–3126. 2016. Print.
