Neural Impact of Cognitive Mindset in Older Adults Using Statistical and Machine Learning Algorithms
Authors: Raja Venkat Ram V, M. Raghavender Sharma, Archana Patil, D.Gopinath, Moh Riyazuddin, M.V.Ramana Murthy
DOI: 10.37326/ajsev8.12/2068
Page No: 102-114
Abstract
The physical and mental capacities of healthy older persons frequently deteriorate with age. Individual differences are observed in the degree of these behavioral and neurocognitive impairments. A reserve, or defense mechanism, that strengthens the brain's resistance to agerelated damage, may be developed by intellectually demanding activities and lifelong experiences, according to the Neurocognitive Hypothesis in cognitive neuroscience. The differences in the degree of visible brain damage and its functional consequences have been well explained by this statistical model. In summary, the statistical modelling presented here illustrates how neurocognitive reserve affects age- and individual-related changes in brain architecture, neural networks, and neural activation patterns. The modelling is based on behavioral and neuroimaging findings. Furthermore, we report preliminary results from structural and functional neuroimaging that lend credence to the idea that neurocognitive reserve functions as a neural resource, reducing the impact of cognitive decline resulting from both the aging process and neurological and psychiatric diseases. In summary, the neurocognitive model provides a dynamic view of resilience and our ability to adjust to brain illness and damage as we age, as predicted by statistical models, even though the processes underpinning the model are still not fully understood. Through predictive modelling, future studies should try to identify the unique elements that support neurocognitive reserve's positive benefits in delaying rapid cognitive decline and fostering psychological resilience in old age.
