Forecasting of Cognitive Neurological Aspects Using Machine Learning Ensemble Algorithms

Raja Venkat Ram V, M. Raghavender Sharma, D. Gopinath

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 age - related 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.

Keywords: Cognitive Neuroimaging, Resilience, Correlation Studies, Ensemble algorithms

How to Cite?: Raja Venkat Ram V, M. Raghavender Sharma, D. Gopinath, "Forecasting of Cognitive Neurological Aspects Using Machine Learning Ensemble Algorithms", Volume 14 Issue 4, April 2025, International Journal of Science and Research (IJSR), Pages: 588-595, https://www.ijsr.net/getabstract.php?paperid=SR25312153537, DOI: https://dx.doi.org/10.21275/SR25312153537