A neural network integrated mathematical model to analyze the impact of nutritional status on cognitive development of child.

Cognitive development is a crucial developmental aspect of children. It is a concise field of study in psychology and neuroscience that focuses on various developmental aspects of the brain. Among all other factors, nutritional status is believed to play a very important role in cognitive development. The purpose of this work is to analyze the impacts of different nutritional status levels on the child's cognitive development. This work designs a model that uses a neural network and differential equations. The neural network is applied on a dataset called "Child Birth Weight Dataset" available at IEEE Dataport ( http://dx.doi.org/10.21227/dvd4-3232) for finding the nutritional status of a child. The different levels of nutritional status, such as low-nutritional status, normal-nutritional status, and over-nutritional status are integrated with the formulated differential equations. The model is computationally simulated considering four different sets of parameter values that represent four different perspectives such as 'only positive', 'only negative', 'mix and unequal weight', and 'mix and equal weight' of the influencing factors. The experimental results show that normal-nutritional status is the best nutritional status for cognitive development. However, the best cognitive development happens when all other influencing factors like environmental effects, socioeconomic status, heredity, learning opportunities, and use of experiences are given equal importance. The results also depict that the low- and over-nutritional status cannot restrict cognitive development for a long time. After a certain period, the development gets triggered and it happens. It may be slow and not up to the mark of the development under normal-nutritional status, but it happens. Simply it can be said that nutritional status alone does not have control over the cognitive development of a child. Along with nutritional status, other influencing factors are important too.