Application of Neural Network's Modeling for Improvement of Children's Reading Brain Performance (A Case Study Assessment)

Overwhelming majority of neurobiologists' research efforts has recently revealed findings about common increasingly sophisticated role adopted by Artificial Neural Networks (ANN s ). This role applied commonly for systematic realistic modeling of interdisciplinary disciplines incorporating neuroscience, education, and cognitive sciences. Accordingly, ANN s Models vary in relation to the nature of assigned brain function to be modeled. For example, as human learning that takes place autonomously according to received stimuli that are realistically simulated through self-organization modeling. This piece of research adopts the conceptual approach of ANN s models inspired by functioning of highly specialized biological neurons in reading brain based on the organization the brain's structures/substructures. Additionally, in accordance with the prevailing concept of individual intrinsic characterized properties of highly specialized neurons, presented models closely correspond to performance of these neurons for developing reading brain in a significant way. More specifically, introduced models concerned with their important role played in carrying out cognitive brain function' outcomes. The cognitive goal for reading brain is to translate that orthographic word-from into a spoken word (phonological word-form). In this context presented work herein, reveals via ANN simulation results: How a set of highly specialized neurons could be dynamically involved in performing development of cognitive reading brain function. More precisely, the objective of adopted simulation approach is to reveal how a group of tiny individual specialized neurons are capable to work cooperatively together in order to produce an intellectual-like behavioral learning to read, that exhibits proper cognitive decoding of orthographic word-form into phonological word-form. Interestingly, obtained results of presented case study (at some elementary school) shown to be in well agreement with obtained ANN simulation results