This research work studies the human brain information processing dynamics by transforming the stage model
formulated by Atkinson and Shiffrin into two deterministic mathematical models. This makes it more amenable to
mathematical analysis. The two models are bottom-up processing mathematical model and top-down processing mathematical
model. The bottom-up processing is data driven while the top-down processing is triggered by experience or prior knowledge.
Both analytical and numerical methods are used in the analysis of the models. The existence and stability of equilibrium states
of the models are investigated, and threshold values of certain parameters of the models arising from the investigation were
obtained and interpreted in physical terms. Numerical experiments are also carried out using hypothetical data to further
investigate the effect of certain parameters on the human brain information processing process. The results show that attention,
repetition and rehearsal play significant roles in learning process. Furthermore, repetition and rehearsal is strongly
recommended as an effective way of retaining information. In addition, the instructors should ensure that the students feel
physically and psychologically safe in any environment in order to pay adequate attention.
Shikaa Samuel, Taparki Richard, Ajai John Tyavbee, Aboiyar Terhemen. (2015). A Mathematical Model to Study the Human Brain Information Processing Dynamics. American Journal of Applied Mathematics, 3(5)