Integration of Nanomaterials and DBS to Improve Basal Ganglia Oscillations Using Delayed Van der Pol Model

Abstract

Basal ganglia play a crucial role in motor control and the challenges posed by pathological oscillations, especially in Parkinsons disease. Although deep brain stimulation (DBS) is effective in attenuating pathological frequencies, it often leads to side effects. This study presents a comprehensive framework for understanding and improving neural oscillation dynamics by integrating nanomaterials with DBS. Nanomaterials with their controllable frequencies through length, width, and structure could stabilize oscillations and maintain normal neural frequencies. This study introduces three mathematical models: the DBS model, the nanomaterials model, and a combined model of both, which use the Van der Pol delay model to demonstrate how the periodic force and nanomaterials collaborate to stabilize brain activity. Numerical simulations indicate that DBS by itself lowers harmful frequencies but might make the motor cortex unstable because it increases the strength of signals. In contrast, the nanomaterial models reduce the amplitude and activate the motor cortex. The combination of DBS and nanomaterials significantly improves stability, reduces pathological oscillations, and decreases hyperactivity. The use of nanomaterials must be carefully monitored to ensure that they do not suppress normal neural activity, highlighting the need for experimental validation. This study provides a promising direction for the development of personalized therapeutic technologies that balance the suppression of pathological activity with the preservation of normal neural function.