The Longevity of Neural Interfaces-Mechanical Oscillation of Thin Film Metal-Based Neural Electrodes Determine Stability During Electrical Stimulation

The success of bioelectronics medicine with neural implants inevitably depends on the longevity of neural interfaces where a full understanding of the associated risks serves as the first step, to begin with. Until now, failure of neural electrodes is primarily explained by extreme electrochemical reactions, whereas no direct link between electrical stimulation and mechanical deformation of microelectrodes can be proved. The research provides new quantitative evidence of electrically induced mechanical vibrations in thin film neural interfaces. This study investigates the dynamic changes in intrinsic mechanical stress in clinically used neural electrodes under electrical stimulation. Via live imaging of the electrode plane, the deformation and progressive adhesion loss of the thin film during stimulation is for the first time approved. The results reveal nano-oscillations in the interfaces under alternating current. This hints at a direct link between electrochemical charge transfer and mechanical stability. Considering neural interfaces as resonating actuators serves as a key to assessing the stability of neural interfaces and a valuable input to a longstanding question on the associated failure mechanisms of thin film microelectrodes. It is believed, that the outcome of this work may significantly contribute to improving the future design of thin film neural interfaces and better conditioning them for life-long reliability. A novel approach presents neural thin film interfaces as resonating systems. Direct measurements prove mechanical-electrical nano-vibrations of thin film metallization in response to electrical current during stimulation. The correlation between electrochemical reactions and mechanical deformation unveils insights into potential fatigue and failure mechanisms. This opens a new window in research for future electrode designs and low-vibration stimulation parameters.image