Coupled Eulerian–Lagrangian model prediction of neural tissue strain during microelectrode insertion

Implanted neural microelectrodes are an important tool for recording from and stimulating the cerebral cortex. The performance of chronically implanted devices, however, is often hindered by the development of a reactive tissue response. Previous computational models have investigated brain strain from micromotions of neural electrodes after they have been inserted, to investigate design parameters that might minimize triggers to the reactive tissue response. However, these models ignore tissue damage created during device insertion, an important contributing factor to the severity of inflammation. The objective of this study was to evaluate the effect of electrode geometry, insertion speed, and surface friction on brain tissue strain during insertion.