Stab injury and device implantation within the brain results in inversely multiphasic neuroinflammatory and neurodegenerative responses

An estimated 25 million people in the US alone rely on implanted medical devices, similar to 2.5 million implanted within the nervous system. Even though many devices perform adequately for years, the host response to medical devices often severely limits tissue integration and long-term performance. This host response is believed to be particularly limiting in the case of intracortical microelectrodes, where it has been shown that glial cell encapsulation and localized neuronal cell loss accompany intracortical microelectrode implantation. Since neuronal ensembles must be within similar to 50 mu m of the electrode to obtain neuronal spikes and local field potentials, developing a better understanding of the molecular and cellular environment at the device-tissue interface has been the subject of significant research. Unfortunately, immunohistochemical studies of scar maturation in correlation to device function have been inconclusive. Therefore, here we present a detailed quantitative study of the cellular events and the stability of the blood-brain barrier (BBB) following intracortical microelectrode implantation and cortical stab injury in a chronic survival model. We found two distinctly inverse multiphasic profiles for neuronal survival in device-implanted tissue compared to stab-injured animals. For chronically implanted animals, we observed a biphasic paradigm between blood-derived/trauma-induced and CNS-derived inflammatory markers driving neurodegeneration at the interface. In contrast, stab injured animals demonstrated a CNS-mediated neurodegenerative environment. Collectively these data provide valuable insight to the possibility of multiple roles of chronic neuroinflammatory events on BBB disruption and localized neurodegeneration, while also suggesting the importance to consider multiphasic neuroinflammatory kinetics in the design of therapeutic strategies for stabilizing neural interfaces.