Bioimpedance modeling to monitor astrocytic response to chronically implanted electrodes.

The widespread adoption of neural prosthetic devices is currently hindered by our inability to reliably record neural signals from chronically implanted electrodes. The extent to which the local tissue response to implanted electrodes influences recording failure is not well understood. To investigate this phenomenon, impedance spectroscopy has shown promise for use as a non-invasive tool to estimate the local tissue response to microelectrodes. Here, we model impedance spectra from chronically implanted rats using the well-established Cole model, and perform a correlation analysis of modeled parameters with histological markers of astroglial scar, including glial fibrillary acid protein (GFAP) and 4',6-diamidino-2- phenylindole (DAPI). Correlations between modeled parameters and GFAP were significant for three parameters studied: Py value, R(o) and |Z|(1 kHz), and in all cases were confined to the first 100 microm from the interface. Py value was the only parameter also correlated with DAPI in the first 100 microm. Our experimental results, along with computer simulations, suggest that astrocytes are a predominant cellular player affecting electrical impedance spectra. The results also suggest that the largest contribution from reactive astrocytes on impedance spectra occurs in the first 100 microm from the interface, where electrodes are most likely to record electrical signals. These results form the basis for future approaches where impedance spectroscopy can be used to evaluate neural implants, evaluate strategies to minimize scar and potentially develop closed-loop prosthetic devices.

Duke Scholars

Author Ravi Venkat Bellamkonda Biomedical Engineering