Characteristics of electrode impedance and stimulation efficacy of a chronic cortical implant using novel annulus electrodes in rat motor cortex

Chun Wang, Emma Kate Brunton, Saman Haghgooie, Kahli Cassells, Arthur Lowery, Ramesh Rajan

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27 Citations (Scopus)


Objective. Cortical neural prostheses with implanted electrode arrays have been used to restore compromised brain functions but concerns remain regarding their long-term stability and functional performance. Approach. Here we report changes in electrode impedance and stimulation thresholds for a custom-designed electrode array implanted in rat motor cortex for up to three months. Main Results. The array comprises four 2000 microm long electrodes with a large annular stimulating surface (7860-15700 microm(2)) displaced from the penetrating insulated tip. Compared to pre-implantation in vitro values there were three phases of impedance change: (1) an immediate large increase of impedance by an average of two-fold on implantation; (2) a period of continued impedance increase, albeit with considerable variability, which reached a peak at approximately four weeks post-implantation and remained high over the next two weeks; (3) finally, a period of 5-6 weeks when impedance stabilized at levels close to those seen immediately post-implantation. Impedance could often be temporarily decreased by applying brief trains of current stimulation, used to evoke motor output. The stimulation threshold to induce observable motor behaviour was generally between 75-100 microA, with charge density varying from 48-128 microC cm(-2), consistent with the lower current density generated by electrodes with larger stimulating surface area. No systematic change in thresholds occurred over time, suggesting that device functionality was not compromised by the factors that caused changes in electrode impedance. Significance. The present results provide support for the use of annulus electrodes in future applications in cortical neural prostheses.
Original languageEnglish
Pages (from-to)1 - 19
Number of pages19
JournalJournal of Neural Engineering
Issue number4 (Art. No.: 046010)
Publication statusPublished - 2013

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