Penetrating intracortical electrode arrays that record brain activity longitudinally are powerful tools for basic neuroscience research and emerging clinical applications. However, regardless of the technology used, signals recorded by these electrodes degrade over time. The failure mechanisms of these electrodes are understood to be a complex combination of the biological reactive tissue response and material failure of the device over time. While mechanical mismatch between the brain tissue and implanted neural electrodes have been studied as a source of chronic inflammation and performance degradation, the electrode failure caused by mechanical mismatch between different material properties and different structural components within a device have remained poorly characterized. Using Finite Element Model (FEM) we simulate the mechanical strain on a planar silicon electrode. The results presented here demonstrate that mechanical mismatch between iridium and silicon leads to concentrated strain along the border of the two materials. This strain is further focused on small protrusions such as the electrical traces in planar silicon electrodes. These findings are confirmed with chronic in vivo data (133–189 days) in mice by correlating a combination of single-unit electrophysiology, evoked multi-unit recordings, electrochemical impedance spectroscopy, and scanning electron microscopy from traces and electrode sites with our modeling data. Several modes of mechanical failure of chronically implanted planar silicon electrodes are found that result in degradation and/or loss of recording. These findings highlight the importance of strains and material properties of various subcomponents within an electrode array.
Background
Intracortical electrode arrays that can record extracellular action potentials from small, targeted groups of neurons are critical for basic neuroscience research and emerging clinical applications. In general, these electrode devices suffer from reliability and variability issues, which have led to comparative studies of existing and emerging electrode designs to optimize performance. Comparisons of different chronic recording devices have been limited to single-unit (SU) activity and employed a bulk averaging approach treating brain architecture as homogeneous with respect to electrode distribution.
New Method
In this study, we optimize the methods and parameters to quantify evoked multi-unit (MU) and local field potential (LFP) recordings in 8 mice visual cortices.
Results
These findings quantify the large recording differences stemming from anatomical differences in depth and the layer dependent relative changes to SU and MU recording performance over 6-months. For example, performance metrics in Layer V and stratum pyramidale were initially higher than Layer II/III, but decrease more rapidly. On the other hand, Layer II/III maintained recording metrics longer. In addition, chronic changes at the level of layer IV are evaluated using visually evoked current source density.
Comparison with Existing Method(s)
The use of MU and LFP activity for evaluation and tracking biological depth provides a more comprehensive characterization of the electrophysiological performance landscape of microelectrodes.
Conclusions
A more extensive spatial and temporal insight into the chronic electrophysiological performance over time will help uncover the biological and mechanical failure mechanisms of the neural electrodes and direct future research toward the elucidation of design optimization for specific applications.
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