Basic NeuroscienceA cranial window imaging method for monitoring vascular growth around chronically implanted micro-ECoG devices
Introduction
The formation of scar tissue around chronically implanted neural micro-electrode arrays can significantly decrease the quality of the recorded signals, often rendering the devices unusable (Szarowski et al., 2003, Williams et al., 1999, Woolley et al., 2011). This well-known problem has led to a push toward less invasive neural implants, such as electrocorticography (ECoG), and more recently, micro-ECoG (Fig. 1), which sit on top of the cortical surface rather than penetrating into it (Gierthmuehlen et al., 2011, Kitzmiller et al., 2006, Thongpang et al., 2011, Viventi et al., 2011, Wang et al., 2009). These devices are thought to strike a potential balance between the spatial resolution necessary for performing brain computer interfacing (BCI) tasks and the long-term stability required for human implantation.
Due to their minimally invasive nature, it is thought that the tissue surrounding surface electrode arrays elicits very little response to their presence. However, although there has been extensive research into in vivo biological responses to penetrating neural micro-electrode arrays (MEAs) (Williams et al., 2007, Woolley et al., 2011), there has been little investigation into tissue responses to MEAs implanted on the surface of the cerebral cortex. The assumption that these devices elicit little tissue response is based on results from traditional histological studies of brains implanted with surface electrode arrays (Henle et al., 2011). In order to perform these types of studies, however, the brain must be removed from the skull, and in the process, the electrode array is also removed from the cortical surface, resulting in disruption of the dura mater and any blood vessels and tissues that have grown around the device. Fong et al. (2012) have reported vascular changes occurring around clinically implanted macro electrocorticography grids for mapping of seizure onset zones. In order to verify whether similar tissue changes occur around micro-ECoG devices, an imaging technique that does not require explantation of the brain and device would be advantageous.
The cranial window imaging method has been used extensively for other in vivo biological studies, particularly for imaging of tumor formation and vascular dynamics (Brown et al., 2010, Fukumura et al., 2001, Villringer et al., 1994). This technique employs a glass coverslip, chronically implanted on the surface of the cerebral cortex, through which the cranial tissue can be observed over extended time periods, from weeks to months. Since micro-ECoG devices sit on the surface of the cerebral cortex, their implantation is amenable to this imaging approach.
The objective of this study was to use a cranial window imaging method to study the tissue reaction to implanted micro-ECoG devices. By placing a glass coverslip over the top of the micro-ECoG device during implantation, a cranial window model was developed for imaging the tissue surrounding the implanted device. Use of this technique makes it possible to view the vasculature and other soft tissues that are often destroyed during traditional histological experiments, and also allows for observations of the tissue response at many different time points per animal, since the tissue can be imaged longitudinally in vivo. In this study we concentrate on the imaging of vascular responses to implanted micro-ECoG devices, as a first step toward chronic imaging of a multitude of different cell types.
Section snippets
Device fabrication
The micro-ECoG array is shown in Fig. 1(a). The device consisted of 16 electrode sites encapsulated in a Parylene C substrate. 12 holes were present through the device substrate, between the electrode sites. The electrode sites were 200 μm in diameter and the spacing between the site centers was 750 μm. The devices were fabricated following the process described in Fig. 1(b) (Thongpang et al., 2011). A Parylene C layer was deposited onto a blank silicon wafer using a vacuum deposition system (PDS
Longitudinal tissue response
The progression of vascular growth around an epidurally implanted micro-ECoG device is shown in Fig. 4. Blood vessels began to grow through individual holes in the Parylene substrate of the device on day five, and continued to spread over the entire top surface of the micro-ECoG array over time. In this example, it appears that there had been a micro-hematoma on day 10. The dark areas in the image are indicative of old blood that had pooled beneath the window. On day 15, the bleed was still
Discussion
The goal of the current study was to develop a method for visualization of the tissue surrounding an implanted surface electrode array without disrupting the device–tissue interface. The cranial window imaging method proved very useful for this application. The majority of previous cranial window experiments have been carried out in mouse models and did not involve the use of implantable devices or devices placed on the cortical surface (Holtmaat et al., 2009, Trachtenberg et al., 2002). The
Conclusion
The cranial window imaging method has proven a useful technique for monitoring the tissue response to surface electrode arrays in vivo. Use of this technique has revealed the presence of micro-hematomas around every implanted device, but at varying time points. These hematomas could be contributing to changes in the recorded signal over the course of the implant lifetime, and would not be observable using traditional histological techniques. Moving forward, additional studies are necessary in
Acknowledgements
This work was sponsored by the Defense Advanced Research Projects Agency (DARPA) Microsystems Technology Office (MTO), under the auspices of Dr. Jack W. Judy ([email protected]) as part of the Reliable Neural Technology Program, through the Space and Naval Warfare Systems Command (SPAWAR) Systems Center (SSC) Pacific grants No. N66001-11-1-4013 and No. N66001-12-C-4025. As well as by the National Institutes of Health (NIH NIBIB 1R01EB009103-01, NIH NIBIB 2R01EB000856-06, and NIH NIBIB
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