Abstract
Intracranial electrode arrays for recording and stimulating electrical brain activity have facilitated major advances in the treatment of neurological conditions over the past decade. When compared to scalp electroencephalography (EEG), cortical recordings have demonstrated superior spatial resolution and consequently a greater potential for cognitive command output. Traditional cortical arrays require direct implantation into the brain via open craniotomy, which is a delicate and lengthy procedure. This can lead to inflammatory tissue responses amongst other clinical complications and has necessitated the development of minimally invasive methods that circumvent or mitigate brain trauma. In this study, we demonstrate the feasibility of chronically recording brain activity from within an external cerebral vein using a passive stent - electrode recording array (stentrode). We achieved implantation into a superficial cortical vein lying adjacent to the motor cortex using catheter angiography. Access was made via vascular puncture in the external jugular vein in the neck. Following successful implantation, we demonstrated neural recordings in freely moving sheep for time periods up to 190 days. Venous internal lumen patency was preserved for the duration of implantation. Spectral content and bandwidth of vascular electrocorticography were found to be comparable to those of recordings from epidural surface arrays.
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Acknowledgements
The Vascular Bionics Laboratory would like to acknowledge all participants and contributors to our work thus far. In particular, we would like to recognise the input of
The University of Melbourne
• Dept. of Medicine
• Dept. of Electrical and Electronic Engineering
The Florey Institute of Neuroscience and Mental Health
The Royal Melbourne Hospital
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Oxley, T.J. et al. (2017). A Minimally Invasive Endovascular Stent-Electrode Array for Chronic Recordings of Cortical Neural Activity. In: Guger, C., Allison, B., Lebedev, M. (eds) Brain-Computer Interface Research. SpringerBriefs in Electrical and Computer Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-64373-1_6
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DOI: https://doi.org/10.1007/978-3-319-64373-1_6
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