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An Investigation into Neural Tissue-Electrode Contact as a Performance Impairing Factor in Flexible, Micro-Electrocorticographic Probes Meant for Brain-Computer Interfacing

  • Author / Creator
    Cunningham, Joshua Michael
  • The on-going development of micro- and nano-fabrication methods is facilitating interest and investigation into neural probes and implants for use as neurosurgical diagnostic tools and brain-computer interfaces (BCI). Key to the development of all neural probes, from invasive to non-invasive, is the improvement of the spatial resolution of the device while maintaining acceptable temporal sampling rates. The partially-invasive electrocorticogram (ECoG) is one such neural probe technology that has been advanced significantly in recent years and is currently a top performer when applied in BCI applications due to its high bandwidth and the lack of any acute glial immune response to its presence. The electrodes of flexible micro-ECoG (μECoG) probes have been reduced in diameter from 3 mm to tens of microns and have had the number of recording sites increased from 16 to 256. But, will the continued reduction in electrode size using current fabrication methods and materials limit/prevent contact from being made between the electrode surface and the cortical tissue and thereby affect the signal quality negatively? This thesis serves as a preliminary exploration into this problem through mechanical deflection testing of microfabricated flexible μECoG probe arrays with 20 and 30 μm electrodes that have been electrochemically modified to obtain various interface depths and comparing the results to a simple mathematical equation used to model static deflection in discs. This is the first time, to my knowledge, that electrode-tissue contact being lost at some point due to physical and geometrical restraining factors has been brought to light as an issue and been given any specific consideration as to what performance limitations might arise, and to also explore some possible solutions. I found that for a flexible MEA with an insulating Parylene-C layer around 2 μm thick, contact could not be established during pressure-induced deflection tests of either of the as-made, unmodified 20 and 30 μm diameter electrodes. However, by electrodepositing additional electrode material, PEDOT:ClO4 and gold, I demonstrate that these void spaces can be effectively filled, thereby enabling electrode-tissue contact once again and obtaining maximum signal strength. The use of a simple equation calculating the magnitude of deflection at the centre of a circular disc can predict whether electrode-electrode contact will be made during deflection test done by applying pressure onto the flexible probes to complete a circuit, indicating contact being made. This model proved to be imperfect and inaccurate but the points lined up well with a curve that had physical parameters that didn’t match reality. It is possible that this method could be refined significantly to serve as a more accurate predictor. The exploration and investigation into the human brain is one of the most important and thrilling scientific tasks humankind knows of and it may also be the most interdisciplinary project at the global scale to have ever been attempted, but with that many people and that much time and energy being poured into this expedition and the never-ending ethical dilemmas and hurdles of human testing that have to be overcome, all the data that gets collected needs to be the rawest, strongest and highest-fidelity data possible or it could prevent or limit analysis and interpretation. By making the neural probe community aware of this design consideration and by taking steps to avoid limitations that change the fundamental signal capture mechanisms involving electrode-tissue contact, it should be possible to further reduce the diameter of electrodes in flexible microECoG neural probes while maintaining a high signal. With a neural probe containing a high-resolution multi-electrode array (MEA) that provides a clean, stable array of signals over a reasonable area, computer algorithms can be applied in numerous ways. Once an interface for communication directly with computer systems is established, it is possible for software to learn to recognise more complex patterns through higher resolution inputs and execute tasks such as: fine movement control of robotic prostheses and systems; actively stimulating a region to mimic a catalogued pattern to prevent/lesson neurological episodes such as seizures; or for treating or mediating degenerative and other neurological diseases in ways yet unknown.

  • Subjects / Keywords
  • Graduation date
    Fall 2017
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/R3MK65N9H
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.