My Research

Masters Thesis at Purdue University

Many technologies have been developed to record electrophysiological signals from the brain. Some of the most well known include silicon probes, microwires, and flexible surface arrays, with each having applications they are suited for and their own shortcomings. One type of electrode that has unmet potential as a transparent, flexible array using poly(3,4-ethylene dioxythiophene): polystyrene sulfonate (PEDOT:PSS) coatings. While many groups have worked to develop them and improve characteristics, no group has been able to fully characterize the capacitance and electrochemical gating properties of PEDOT:PSS, leading to an incomplete understanding of electrodes that make use of PEDOT:PSS. Using an electrochemical gating model and capacitance-voltage sweeps, we can begin to build a better understanding of this complex polymer, and eventually use that to build up devices that function to record neural data with less noise, improving our understanding of neural mechanisms and possibly allowing for better diagnosis and treatment of neural disorders.

Dissertation


Doctoral Thesis at UT Austin

Carbon Nanotube Fiber Array for Deep Brain Recording and Stimulation

The burden of neurological and neuropsychiatric disorders has been increasing in recent times, with neuropsychiatric disorders being the leading cause of disability worldwide.[1]–[5] The current route of treatment centers around pharmaceuticals and psychotherapy, however these courses of treatment are limited, often having many adverse side effects.[2] To better understand these disorders and how they can be more effectively treated, better tools are first needed. Many common neurological disorders occur in deep brain structures that are difficult to access with current electrodes since standard metal and silicon electrodes often cause tissue damage during insertion that makes chronic recordings difficult.[4], [6]–[8] We propose a carbon fiber electrode array that can penetrate deep brain structures (>10mm) in order to record electrophysiological data and help researchers better understand the mechanisms underlying disorders like anxiety, depression, and PTSD. Carbon fibers have the added benefit of flexibility with a Young’s modulus more comparable to brain tissue than conventional metals used in electrode arrays.[9]–[11] This mechanical property lessens the likelihood of biofouling during implantation, making it an ideal candidate for chronic implantation. Carbon fibers have better charge injection capabilities than metal electrodes, making this electrode array will also be capable of stimulation.[12]–[17] Normally carbon fiber arrays are difficult to fabricate since the carbon fibers are not compatible with bulk silicon microfabrication,[10], [18] but we are proposing a new method that combines silicon microfabrication techniques with out of plane assembly to produce 2D, high throughput devices.[19] Once a repeatable fabrication method is confirmed, the devices will be analyzed electrically through impedance measurements to better understand recording capabilities and cyclic voltammetry tests to analyze charge injection capabilities. The probes will then be mechanically characterized during insertion using phantom brains made of a porous composite hydrogel that closely mimics neural tissue having a dynamic mechanical response.[20] After conducting these tests, we are confident that the probes are able to record, stimulate, and be inserted into the brain with minimal trauma, and we will move on to in vivo testing of the probes using non-human primates. Once verified in vivo the carbon nanofiber electrode arrays will be a powerful, multimodal tool that can be used in various research settings to help discover the modalities underlying neurological and neuropsychiatric disorders.

Resources:

[1] V. L. Feigin et al., The Lancet Neurology, 2019; [2] A. Bystritsky, S. S. Khalsa, M. E. Cameron, and J. Schiffman, P T, 2013.; [3] B. Bandelow and S. Michaelis, Dialogues Clin Neurosci, 2015.; [4] G. G. Calhoon and K. M. Tye, Nat Neurosci, 2015; [5] E. R. Duval, A. Javanbakht, and I. Liberzon, Ther Clin Risk Manag, 2015; [6] S. N. Haber and T. E. J. Behrens, Neuron, 2014; [7] cL. M. Williams, The Lancet Psychiatry, 2016; [8] K. J. Ressler and H. S. Mayberg, Nat Neurosci, 2007; [9] G. Guitchounts, J. E. Markowitz, W. A. Liberti, and T. J. Gardner, J. Neural Eng., 2013; [10] P. R. Patel et al., J. Neural Eng., 2016; [11] J. P. Seymour and D. R. Kipke, Biomaterials, 2007; [12] S. F. Cogan, Annual Review of Biomedical Engineering, 2008; [13] V. S. Polikov, P. A. Tresco, and W. M. Reichert, Journal of Neuroscience Methods, 2005; [14] J. P. Harris et al., J. Neural Eng., 2011.; [15] R. Biran, D. C. Martin, and P. A. Tresco, Experimental Neurology, 2005.; [16] Y.-T. Kim, R. W. Hitchcock, M. J. Bridge, and P. A. Tresco, Biomaterials, 2004.; [17] D. H. Szarowski et al., Brain Research, 2003.; [18] P. R. Patel et al., J. Neural Eng., 2015.; [19] T. L. Massey et al., J. Neural Eng., 2019; [20] A. E. Forte et al., Materials & Design, 2016.