Liquid crystal optrode arrays: a novel approach to neural interfaces
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1
University of New South Wales, School of Electrical Engineering and Telecommunications, Australia
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2
University of New South Wales, Graduate School of Biomedical Engineering, Australia
Closed-loop brain/machine interfaces (BMIs) have the potential to restore lost functions in disabled people and enhance the capabilities of able-bodied people. However, designing a practical in-vivo device with a million neuronal connections – a stated DARPA goal [1] - is extremely challenging.
We present a novel design of an optical electrode (optrode) formed into a multi-unit array. It is based on ferroelectric liquid crystals (LCs), having the potential to scale up to millions of channels with high spatial density and representing an attractive alternative to existing multi electrode arrays (MEAs). The technology we propose records neuronal signals optically, through LC “pixels” [2], and it is based on optical transducers originally developed by the investigators for industrial sensing [3,4]. This innovative approach offers all the benefits of existing MEAs, but with several important advantages: (i) it decouples the reading electronics from the biological tissue; (ii) it does not require any wiring, as the multiplexing is performed optically; (iii) it is entirely passive.
Principle of operation
The core of the proposed approach is an LC cell sensitive to very small voltages. High sensitivity is achieved through the utilisation of a particular class of ferroelectric LCs, whose molecular arrangement can be continuously deformed by the presence of an electric field in the so called “deformed helix” mode of operation. In a typical configuration, illustrated in Figure 1, an LC layer is sandwiched between two substrates: the bottom is glass coated with a thin transparent metal layer (indium tin oxide, ITO) and the top is silicon with gold though silicon vias (TSVs). The ITO layer and the TSV constitute the two electrodes of the LC cell, so that a voltage difference applied between them creates an electric field inside the LC layer, thus deforming its structure. This deformation, in turn, modifies the birefringence of the LC layer, whose change can be detected optically in reflection. In practice, a light beam is shone through a linear polariser onto the LC cell from its ITO side, so that light traverses the LC layer and is reflected by the bottom of the gold TSV, back through the LC, the ITO and the polariser. By adjusting the alignment of the LC with respect to the polariser, it is possible to make the intensity of the reflected light proportional to the applied voltage [3]. This setup can be thought of as a pixel of a LC display operated in reverse: instead of applying a known voltage to control the amount of light reflected, we measure the intensity of reflected light to determine the voltage across the cell.
The optrode array we propose consists of a matrix of the LC “pixels” described above, where the biological tissue is in contact with the top of the TSVs and the ITO layer is a ground common to all pixels and electrically connected to the tissue bath. The optrodes can be interrogated optically in parallel with an optical fiber bundle or sequentially with a single scanning optical fiber, this is represented in Figure 1 by a generic optical readout system. Since this device works with a wide range of wavelengths, it is conceivable that another possible way of interrogating all the pixels in parallel is to illuminate the TSVs with visible light and take pictures of the bottom of the device at high speed. This latter point of view supports the claim that this method is scalable to millions of high-density channels, as cameras with megapixel resolution at thousands of frames per second are commercially available.
Simulations
In order to assess the feasibility of the proposed approach we have performed extensive simulations in COMSOL, including all the important details of the system, such as the electrode-electrolyte bilayer and LC relaxation. The geometry of the simulation is shown in Figure 2 (from [2]). Our results confirm that extracellular voltages as low as tens of microvolts are detectable with the proposed optrode array, provided that relative intensity noise of the optical source is low enough. Our modeling also suggests that the signal to noise ratio does not degrade when reducing the size of the optrodes, as both the impedance of the LC cell and of the electrode-electrolyte bilayer scale in the same way with the electrode area. Finally, the numerical calculations show that LC response is linear and fast enough to reproduce typical neuronal spikes with minimal distortion.
Experiments
We have built a prototype with 323 optrodes and glued it to the bottom of a Petri dish (see Figure 3). This device has been tested by filling the dish with physiological solution and applying sinusoidal voltages of various frequencies between the ITO layer, connected to the wire visible in the figure, and the physiological solution itself. The reflectance from each optrode has been measured by means of an optical fiber and standard telecommunication components using light at 1550nm shone and collected from the bottom of the dish. Our preliminary results show that the optrode array works as expected, particularly in terms of linearity and response time. On the other hand, the sensitivity obtained in these preliminary experiments is still relatively low and suggests that high-end or custom-made components are needed for the optical interrogation. We pint out that the optical readout system is completely decoupled from the biological tissue, so that any improvement to it, irrespective of how complex, will not affect the original electrical signal.
Conclusions
We are at the first stages of the development of this new exciting optical technology and our theoretical and experimental results indicate that it is a viable alternative to traditional MEAs. The most important advantages are its scalability, the fact that the readout system is electrically decoupled from the biological tissue and the fact that no power is required for the device, as light is generated and analyzed by the readout system. Further work is required to increase the sensitivity of the system, which we are currently undertaking.
Acknowledgements
This study was supported by funding from UNSW Sydney’s Proof of Concept Program (grant no. 11_2663) and the Australian Research Council’s Discovery Program (grant no. DP160104625). This work was performed in part at the NSW Node of the Australian National Fabrication Facility.
References
[1] https://www.darpa.mil/program/neural-engineering-system-design
[2] A. Al Abed, H. Srinivas, J. Firth, F. Ladouceur, N. H. Lovell, and L. Silvestri, “A biopotential optrode array: operation principles and simulations”, Scientific Reports 8, 2690 (2018).
[3] Z. Brodzeli, L. Silvestri, A Michie, Q. Guo, E.P. Pozhidaev, V. Chigrinov and F. Ladouceur, “Sensors at your fibre tips: a novel liquid crystal-based photonic transducer for sensing systems”, J. Lightwave Technology 31, 2940 (2013).
[4] J. Firth, F. Ladouceur, Z. Brodzeli, C. Bruin, H. Wang, L. Silvestri, “Liquid Crystal based optical telemetry applied to 4–20mA current loop networks”, Sensors and Actuators A: Physical 260, 124-130 (2017).
Keywords:
optrode array,
Liquid Crystals,
brain machine interfaces,
Optical Fibers,
Multi electrode arrays
Conference:
MEA Meeting 2018 | 11th International Meeting on Substrate Integrated Microelectrode Arrays, Reutlingen, Germany, 4 Jul - 6 Jul, 2018.
Presentation Type:
Oral Presentation
Topic:
Microelectrode Array Technology
Citation:
Ladouceur
F,
Silvestri
L,
Firth
J,
Al Abed
A and
Lovell
NH
(2019). Liquid crystal optrode arrays: a novel approach to neural interfaces.
Conference Abstract:
MEA Meeting 2018 | 11th International Meeting on Substrate Integrated Microelectrode Arrays.
doi: 10.3389/conf.fncel.2018.38.00110
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Received:
08 Mar 2018;
Published Online:
17 Jan 2019.
*
Correspondence:
Prof. François Ladouceur, University of New South Wales, School of Electrical Engineering and Telecommunications, Sydney, Australia, f.ladouceur@unsw.edu.au
Dr. Leonardo Silvestri, University of New South Wales, Graduate School of Biomedical Engineering, Sydney, Australia, l.silvestri@unsw.edu.au