Research Collection Doctoral Thesis High-Density Microelectrode Array Platform in CMOS Technology Author(s): Muller, Jan Publication Date: 2015 Permanent Link: https://doi.org/10.3929/ethz-a-010554762 Rights / License: In Copyright - Non-Commercial Use Permitted This page was generated automatically upon download from the ETH Zurich Research Collection. For more information please consult the Terms of use. ETH Library DISS. ETH No. 22,625 High-Density Microelectrode Array Platform in CMOS Technology A thesis submitted to attain the degree of Doctor Of Sciences of ETH Zurich (Dr. sc. ETH Zurich) presented by Jan Muller¨ MSc ETH in Electrical Engineering and Information Technology Born January 7th, 1984 Citizen of Matzendorf (SO), Switzerland accepted on the recommendation of Prof. Dr. Andreas Hierlemann Prof. Dr. Tobias Delbruck Dr. Douglas J. Bakkum 2015 Copyright © 2015 by Jan Muller,¨ Bio Engineering Laboratory All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without the prior written permission of the copyright holder. Cover page: The image shows a CMOS die of the developed microsystem bonded to a green printed circuit board. The images on the back page are taken from the `Major Results' Section 1.6 on page 8. Printed by Druckzentrum ETH Zurich. Published by: Bio Engineering Laboratory, BEL ETH Zurich Mattenstrasse 26 4058 Basel Switzerland Contents 1 Introduction1 1.1 Motivation...............................2 1.2 Applications..............................3 1.3 Considerations for the measurement setup.............4 1.4 Scope and structure of the Thesis..................4 1.5 Author contributions.........................6 1.6 Major Results.............................8 2 A 1024-Channel CMOS Microelectrode Array With 26,400 Elec- trodes for Recording and Stimulation of Electrogenic Cells In Vitro 11 2.1 Introduction.............................. 13 2.2 System Design............................. 15 2.3 Switch Matrix............................. 17 2.4 Readout................................ 20 2.5 Stimulation units........................... 27 2.6 Chip implementation......................... 28 2.7 Measurement............................. 30 2.8 Comparison To State-of-the-art and Conclusion.......... 34 3 High-resolution CMOS MEA platform to study neurons at sub- cellular, cellular and network levels 39 3.1 Introduction.............................. 40 3.2 Materials and methods........................ 42 3.3 Results................................. 49 3.4 Discussion and outlook........................ 60 iii Contents 4 Selection of best recording sites for optimizing spike-sorting yield 65 4.1 Introduction.............................. 67 4.2 Performance assessment of recording configurations........ 69 4.3 Example................................ 74 4.4 Electrode selection algorithms.................... 76 4.5 Technology application........................ 79 4.6 Discussion and conclusion...................... 81 5 Sub-millisecond closed-loop feedback stimulation between arbi- trary sets of individual neurons 85 5.1 Introduction.............................. 86 5.2 Methods................................ 89 5.3 Evaluation and Results........................ 93 5.4 Discussion............................... 103 5.5 Conclusion............................... 105 6 Conclusion 107 6.1 Improvements over previous designs................. 108 6.2 Measurement setup.......................... 109 6.3 Signal processing and spike-sorting considerations......... 109 7 Outlook 113 Appendix 131 A Glossary 131 B Publications 135 C Acknowledgements 143 D Curriculum Vitae 145 iv Abstract This thesis presents the design, implementation, and application of a high- density microelectrode array (MEA) platform based on complementary-metal- oxide-semiconductor (CMOS) technology, for bi-directional interaction with elec- trogenic cells. Studying how networks of neurons process information and whether they exhibit plasticity requires access to many neurons in parallel for extended time periods. MEAs are useful tools for such studies, as they provide non-invasive access to many neurons. They are used to measure the extracellular potentials that are generated by the action potentials of the individual neurons. Using CMOS technology to implement MEAs brings several advantages. A high integration density of electrodes can be achieved through routing of the elec- trode signals by using the multiple metal layers that are available in standard CMOS technology. The electrode density can be further increased by employing electronic switches to implement multiplexing techniques. Detrimental effects of parasitic off-chip connections can be reduced by integrating amplifier circuitry on the same substrate as the sensing electrodes. By additionally integrating analog- to-digital (A/D) converters on the same substrate, only digital data, which are almost immune to interference noise, are transmitted off chip. Finally, complex integrated systems can be devised that include additional units, such as electrical stimulation buffers, which obviates the need for external components. The device presented in this work features a 3:85×2:10 mm2 electrode array with 26,400 Pt-microelectrodes, arranged in a grid-like configuration with a center- to-center pitch of 17:5 µm. By means of an analog switch matrix, an almost arbitrary subset of the electrodes can be connected to 1024 low-noise readout amplifiers, as well as 32 dual-mode current- and voltage-stimulation units, all of which reside at the periphery of the electrode array. Instead of integrating the amplifiers right next to the electrodes (as it is done for the pixel concept), the switch matrix concept allows for decoupling electrode pitch from needed area for circuits and amplifiers at each electrode. Thus, the trade-off between high electrode density on the one hand, and limited amplifier area and resulting noise on the other hand is relaxed. The amplifiers exhibit very low readout noise levels | 2:4 µVrms in the action potential signal band (300 Hz { 10 kHz) | and provide programmable gains of up to 78 dB. On-chip ADCs sample the data at 20 kHz. The combination of switch-matrix architecture for the circuitry and high-resolution electrode array renders the device suitable for recording signals of individual neurons and even axonal arbors of single cells with signal amplitudes as small as a few microvolts. A custom printed-circuit board (PCB) was developed to provide reference volt- ages for the analog circuitry of the CMOS device and to interface with the system digital core for data transfer off chip. The data are streamed to an FPGA to enable real-time signal processing, such as band-pass filtering and spike sort- v Abstract ing. The data are then packaged into UDP (user datagram protocol) frames and transmitted over Ethernet to a host computer. To handle the large amount of data (24 MB/s), a custom UDP accelerator was developed to bypass the slow network stack running on a microcontroller on the FPGA. To operate the setup, software for the host computer was developed to config- ure the CMOS device, as well as for online analysis and visualization of the recorded data. Based on the theoretically expected spike sorting error under the assumption of optimal recording conditions, a framework was established to eval- uate different suitable electrode configurations for given recording scenarios. An algorithm and objective measure to automatically determine optimal recording electrodes was also developed. Cultures of rat cortical neurons were grown on the electrode array for months, and various experiments were performed to validate the proper functioning of the device. Spike-sorting of the neuronal activity, recorded by all 26,400 electrodes, revealed more than 2000 distinct extracellular field potentials that could be at- tributed to individual neurons. Images of fluorescently labeled cells correlated well with the electrically identified cell positions, which confirmed the suitability of the system and setup to characterize neuronal networks. By computing the spike-triggered averages ofthe extracellular signals of a specific neuron while at the same time scanning through all available electrodes, large axonal arbors of single cells were revealed, which extended over large distances within the 8 mm2 array area. Recruiting of the recording electrodes right below the axonal path- ways allowed for the study of axonal signal propagation at high spatiotemporal resolution. Parameters, such as the axonal action potential progagation velocity were analyzed in detail and found to vary between 0.9 m/s and 0.4 m/s along a single branch of the same axon. vi Zusammenfassung Die vorliegende Arbeit beschreibt die Entwicklung, Realisierung und Anwen- dung eines CMOS-basierten Mikroelektrodenarrays mit hoher r¨aumlicher Au- fl¨osung fur¨ extrazellul¨are Messungen und Stimulation von elektrogenen Zellen. Um Informationsverarbeitung und Plastizit¨at in Netzwerken von Nervenzellen zu erforschen, braucht es gleichzeitigen Zugang zu m¨oglichst vielen solchen Ner- venzellen uber¨ einen l¨angeren Zeitraum. Mikroelektrodenarrays sind nutzliche¨ Werkzeuge, um die Interaktion von Nervenzellen zu untersuchen, da sie extrazel- lul¨are Potentiale von vielen Zellen gleichzeitig nicht-invasiv messen k¨onnen. Mikroelektrodenarrays in CMOS Technologie bieten einige Vorteile. So kann z.B. eine hohe Integrationsdichte von Mikroelektroden