Publications
Selected Publications

High-resolution CMOS MEA platform to study neurons at subcellular, cellular, and network levels
Presenting measurements of neuronal preparations with a novel CMOS-based microelectrode array at high-spatiotemporal-resolution on subcellular, cellular, and network level.
J. Müller, M. Ballini, P. Livi, Y. Chen, M. Radivojevic, A. Shadmani, V. Viswam, I. L. Jones, M. Fiscella, R. Diggelmann, A. Stettler, U. Frey, D. J. Bakkum, and A. Hierlemann, “High-resolution CMOS MEA platform to study neurons at subcellular, cellular, and network levels,” Lab Chip, vol. 15, no. 13, pp. 2767–2780, May 2015.

Revealing Neuronal Function through Microelectrode Array Recordings
Reviewing the current understanding of microelectrode signals and the techniques for analyzing them, with focus on the ongoing advancements in microelectrode technology (in vivo and in vitro) and recent advanced microelectrode array measurement methods that facilitate the understanding of single neurons and network function.
M. E. J. Obien, K. Deligkaris, T. Bullmann, D. J. Bakkum, and U. Frey, “Revealing Neuronal Function through Microelectrode Array Recordings,” Front. Neurosci., 8:423, Jan 2015.
A 1024-Channel CMOS Microelectrode Array With 26,400 Electrodes for Recording and Stimulation of Electrogenic Cells In Vitro
A high-resolution CMOS-based microelectrode array featuring 1,024 low-noise readout channels, 26,400 electrodes at a density of 3,265 electrodes per mm2, including on-chip 10bit ADCs and consuming only 75 mW.
M. Ballini, J. Muller, P. Livi, Y. Chen, U. Frey, A. Stettler, A. Shadmani, V. Viswam, I. L. Jones, D. Jackel, M. Radivojevic, M. K. Lewandowska, W. Gong, M. Fiscella, D. J. Bakkum, F. Heer, and A. Hierlemann, “A 1024-Channel CMOS Microelectrode Array With 26,400 Electrodes for Recording and Stimulation of Electrogenic Cells In Vitro,” IEEE Journal of Solid-State Circuits, vol. 49, no. 11, pp. 2705-2719, 2014.
Tracking axonal action potential propagation on a high-density microelectrode array across hundreds of sites
Demonstrating a method to electrically visualize action potential propagation on axons and revealing
large variations in velocity.
D. J. Bakkum, U. Frey, M. Radivojevic, T. L. Russell, J. Muller, M. Fiscella, H. Takahashi, and A. Hierlemann, “Tracking axonal action potential propagation on a high-density microelectrode array across hundreds of sites,” Nature Communications, 4:2181, Jul 2013.
Microelectronic System for High-Resolution Mapping of Extracellular Electric Fields Applied to Brain Slices
Recording and modeling extracellular action potentials of Purkinje cells at subcellular resolution.
U. Frey, U. Egert, F. Heer, S. Hafizovic, and A. Hierlemann, “Microelectronic System for High-Resolution Mapping of Extracellular Electric Fields Applied to Brain Slices,” Biosensors and Bioelectronics, vol. 24, no. 7, pp. 2191-2198, 2009.
Modulation of Cardiomyocyte Electrical Properties Using Regulated Bone Morphogenetic Protein-2 Expression
Controlling BMP-2 expression to modulate the electrophysiological properties of cardiomyocytes using an HD-MEA for detailed monitoring.
C. D. Sanchez-Bustamante, U. Frey, J. M. Kelm, A. Hierlemann, and M. Fussenegger,
“Modulation of Cardiomyocyte Electrical Properties Using Regulated Bone Morphogenetic Protein-2 Expression,” Tissue Engineering Part A, vol. 14, no. 12, pp. 1969-1988, 2008.
All Publications
Hruska-Plochan, Marian; Betz, Katharina M; Ronchi, Silvia; Wiersma, Vera I; Maniecka, Zuzanna; Hock, Eva-Maria; Laferriere, Florent; Sahadevan, Sonu; Hoop, Vanessa; Delvendahl, Igor; Panatta, Martina; van der Bourg, Alexander; Bohaciakova, Dasa; Frontzek, Karl; Aguzzi, Adriano; Lashley, Tammaryn; Robinson, Mark D; Karayannis, Theofanis; Mueller, Martin; Hierlemann, Andreas; Polymenidou, Magdalini Human neural networks with sparse TDP-43 pathology reveal NPTX2 misregulation in ALS/FTLD Journal Article BioRxiv, 2021. Abstract | Links | BibTeX | Tags: Inhibitory Neurons, MEA Technology, Neuronal Networks Yuan, Xinyue; Hierlemann, Andreas; Frey, Urs Extracellular Recording of Entire Neural Networks Using a Dual-Mode Microelectrode Array With 19,584 Electrodes and High SNR Journal Article IEEE, 2021. Abstract | Links | BibTeX | Tags: ETH-CMOS-MEA, MEA Technology Yuan, Xinyue; Schröter, Manuel; Obien, Marie Engelene J; Fiscella, Michele; Gong, Wei; Kikuchi, Tetsuhiro; Odawara, Aoi; Noji, Shuhei; Suzuki, Ikuro; Takahashi, Jun; Hierlemann, Andreas; Frey, Urs Versatile live-cell activity analysis platform for characterization of neuronal dynamics at single-cell and network level Journal Article Nature Communications, 11 (4854), 2020. Abstract | Links | BibTeX | Tags: ETH-CMOS-MEA, MEA Technology Diggelmann, Roland; Fiscella, Michele; Hierlemann, Andreas; Franke, Felix Automatic Spike Sorting Algorithm for High-Density Microelectrode Arrays Journal Article Journal of Neurophysiology, 120 (4), 2018. Abstract | Links | BibTeX | Tags: MEA Technology Dragas, Jelena; Viswam, Vijay; Shadmani, Amir; Chen, Yihui; Bounik, Raziyeh; Stettler, Alexander; Radivojevic, Milos; Geissler, Sydney; Obien, Marie Engelene J; Müller, Jan; Hierlemann, Andreas IEEE journal of solid-state circuits, 52 (6), pp. 1576-1590, 2017, ISSN: 0018-9200. Abstract | Links | BibTeX | Tags: ETH-CMOS-MEA, MEA Technology Obien, Marie Engelene J; Deligkaris, Kosmas; Bullmann, Torsten; Bakkum, Douglas J; Frey, Urs Revealing neuronal function through microelectrode array recordings Journal Article Frontiers in Neuroscience, 9 , pp. 423, 2015, ISSN: 1662453X. Abstract | Links | BibTeX | Tags: MEA Technology, Review Ballini, Marco; Müller, Jan; Livi, Paolo; Chen, Yihui; Frey, Urs; Stettler, Alexander; Shadmani, Amir; Viswam, Vijay; Jones, Ian L; Jäckel, David; Radivojevic, Milos; Lewandowska, Marta K; Gong, Wei; Fiscella, Michele; Bakkum, Douglas J; Heer, Flavio; Hierlemann, Andreas A 1024-channel CMOS microelectrode array with 26,400 electrodes for recording and stimulation of electrogenic cells in vitro Journal Article IEEE Journal of Solid-State Circuits, 49 (11), pp. 2705-2719, 2014, ISSN: 00189200. Abstract | Links | BibTeX | Tags: MaxOne, MEA Technology Müller, Jan; Bakkum, Douglas J; Hierlemann, Andreas Sub-millisecond closed-loop feedback stimulation between arbitrary sets of individual neurons. Journal Article Frontiers in Neural Circuits, 6 , pp. 121, 2013, ISSN: 1662-5110. Abstract | Links | BibTeX | Tags: ETH-CMOS-MEA, MEA Technology, Neuronal Networks, Stimulation Hierlemann, Andreas; Frey, Urs; Hafizovic, Sadik; Heer, Flavio Growing cells atop microelectronic chips: Interfacing electrogenic cells in vitro with CMOS-based microelectrode arrays Journal Article Proceedings of the IEEE, 99 (2), pp. 252-284, 2011, ISSN: 00189219. Abstract | Links | BibTeX | Tags: ETH-CMOS-MEA, MEA Technology, Review Livi, Paolo; Heer, Flavio; Frey, Urs; Bakkum, Douglas J; Hierlemann, Andreas Compact voltage and current stimulation buffer for high-density microelectrode arrays Journal Article IEEE Transactions on Biomedical Circuits and Systems, 4 (6), pp. 372-378, 2010, ISSN: 19324545. Abstract | Links | BibTeX | Tags: ETH-CMOS-MEA, MEA Technology, Stimulation Frey, Urs; Sedivy, Jan; Heer, Flavio; Pedron, Rene; Ballini, Marco; Müller, Jan; Bakkum, Douglas J; Hafizovic, Sadik; Faraci, Francesca D; Greve, Frauke; Kirstein, Kay Uwe; Hierlemann, Andreas Switch-matrix-based high-density microelectrode array in CMOS technology Journal Article IEEE Journal of Solid-State Circuits, 45 (2), pp. 467-482, 2010, ISSN: 00189200. Abstract | Links | BibTeX | Tags: ETH-CMOS-MEA, MEA Technology Heer, Flavio; Hafizovic, Sadik; Franks, Wendy; Blau, Axel; Ziegler, Christiane; Hierlemann, Andreas CMOS microelectrode array for bidirectional interaction with neuronal networks Journal Article IEEE Journal of Solid-State Circuits, 41 (7), pp. 1620-1629, 2006, ISSN: 00189200. Abstract | Links | BibTeX | Tags: ETH-CMOS-MEA, MEA Technology, Neuronal Networks, Stimulation Franks, Wendy; Schenker, Iwan; Schmutz, Patrik; Hierlemann, Andreas Impedance characterization and modeling of electrodes for biomedical applications Journal Article IEEE Transactions on Biomedical Engineering, 52 (7), pp. 1295-1302, 2005, ISSN: 00189294. Abstract | Links | BibTeX | Tags: MEA Technology Jenkner, Martin; Tartagni, Marco; Hierlemann, Andreas; Thewes, Roland Cell-based CMOS sensor and actuator arrays Journal Article IEEE Journal of Solid-State Circuits, 39 (12), pp. 2431-2437, 2004, ISSN: 00189200. Abstract | Links | BibTeX | Tags: MEA Technology, Review Heer, Flavio; Franks, Wendy; Blau, Axel; Taschini, S; Ziegler, Christiane; Hierlemann, Andreas; Baltes, Henry CMOS microelectrode array for the monitoring of electrogenic cells Journal Article Biosensors & Bioelectronics, 20 (2), pp. 358-366, 2004, ISSN: 0956-5663. Abstract | Links | BibTeX | Tags: ETH-CMOS-MEA, MEA Technology2021
title = {Human neural networks with sparse TDP-43 pathology reveal NPTX2 misregulation in ALS/FTLD},
author = {Marian Hruska-Plochan and Katharina M. Betz and Silvia Ronchi and Vera I. Wiersma and Zuzanna Maniecka and Eva-Maria Hock and Florent Laferriere and Sonu Sahadevan and Vanessa Hoop and Igor Delvendahl and Martina Panatta and Alexander van der Bourg and Dasa Bohaciakova and Karl Frontzek and Adriano Aguzzi and Tammaryn Lashley and Mark D. Robinson and Theofanis Karayannis and Martin Mueller and Andreas Hierlemann and Magdalini Polymenidou},
url = {https://doi.org/10.1101/2021.12.08.471089},
doi = {10.1101/2021.12.08.471089},
year = {2021},
date = {2021-12-09},
journal = {BioRxiv},
abstract = {Human cellular models of neurodegeneration require reproducibility and longevity, which is necessary for simulating these age-dependent diseases. Such systems are particularly needed for TDP-43 proteinopathies1,2, which involve human-specific mechanisms3–6 that cannot be directly studied in animal models. To explore the emergence and consequences of TDP-43 pathologies, we generated iPSC-derived, colony morphology neural stem cells (iCoMoNSCs) via manual selection of neural precursors7. Single-cell transcriptomics (scRNA-seq) and comparison to independent NSCs8, showed that iCoMoNSCs are uniquely homogenous and self-renewing. Differentiated iCoMoNSCs formed a self-organized multicellular system consisting of synaptically connected and electrophysiologically active neurons, which matured into long-lived functional networks. Neuronal and glial maturation in iCoMoNSC-derived cultures was similar to that of cortical organoids9. Overexpression of wild-type TDP-43 in a minority of iCoMoNSC-derived neurons led to progressive fragmentation and aggregation, resulting in loss of function and neurotoxicity. scRNA-seq revealed a novel set of misregulated RNA targets coinciding in both TDP-43 overexpressing neurons and patient brains exhibiting loss of nuclear TDP-43. The strongest misregulated target encoded for the synaptic protein NPTX2, which was consistently misaccumulated in ALS and FTLD patient neurons with TDP-43 pathology. Our work directly links TDP-43 misregulation and NPTX2 accumulation, thereby highlighting a new pathway of neurotoxicity.},
keywords = {Inhibitory Neurons, MEA Technology, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
title = {Extracellular Recording of Entire Neural Networks Using a Dual-Mode Microelectrode Array With 19,584 Electrodes and High SNR},
author = {Xinyue Yuan and Andreas Hierlemann and Urs Frey},
url = {https://ieeexplore.ieee.org/document/9385387},
doi = {10.1109/JSSC.2021.3066043},
year = {2021},
date = {2021-03-24},
journal = {IEEE},
abstract = {Electrophysiological research on neural networks and their activity focuses on the recording and analysis of large data sets that include information of thousands of neurons. CMOS microelectrode arrays (MEAs) feature thousands of electrodes at a spatial resolution on the scale of single cells and are, therefore, ideal tools to support neural-network research. Moreover, they offer high spatio-temporal resolution and signal-to-noise ratio (SNR) to capture all features and subcellular-resolution details of neuronal signaling. Here, we present a dual-mode (DM) MEA, which enables simultaneous: 1) full-frame readout from all electrodes and 2) high-SNR readout from an arbitrarily selectable subset of electrodes. The DM-MEA includes 19,584 electrodes, 19,584 full-frame recording channels with noise levels of 10.4 μVrms in the action potential (AP) frequency band (300 Hz-5 kHz), 246 low-noise recording channels with noise levels of 3.0 μVrms in the AP band and eight stimulation units. The capacity to simultaneously perform full-frame and high-SNR recordings endows the presented DM-MEA with great flexibility for various applications in neuroscience and pharmacology.},
keywords = {ETH-CMOS-MEA, MEA Technology},
pubstate = {published},
tppubtype = {article}
}2020
title = {Versatile live-cell activity analysis platform for characterization of neuronal dynamics at single-cell and network level},
author = {Xinyue Yuan and Manuel Schröter and Marie Engelene J. Obien and Michele Fiscella and Wei Gong and Tetsuhiro Kikuchi and Aoi Odawara and Shuhei Noji and Ikuro Suzuki and Jun Takahashi and Andreas Hierlemann and Urs Frey},
url = {https://www.nature.com/articles/s41467-020-18620-4#citeas},
doi = {10.1038/s41467-020-18620-4},
year = {2020},
date = {2020-09-25},
journal = {Nature Communications},
volume = {11},
number = {4854},
abstract = {Chronic imaging of neuronal networks in vitro has provided fundamental insights into mechanisms underlying neuronal function. Current labeling and optical imaging methods, however, cannot be used for continuous and long-term recordings of the dynamics and evolution of neuronal networks, as fluorescent indicators can cause phototoxicity. Here, we introduce a versatile platform for label-free, comprehensive and detailed electrophysiological live-cell imaging of various neurogenic cells and tissues over extended time scales. We report on a dual-mode high-density microelectrode array, which can simultaneously record in (i) full-frame mode with 19,584 recording sites and (ii) high-signal-to-noise mode with 246 channels. We set out to demonstrate the capabilities of this platform with recordings from primary and iPSC-derived neuronal cultures and tissue preparations over several weeks, providing detailed morpho-electrical phenotypic parameters at subcellular, cellular and network level. Moreover, we develop reliable analysis tools, which drastically increase the throughput to infer axonal morphology and conduction speed.},
keywords = {ETH-CMOS-MEA, MEA Technology},
pubstate = {published},
tppubtype = {article}
}2018
title = {Automatic Spike Sorting Algorithm for High-Density Microelectrode Arrays},
author = {Roland Diggelmann and Michele Fiscella and Andreas Hierlemann and Felix Franke},
url = {https://www.physiology.org/doi/pdf/10.1152/jn.00803.2017},
doi = {10.1152/jn.00803.2017},
year = {2018},
date = {2018-09-12},
journal = {Journal of Neurophysiology},
volume = {120},
number = {4},
abstract = {High-density microelectrode arrays (HD-MEAs) can be used to record extracellular action potentials from hundreds to thousands of neurons simultaneously. Efficient spike-sorters have to be developed to cope with such large data volumes. Most existing spike sorting methods for single electrodes or small multi-electrodes, however, suffer from the "curse of dimensionality", and cannot be directly applied to recordings with hundreds of electrodes. This holds particularly true for the standard reference spike sorting algorithm, principal-component-analysis-based feature extraction, followed by k-means or expectation maximization clustering, against which most spike-sorters are evaluated. We present a spike sorting algorithm that circumvents the dimensionality problem by sorting local groups of electrodes independently using classical spike sorting approaches. It is scalable to any number of recording electrodes and well suited for parallel computing. The combination of data pre-whitening before the principal-component-analysis-based extraction and a parameter-free clustering algorithm obviated the need for parameter adjustments. We evaluated its performance using surrogate data in which we systematically varied spike amplitudes and spike rates and which were generated by inserting template spikes into the voltage traces of real recordings. In a direct comparison, our algorithm could compete with existing state-of-the-art spike sorters in terms of sensitivity and precision, while parameter adjustment or manual cluster curation were not required.},
keywords = {MEA Technology},
pubstate = {published},
tppubtype = {article}
}2017
title = {A Multi-Functional Microelectrode Array Featuring 59760 Electrodes, 2048 Electrophysiology Channels, Stimulation, Impedance Measurement and Neurotransmitter Detection Channels},
author = {Jelena Dragas and Vijay Viswam and Amir Shadmani and Yihui Chen and Raziyeh Bounik and Alexander Stettler and Milos Radivojevic and Sydney Geissler and Marie Engelene J Obien and Jan Müller and Andreas Hierlemann},
url = {http://ieeexplore.ieee.org/document/7913669/},
doi = {10.1109/JSSC.2017.2686580},
issn = {0018-9200},
year = {2017},
date = {2017-04-27},
journal = {IEEE journal of solid-state circuits},
volume = {52},
number = {6},
pages = {1576-1590},
abstract = {Biological cells are characterized by highly complex phenomena and processes that are, to a great extent, interdependent. To gain detailed insights, devices designed to study cellular phenomena need to enable tracking and manipulation of multiple cell parameters in parallel; they have to provide high signal quality and high spatiotemporal resolution. To this end, we have developed a CMOS-based microelectrode array system that integrates six measurement and stimulation functions, the largest number to date. Moreover, the system features the largest active electrode array area to date (4.48×2.43 mm(2)) to accommodate 59,760 electrodes, while its power consumption, noise characteristics, and spatial resolution (13.5 mum electrode pitch) are comparable to the best state-of-the-art devices. The system includes: 2,048 action-potential (AP, bandwidth: 300 Hz to 10 kHz) recording units, 32 local-field-potential (LFP, bandwidth: 1 Hz to 300 Hz) recording units, 32 current recording units, 32 impedance measurement units, and 28 neurotransmitter detection units, in addition to the 16 dual-mode voltage-only or current/voltage-controlled stimulation units. The electrode array architecture is based on a switch matrix, which allows for connecting any measurement/stimulation unit to any electrode in the array and for performing different measurement/stimulation functions in parallel.},
keywords = {ETH-CMOS-MEA, MEA Technology},
pubstate = {published},
tppubtype = {article}
}2015
title = {Revealing neuronal function through microelectrode array recordings},
author = {Marie Engelene J Obien and Kosmas Deligkaris and Torsten Bullmann and Douglas J Bakkum and Urs Frey},
url = {https://www.frontiersin.org/articles/10.3389/fnins.2014.00423/full},
doi = {10.3389/fnins.2014.00423},
issn = {1662453X},
year = {2015},
date = {2015-01-06},
journal = {Frontiers in Neuroscience},
volume = {9},
pages = {423},
abstract = {Microelectrode arrays and microprobes have been widely utilized to measure neuronal activity, both in vitro and in vivo. The key advantage is the capability to record and stimulate neurons at multiple sites simultaneously. However, unlike the single-cell or single-channel resolution of intracellular recording, microelectrodes detect signals from all possible sources around every sensor. Here, we review the current understanding of microelectrode signals and the techniques for analyzing them. We introduce the ongoing advancements in microelectrode technology, with focus on achieving higher resolution and quality of recordings by means of monolithic integration with on-chip circuitry. We show how recent advanced microelectrode array measurement methods facilitate the understanding of single neurons as well as network function.},
keywords = {MEA Technology, Review},
pubstate = {published},
tppubtype = {article}
}2014
title = {A 1024-channel CMOS microelectrode array with 26,400 electrodes for recording and stimulation of electrogenic cells in vitro},
author = {Marco Ballini and Jan Müller and Paolo Livi and Yihui Chen and Urs Frey and Alexander Stettler and Amir Shadmani and Vijay Viswam and Ian L Jones and David Jäckel and Milos Radivojevic and Marta K Lewandowska and Wei Gong and Michele Fiscella and Douglas J Bakkum and Flavio Heer and Andreas Hierlemann},
url = {http://ieeexplore.ieee.org/document/6923484/},
doi = {10.1109/JSSC.2014.2359219},
issn = {00189200},
year = {2014},
date = {2014-10-14},
journal = {IEEE Journal of Solid-State Circuits},
volume = {49},
number = {11},
pages = {2705-2719},
abstract = {To advance our understanding of the functioning of neuronal ensembles, systems are needed to enable simultaneous recording from a large number of individual neurons at high spa-tiotemporal resolution and good signal-to-noise ratio. Moreover, stimulation capability is highly desirable for investigating, for example, plasticity and learning processes. Here, we present a microelectrode array (MEA) system on a single CMOS die for in vitro recording and stimulation. The system incorporates 26,400 platinum electrodes, fabricated by in-house post-processing, over a large sensing area (3.85 2.10 mm) with sub-cellular spatial resolution (pitch of 17.5 µm). Owing to an area and power efficient implementation, we were able to integrate 1024 readout channels on chip to record extracellular signals from a user-specified selection of electrodes. These channels feature noise values of 2.4 µV in the action-potential band (300 Hz–10 kHz) and 5.4 µV in the local-field-potential band (1 Hz–300 Hz), and provide programmable gain (up to 78 dB) to accommodate various biological preparations. Amplified and filtered signals are digitized by 10 bit parallel single-slope ADCs at 20 kSamples/s. The system also includes 32 stimulation units, which can elicit neural spikes through either current or voltage pulses. The chip consumes only 75 mW in total, which obviates the need of active cooling even for sensitive cell cultures.},
keywords = {MaxOne, MEA Technology},
pubstate = {published},
tppubtype = {article}
}2013
title = {Sub-millisecond closed-loop feedback stimulation between arbitrary sets of individual neurons.},
author = {Jan Müller and Douglas J Bakkum and Andreas Hierlemann},
url = {https://www.frontiersin.org/articles/10.3389/fncir.2012.00121/full},
doi = {10.3389/fncir.2012.00121},
issn = {1662-5110},
year = {2013},
date = {2013-01-10},
journal = {Frontiers in Neural Circuits},
volume = {6},
pages = {121},
abstract = {We present a system to artificially correlate the spike timing between sets of arbitrary neurons that were interfaced to a complementary metal-oxide-semiconductor (CMOS) high-density microelectrode array (MEA). The system features a novel reprogrammable and flexible event engine unit to detect arbitrary spatio-temporal patterns of recorded action potentials and is capable of delivering sub-millisecond closed-loop feedback of electrical stimulation upon trigger events in real-time. The relative timing between action potentials of individual neurons as well as the temporal pattern among multiple neurons, or neuronal assemblies, is considered an important factor governing memory and learning in the brain. Artificially changing timings between arbitrary sets of spiking neurons with our system could provide a "knob" to tune information processing in the network.},
keywords = {ETH-CMOS-MEA, MEA Technology, Neuronal Networks, Stimulation},
pubstate = {published},
tppubtype = {article}
}2011
title = {Growing cells atop microelectronic chips: Interfacing electrogenic cells in vitro with CMOS-based microelectrode arrays},
author = {Andreas Hierlemann and Urs Frey and Sadik Hafizovic and Flavio Heer},
url = {http://ieeexplore.ieee.org/document/5594982/},
doi = {10.1109/JPROC.2010.2066532},
issn = {00189219},
year = {2011},
date = {2011-02-01},
journal = {Proceedings of the IEEE},
volume = {99},
number = {2},
pages = {252-284},
abstract = {Complementary semiconductor-metal-oxide (CMOS) technology is a very powerful technology that can be more or less directly interfaced to electrogenic cells, like heart or brain cells in vitro. To this end, the cells are cultured directly atop the CMOS chips, which usually undergo dedicated postprocessing to obtain a reliable bidirectional interface via noble-metal microelectrodes or high-k dielectrics. The big advantages of using CMOS integrated circuits (ICs) include connectivity, the possibility to address a large number of microelectrodes on a tiny chip, and signal quality, the possibility to condition small signals right at the spot of their generation. CMOS will be demonstrated to constitute an enabling technology that opens a route to high-spatio-temporal-resolution and low-noise electrophysiological recordings from a variety of biological preparations, such as brain slices, or cultured cardiac and brain cells. The recording technique is extracellular and noninvasive, and the CMOS chips do not leak out any toxic compounds, so that the cells remain viable for extended times. In turn, the CMOS chips have been demonstrated to survive several months of culturing while being fully immersed in saline solution and being exposed to cellular metabolic products. The latter requires dedicated passivation and packaging techniques as will be shown. Fully integrated, monolithic microelectrode systems, which feature large numbers of tightly spaced microelectrodes and the associated circuitry units for bidirectional interaction (stimulation and recording), will be in the focus of this review. The respective dense microelectrode arrays (MEAs) with small pixels enable subcellular-resolution investigation of regions of interest in, e.g., neurobiological preparations, and, at the same time, the large number of electrodes allows for studying the activity of entire neuronal networks . Application areas include neuroscience, as the devices enable fundamental neurophysiological insights at the cellular and circuit level, as well as medical diagnostics and pharmacology.},
keywords = {ETH-CMOS-MEA, MEA Technology, Review},
pubstate = {published},
tppubtype = {article}
}2010
title = {Compact voltage and current stimulation buffer for high-density microelectrode arrays},
author = {Paolo Livi and Flavio Heer and Urs Frey and Douglas J Bakkum and Andreas Hierlemann},
url = {http://ieeexplore.ieee.org/document/5617318/},
doi = {10.1109/TBCAS.2010.2080676},
issn = {19324545},
year = {2010},
date = {2010-11-01},
journal = {IEEE Transactions on Biomedical Circuits and Systems},
volume = {4},
number = {6},
pages = {372-378},
abstract = {We report on a compact (0.02 mm2 ) buffer for both voltage and current stimulation of electrogenic cells on a complementary metal-oxide semiconductor microelectrode array. In voltage mode, the circuit is a high-current class-AB voltage follower, based on a local common-mode feedback (LCMFB) amplifier. In current mode, the circuit is a current conveyor of type II, using the same LCMFB amplifier with cascode stages to increase the gain. The circuit shows good linearity in the 0.5-3.5 V input range and has extensively been used for stimulation of neuronal cultures.},
keywords = {ETH-CMOS-MEA, MEA Technology, Stimulation},
pubstate = {published},
tppubtype = {article}
}
title = {Switch-matrix-based high-density microelectrode array in CMOS technology},
author = {Urs Frey and Jan Sedivy and Flavio Heer and Rene Pedron and Marco Ballini and Jan Müller and Douglas J Bakkum and Sadik Hafizovic and Francesca D Faraci and Frauke Greve and Kay Uwe Kirstein and Andreas Hierlemann},
url = {http://ieeexplore.ieee.org/document/5405139/},
doi = {10.1109/JSSC.2009.2035196},
issn = {00189200},
year = {2010},
date = {2010-02-02},
journal = {IEEE Journal of Solid-State Circuits},
volume = {45},
number = {2},
pages = {467-482},
abstract = {We report on a CMOS-based microelectrode array (MEA) featuring 11, 011 metal electrodes and 126 channels, each of which comprises recording and stimulation electronics, for extracellular bidirectional communication with electrogenic cells, such as neurons or cardiomyocytes. The important features include: (i) high spatial resolution at (sub)cellular level with 3150 electrodes per mm2 (electrode diameter 7 um, electrode pitch 18 um); (ii) a reconflgurable routing of the recording sites to the 126 channels; and (iii) low noise levels.},
keywords = {ETH-CMOS-MEA, MEA Technology},
pubstate = {published},
tppubtype = {article}
}2006
title = {CMOS microelectrode array for bidirectional interaction with neuronal networks},
author = {Flavio Heer and Sadik Hafizovic and Wendy Franks and Axel Blau and Christiane Ziegler and Andreas Hierlemann},
url = {http://ieeexplore.ieee.org/document/1644873/},
doi = {10.1109/ESSCIR.2005.1541628},
issn = {00189200},
year = {2006},
date = {2006-06-26},
journal = {IEEE Journal of Solid-State Circuits},
volume = {41},
number = {7},
pages = {1620-1629},
abstract = {A CMOS metal-electrode-based micro system for bidirectional communication (stimulation and recording) with neuronal cells in vitro is presented. The chip overcomes the interconnect challenge that limits today's bidirectional microelectrode arrays. The microsystem has been fabricated in an industrial CMOS technology with several post-CMOS processing steps to realize 128 biocompatible electrodes and to ensure chip stability in physiological saline. The system comprises all necessary control circuitry and on-chip A/D and D/A conversion. A modular design has been implemented, where individual stimulation- and signal-conditioning circuitry units are associated with each electrode. Stimulation signals with a resolution of 8 bits can be sent to any subset of electrodes at a rate of 60 kHz, while all electrodes of the chip are continuously sampled at a rate of 20 kHz. The circuitry at each electrode can be individually reset to its operating point in order to suppress artifacts evoked by the stimulation pulses. Biological measurements from cultured neuronal networks originating from dissociated cortical tissue of fertilized chicken eggs with amplitudes of up to 500 muVpp are presented.},
keywords = {ETH-CMOS-MEA, MEA Technology, Neuronal Networks, Stimulation},
pubstate = {published},
tppubtype = {article}
}2005
title = {Impedance characterization and modeling of electrodes for biomedical applications},
author = {Wendy Franks and Iwan Schenker and Patrik Schmutz and Andreas Hierlemann},
url = {http://ieeexplore.ieee.org/document/1440608/},
doi = {10.1109/TBME.2005.847523},
issn = {00189294},
year = {2005},
date = {2005-06-13},
journal = {IEEE Transactions on Biomedical Engineering},
volume = {52},
number = {7},
pages = {1295-1302},
abstract = {A low electrode-electrolyte impedance interface is critical in the design of electrodes for biomedical applications. To design low-impedance interfaces a complete understanding of the physical processes contributing to the impedance is required. In this work a model describing these physical processes is validated and extended to quantify the effect of organic coatings and incubation time. Electrochemical impedance spectroscopy has been used to electrically characterize the interface for various electrode materials: platinum, platinum black, and titanium nitride; and varying electrode sizes: 1 cm2, and 900 mu m2. An equivalent circuit model comprising an interface capacitance, shunted by a charge transfer resistance, in series with the solution resistance has been fitted to the experimental results. Theoretical equations have been used to calculate the interface capacitance impedance and the solution resistance, yielding results that correspond well with the fitted parameter values, thereby confirming the validity of the equations. The effect of incubation time, and two organic cell-adhesion promoting coatings, poly-L-lysine and laminin, on the interface impedance has been quantified using the model. This demonstrates the benefits of using this model in developing better understanding of the physical processes occurring at the interface in more complex, biomedically relevant situations.},
keywords = {MEA Technology},
pubstate = {published},
tppubtype = {article}
}2004
title = {Cell-based CMOS sensor and actuator arrays},
author = {Martin Jenkner and Marco Tartagni and Andreas Hierlemann and Roland Thewes},
url = {http://ieeexplore.ieee.org/document/1362853/},
doi = {10.1109/JSSC.2004.837082},
issn = {00189200},
year = {2004},
date = {2004-11-30},
journal = {IEEE Journal of Solid-State Circuits},
volume = {39},
number = {12},
pages = {2431-2437},
abstract = {In recent years, increasing knowledge about in vitro cell handling and culturing has encouraged a variety of CMOS-based approaches to stimulate and detect electrical activity of biological cells. This paper outlines in a topical review the scope of cell-based biosensors and actuators for in vitro applications ranging from single-cell detection to multisite probing of complex neural tissue. Recent examples are selected to demonstrate how standard CMOS processes have been used to engineer arrays with different functionality.},
keywords = {MEA Technology, Review},
pubstate = {published},
tppubtype = {article}
}
title = {CMOS microelectrode array for the monitoring of electrogenic cells},
author = {Flavio Heer and Wendy Franks and Axel Blau and S Taschini and Christiane Ziegler and Andreas Hierlemann and Henry Baltes},
url = {http://www.sciencedirect.com/science/article/pii/S0956566304000806?via%3Dihub},
doi = {10.1016/j.bios.2004.02.006},
issn = {0956-5663},
year = {2004},
date = {2004-03-19},
journal = {Biosensors & Bioelectronics},
volume = {20},
number = {2},
pages = {358-366},
abstract = {Signal degradation and an array size dictated by the number of available interconnects are the two main limitations inherent to standalone microelectrode arrays (MEAs). A new biochip consisting of an array of microelectrodes with fully-integrated analog and digital circuitry realized in an industrial CMOS process addresses these issues. The device is capable of on-chip signal filtering for improved signal-to-noise ratio (SNR), on-chip analog and digital conversion, and multiplexing, thereby facilitating simultaneous stimulation and recording of electrogenic cell activity. The designed electrode pitch of 250 mu m significantly limits the space available for circuitry: a repeated unit of circuitry associated with each electrode comprises a stimulation buffer and a bandpass filter for readout. The bandpass filter has corner frequencies of 100 Hz and 50 kHz, and a gain of 1000. Stimulation voltages are generated from an 8-bit digital signal and converted to an analog signal at a frequency of 120 kHz. Functionality of the read-out circuitry is demonstrated by the measurement of cardiomyocyte activity. The microelectrode is realized in a shifted design for flexibility and biocompatibility. Several microelectrode materials (platinum, platinum black and titanium nitride) have been electrically characterized. An equivalent circuit model, where each parameter represents a macroscopic physical quantity contributing to the interface impedance, has been successfully fitted to experimental results.},
keywords = {ETH-CMOS-MEA, MEA Technology},
pubstate = {published},
tppubtype = {article}
}