A 16384-electrode 1024-channel multimodal CMOS MEA for high-throughput intracellular action potential measurements and impedance spectroscopy in drug-screening applications

López, Carolina Mora; Chun, Ho Sung; Berti, L.; Wang, Shiwei; Putzeys, Jan; Bulcke, Carl Van Den; Weijers, Jan-Willem; Firrincieli, Andrea; Reumers, Veerle; Braeken, Dries; Helleputte, Nick Van

doi:10.1109/isscc.2018.8310385

Cited by 26 publications

(12 citation statements)

References 6 publications

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“…Figure 8 shows the comparison of this work with previous works for high-density CMOS-MEA by relationships between readout channels number and readout noise. The noise in this work is one of the lowest levels in the previous works of the APS readout scheme (Imfeld et al, 2008; Huys et al, 2012; Johnson et al, 2013; Bertotti et al, 2014; Yuan et al, 2016; Lopez et al, 2018) and it is comparable with the previous works of switching matrix readout scheme (Ballini et al, 2014; Yuan et al, 2016), which has an advantage usable in readout noise reduction. The largest number of the channels in previous works is also feasible with the four-tier ADC implementation by applying the technology proposed in this work.…”

Section: Scalability and Comparison With Previous Worksupporting

confidence: 67%

A 4.8-μVrms-Noise CMOS-Microelectrode Array With Density-Scalable Active Readout Pixels via Disaggregated Differential Amplifier Implementation

Ogi¹,

Kato²,

Nakashima³

et al. 2019

Front. Neurosci.

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We demonstrate a 4.8-μV rms noise microelectrode array (MEA) based on the complementary-metal-oxide-semiconductor active-pixel-sensors readout technique with disaggregated differential amplifier implementation. The circuit elements of the differential amplifier are divided into a readout pixel, a reference pixel, and a column circuit. This disaggregation contributes to the small area of the readout pixel, which is less than 81 μm 2 . We observed neuron signals around 100 μV with 432 electrodes in a fabricated prototype chip. The implementation has technological feasibility of up to 12-μm-pitch electrode density and 6,912 readout channels for high-spatial resolution mapping of neuron network activity.

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Section: Scalability and Comparison With Previous Worksupporting

confidence: 67%

A 4.8-μVrms-Noise CMOS-Microelectrode Array With Density-Scalable Active Readout Pixels via Disaggregated Differential Amplifier Implementation

Ogi¹,

Kato²,

Nakashima³

et al. 2019

Front. Neurosci.

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“…Importantly, the injection of the negative I e is sustained throughout the pCC intracellular recording ( Fig. 2d) and contrasts other substrate-based electrode work that use electroporation 7,8,13,27,28,35,36 : in previous substrate-based work, electroporation was performed using a voltage application and their signal was recorded using a voltage amplifier, and thus electroporation and recording couldn't be concurrent. The purpose of our continued current injection is twofold.…”

Section: Intracellular Recording and Stimulation Of Neuronsmentioning

confidence: 83%

“…The capabilities brought by this CMOS-neuroelectronic interface (CNEI) can be highlighted in contrast to three other mainstream electrophysiology techniques. First, CMOS microelectrode arrays (MEAS) [9][10][11][12][13] , featuring as many as ~65,000 electrodes/circuit channels 12 , can monitor a large number of neurons, but they are an extracellular technique and so cannot measure subthreshold events that are critical for examining the synaptic connectivity of neurons 5 . In contrast, our CNEI subsumes the capability of the CMOS MEA (extracellular measurements of a large number of cells) and expands that parallelism to the intracellular measurements.…”

mentioning

confidence: 99%

A nanoelectrode array for obtaining intracellular recordings from thousands of connected neurons

et al. 2019

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Current electrophysiological or optical techniques cannot reliably perform simultaneous intracellular recordings from more than a few tens of neurons. Here, we report a nanoelectrode array that can simultaneously obtain intracellular recordings from thousands of connected mammalian neurons in vitro. The array consists of 4,096 platinum-black electrodes with nanoscale roughness fabricated on top of a silicon chip that monolithically integrates 4,096 microscale amplifiers, configurable into pseudo-current-clamp mode (for concurrent current injection and voltage recording) or into pseudo-voltage-clamp mode (for concurrent voltage application and current recording). We used the array in pseudo-voltage-clamp mode to measure the effects of drugs on ion-channel currents. In pseudo-current-clamp mode, the array recorded intracellular action potentials and post-synaptic potentials from over thousands of neurons. In addition, we mapped over 300 excitatory and inhibitory synaptic connections from over 1,700 neurons that were recorded for 19 mins. This high-throughput intracellular-recording technology could benefit functional connectome mapping, electrophysiological screening, and other functional interrogations of neuronal networks. The patch clamp electrode is celebrated for its high-sensitivity intracellular recording that can measure not only action potential (AP) propagation in neurons but also subthreshold events such as postsynaptic potentials (PSPs). Dense, parallel execution of such high-Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:

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“… 550 Lopez et al. 549 , 550 used this strategy for high-throughput electrical activity monitoring of cardiomyocytes, measuring cardiac cell contractility in real-time. During the contraction phase, the interface impedance dropped, indicating a separation between the cell and the electrode, while during the relaxation phase the impedance increased again.…”

Section: Microarray Strategies Applied In Biomaterials Screening and Used To Model The Cellular Microenvironmentmentioning

confidence: 99%

High-Throughput Methods in the Discovery and Study of Biomaterials and Materiobiology

et al. 2021

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The complex interaction of cells with biomaterials (i.e., materiobiology) plays an increasingly pivotal role in the development of novel implants, biomedical devices, and tissue engineering scaffolds to treat diseases, aid in the restoration of bodily functions, construct healthy tissues, or regenerate diseased ones. However, the conventional approaches are incapable of screening the huge amount of potential material parameter combinations to identify the optimal cell responses and involve a combination of serendipity and many series of trial-and-error experiments. For advanced tissue engineering and regenerative medicine, highly efficient and complex bioanalysis platforms are expected to explore the complex interaction of cells with biomaterials using combinatorial approaches that offer desired complex microenvironments during healing, development, and homeostasis. In this review, we first introduce materiobiology and its high-throughput screening (HTS). Then we present an in-depth of the recent progress of 2D/3D HTS platforms (i.e., gradient and microarray) in the principle, preparation, screening for materiobiology, and combination with other advanced technologies. The Compendium for Biomaterial Transcriptomics and high content imaging, computational simulations, and their translation toward commercial and clinical uses are highlighted. In the final section, current challenges and future perspectives are discussed. High-throughput experimentation within the field of materiobiology enables the elucidation of the relationships between biomaterial properties and biological behavior and thereby serves as a potential tool for accelerating the development of high-performance biomaterials.

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A 16384-electrode 1024-channel multimodal CMOS MEA for high-throughput intracellular action potential measurements and impedance spectroscopy in drug-screening applications

Cited by 26 publications

References 6 publications

A 4.8-μVrms-Noise CMOS-Microelectrode Array With Density-Scalable Active Readout Pixels via Disaggregated Differential Amplifier Implementation

A 4.8-μVrms-Noise CMOS-Microelectrode Array With Density-Scalable Active Readout Pixels via Disaggregated Differential Amplifier Implementation

A nanoelectrode array for obtaining intracellular recordings from thousands of connected neurons

High-Throughput Methods in the Discovery and Study of Biomaterials and Materiobiology

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