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CMOS microelectrode arrays (MEAs) can record electrophysiological activities of a large number of neurons in parallel but only extracellularly with a low signal-to-noise ratio. Patch-clamp electrodes can perform intracellular recording with a high signal-to-noise ratio but only from a few neurons in parallel. Recently, we have developed and reported a neuroelectronic interface that combines the parallelism of the CMOS MEA and the intracellular sensitivity of the patch clamp. Here, we report the design and characterization of the CMOS integrated circuit (IC), a critical component of the neuroelectronic interface. Fabricated in 0.18- $\mu \text{m}$ technology, the IC features an array of 4096 platinum black (PtB) nanoelectrodes spaced at a 20- $\mu \text{m}$ pitch on its surface and contains 4096 active pixel circuits. Each active pixel circuit, consisting of a new switched-capacitor current injector—-capable of injecting from ±15 pA to ±0.7 $\mu \text{A}$ with a 5-pA resolution—-and an operational amplifier, is highly configurable. When configured into the current-clamp mode, the pixel intracellularly records membrane potentials, including subthreshold activities with ~23- $\mu \text{V}_{\mathrm {rms}}$ input-referred noise while injecting a current for simultaneous stimulation. When configured into the voltage-clamp mode, the pixel becomes a switched-capacitor transimpedance amplifier with ~1-pArms input-referred noise and intracellularly records ion channel currents while applying a voltage for simultaneous stimulation. Such voltage-/current-clamp intracellular recording/stimulation is a feat only previously possible with the patch-clamp method. At the same time, as an array, the IC overcomes the lack of parallelism of the patch-clamp method, measuring thousands of mammalian neurons in parallel, with full-frame intracellular recording/stimulation at 9.4 kHz.

Developing a new tool capable of high-precision electrophysiological recording of a large network of electrogenic cells has long been an outstanding challenge in neurobiology and cardiology. Here, we combine nanoscale intracellular electrodes with complementary metal-oxide-semiconductor (CMOS) integrated circuits to realize a high-fidelity all-electrical electrophysiological imager for parallel intracellular recording at the network level. Our CMOS nanoelectrode array has 1,024 recording/stimulation 'pixels' equipped with vertical nanoelectrodes, and can simultaneously record intracellular membrane potentials from hundreds of connected in vitro neonatal rat ventricular cardiomyocytes. We demonstrate that this network-level intracellular recording capability can be used to examine the effect of pharmaceuticals on the delicate dynamics of a cardiomyocyte network, thus opening up new opportunities in tissue-based pharmacological screening for cardiac and neuronal diseases as well as fundamental studies of electrogenic cells and their networks.

CMOS technology and its Moore’s Law scaling is an enormously successful technology paradigm that has continued to transform our computation and communication abilities. Outside the applications in computation and communication, CMOS technology has been increasingly applied to the life sciences, with a wealth of silicon integrated circuits developed to interface with biological molecules and cells. Concretely, large-scale arrays of active electrodes are integrated using CMOS technology for highly parallel electronic detection of biomolecular/ionic charges and cellular potentials for DNA sequencing, molecular diagnostics, and electrophysiology. Parallelism enabled by CMOS scalability is well suited to process the big data in these biotechnological applications. Here we offer a brief review on these CMOS-bio interfaces, while the corresponding presentation will focus on a sub-topic of CMOS electrophysiology with mammalian neurons.

Ion-sensitive field-effect transistors (ISFETs) have been used to detect a variety of biomolecules whose charges alter the current or threshold voltage of the transistor. ISFETs can be built into large-scale arrays by CMOS compatible technology, offering the promise of highly parallel, all-electrical biomolecule sensing in a true chip-scale construct. Although CMOS-ISFET-based biomolecule detection has been amply demonstrated, a comprehensive optimization study of its sensitivity based on the device design, which would aid the development of large-scale arrays, remains lacking. Here, we present a systematic optimization strategy for CMOS-ISFET-based biomolecule sensing, using real-time DNA hybridization detection as an example. We analytically show that biasing the ISFETs close to the threshold is optimal, whereas minimizing the channel-to-sensing area ratio is beneficial but with limited sensitivity enhancement due to the double-layer capacitance of the sensing area. We then experimentally confirm our strategy with 26 ISFETs of varying sizes and biases from two CMOS chips, which detect the same 200-nM target DNA with different hybridization signals. The measured data correlate well to the presented theory. Our results are generally applicable to detecting other types of biomolecules, and may help in developing large-scale arrays of electrical biomolecular sensors.

The parallelization of intracellular recording can greatly benefit the study of complex neuronal networks, but it has proven difficult to achieve. To meet this challenge, we have been developing large-scale arrays of intracellular vertical nanoscale electrodes operated by underlying CMOS integrated circuits. The development has been fruitful, and our first-generation CMOS nanoelectrode array hit a milestone by intracellularly recording from up to 235 networked cardiomyocytes in parallel. We reported this first-generation system and its unprecedented parallelism in intracellular recording in Nature Nanotechnology 12, 460 (2017). The present paper is a review of this work with a special focus on the development of its CMOS integrated circuit.

Electrode technology for electrophysiology has a long history of innovation, with some decisive steps including the development of the voltage-clamp measurement technique by Hodgkin and Huxley in the 1940s and the invention of the patch clamp electrode by Neher and Sakmann in the 1970s. The high-precision intracellular recording enabled by the patch clamp electrode has since been a gold standard in studying the fundamental cellular processes underlying the electrical activities of neurons and other excitable cells. One logical next step would then be to parallelize these intracellular electrodes, since simultaneous intracellular recording from a large number of cells will benefit the study of complex neuronal networks and will increase the throughput of electrophysiological screening from basic neurobiology laboratories to the pharmaceutical industry. Patch clamp electrodes, however, are not built for parallelization; as for now, only ∼10 patch measurements in parallel are possible. It has long been envisioned that nanoscale electrodes may help meet this challenge. First, nanoscale electrodes were shown to enable intracellular access. Second, because their size scale is within the normal reach of the standard top-down fabrication, the nanoelectrodes can be scaled into a large array for parallelization. Third, such a nanoelectrode array can be monolithically integrated with complementary metal-oxide semiconductor (CMOS) electronics to facilitate the large array operation and the recording of the signals from a massive number of cells. These are some of the central ideas that have motivated the research activity into nanoelectrode electrophysiology, and these past years have seen fruitful developments. This Account aims to synthesize these findings so as to provide a useful reference. Summing up from the recent studies, we will first elucidate the morphology and associated electrical properties of the interface between a nanoelectrode and a cellular membrane, clarifying how the nanoelectrode attains intracellular access. This understanding will be translated into a circuit model for the nanobio interface, which we will then use to lay out the strategies for improving the interface. The intracellular interface of the nanoelectrode is currently inferior to that of the patch clamp electrode; reaching this benchmark will be an exciting challenge that involves optimization of electrode geometries, materials, chemical modifications, electroporation protocols, and recording/stimulation electronics, as we describe in the Account. Another important theme of this Account, beyond the optimization of the individual nanoelectrode-cell interface, is the scalability of the nanoscale electrodes. We will discuss this theme using a recent development from our groups as an example, where an array of ca. 1000 nanoelectrode pixels fabricated on a CMOS integrated circuit chip performs parallel intracellular recording from a few hundreds of cardiomyocytes, which marks a new milestone in electrophysiology.

Electrical sensing of biomolecules has been an important pursuit due to the label-free operation and chip-scale construct such sensing modality can enable. In particular, electrical biomolecular sensors based on nanomaterials such as semiconductor nanowires, carbon nanotubes, and graphene have demonstrated high sensitivity, which in the case of nanowires and carbon nanotubes can surpass typical optical detection sensitivity. Among these nanomaterials, graphene is well suited for a practical candidate for implementing a large-scale array of biomolecular sensors, as its two-dimensional morphology is readily compatible with industry standard top-down fabrication techniques. In our recent work published in 2014 Nature Communications, we demonstrated these benefits by creating DNA sensor arrays from chemical vapor deposition (CVD) graphene. The present chapter, which is a review of this recent work, outlines procedures demonstrating the use of individual graphene sites of the array in dual roles--electrophoretic electrodes for site specific probe DNA immobilization and field effect transistor (FET) sensors for detection of target DNA hybridization. The 100 fM detection sensitivity achieved in 7 out of 8 graphene FET sensors in the array combined with the alternative use of the graphene channels as electrophoretic electrodes for probe deposition represent steps toward creating an all-electrical multiplexed DNA array.

CMOS technology and its Moore’s Law scaling is an enormously successful technology paradigm that has continued to transform our computation and communication abilities. Outside the applications in computation and communication, CMOS technology has been increasingly applied to the life sciences, with a wealth of silicon integrated circuits developed to interface with biological molecules and cells. Concretely, large-scale arrays of active electrodes are integrated using CMOS technology for highly parallel electronic detection of biomolecular/ionic charges and cellular potentials for DNA sequencing, molecular diagnostics, and electrophysiology. Parallelism enabled by CMOS scalability is well suited to process the big data in these biotechnological applications. Here we offer a brief review on these CMOS-bio interfaces, while the corresponding presentation will focus on a sub-topic of CMOS electrophysiology with mammalian neurons.

Session: Semantic Multimedia (short paper); International audience; Execution traces have become essential resources that many developers analyze to debug their applications. Ideally, a developer wants to quickly detect whether there are anomalies on his application or not. However, in practice, the size of multimedia applications trace can reach gigabytes, which makes their exploitation very complex. Usually, developers use visualization tools before stating a hypothesis. In this paper, we argue that this solution is not satisfactory and propose to automatically provide a diagnosis by comparing execution traces. We use distance-based models and conduct a user case to show how TED, our automatic trace diagnosis tool, provides semantic added-value information to the developer. Performance evaluation over real world data shows that our approach is scalable.