In vivo recording of neural action-potential and local-field-potential signals requires the use of high-resolution penetrating probes. Several international initiatives to better understand the brain are driving technology efforts towards maximizing the number of recording sites while minimizing the neural probe dimensions. We designed and fabricated (0.13-μm SOI Al CMOS) a 384-channel configurable neural probe for large-scale in vivo recording of neural signals. Up to 966 selectable active electrodes were integrated along an implantable shank (70 μm wide, 10 mm long, 20 μm thick), achieving a crosstalk of -64.4 dB. The probe base (5 × 9 mm ² ) implements dual-band recording and a 171.6 Mbps digital interface. Measurement results show a total input-referred noise of 6.4 μV _rms and a total power consumption of 49.1 μW/channel.

We present a high electrode density and high channel count CMOS (complementary metal-oxide-semiconductor) active neural probe containing 1344 neuron sized recording pixels (20 µm × 20 µm) and 12 reference pixels (20 µm × 80 µm), densely packed on a 50 µm thick, 100 µm wide, and 8 mm long shank. The active electrodes or pixels consist of dedicated in-situ circuits for signal source amplification, which are directly located under each electrode. The probe supports the simultaneous recording of all 1356 electrodes with sufficient signal to noise ratio for typical neuroscience applications. For enhanced performance, further noise reduction can be achieved while using half of the electrodes (678). Both of these numbers considerably surpass the state-of-the art active neural probes in both electrode count and number of recording channels. The measured input referred noise in the action potential band is 12.4 µVrms, while using 678 electrodes, with just 3 µW power dissipation per pixel and 45 µW per read-out channel (including data transmission).

Multi-electrode arrays (MEAs) are a candidate technology to screen cardiotoxicity in vitro because they enable noninvasive recording of cardiac beating rate, electrical field potential duration, and other parameters. In this paper, we present an active MEA chip featuring 16 384 electrodes, 1024 simultaneous readout channels, and 64 stimulation units (SUs) to enable six different cell-interfacing modalities: extracellular and intracellular recording, current and voltage stimulation, fast impedance motoring, and impedance spectroscopy (IS). The chip was designed and fabricated in a 0.13- $\mu \text{m}$ Al CMOS technology, and the electrodes were fabricated on top of the silicon substrate using biocompatible TiN. Measurement results show a total input-referred noise of $7.5 \pm 0.6~\mu \text{V}_{\mathrm{rms}}$ and $12.0 \pm 2.4~\mu \text{V}_{\mathrm {rms}}$ for the action potential and full bands, respectively, with a total power consumption of 95 mW for 1024 readout channels. We have experimentally validated the CMOS MEA in in vitro experiments, demonstrating all the different modalities. This novel platform will potentially enable high-throughput electrical activity monitoring and drug screening of cardiomyocytes.

High-density silicon probes have transformed neuroscience by enabling large-scale neural recordings at single-cell resolution. However, existing technologies have provided limited functionality in nonhuman primates (NHPs) such as macaques. In the present report, we describe the design, fabrication and performance of Neuropixels 1.0 NHP, a high-channel electrode array designed to enable large-scale acute recording throughout large animal brains. The probe features 4,416 recording sites distributed along a 45-mm shank. Experimenters can programmably select 384 recording channels, enabling simultaneous multi-area recording from thousands of neurons with single or multiple probes. This technology substantially increases scalability and recording access relative to existing technologies and enables new classes of experiments that involve electrophysiological mapping of brain areas at single-neuron and single-spike resolution, measurement of spike–spike correlations between cells and simultaneous brain-wide recordings at scale.

Large-scale $in\ vivo$ electrophysiology requires tools that enable simultaneous recording of multiple brain regions at single-neuron level. This calls for the design of more compact neural probes that offer even larger arrays of addressable sites and high channel counts. With this aim, we present in this paper a quad-shank approach to integrate as many as 5,120 sites on a single probe. Compact fully-differential recording channels were designed using a single-gain-stage neural amplifier with a 14-bit ADC, achieving a mean input-referred noise of 7.44 μ $\text{V}_{\text{rms}}$ in the action-potential band and 7.65 μ $\text{V}_{\text{rms}}$ in the local-field-potential band, a mean total harmonic distortion of 0.17% at 1 kHz and a mean input-referred offset of 169 μV. The probe base incorporates 384 channels with on-chip power management, reference-voltage generation and digital control, thus achieving the highest level of integration in a neural probe and excellent channel-to-channel uniformity. Therefore, no calibration or external circuitry are required to achieve the above-mentioned performance. With a total area of $2.2 \times 8.67\text{ mm}^2$ and a power consumption of 36.5 mW, the presented probe enables full-system miniaturization for acute or chronic use in small rodents.

Although CMOS fabrication has enabled a quick evolution in the design of high-density neural probes and neural-recording chips, the scaling and miniaturization of the complete data-acquisition systems has happened at a slower pace. This is mainly due to the complexity and the many requirements that change depending on the specific experimental settings. In essence, the fundamental challenge of a neural-recording system is getting the signals describing the largest possible set of neurons out of the brain and down to data storage for analysis. This requires a complete system optimization that considers the physical, electrical, thermal and signal-processing requirements, while accounting for available technology, manufacturing constraints and budget. Here we present a scalable and open-standards-based open-source data-acquisition system capable of recording from over 10,000 channels of raw neural data simultaneously. The components and their interfaces have been optimized to ensure robustness and minimum invasiveness in small-rodent electrophysiology.