An Event-based Neural Compressive Telemetry with >11× Loss-less Data Reduction for High-bandwidth Intracortical Brain Computer Interfaces.

Intracortical brain-computer interfaces offer superior spatial and temporal resolutions, but face challenges as the increasing number of recording channels introduces high amounts of data to be transferred. This requires power-hungry data serialization and telemetry, leading to potential tissue damage risks. To address this challenge, this paper introduces an event-based neural compressive telemetry (NCT) consisting of 8 channel-rotating Δ-ADCs, an event-driven serializer supporting a proposed ternary address event representation protocol, and an event-based LVDS driver. Leveraging a high sparsity of extracellular spikes and high spatial correlation of the high-density recordings, the proposed NCT achieves a compression ratio of >11.4×, while consumes only 1 µW per channel, which is 127× more efficient than state of the art. The NCT well preserves the spike waveform fidelity, and has a low normalized RMS error <23% even with a spike amplitude down to only 31 µV.

An AC-Coupled 1st-order Δ-ΔΣ Readout IC for Area-Efficient Neural Signal Acquisition.

The current demand for high-channel-count neural-recording interfaces calls for more area- and power-efficient readout architectures that do not compromise other electrical performances. In this paper, we present a miniature 128-channel neural recording integrated circuit (NRIC) for the simultaneous acquisition of local field potentials (LFPs) and action potentials (APs), which can achieve a very good compromise between area, power, noise, input range and electrode DC offset cancellation. An AC-coupled 1st-order digitally-intensive Δ-ΔΣ architecture is proposed to achieve this compromise and to leverage the advantages of a highly-scaled technology node. A prototype NRIC, including 128 channels, a newly-proposed area-efficient bulk-regulated voltage reference, biasing circuits and a digital control, has been fabricated in 22-nm FDSOI CMOS and fully characterized. Our proposed architecture achieves a total area per channel of 0.005 mm2, a total power per channel of 12.57 µW, and an input-referred noise of 7.7 ± 0.4 µVrms in the AP band and 11.9 ± 1.1 µVrms in the LFP band. A very good channel-to-channel uniformity is demonstrated by our measurements. The chip has been validated in vivo, demonstrating its capability to successfully record full-band neural signals.

Large-scale high-density brain-wide neural recording in nonhuman primates.

High-density, integrated silicon electrodes have begun to transform systems neuroscience, by enabling large-scale neural population recordings with single cell resolution. Existing technologies, however, have provided limited functionality in nonhuman primate species such as macaques, which offer close models of human cognition and behavior. Here, we report the design, fabrication, and performance of Neuropixels 1.0-NHP, a high channel count linear electrode array designed to enable large-scale simultaneous recording in superficial and deep structures within the macaque or other large animal brain. These devices were fabricated in two versions: 4416 electrodes along a 45 mm shank, and 2496 along a 25 mm shank. For both versions, users can programmatically select 384 channels, enabling simultaneous multi-area recording with a single probe. We demonstrate recording from over 3000 single neurons within a session, and simultaneous recordings from over 1000 neurons using multiple probes. This technology represents a significant increase in recording access and scalability relative to existing technologies, and enables new classes of experiments involving fine-grained electrophysiological characterization of brain areas, functional connectivity between cells, and simultaneous brain-wide recording at scale.

A Compact Quad-Shank CMOS Neural Probe With 5,120 Addressable Recording Sites and 384 Fully Differential Parallel Channels.

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 µVrms in the action-potential band and 7.65 µVrms 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 × 8.67 mm2 and a power consumption of 36.5 mW, the presented probe enables full-system miniaturization for acute or chronic use in small rodents.

High-Density Electrical Recording and Impedance Imaging With a Multi-Modal CMOS Multi-Electrode Array Chip.

Multi-electrode arrays, both active or passive, emerged as ideal technologies to unveil intricated electrophysiological dynamics of cells and tissues. Active MEAs, designed using complementary metal oxide semiconductor technology (CMOS), stand over passive devices thanks to the possibility of achieving single-cell resolution, the reduced electrode size, the reduced crosstalk and the higher functionality and portability. Nevertheless, most of the reported CMOS MEA systems mainly rely on a single operational modality, which strongly hampers the applicability range of a single device. This can be a limiting factor considering that most biological and electrophysiological dynamics are often based on the synergy of multiple and complex mechanisms acting from different angles on the same phenomena. Here, we designed a CMOS MEA chip with 16,384 titanium nitride electrodes, 6 independent operational modalities and 1,024 parallel recording channels for neuro-electrophysiological studies. Sixteen independent active areas are patterned on the chip surface forming a 4 × 4 matrix, each one including 1,024 electrodes. Electrodes of four different sizes are present on the chip surface, ranging from 2.5 × 3.5 µm2 up to 11 × 11.0 µm2, with 15 µm pitch. In this paper, we exploited the impedance monitoring and voltage recording modalities not only to monitor the growth and development of primary rat hippocampal neurons, but also to assess their electrophysiological activity over time showing a mean spike amplitude of 144.8 ± 84.6 µV. Fixed frequency (1 kHz) and high sampling rate (30 kHz) impedance measurements were used to evaluate the cellular adhesion and growth on the chip surface. Thanks to the high-density configuration of the electrodes, as well as their dimension and pitch, the chip can appreciate the evolutions of the cell culture morphology starting from the moment of the seeding up to mature culture conditions. The measurements were confirmed by fluorescent staining. The effect of the different electrode sizes on the spike amplitudes and noise were also discussed. The multi-modality of the presented CMOS MEA allows for the simultaneous assessment of different physiological properties of the cultured neurons. Therefore, it can pave the way both to answer complex fundamental neuroscience questions as well as to aid the current drug-development paradigm.

Fine-scale mapping of cortical laminar activity during sleep slow oscillations using high-density linear silicon probes.

BACKGROUND: The cortical slow (∼1 Hz) oscillation (SO), which is thought to play an active role in the consolidation of memories, is a brain rhythm characteristic of slow-wave sleep, with alternating periods of neuronal activity and silence. Although the laminar distribution of cortical activity during SO is well-studied by using linear neural probes, traditional devices have a relatively low (20-100 µm) spatial resolution along cortical layers. NEW METHOD: In this work, we demonstrate a high-density linear silicon probe fabricated to record the SO with very high spatial resolution (∼6 µm), simultaneously from multiple cortical layers. Ketamine/xylazine-induced SO was acquired acutely from the neocortex of rats, followed by the examination of the high-resolution laminar structure of cortical activity. RESULTS: The probe provided high-quality extracellular recordings, and the obtained cortical laminar profiles of the SO were in good agreement with the literature data. Furthermore, we could record the simultaneous activity of 30-50 cortical single units. Spiking activity of these neurons showed layer-specific differences. COMPARISON WITH EXISTING METHODS: The developed silicon probe measures neuronal activity with at least a three-fold higher spatial resolution compared with traditional linear probes. By exploiting this feature, we could determine the site of up-state initiation with a higher precision than before. Additionally, increased spatial resolution may provide more reliable spike sorting results, as well as a higher single unit yield. CONCLUSIONS: The high spatial resolution provided by the electrodes allows to examine the fine structure of local population activity during sleep SO in greater detail.

Investigation of the Stimulation Capabilities of a High-Resolution Neurorecording Probe for the Application of Closed-Loop Deep Brain Stimulation.

Deep brain stimulation is an established surgical treatment for several neurological and movement disorders, such as Parkinson's disease, in which electrostimulation is applied to targeted deep nuclei in the basal ganglia through implanted electrode leads. Recent technological improvements in the field have focused on the theoretical advantage of current steering and adaptive (closed-loop) deep brain stimulation. Current steering between several active electrodes would allow for improved accuracy when targeting the desired brain structures. This has the additional benefit of avoiding undesired stimulation of neural tracts that are related to side effects, e.g., internal capsule fibres of passage in subthalamic nucleus deep brain stimulation. Closed-loop deep brain stimulation is based on the premise of continuous recording of a proxy for pathological neural activity (such as beta-band power of measured local field potentials in patients with Parkinson's disease) and accordingly adapting the used stimulus parameters. In this study, we investigate the suitability of an existing highresolution neurorecording probe for high-precision neurostimulation. If a subset of the probe's recording electrodes can be used for stimulation, then the probe would be a suitable candidate for closed-loop deep brain stimulation. A finiteelement model is used to calculate the electric potential, induced by current injection through the high-resolution probe, for different sets of active electrodes. Volumes of activated tissue are calculated and a comparison is made between the highresolution probe and a conventional stimulation lead. We investigate the capability of the probe to shift the volume of activated tissue by steering currents to different sets of active electrodes. Finally, safety limits for the injected current are used to determine the size of the volume in which neurons can be activated with the relatively small electrodes patches on the highresolution probe.

A silicon-based neural probe with densely-packed low-impedance titanium nitride microelectrodes for ultrahigh-resolution in vivo recordings.

In this study, we developed and validated a single-shank silicon-based neural probe with 128 closely-packed microelectrodes suitable for high-resolution extracellular recordings. The 8-mm-long, 100-µm-wide and 50-µm-thick implantable shank of the probe fabricated using a 0.13-µm complementary metal-oxide-semiconductor (CMOS) metallization technology contains square-shaped (20 × 20 µm2), low-impedance (~ 50 kΩ at 1 kHz) recording sites made of rough and porous titanium nitride which are arranged in a 32 × 4 dense array with an inter-electrode pitch of 22.5 µm. The electrophysiological performance of the probe was tested in in vivo experiments by implanting it acutely into neocortical areas of anesthetized animals (rats, mice and cats). We recorded local field potentials, single- and multi-unit activity with superior quality from all layers of the neocortex of the three animal models, even after reusing the probe in multiple (> 10) experiments. The low-impedance electrodes monitored spiking activity with high signal-to-noise ratio; the peak-to-peak amplitude of extracellularly recorded action potentials of well-separable neurons ranged from 0.1 mV up to 1.1 mV. The high spatial sampling of neuronal activity made it possible to detect action potentials of the same neuron on multiple, adjacent recording sites, allowing a more reliable single unit isolation and the investigation of the spatiotemporal dynamics of extracellular action potential waveforms in greater detail. Moreover, the probe was developed with the specific goal to use it as a tool for the validation of electrophysiological data recorded with high-channel-count, high-density neural probes comprising integrated CMOS circuitry.

Fully integrated silicon probes for high-density recording of neural activity.

Sensory, motor and cognitive operations involve the coordinated action of large neuronal populations across multiple brain regions in both superficial and deep structures. Existing extracellular probes record neural activity with excellent spatial and temporal (sub-millisecond) resolution, but from only a few dozen neurons per shank. Optical Ca2+ imaging offers more coverage but lacks the temporal resolution needed to distinguish individual spikes reliably and does not measure local field potentials. Until now, no technology compatible with use in unrestrained animals has combined high spatiotemporal resolution with large volume coverage. Here we design, fabricate and test a new silicon probe known as Neuropixels to meet this need. Each probe has 384 recording channels that can programmably address 960 complementary metal-oxide-semiconductor (CMOS) processing-compatible low-impedance TiN sites that tile a single 10-mm long, 70 × 20-µm cross-section shank. The 6 × 9-mm probe base is fabricated with the shank on a single chip. Voltage signals are filtered, amplified, multiplexed and digitized on the base, allowing the direct transmission of noise-free digital data from the probe. The combination of dense recording sites and high channel count yielded well-isolated spiking activity from hundreds of neurons per probe implanted in mice and rats. Using two probes, more than 700 well-isolated single neurons were recorded simultaneously from five brain structures in an awake mouse. The fully integrated functionality and small size of Neuropixels probes allowed large populations of neurons from several brain structures to be recorded in freely moving animals. This combination of high-performance electrode technology and scalable chip fabrication methods opens a path towards recording of brain-wide neural activity during behaviour.

Ultra-high-density in-vivo neural probes.

The past decade has witnessed an explosive growth in our ability to observe and measure brain activity. Among different functional brain imaging techniques, the electrical measurement of neural activity using neural probes provides highest temporal resolution. Yet, the electrode density and the observability of currently available neural probe technologies fall short of the density of neurons in the brain by several orders of magnitude. This paper presents opportunities for neural probes to utilize advances in CMOS technology for increasing electrode density and observability of neural activity, while minimizing the tissue damage. The authors present opportunities for neural probes to adapt advanced CMOS technologies and discuss challenges in terms of maintaining the signal integrity and implementing data communication.

Towards a noise prediction model for in vivo neural recording.

The signal-to-noise ratio of in vivo extracellular neural recordings with microelectrodes is influenced by many factors including the impedance of the electrode-tissue interface, the noise of the recording equipment and biological background noise from distant neurons. In this work we study the different noise sources affecting the quality of neural signals. We propose a simplified noise model as an analytical tool to predict the noise of an electrode given its geometrical dimensions and impedance characteristics. With this tool we are able to quantify different noise sources, which is important to determine realistic noise specifications for the design of electronic neural recording interfaces.