Advancing the interfacing performances of chronically implantable neural probes in the era of CMOS neuroelectronics.

Tissue penetrating microelectrode neural probes can record electrophysiological brain signals at resolutions down to single neurons, making them invaluable tools for neuroscience research and Brain-Computer-Interfaces (BCIs). The known gradual decrease of their electrical interfacing performances in chronic settings, however, remains a major challenge. A key factor leading to such decay is Foreign Body Reaction (FBR), which is the cascade of biological responses that occurs in the brain in the presence of a tissue damaging artificial device. Interestingly, the recent adoption of Complementary Metal Oxide Semiconductor (CMOS) technology to realize implantable neural probes capable of monitoring hundreds to thousands of neurons simultaneously, may open new opportunities to face the FBR challenge. Indeed, this shift from passive Micro Electro-Mechanical Systems (MEMS) to active CMOS neural probe technologies creates important, yet unexplored, opportunities to tune probe features such as the mechanical properties of the probe, its layout, size, and surface physicochemical properties, to minimize tissue damage and consequently FBR. Here, we will first review relevant literature on FBR to provide a better understanding of the processes and sources underlying this tissue response. Methods to assess FBR will be described, including conventional approaches based on the imaging of biomarkers, and more recent transcriptomics technologies. Then, we will consider emerging opportunities offered by the features of CMOS probes. Finally, we will describe a prototypical neural probe that may meet the needs for advancing clinical BCIs, and we propose axial insertion force as a potential metric to assess the influence of probe features on acute tissue damage and to control the implantation procedure to minimize iatrogenic injury and subsequent FBR.

Integrated Micro-Devices for a Lab-in-Organoid Technology Platform: Current Status and Future Perspectives.

Advancements in stem cell technology together with an improved understanding of in vitro organogenesis have enabled new routes that exploit cell-autonomous self-organization responses of adult stem cells (ASCs) and homogenous pluripotent stem cells (PSCs) to grow complex, three-dimensional (3D), mini-organ like structures on demand, the so-called organoids. Conventional optical and electrical neurophysiological techniques to acquire functional data from brain organoids, however, are not adequate for chronic recordings of neural activity from these model systems, and are not ideal approaches for throughput screenings applied to drug discovery. To overcome these issues, new emerging approaches aim at fusing sensing mechanisms and/or actuating artificial devices within organoids. Here we introduce and develop the concept of the Lab-in-Organoid (LIO) technology for in-tissue sensing and actuation within 3D cell aggregates. This challenging technology grounds on the self-aggregation of brain cells and on integrated bioelectronic micro-scale devices to provide an advanced tool for generating 3D biological brain models with in-tissue artificial functionalities adapted for routine, label-free functional measurements and for assay's development. We complete previously reported results on the implementation of the integrated self-standing wireless silicon micro-devices with experiments aiming at investigating the impact on neuronal spheroids of sinusoidal electro-magnetic fields as those required for wireless power and data transmission. Finally, we discuss the technology headway and future perspectives.

Electrophysiology Read-Out Tools for Brain-on-Chip Biotechnology.

Brain-on-Chip (BoC) biotechnology is emerging as a promising tool for biomedical and pharmaceutical research applied to the neurosciences. At the convergence between lab-on-chip and cell biology, BoC couples in vitro three-dimensional brain-like systems to an engineered microfluidics platform designed to provide an in vivo-like extrinsic microenvironment with the aim of replicating tissue- or organ-level physiological functions. BoC therefore offers the advantage of an in vitro reproduction of brain structures that is more faithful to the native correlate than what is obtained with conventional cell culture techniques. As brain function ultimately results in the generation of electrical signals, electrophysiology techniques are paramount for studying brain activity in health and disease. However, as BoC is still in its infancy, the availability of combined BoC-electrophysiology platforms is still limited. Here, we summarize the available biological substrates for BoC, starting with a historical perspective. We then describe the available tools enabling BoC electrophysiology studies, detailing their fabrication process and technical features, along with their advantages and limitations. We discuss the current and future applications of BoC electrophysiology, also expanding to complementary approaches. We conclude with an evaluation of the potential translational applications and prospective technology developments.

Surface-Functionalized Self-Standing Microdevices Exhibit Predictive Localization and Seamless Integration in 3D Neural Spheroids.

Brain organoids is an exciting technology proposed to advance studies on human brain development, diseases, and possible therapies. Establishing and applying such models, however, is hindered by the lack of technologies to chronically monitor neural activity. A promising new approach comprising self-standing biosensing microdevices capable of achieving seamless tissue integration during cell aggregation and culture. To date, there is little information on how to control the aggregation of such bioartificial 3D neural assemblies. Here, the growth of hybrid neurospheroids obtained by the aggregation of silicon sham microchips (100 × 100 × 50 µm3 ) with primary cortical cells is investigated. Results obtained via protein-binding microchips with different molecules reveal that surface functionalization can tune the integration and final 3D location of self-standing microdevices into neurospheroids. Morphological and functional characterization suggests that the presence of an integrated microdevice does not alter spheroid growth, cellular composition, nor functional development. Ultimately, cells and microdevices constituting such hybrid neurospheroids can be disaggregated for further single-cell analysis, and quantifications confirm an unaltered ratio of neurons and glia. These results uncover the potential of surface-engineered self-standing microdevices to grow untethered 3D brain tissue models with inbuilt bioelectronic sensors at predefined sites.

Active High-Density Electrode Arrays: Technology and Applications in Neuronal Cell Cultures.

Active high-density electrode arrays realized with complementary metal-oxide-semiconductor (CMOS) technology provide electrophysiological recordings from several thousands of closely spaced microelectrodes. This has drastically advanced the spatiotemporal recording resolution of conventional multielectrode arrays (MEAs). Thus, today's electrophysiology in neuronal cultures can exploit label-free electrical readouts from a large number of single neurons within the same network. This provides advanced capabilities to investigate the properties of self-assembling neuronal networks, to advance studies on neurotoxicity and neurodevelopmental alterations associated with human brain diseases, and to develop cell culture models for testing drug- or cell-based strategies for therapies.Here, after introducing the reader to this neurotechnology, we summarize the results of different recent studies demonstrating the potential of active high-density electrode arrays for experimental applications. We also discuss ongoing and possible future research directions that might allow for moving these platforms forward for screening applications.

SiNAPS: An implantable active pixel sensor CMOS-probe for simultaneous large-scale neural recordings.

Large-scale neural recordings with high spatial and temporal accuracy are instrumental to understand how the brain works. To this end, it is of key importance to develop probes that can be conveniently scaled up to a high number of recording channels. Despite recent achievements in complementary metal-oxide semiconductor (CMOS) multi-electrode arrays probes, in current circuit architectures an increase in the number of simultaneously recording channels would significantly increase the total chip area. A promising approach for overcoming this scaling issue consists in the use of the modular Active Pixel Sensor (APS) concept, in which a small front-end circuit is located beneath each electrode. However, this approach imposes challenging constraints on the area of the in-pixel circuit, power consumption and noise. Here, we present an APS CMOS-probe technology for Simultaneous Neural recording that successfully addresses all these issues for whole-array read-outs at 25 kHz/channel from up to 1024 electrode-pixels. To assess the circuit performances, we realized in a 0.18 µm CMOS technology an implantable single-shaft probe with a regular array of 512 electrode-pixels with a pitch of 28 µm. Extensive bench tests showed an in-pixel gain of 45.4 ± 0.4 dB (low pass, F-3 dB = 4 kHz), an input referred noise of 7.5 ± 0.67 µVRMS (300 Hz to 7.5 kHz) and a power consumption <6 µW/pixel. In vivo acute recordings demonstrate that our SiNAPS CMOS-probe can sample full-band bioelectrical signals from each electrode, with the ability to resolve and discriminate activity from several packed neurons both at the spatial and temporal scale. These results pave the way to new generations of compact and scalable active single/multi-shaft brain recording systems.

Exploiting All Programmable SoCs in Neural Signal Analysis: A Closed-Loop Control for Large-Scale CMOS Multielectrode Arrays.

Microelectrode array (MEA) systems with up to several thousands of recording electrodes and electrical or optical stimulation capabilities are commercially available or described in the literature. By exploiting their submillisecond and micrometric temporal and spatial resolutions to record bioelectrical signals, such emerging MEA systems are increasingly used in neuroscience to study the complex dynamics of neuronal networks and brain circuits. However, they typically lack the capability of implementing real-time feedback between the detection of neuronal spiking events and stimulation, thus restricting large-scale neural interfacing to open-loop conditions. In order to exploit the potential of such large-scale recording systems and stimulation, we designed and validated a fully reconfigurable FPGA-based processing system for closed-loop multichannel control. By adopting a Xilinx Zynq-all-programmable system on chip that integrates reconfigurable logic and a dual-core ARM-based processor on the same device, the proposed platform permits low-latency preprocessing (filtering and detection) of spikes acquired simultaneously from several thousands of electrode sites. To demonstrate the proposed platform, we tested its performances through ex vivo experiments on the mice retina using a state-of-the-art planar high-density MEA that samples 4096 electrodes at 18 kHz and record light-evoked spikes from several thousands of retinal ganglion cells simultaneously. Results demonstrate that the platform is able to provide a total latency from whole-array data acquisition to stimulus generation below 2 ms. This opens the opportunity to design closed-loop experiments on neural systems and biomedical applications using emerging generations of planar or implantable large-scale MEA systems.

A Synchronous Neural Recording Platform for Multiple High-Resolution CMOS Probes and Passive Electrode Arrays.

Electrophysiological signals in the brain are distributed over broad spatial and temporal scales. Monitoring these signals at multiple scales is fundamental in order to decipher how brain circuits operate and might dysfunction in disease. A possible strategy to enlarge the experimentally accessible spatial and temporal scales consists in combining the use of multiple probes with different resolutions and sensing areas. Here, we propose a neural recording system capable of simultaneous and synchronous acquisitions from a new generation of high-resolution CMOS probes (512 microelectrodes, 25 kHz/electrode whole-array sampling frequency) as well as from a custom-designed CMOS-based headstage. While CMOS probes can provide recordings from a large number of closely spaced electrodes on single-shaft devices, the CMOS-based headstage can be used to interface the wide range of available intra- or epi-cortical passive electrode array devices. The current platform was designed to simultaneously manage high-resolution recordings from up to four differently located CMOS probes and from a single 36-channels low-resolution passive electrode array device. The design, implementation, and performances for both ICs and for the FPGA-based interface are presented. Experiments on retina and neuronal culture preparations demonstrate the recording of neural spiking activity for both CMOS devices and the functionality of the system.

Independent Component Decomposition of Human Somatosensory Evoked Potentials Recorded by Micro-Electrocorticography.

High-density surface microelectrodes for electrocorticography (ECoG) have become more common in recent years for recording electrical signals from the cortex. With an acceptable invasiveness/signal fidelity trade-off and high spatial resolution, micro-ECoG is a promising tool to resolve fine task-related spatial-temporal dynamics. However, volume conduction - not a negligible phenomenon - is likely to frustrate efforts to obtain reliable and resolved signals from a sub-millimeter electrode array. To address this issue, we performed an independent component analysis (ICA) on micro-ECoG recordings of somatosensory-evoked potentials (SEPs) elicited by median nerve stimulation in three human patients undergoing brain surgery for tumor resection. Using well-described cortical responses in SEPs, we were able to validate our results showing that the array could segregate different functional units possessing unique, highly localized spatial distributions. The representation of signals through the root-mean-square (rms) maps and the signal-to-noise ratio (SNR) analysis emphasizes the advantages of adopting a source analysis approach on micro-ECoG recordings in order to obtain a clear picture of cortical activity. The implications are twofold: while on one side ICA may be used as a spatial-temporal filter extracting micro-signal components relevant to tasks for brain-computer interface (BCI) applications, it could also be adopted to accurately identify the sites of nonfunctional regions for clinical purposes.

Microelectronics, bioinformatics and neurocomputation for massive neuronal recordings in brain circuits with large scale multielectrode array probes.

Deciphering neural network function in health and disease requires recording from many active neurons simultaneously. Developing approaches to increase their numbers is a major neurotechnological challenge. Parallel to recent advances in optical Ca(2+) imaging, an emerging approach consists in adopting complementary-metal-oxide-semiconductor (CMOS) technology to realize MultiElectrode Array (MEA) devices. By implementing signal conditioning and multiplexing circuits, these devices allow nowadays to record from several thousands of single neurons at sub-millisecond temporal resolution. At the same time, these recordings generate very large data streams which become challenging to analyze. Here, at first we shortly review the major approaches developed for data management and analysis for conventional, low-resolution MEAs. We highlight how conventional computational tools cannot be easily up-scaled to very large electrode array recordings, and custom bioinformatics tools are an emerging need in this field. We then introduce a novel approach adapted for the acquisition, compression and analysis of extracellular signals acquired simultaneously from 4096 electrodes with CMOS MEAs. Finally, as a case study, we describe how this novel large scale recording platform was used to record and analyze extracellular spikes from the ganglion cell layer in the wholemount retina at pan-retinal scale following patterned light stimulation.

PEDOT-CNT-Coated Low-Impedance, Ultra-Flexible, and Brain-Conformable Micro-ECoG Arrays.

Electrocorticography (ECoG) is becoming a common tool for clinical applications, such as preparing patients for epilepsy surgery or localizing tumor boundaries, as it successfully balances invasiveness and information quality. Clinical ECoG arrays use millimeter-scale electrodes and centimeter-scale pitch and cannot precisely map neural activity. Higher-resolution electrodes are of interest for both current clinical applications, providing access to more precise neural activity localization and novel applications, such as neural prosthetics, where current information density and spatial resolution is insufficient to suitably decode signals for a chronic brain-machine interface. Developing such electrodes is not trivial because their small contact area increases the electrode impedance, which seriously affects the signal-to-noise ratio, and adhering such an electrode to the brain surface becomes critical. The most straightforward approach requires increasing the array conformability with flexible substrates while improving the electrode performance using materials with superior electrochemical properties. In this paper, we propose an ultra-flexible and conformable polyimide-based micro-ECoG array of submillimeter recording sites electrochemically coated with high surface area conductive polymer-carbon nanotube composites to improve their brain-electrical coupling capabilities. We characterized our devices both electrochemically and by recording from rat somatosensory cortex in vivo. The performance of the coated and uncoated electrodes was directly compared by simultaneously recording the same neuronal activity during multiwhisker deflection stimulation. Finally, we assessed the effect of electrode size on the extraction of somatosensory evoked potentials and found that in contrast to the normal high-impedance microelectrodes, the recording capabilities of our low-impedance microelectrodes improved upon reducing their size from 0.2 to 0.1 mm.

A compact and autoclavable system for acute extracellular neural recording and brain pressure monitoring for humans.

One of the most difficult tasks for the surgeon during the removal of low-grade gliomas is to identify as precisely as possible the borders between functional and non-functional brain tissue with the aim of obtaining the maximal possible resection which allows to the patient the longer survival. For this purpose, systems for acute extracellular recordings of single neuron and multi-unit activity are considered promising. Here we describe a system to be used with 16 microelectrodes arrays that consists of an autoclavable headstage, a built-in inserter for precise electrode positioning and a system that measures and controls the pressure exerted by the headstage on the brain with a twofold purpose: to increase recording stability and to avoid disturbance of local perfusion which would cause a degradation of the quality of the recording and, eventually, local ischemia. With respect to devices where only electrodes are autoclavable, our design permits the reduction of noise arising from long cable connections preserving at the same time the flexibility and avoiding long-lasting gas sterilization procedures. Finally, size is much smaller and set up time much shorter compared to commercial systems currently in use in surgery rooms, making it easy to consider our system very useful for intra-operatory mapping operations.

A programmable closed-loop recording and stimulating wireless system for behaving small laboratory animals.

A portable 16-channels microcontroller-based wireless system for a bi-directional interaction with the central nervous system is presented in this work. The device is designed to be used with freely behaving small laboratory animals and allows recording of spontaneous and evoked neural activity wirelessly transmitted and stored on a personal computer. Biphasic current stimuli with programmable duration, frequency and amplitude may be triggered in real-time on the basis of the recorded neural activity as well as by the animal behavior within a specifically designed experimental setup. An intuitive graphical user interface was developed to configure and to monitor the whole system. The system was successfully tested through bench tests and in vivo measurements on behaving rats chronically implanted with multi-channels microwire arrays.

Biologically compatible neural interface to safely couple nanocoated electrodes to the surface of the brain.

The ongoing interest in densely packed miniaturized electrode arrays for high-resolution epicortical recordings has induced many researchers to explore the use of nanomaterial coatings to reduce electrode impedance while increasing signal-to-noise ratio and charge injection capability. Although these materials are very effective, their use in clinical practice is strongly inhibited by concerns about the potential risks derived from the use of nanomaterials in direct contact with the human brain. In this work we propose a novel approach to safely couple nanocoated electrodes to the brain surface by encapsulating them with a biocompatible hydrogel. We prove that fibrin hydrogel coating over nanocoated high-density arrays of epicortical microelectrodes is electrically transparent and allows avoiding direct exposure of the brain tissue to the nanocoatings while maintaining all the advantages derived from the nanostructured electrode surface. This method may make available acute and sub-acute neural recordings with nanocoated high-resolution arrays for clinical applications.

Carbon nanotube composite coating of neural microelectrodes preferentially improves the multiunit signal-to-noise ratio.

Extracellular metal microelectrodes are widely used to record single neuron activity in vivo. However, their signal-to-noise ratio (SNR) is often far from optimal due to their high impedance value. It has been recently reported that carbon nanotube (CNT) coatings may decrease microelectrode impedance, thus improving their performance. To tease out the different contributions to SNR of CNT-coated microelectrodes we carried out impedance and noise spectroscopy measurements of platinum/tungsten microelectrodes coated with a polypyrrole-CNT composite. Neuronal signals were recorded in vivo from rat cortex by employing tetrodes with two recording sites coated with polypyrrole-CNT and the remaining two left untreated. We found that polypyrrole-CNT coating significantly reduced the microelectrode impedance at all neuronal signal frequencies (from 1 to 10 000 Hz) and induced a significant improvement of the SNR, up to fourfold on average, in the 150-1500 Hz frequency range, largely corresponding to the multiunit frequency band. An equivalent circuit, previously proposed for porous conducting polymer coatings, reproduced the impedance spectra of our coated electrodes but could not explain the frequency dependence of SNR improvement following polypyrrole-CNT coating. This implies that neither the neural signal amplitude, as recorded by a CNT-coated metal microelectrode, nor noise can be fully described by the equivalent circuit model we used here and suggests that a more detailed approach may be needed to better understand the signal propagation at the electrode-solution interface. Finally, the presence of significant noise components that are neither thermal nor electronic makes it difficult to establish a direct relationship between the actual electrode noise and the impedance spectra.