High-resolution extracellular stimulation of dispersed hippocampal culture with high-density CMOS multielectrode array based on non-Faradaic electrodes

Modular Electrode Array for Multi-site Extracellular Recordings from Brains of Freely Moving Rodents

Multi-site extracellular recordings from awake, freely moving rodents are an insightful technique that allows deduction of the dynamics of neural activity within a network of brain regions. Multiple advances in the design and materials of recording setups are available in the literature. However, most of these designs require several skill sets to assemble the electrodes and are expensive. Here, we explain in detail a custom design to build a multi-site (16 sites) electrode array (EA) and record extracellular electrical signals (local field potential and multi-unit spiking activity) at variable depths in freely behaving rodents. This EA weighs ∼3.0 g and costs less than $30. It provides mesoscopic neural activity maps (at millimeter scale) at low spatial resolution, thus enabling the experimenting group to further target specific regions with more expensive high-density probes at the resolution of an individual neuron. The article outlines the processes of building and implanting the array and recording neural activity during a behavior task. We also highlight the limitations of our design and the necessary steps to troubleshoot common issues faced during the initial implementation of the protocols. Finally, we explain the specific data one would obtain while using the probes during social interactions between rodents. © 2022 Wiley Periodicals LLC. Basic Protocol 1: Preparation of the electrode array Basic Protocol 2: Surgical implantation of the electrode array Basic Protocol 3: Recording of neural activity from the electrode array while a mouse performs social investigation of a novel conspecific Basic Protocol 4: Histology and electrode registration.

Time for NanoNeuro

The study of electronic properties of materials at the nanoscale has unveiled physical laws and generated materials such as nanoparticles, quantum dots, nanodiamonds, nanoelectrodes, and nanoprobes. Independently, large-scale public and private neuroscience programs have been launched to develop methods to measure and manipulate neural circuits in living animals and humans. Here, we review an upcoming field, NanoNeuro, defined as the intersection of nanoscience and neuroscience, that aims to develop nanoscale methods to record and stimulate neuronal activity. Because of their unique physical properties, nanomaterials have intrinsic advantages as biosensors and actuators, and they may be applicable to humans without the need for genetic modifications. Thus, nanoscience could make major methodological contributions to the future of neuroscience and, more generally, to biomedical sciences.

A very large-scale microelectrode array for cellular-resolution electrophysiology

In traditional electrophysiology, spatially inefficient electronics and the need for tissue-to-electrode proximity defy non-invasive interfaces at scales of more than a thousand low noise, simultaneously recording channels. Using compressed sensing concepts and silicon complementary metal-oxide-semiconductors (CMOS), we demonstrate a platform with 65,536 simultaneously recording and stimulating electrodes in which the per-electrode electronics consume an area of 25.5 μm by 25.5 μm. Application of this platform to mouse retinal studies is achieved with a high-performance processing pipeline with a 1 GB/s data rate. The platform records from 65,536 electrodes concurrently with a ~10 µV r.m.s. noise; senses spikes from more than 34,000 electrodes when recording across the entire retina; automatically sorts and classifies greater than 1700 neurons following visual stimulation; and stimulates individual neurons using any number of the 65,536 electrodes while observing spikes over the entire retina. The approaches developed here are applicable to other electrophysiological systems and electrode configurations.

Large electronics limit low-noise, non-invasive electrophysiological measurements to a thousand simultaneously recording channels. Here the authors build an array of 65k simultaneously recording and stimulating electrodes and use it to sort and classify single neurons across the entire mouse retina.

From the neuron doctrine to neural networks

For over a century, the neuron doctrine--which states that the neuron is the structural and functional unit of the nervous system--has provided a conceptual foundation for neuroscience. This viewpoint reflects its origins in a time when the use of single-neuron anatomical and physiological techniques was prominent. However, newer multineuronal recording methods have revealed that ensembles of neurons, rather than individual cells, can form physiological units and generate emergent functional properties and states. As a new paradigm for neuroscience, neural network models have the potential to incorporate knowledge acquired with single-neuron approaches to help us understand how emergent functional states generate behaviour, cognition and mental disease.

Tools for probing local circuits: high-density silicon probes combined with optogenetics

To understand how function arises from the interactions between neurons, it is necessary to use methods that allow the monitoring of brain activity at the single-neuron, single-spike level and the targeted manipulation of the diverse neuron types selectively in a closed-loop manner. Large-scale recordings of neuronal spiking combined with optogenetic perturbation of identified individual neurons has emerged as a suitable method for such tasks in behaving animals. To fully exploit the potential power of these methods, multiple steps of technical innovation are needed. We highlight the current state of the art in electrophysiological recording methods, combined with optogenetics, and discuss directions for progress. In addition, we point to areas where rapid development is in progress and discuss topics where near-term improvements are possible and needed.

Revealing neuronal function through microelectrode array recordings

Microelectrode arrays and microprobes have been widely utilized to measure neuronal activity, both in vitro and in vivo. The key advantage is the capability to record and stimulate neurons at multiple sites simultaneously. However, unlike the single-cell or single-channel resolution of intracellular recording, microelectrodes detect signals from all possible sources around every sensor. Here, we review the current understanding of microelectrode signals and the techniques for analyzing them. We introduce the ongoing advancements in microelectrode technology, with focus on achieving higher resolution and quality of recordings by means of monolithic integration with on-chip circuitry. We show how recent advanced microelectrode array measurement methods facilitate the understanding of single neurons as well as network function.

Tracking axonal action potential propagation on a high-density microelectrode array across hundreds of sites

Axons are traditionally considered stable transmission cables, but evidence of the regulation of action potential propagation demonstrates that axons may have more important roles. However, their small diameters render intracellular recordings challenging, and low-magnitude extracellular signals are difficult to detect and assign. Better experimental access to axonal function would help to advance this field. Here we report methods to electrically visualize action potential propagation and network topology in cortical neurons grown over custom arrays, which contain 11,011 microelectrodes and are fabricated using complementary metal oxide semiconductor technology. Any neuron lying on the array can be recorded at high spatio-temporal resolution, and simultaneously precisely stimulated with little artifact. We find substantial velocity differences occurring locally within single axons, suggesting that the temporal control of a neuron's output may contribute to neuronal information processing.

Nanowire electrodes for high-density stimulation and measurement of neural circuits

Brain-machine interfaces (BMIs) that can precisely monitor and control neural activity will likely require new hardware with improved resolution and specificity. New nanofabricated electrodes with feature sizes and densities comparable to neural circuits may lead to such improvements. In this perspective, we review the recent development of vertical nanowire (NW) electrodes that could provide highly parallel single-cell recording and stimulation for future BMIs. We compare the advantages of these devices and discuss some of the technical challenges that must be overcome for this technology to become a platform for next-generation closed-loop BMIs.

High-density microelectrode array recordings and real-time spike sorting for closed-loop experiments: an emerging technology to study neural plasticity

Understanding plasticity of neural networks is a key to comprehending their development and function. A powerful technique to study neural plasticity includes recording and control of pre- and post-synaptic neural activity, e.g., by using simultaneous intracellular recording and stimulation of several neurons. Intracellular recording is, however, a demanding technique and has its limitations in that only a small number of neurons can be stimulated and recorded from at the same time. Extracellular techniques offer the possibility to simultaneously record from larger numbers of neurons with relative ease, at the expenses of increased efforts to sort out single neuronal activities from the recorded mixture, which is a time consuming and error prone step, referred to as spike sorting. In this mini-review, we describe recent technological developments in two separate fields, namely CMOS-based high-density microelectrode arrays, which also allow for extracellular stimulation of neurons, and real-time spike sorting. We argue that these techniques, when combined, will provide a powerful tool to study plasticity in neural networks consisting of several thousand neurons in vitro.