Perspectives on electrical neural recording: a revisit to the fundamental concepts

Active Neural Interface Circuits and Systems for Selective Control of Peripheral Nerves: A Review

Interfaces with peripheral nerves have been widely developed to enable bioelectronic control of neural activity. Peripheral nerve neuromodulation shows great potential in addressing motor dysfunctions, neurological disorders, and psychiatric conditions. The integration of high-density neural electrodes with stimulation and recording circuits poses a challenge in the design of neural interfaces. Recent advances in active electrode strategies have achieved improved reliability and performance by implementing in-situ control, stimulation, and recording of neural fibers. This paper presents an overview of state-of-the-art neural interface systems that comprise a range of neural electrodes, neurostimulators, and bio-amplifier circuits, with a special focus on interfaces for the peripheral nerves. A discussion on the efficacy of active electrode systems and recommendations for future directions conclude this paper.

Recording Quality Is Systematically Related to Electrode Impedance

Extracellular recordings with planar microelectrodes are the gold standard technique for recording the fast action potentials of neurons in the intact brain. The introduction of microfabrication techniques has revolutionized the in vivo recording of neuronal activity and introduced high-density, multi-electrode arrays that increase the spatial resolution of recordings and the number of neurons that can be simultaneously recorded. Despite these innovations, there is still debate about the ideal electrical transfer characteristics of extracellular electrodes. This uncertainty is partly due to the lack of systematic studies comparing electrodes with different characteristics, particularly for chronically implanted arrays over extended time periods. Here a high-density, flexible, and thin-film array is fabricated and tested, containing four distinct electrode types differing in surface material and surface topology and, thus, impedance. It is found that recording quality is strongly related to electrode impedance with signal amplitude and unit yield negatively correlated to impedance. Electrode impedances are stable for the duration of the experiment (up to 12 weeks) and recording quality does not deteriorate. The findings support the expectation from the theory that recording quality will increase as impedance decreases.

From Finite Element Simulations to Equivalent Circuit Models of Extracellular Neuronal Recording Systems Based on Planar and Mushroom Electrodes

OBJECTIVE

define a new methodology to build multi-compartment lumped-elements equivalent circuit models for neuron/electrode systems.

METHODS

the equivalent circuit topology is derived by careful scrutiny of accurate and validated multiphysics finite-elements method (FEM) simulations that couple ion transport in the intra- and extracellular fluids, activation of the neuron membrane ion channels, and signal acquisition by the electronic readout.

RESULTS

robust and accurate circuit models are systematically derived, suited to represent the dynamics of the sensed extracellular signals over a wide range of geometrical/physical parameters (neuron and electrode sizes, electrolytic cleft thicknesses, readout input impedance, non-uniform ion channel distributions). FEM simulations point out phenomena that escape an accurate description by equivalent circuits; notably: steric effects in the thin electrolytic cleft and the impact of extracellular ion transport on the reversal potentials of the Hodgkin-Huxley neuron model.

CONCLUSION

our multi-compartment equivalent circuits match accurately the FEM simulations. They unveil the existence of an optimum number of compartments for accurate circuit simulation. FEM simulations suggest that while steric effects are in most instances negligible, the extracellular ion transport affects the reversal potentials and consequently the recorded signal if the electrolytic cleft becomes thinner than approximately 100 nm.

SIGNIFICANCE

the proposed methodology and circuit models improve upon the existing area and point contact models. The coupling between the extracellular concentrations and reversal potential highlighted by FEM simulations emerges as a challenge for future developments in lumped-element modeling of the neuron/sensor interface.

Solid-State Nanopores for Biomolecular Analysis and Detection

Advances in nanopore technology and data processing have rendered DNA sequencing highly accessible, unlocking a new realm of biotechnological opportunities. Commercially available nanopores for DNA sequencing are of biological origin and have certain disadvantages such as having specific environmental requirements to retain functionality. Solid-state nanopores have received increased attention as modular systems with controllable characteristics that enable deployment in non-physiological milieu. Thus, we focus our review on summarizing recent innovations in the field of solid-state nanopores to envision the future of this technology for biomolecular analysis and detection. We begin by introducing the physical aspects of nanopore measurements ranging from interfacial interactions at pore and electrode surfaces to mass transport of analytes and data analysis of recorded signals. Then, developments in nanopore fabrication and post-processing techniques with the pros and cons of different methodologies are examined. Subsequently, progress to facilitate DNA sequencing using solid-state nanopores is described to assess how this platform is evolving to tackle the more complex challenge of protein sequencing. Beyond sequencing, we highlight the recent developments in biosensing of nucleic acids, proteins, and sugars and conclude with an outlook on the frontiers of nanopore technologies.

Methods of poly(3,4)-ethylenedioxithiophene (PEDOT) electrodeposition on metal electrodes for neural stimulation and recording

Conductive polymers are of great interest in the field of neural electrodes because of their potential to improve the interfacial properties of electrodes. In particular, the conductive polymer poly (3,4)-ethylenedioxithiophene (PEDOT) has been widely studied for neural applications.Objective:This review compares methods for electrodeposition of PEDOT on metal neural electrodes, and analyses the effects of deposition methods on morphology and electrochemical performance.Approach:Electrochemical performances were analysed against several deposition method choices, including deposition charge density and co-ion, and correlations were explained to morphological and structural arguments as well as characterisation methods choices.Main results:Coating thickness and charge storage capacity are positively correlated with PEDOT electrodeposition charge density. We also show that PEDOT coated electrode impedance at 1 kHz, the only consistently reported impedance quantity, is strongly dependent upon electrode radius across a wide range of studies, because PEDOT coatings reduces the reactance of the complex impedance, conferring a more resistive behaviour to electrodes (at 1 kHz) dominated by the solution resistance and electrode geometry. This review also summarises how PEDOT co-ion choice affects coating structure and morphology and shows that co-ions notably influence the charge injection limit but have a limited influence on charge storage capacity and impedance. Finally we discuss the possible influence of characterisation methods to assess the robustness of comparisons between published results using different methods of characterisation.Significance:This review aims to serve as a common basis for researchers working with PEDOT by showing the effects of deposition methods on electrochemical performance, and aims to set a standard for accurate and uniform reporting of methods.

Multiscale simulation analysis of passive and active micro/nanoelectrodes for CMOS-based in vitro neural sensing devices

Neuron and neural network studies are remarkably fostered by novel stimulation and recording systems, which often make use of biochips fabricated with advanced electronic technologies and, notably, micro- and nanoscale complementary metal-oxide semiconductor (CMOS). Models of the transduction mechanisms involved in the sensor and recording of the neuron activity are useful to optimize the sensing device architecture and its coupling to the readout circuits, as well as to interpret the measured data. Starting with an overview of recently published integrated active and passive micro/nanoelectrode sensing devices for in vitro studies fabricated with modern (CMOS-based) micro-nano technology, this paper presents a mixed-mode device-circuit numerical-analytical multiscale and multiphysics simulation methodology to describe the neuron-sensor coupling, suitable to derive useful design guidelines. A few representative structures and coupling conditions are analysed in more detail in terms of the most relevant electrical figures of merit including signal-to-noise ratio. This article is part of the theme issue 'Advanced neurotechnologies: translating innovation for health and well-being'.