Equivalent Circuit of the Neuro-Electronic Junction for Signal Recordings From Planar and Engulfed Micro-Nano-Electrodes

Modeling and Analysis of Environmental Electromagnetic Interference in Multiple-Channel Neural Recording Systems for High Common-Mode Interference Rejection Performance

Environmental electromagnetic interference (EMI) has always been a major interference source for multiple-channel neural recording systems, and little theoretical work has been attempted to address it. In this paper, equivalent circuit models are proposed to model both electromagnetic interference sources and neural signals in such systems, and analysis has been performed to generate the design guidelines for neural probes and the subsequent recording circuit towards higher common-mode interference (CMI) rejection performance while maintaining the recorded neural action potential (AP) signal quality. In vivo animal experiments with a configurable 32-channel neural recording system are carried out to validate the proposed models and design guidelines. The results show the power spectral density (PSD) of environmental 50 Hz EMI interference is reduced by three orders from 4.43 × 10-3 V2/Hz to 4.04 × 10-6 V2/Hz without affecting the recorded AP signal quality in an unshielded experiment environment.

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.

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'.

Advances in Cell-Conductive Polymer Biointerfaces and Role of the Plasma Membrane

The plasma membrane (PM) is often described as a wall, a physical barrier separating the cell cytoplasm from the extracellular matrix (ECM). Yet, this wall is a highly dynamic structure that can stretch, bend, and bud, allowing cells to respond and adapt to their surrounding environment. Inspired by shapes and geometries found in the biological world and exploiting the intrinsic properties of conductive polymers (CPs), several biomimetic strategies based on substrate dimensionality have been tailored in order to optimize the cell-chip coupling. Furthermore, device biofunctionalization through the use of ECM proteins or lipid bilayers have proven successful approaches to further maximize interfacial interactions. As the bio-electronic field aims at narrowing the gap between the electronic and the biological world, the possibility of effectively disguising conductive materials to "trick" cells to recognize artificial devices as part of their biological environment is a promising approach on the road to the seamless platform integration with cells.

Ultrastructural Analysis of Neuroimplant-Parenchyma Interfaces Uncover Remarkable Neuroregeneration Along-With Barriers That Limit the Implant Electrophysiological Functions

Despite increasing use of in vivo multielectrode array (MEA) implants for basic research and medical applications, the critical structural interfaces formed between the implants and the brain parenchyma, remain elusive. Prevailing view assumes that formation of multicellular inflammatory encapsulating-scar around the implants [the foreign body response (FBR)] degrades the implant electrophysiological functions. Using gold mushroom shaped microelectrodes (gMμEs) based perforated polyimide MEA platforms (PPMPs) that in contrast to standard probes can be thin sectioned along with the interfacing parenchyma; we examined here for the first time the interfaces formed between brains parenchyma and implanted 3D vertical microelectrode platforms at the ultrastructural level. Our study demonstrates remarkable regenerative processes including neuritogenesis, axon myelination, synapse formation and capillaries regrowth in contact and around the implant. In parallel, we document that individual microglia adhere tightly and engulf the gMμEs. Modeling of the formed microglia-electrode junctions suggest that this configuration suffice to account for the low and deteriorating recording qualities of in vivo MEA implants. These observations help define the anticipated hurdles to adapting the advantageous 3D in vitro vertical-electrode technologies to in vivo settings, and suggest that improving the recording qualities and durability of planar or 3D in vivo electrode implants will require developing approaches to eliminate the insulating microglia junctions.

A Frequency Domain Analysis of the Excitability and Bifurcations of the FitzHugh-Nagumo Neuron Model

The dynamics of neurons consist of oscillating patterns of a membrane potential that underpin the operation of biological intelligence. The FitzHugh-Nagumo (FHN) model for neuron excitability generates rich dynamical regimes with a simpler mathematical structure than the Hodgkin-Huxley model. Because neurons can be understood in terms of electrical and electrochemical methods, here we apply the analysis of the impedance response to obtain the characteristic spectra and their evolution as a function of applied voltage. We convert the two nonlinear differential equations of FHN into an equivalent circuit model, classify the different impedance spectra, and calculate the corresponding trajectories in the phase plane of the variables. In analogy to the field of electrochemical oscillators, impedance spectroscopy detects the Hopf bifurcations and the spiking regimes. We show that a neuron element needs three essential internal components: capacitor, inductor, and negative differential resistance. The method supports the fabrication of memristor-based artificial neural networks.

Nanotechnology: new opportunities for the development of patch-clamps

The patch-clamp technique is one of the best approaches to investigate neural excitability. Impressive improvements towards the automation of the patch-clamp technique have been made, but obvious limitations and hurdles still exist, such as parallelization, volume displacement in vivo, and long-term recording. Nanotechnologies have provided opportunities to overcome these hurdles by applying electrical devices on the nanoscale. Electrodes based on nanowires, nanotubes, and nanoscale field-effect transistors (FETs) are confirmed to be robust and less invasive tools for intracellular electrophysiological recording. Research on the interface between the nanoelectrode and cell membrane aims to reduce the seal conductance and further improve the recording quality. Many novel recording approaches advance the parallelization, and precision with reduced invasiveness, thus improving the overall intracellular recording system. The combination of nanotechnology and the present intracellular recording framework is a revolutionary and promising orientation, potentially becoming the next generation electrophysiological recording technique and replacing the conventional patch-clamp technique. Here, this paper reviews the recent advances in intracellular electrophysiological recording techniques using nanotechnology, focusing on the design of noninvasive and greatly parallelized recording systems based on nanoelectronics.

Influence of Neuronal Morphology on the Shape of Extracellular Recordings With Microelectrode Arrays: A Finite Element Analysis

OBJECTIVE

Measuring neuronal cell activity using microelectrode arrays reveals a great variety of derived signal shapes within extracellular recordings. However, possible mechanisms responsible for this variety have not yet been entirely determined, which might hamper any subsequent analysis of the recorded neuronal data.

METHODS

To investigate this issue, we propose a computational model based on the finite element method describing the electrical coupling between an electrically active neuron and an extracellular recording electrode in detail. This allows for a systematic study of possible parameters that may play an essential role in defining or altering the shape of the measured electrode potential.

RESULTS

Our results indicate that neuronal geometry, neurite structure, as well as the actual pathways of input potentials that evoke action potential generation, have a significant impact on the shape of the resulting extracellular electrode recording and explain most of the known variations of signal shapes.

CONCLUSION

The presented models offer a comprehensive insight into the effect of geometrical and morphological factors on the resulting electrode signal.

SIGNIFICANCE

Computational modeling complemented with experimental measurements shows much promise to yield meaningful insights into the electrical activity of a neuronal network.

Soft Modular Electronic Blocks (SMEBs): A Strategy for Tailored Wearable Health-Monitoring Systems

Precise monitoring of human body signals can be achieved by soft, conformal contact and precise arrangement of wearable devices to the desired body positions. So far, no design and fabrication methodology in soft wearable devices is able to address the variations in the form factor of the human body such as the various sizes and shapes of individual body parts, which can significantly cause misalignments and the corresponding inaccurate monitoring. Here, a concept of soft modular electronic blocks (SMEBs) enabling the assembly of soft wearable systems onto human skin with functions and layouts tailored to the form factors of individuals' bodies is presented. Three types of SMEBs are developed as fundamental building blocks for functional modularization. The physical design of SMEBs is optimized for a mechanically stable island-bridge configuration. The prepared SMEBs can be integrated onto a target body part through rapid, room-temperature (RT) assembly (<5 s) using an oxygen plasma-induced siloxane bonding method. A soft metacarpophalangeal (MP) joints flexion monitoring system that is tailored to allow for accurate monitoring for multiple individuals with unique joint and hand sizes is demonstrated.

Bioelectronics goes 3D: new trends in cell–chip interface engineering

Bioelectronic platforms can be used for electrophysiology, monitoring and stimulating specific cellular functions.