Special Issue "Smart Electrical Circuits and Systems for Neural Interface"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Bioelectronics".

Deadline for manuscript submissions: 30 April 2020.

Special Issue Editor

Dr. Hangue Park
E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA
Interests: sensorimotor loop intervention with artificial sensory feedback; human augmentation/rehabilitation; rhythmic/patterned muscle activity; spinal cord injury; assistive technology; teleoperation

Special Issue Information

Dear Colleagues,

We are organizing a Special Issue entitled "Smart Electrical Circuits and Systems for Neural Interface" in MDPI’s Electronics journal, https://www.mdpi.com/journal/electronics. We invite researchers all around world to share great ideas and simulation/experiment data.

The nervous system is highly adaptive. If we can interface and communicate with the nervous system, we can guide neural adaptation in the proper direction for the desired human augmentation or rehabilitation. We can also guide neural adaptation in response to internal and environmental changes, because natural adaptation is often sub-optimal and results in undesirable secondary conditions. Electrical circuits and systems can favorably intervene in the operation of the nervous system, as the neural signal can be recorded and modulated electrically. The goal of favorable neural intervention can be achieved only when all components of the electrical neural interface work in harmony. The electrical neural interface can be composed of several electrical components, including but not limited to electrodes, neural amplifiers, filters, analog-to-digital converters, microprocessors, neural stimulators, power management, wireless power transfer, wireless transceivers, and antenna.

In this Special Issue, we would like to provide researchers with an overview of the current trends in electrical circuits and systems for neural interfaces. We hope that the high-quality papers we will collect and publish will provide a chance for all of us to review the current status of the electrical circuits and systems for neural interfaces and to consider the future of this field.

Dr. Hangue Park
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • neural interface
  • neural recording
  • neural stimulation
  • neural circuits and systems
  • human augmentation
  • human rehabilitation

Published Papers (2 papers)

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Research

Open AccessArticle
Switch Elements with S-Shaped Current-Voltage Characteristic in Models of Neural Oscillators
Electronics 2019, 8(9), 922; https://doi.org/10.3390/electronics8090922 - 22 Aug 2019
Cited by 1
Abstract
In this paper, we present circuit solutions based on a switch element with the S-type I–V characteristic implemented using the classic FitzHugh–Nagumo and FitzHugh–Rinzel models. Using the proposed simplified electrical circuits allows the modeling of the integrate-and-fire neuron and burst oscillation modes with [...] Read more.
In this paper, we present circuit solutions based on a switch element with the S-type I–V characteristic implemented using the classic FitzHugh–Nagumo and FitzHugh–Rinzel models. Using the proposed simplified electrical circuits allows the modeling of the integrate-and-fire neuron and burst oscillation modes with the emulation of the mammalian cold receptor patterns. The circuits were studied using the experimental I–V characteristic of an NbO2 switch with a stable section of negative differential resistance (NDR) and a VO2 switch with an unstable NDR, considering the temperature dependences of the threshold characteristics. The results are relevant for modern neuroelectronics and have practical significance for the introduction of the neurodynamic models in circuit design and the brain–machine interface. The proposed systems of differential equations with the piecewise linear approximation of the S-type I–V characteristic may be of scientific interest for further analytical and numerical research and development of neural networks with artificial intelligence. Full article
(This article belongs to the Special Issue Smart Electrical Circuits and Systems for Neural Interface)
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Open AccessArticle
Remote-Controlled Fully Implantable Neural Stimulator for Freely Moving Small Animal
Electronics 2019, 8(6), 706; https://doi.org/10.3390/electronics8060706 - 22 Jun 2019
Abstract
The application of a neural stimulator to small animals is highly desired for the investigation of electrophysiological studies and development of neuroprosthetic devices. For this purpose, it is essential for the device to be implemented with the capabilities of full implantation and wireless [...] Read more.
The application of a neural stimulator to small animals is highly desired for the investigation of electrophysiological studies and development of neuroprosthetic devices. For this purpose, it is essential for the device to be implemented with the capabilities of full implantation and wireless control. Here, we present a fully implantable stimulator with remote controllability, compact size, and minimal power consumption. Our stimulator consists of modular units of (1) a surface-type cortical array for inducing directional change of a rat, (2) a depth-type array for providing rewards, and (3) a package for accommodating the stimulating electronics, a battery and ZigBee telemetry, all of which are assembled after independent fabrication and implantation using customized flat cables and connectors. All three modules were packaged using liquid crystal polymer (LCP) to avoid any chemical reaction after implantation. After bench-top evaluation of device functionality, the stimulator was implanted into rats to train the animals to turn to the left (or right) following a directional cue applied to the barrel cortex. Functionality of the device was also demonstrated in a three-dimensional (3D) maze structure, by guiding the rats to better navigate in the maze. The movement of the rat could be wirelessly controlled by a combination of artificial sensation evoked by the surface electrode array and reward stimulation. We could induce rats to turn left or right in free space and help their navigation through the maze. The polymeric packaging and modular design could encapsulate the devices with strict size limitations, which made it possible to fully implant the device into rats. Power consumption was minimized by a dual-mode power-saving scheme with duty cycling. The present study demonstrated feasibility of the proposed neural stimulator to be applied to neuroprosthesis research. Full article
(This article belongs to the Special Issue Smart Electrical Circuits and Systems for Neural Interface)
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