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Micromachines
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Neural Interface: From Material to System
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Neural Interface: From Material to System

A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "B：Biology and Biomedicine".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 14866

Special Issue Editor

Dr. Liuyang Sun

E-Mail Website
Guest Editor
2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China
Interests: micro/nano sensing; neural engineering; nanophotonics

Special Issue Information

Dear Colleagues,

From brain–computer interfaces that empower paralyzed individuals to regain mobility, to smart prosthetics that are able to mimic human limbs, the fusion of intelligent bioelectronics and neural interfaces is revolutionizing our understanding of human–machine symbiosis. With the development of multi-disciplinary research, intelligent bioelectronics and neural interfaces have also witnessed numerous breakthroughs. For example, implantable devices can record neural signals for research purposes or deliver precise stimulation for therapeutic interventions; neural probes with multiple electrodes can be inserted into brain tissue to record neural activity from multiple locations simultaneously; and micromachining techniques can contribute to the development of flexible and stretchable electronic devices that can conform to the body's movements, just to name a few. Nevertheless, challenges persist in the realm of intelligent bioelectronics. For devices, efficient signal acquisition and application, as well as enhanced biocompatibility, are urgent issues. In the field of neural interfaces, accurately deciphering complex neural signals and achieving long-term implantation remain forefront challenges. These hurdles necessitate collaborative interdisciplinary efforts and innovative approaches. Accordingly, this Special Issue seeks to showcase research papers, communications, and review articles that focus on the following topics: advanced bioelectronics processing, i.e., biocompatible materials for neuro interfaces, implantable devices, high-throughput systems in intelligent bioelectronics, clinical applications and translational research.

Dr. Liuyang Sun
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 submissions that pass pre-check are 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. Micromachines 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 2600 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 signal encoding and decoding
  • neural electrodes: flexible electrodes, stretchable electrodes
  • bio-sensors and bio-actuators
  • neural signal processing unit
  • BMI-based robots
  • implantable bioelectronics
  • neuroprosthetics
  • neurological disorder diagnosis and treatment

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Published Papers (6 papers)

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Research

15 pages, 7197 KiB  
Article
A Wireless Bi-Directional Brain–Computer Interface Supporting Both Bluetooth and Wi-Fi Transmission
by Wei Ji, Haoyang Su, Shuang Jin, Ye Tian, Gen Li, Yingkang Yang, Jiazhi Li, Zhitao Zhou, Xiaoling Wei, Tiger H. Tao, Lunming Qin, Yifei Ye and Liuyang Sun
Micromachines 2024, 15(11), 1283; https://doi.org/10.3390/mi15111283 - 22 Oct 2024
Viewed by 3416
Abstract
Wireless neural signal transmission is essential for both neuroscience research and neural disorder therapies. However, conventional wireless systems are often constrained by low sampling rates, limited channel counts, and their support of only a single transmission mode. Here, we developed a wireless bi-directional [...] Read more.
Wireless neural signal transmission is essential for both neuroscience research and neural disorder therapies. However, conventional wireless systems are often constrained by low sampling rates, limited channel counts, and their support of only a single transmission mode. Here, we developed a wireless bi-directional brain–computer interface system featuring dual transmission modes. This system supports both low-power Bluetooth transmission and high-sampling-rate Wi-Fi transmission, providing flexibility for various application scenarios. The Bluetooth mode, with a maximum sampling rate of 14.4 kS/s, is well suited for detecting low-frequency signals, as demonstrated by both in vitro recordings of signals from 10 to 50 Hz and in vivo recordings of 16-channel local field potentials in mice. More importantly, the Wi-Fi mode, offering a maximum sampling rate of 56.8 kS/s, is optimized for recording high-frequency signals. This capability was validated through in vitro recordings of signals from 500 to 2000 Hz and in vivo recordings of single-neuron spike firings with amplitudes reaching hundreds of microvolts and high signal-to-noise ratios. Additionally, the system incorporates a wireless stimulation function capable of delivering current pulses up to 2.55 mA, with adjustable pulse width and polarity. Overall, this dual-mode system provides an efficient and flexible solution for both neural recording and stimulation applications. Full article
(This article belongs to the Special Issue Neural Interface: From Material to System)
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16 pages, 16781 KiB  
Article
Multi-Channel Microscale Nerve Cuffs for Spatially Selective Neuromodulation
by Morgan Riley, FNU Tala, Katherine J. Johnson and Benjamin C. Johnson
Micromachines 2024, 15(8), 1036; https://doi.org/10.3390/mi15081036 - 15 Aug 2024
Viewed by 959
Abstract
Peripheral nerve modulation via electrical stimulation shows promise for treating several diseases, but current approaches lack selectivity, leading to side effects. Exploring selective neuromodulation with commercially available nerve cuffs is impractical due to their high cost and limited spatial resolution. While custom cuffs [...] Read more.
Peripheral nerve modulation via electrical stimulation shows promise for treating several diseases, but current approaches lack selectivity, leading to side effects. Exploring selective neuromodulation with commercially available nerve cuffs is impractical due to their high cost and limited spatial resolution. While custom cuffs reported in the literature achieve high spatial resolutions, they require specialized microfabrication equipment and significant effort to produce even a single design. This inability to rapidly and cost-effectively prototype novel cuff designs impedes research into selective neuromodulation therapies in acute studies. To address this, we developed a reproducible method to easily create multi-channel epineural nerve cuffs for selective fascicular neuromodulation. Leveraging commercial flexible printed circuit (FPC) technology, we created cuffs with high spatial resolution (50 μm) and customizable parameters like electrode size, channel count, and cuff diameter. We designed cuffs to accommodate adult mouse or rat sciatic nerves (300–1500 μm diameter). We coated the electrodes with PEDOT:PSS to improve the charge injection capacity. We demonstrated selective neuromodulation in both rats and mice, achieving preferential activation of the tibialis anterior (TA) and lateral gastrocnemius (LG) muscles. Selectivity was confirmed through micro-computed tomography (μCT) and quantified through a selectivity index. These results demonstrate the potential of this fabrication method for enabling selective neuromodulation studies while significantly reducing production time and costs compared to traditional approaches. Full article
(This article belongs to the Special Issue Neural Interface: From Material to System)
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15 pages, 6159 KiB  
Article
High-Porosity Sieve-Type Neural Electrodes for Motor Function Recovery and Nerve Signal Acquisition
by Wonsuk Choi, HyungDal Park, Seonghwan Oh, Seonho Seok, Dae Sung Yoon and Jinseok Kim
Micromachines 2024, 15(7), 862; https://doi.org/10.3390/mi15070862 - 30 Jun 2024
Viewed by 3845
Abstract
In this study, the effects of electrode porosity on nerve regeneration and functional recovery after sciatic nerve transection in rats was investigated. A sieve-type neural electrode with 70% porosity was designed and compared with an electrode with 30% porosity. Electrodes were fabricated from [...] Read more.
In this study, the effects of electrode porosity on nerve regeneration and functional recovery after sciatic nerve transection in rats was investigated. A sieve-type neural electrode with 70% porosity was designed and compared with an electrode with 30% porosity. Electrodes were fabricated from photosensitive polyimide and implanted into the transected sciatic nerves. Motor function recovery was evaluated using the Sciatic Function Index. The number of active channels and their signal quality were recorded and analyzed to assess the sensory neural signal acquisition. Electrical impedance spectroscopy was used to evaluate the electrode performance. The group implanted with the 70% porosity electrode demonstrated significantly enhanced nerve regeneration and motor function recovery, approaching control group levels by the fifth week. In contrast, the group with the 30% porosity electrode exhibited limited improvement. Immunohistochemical analysis confirmed extensive nerve fiber growth within the 70% porous structure. Moreover, the 70% porosity electrode consistently acquired neural signals from more channels compared to the 30% porosity electrode, demonstrating its superior performance in sensory signal detection. These findings emphasize the importance of optimizing electrode porosity in the development of advanced neural interfaces, with the potential to enhance clinical outcomes in peripheral nerve repair and neuroprosthetic applications. Full article
(This article belongs to the Special Issue Neural Interface: From Material to System)
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14 pages, 9925 KiB  
Article
Modulation Steering Motion by Quantitative Electrical Stimulation in Pigeon Robots
by Mingxuan Bi, Huimin Zhang, Yaohong Ma, Hao Wang, Wenbo Wang, Yuan Shi, Wenlong Sheng, Qiushun Li, Guangheng Gao and Lei Cai
Micromachines 2024, 15(5), 595; https://doi.org/10.3390/mi15050595 - 29 Apr 2024
Cited by 1 | Viewed by 3038
Abstract
The pigeon robot has attracted significant attention in the field of animal robotics thanks to its outstanding mobility and adaptive capability in complex environments. However, research on pigeon robots is currently facing bottlenecks, and achieving fine control over the motion behavior of pigeon [...] Read more.
The pigeon robot has attracted significant attention in the field of animal robotics thanks to its outstanding mobility and adaptive capability in complex environments. However, research on pigeon robots is currently facing bottlenecks, and achieving fine control over the motion behavior of pigeon robots through brain–machine interfaces remains challenging. Here, we systematically quantify the relationship between electrical stimulation and stimulus-induced motion behaviors, and provide an analytical method to demonstrate the effectiveness of pigeon robots based on electrical stimulation. In this study, we investigated the influence of gradient voltage intensity (1.2–3.0 V) on the indoor steering motion control of pigeon robots. Additionally, we discussed the response time of electrical stimulation and the effective period of the brain–machine interface. The results indicate that pigeon robots typically exhibit noticeable behavioral responses at a 2.0 V voltage stimulus. Increasing the stimulation intensity significantly controls the steering angle and turning radius (p < 0.05), enabling precise control of pigeon robot steering motion through stimulation intensity regulation. When the threshold voltage is reached, the average response time of a pigeon robot to the electrical stimulation is 220 ms. This study quantifies the role of each stimulation parameter in controlling pigeon robot steering behavior, providing valuable reference information for the precise steering control of pigeon robots. Based on these findings, we offer a solution for achieving precise control of pigeon robot steering motion and contribute to solving the problem of encoding complex trajectory motion in pigeon robots. Full article
(This article belongs to the Special Issue Neural Interface: From Material to System)
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12 pages, 2421 KiB  
Article
Flexible Peripheral Nerve Interfacing Electrode for Joint Position Control in Closed-Loop Neuromuscular Stimulation
by Sia Kim and Kang-Il Song
Micromachines 2024, 15(5), 594; https://doi.org/10.3390/mi15050594 - 29 Apr 2024
Viewed by 1224
Abstract
Addressing peripheral nerve disorders with electronic medicine poses significant challenges, especially in replicating the dynamic mechanical properties of nerves and understanding their functionality. In the field of electronic medicine, it is crucial to design a system that thoroughly understands the functions of the [...] Read more.
Addressing peripheral nerve disorders with electronic medicine poses significant challenges, especially in replicating the dynamic mechanical properties of nerves and understanding their functionality. In the field of electronic medicine, it is crucial to design a system that thoroughly understands the functions of the nervous system and ensures a stable interface with nervous tissue, facilitating autonomous neural adaptation. Herein, we present a novel neural interface platform that modulates the peripheral nervous system using flexible nerve electrodes and advanced neuromodulation techniques. Specifically, we have developed a surface-based inverse recruitment model for effective joint position control via direct electrical nerve stimulation. Utilizing barycentric coordinates, this model constructs a three-dimensional framework that accurately interpolates inverse isometric recruitment values across various joint positions, thereby enhancing control stability during stimulation. Experimental results from rabbit ankle joint control trials demonstrate our model’s effectiveness. In combination with a proportional–integral–derivative (PID) controller, it shows superior performance by achieving reduced settling time (less than 1.63 s), faster rising time (less than 0.39 s), and smaller steady-state error (less than 3 degrees) compared to the legacy model. Moreover, the model’s compatibility with recent advances in flexible interfacing technologies and its integration into a closed-loop controlled functional neuromuscular stimulation (FNS) system highlight its potential for precise neuroprosthetic applications in joint position control. This approach marks a significant advancement in the management of neurological disorders with advanced neuroprosthetic solutions. Full article
(This article belongs to the Special Issue Neural Interface: From Material to System)
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14 pages, 45842 KiB  
Article
A Comparative Study on the Effect of Substrate Structure on Electrochemical Performance and Stability of Electrodeposited Platinum and Iridium Oxide Coatings for Neural Electrodes
by Linze Li, Changqing Jiang and Luming Li
Micromachines 2024, 15(1), 70; https://doi.org/10.3390/mi15010070 - 29 Dec 2023
Cited by 1 | Viewed by 1652
Abstract
Implantable electrodes are crucial for stimulation safety and recording quality of neuronal activity. To enhance their electrochemical performance, electrodeposited nanostructured platinum (nanoPt) and iridium oxide (IrOx) have been proposed due to their advantages of in situ deposition and ease of processing. [...] Read more.
Implantable electrodes are crucial for stimulation safety and recording quality of neuronal activity. To enhance their electrochemical performance, electrodeposited nanostructured platinum (nanoPt) and iridium oxide (IrOx) have been proposed due to their advantages of in situ deposition and ease of processing. However, their unstable adhesion has been a challenge in practical applications. This study investigated the electrochemical performance and stability of nanoPt and IrOx coatings on hierarchical platinum-iridium (Pt-Ir) substrates prepared by femtosecond laser, compared with the coatings on smooth Pt-Ir substrates. Ultrasonic testing, agarose gel testing, and cyclic voltammetry (CV) testing were used to evaluate the coatings’ stability. Results showed that the hierarchical Pt-Ir substrate significantly enhanced the charge-storage capacity of electrodes with both coatings to more than 330 mC/cm2, which was over 75 times that of the smooth Pt-Ir electrode. The hierarchical substrate could also reduce the cracking of nanoPt coatings after ultrasonic, agarose gel and CV testing. Although some shedding was observed in the IrOx coating on the hierarchical substrate after one hour of sonication, it showed good stability in the agarose gel and CV tests. Stable nanoPt and IrOx coatings may not only improve the electrochemical performance but also benefit the function of neurobiochemical detection. Full article
(This article belongs to the Special Issue Neural Interface: From Material to System)
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