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Micromachines
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Implantable Neural Sensors for the Brain Machine Interface
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Implantable Neural Sensors for the Brain Machine Interface

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

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 15711

Special Issue Editor

Prof. Dr. Yoon-Kyu Song

E-Mail Website
Guest Editor
Department of Applied Bioengineering, Graduate School of Convergence Science and Technology, Seoul National University, Seoul 08826, Republic of Korea
Interests: nano and micro electronic; photonic; mechanical devices and their applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Over the last few decades, there has been significant progress made towards our understanding of the mechanisms of brain functions and their role in neurological diseases. Among various neuro-technological tools contributing to this progress, brain–machine interfaces (BMI) with implantable neural sensors have played a key role by enabling the detection of neural activity at unprecedented spatio-temporal resolution from animals. Moreover, recent human clinical trials have extended the potential application of implantable neural sensors to the territory of human health. Through this Special Issue, we would like to establish a forum to discuss the recent developments, remaining challenges, and future directions of implantable neural sensors for brain–machine interfaces.

We invite research papers, reviews and shorter communications that focus on the system design, materials, device fabrication, packaging and characterization of implantable neural sensors to contribute to this Special Issue. Topics of particular interest include, but are not limited to:

  • Implantable ultra-high density or 3D multi-electrode arrays (MEAs)
  • Multi-modal neural probes and sensors
  • Flexible or deformable neural probes
  • Ultra-low power systems-on-a-chip (SoC) for neural sensors
  • Ultra-high density neural sensing microsystems
  • Distributed neural sensing microdevices
  • Energy delivery/harvesting and neural data transmission strategies
  • Microsystem integration technologies
  • Encapsulation materials and techniques
  • Long-term reliability of implantable sensors
  • Implantable sensors for peripheral nerve systems
  • Alternative applications of implantable neural sensors (e.g. sensory prosthetics)
  • Behavioral study in animals with implantable neural sensors
  • Preclinical and clinical trials of implantable neural sensors

Assoc. Prof. Yoon-Kyu Song
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.

Published Papers (3 papers)

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Research

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15 pages, 4573 KiB  
Article
A Scalable and Low Stress Post-CMOS Processing Technique for Implantable Microsensors
by Ah-Hyoung Lee, Jihun Lee, Farah Laiwalla, Vincent Leung, Jiannan Huang, Arto Nurmikko and Yoon-Kyu Song
Micromachines 2020, 11(10), 925; https://doi.org/10.3390/mi11100925 - 5 Oct 2020
Cited by 13 | Viewed by 4881
Abstract
Implantable active electronic microchips are being developed as multinode in-body sensors and actuators. There is a need to develop high throughput microfabrication techniques applicable to complementary metal–oxide–semiconductor (CMOS)-based silicon electronics in order to process bare dies from a foundry to physiologically compatible implant [...] Read more.
Implantable active electronic microchips are being developed as multinode in-body sensors and actuators. There is a need to develop high throughput microfabrication techniques applicable to complementary metal–oxide–semiconductor (CMOS)-based silicon electronics in order to process bare dies from a foundry to physiologically compatible implant ensembles. Post-processing of a miniature CMOS chip by usual methods is challenging as the typically sub-mm size small dies are hard to handle and not readily compatible with the standard microfabrication, e.g., photolithography. Here, we present a soft material-based, low chemical and mechanical stress, scalable microchip post-CMOS processing method that enables photolithography and electron-beam deposition on hundreds of micrometers scale dies. The technique builds on the use of a polydimethylsiloxane (PDMS) carrier substrate, in which the CMOS chips were embedded and precisely aligned, thereby enabling batch post-processing without complication from additional micromachining or chip treatments. We have demonstrated our technique with 650 μm × 650 μm and 280 μm × 280 μm chips, designed for electrophysiological neural recording and microstimulation implants by monolithic integration of patterned gold and PEDOT:PSS electrodes on the chips and assessed their electrical properties. The functionality of the post-processed chips was verified in saline, and ex vivo experiments using wireless power and data link, to demonstrate the recording and stimulation performance of the microscale electrode interfaces. Full article
(This article belongs to the Special Issue Implantable Neural Sensors for the Brain Machine Interface)
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9 pages, 1195 KiB  
Communication
An Implantable Cranial Window Using a Collagen Membrane for Chronic Voltage-Sensitive Dye Imaging
by Nobuo Kunori and Ichiro Takashima
Micromachines 2019, 10(11), 789; https://doi.org/10.3390/mi10110789 - 18 Nov 2019
Cited by 11 | Viewed by 4499
Abstract
Incorporating optical methods into implantable neural sensing devices is a challenging approach for brain–machine interfacing. Specifically, voltage-sensitive dye (VSD) imaging is a powerful tool enabling visualization of the network activity of thousands of neurons at high spatiotemporal resolution. However, VSD imaging usually requires [...] Read more.
Incorporating optical methods into implantable neural sensing devices is a challenging approach for brain–machine interfacing. Specifically, voltage-sensitive dye (VSD) imaging is a powerful tool enabling visualization of the network activity of thousands of neurons at high spatiotemporal resolution. However, VSD imaging usually requires removal of the dura mater for dye staining, and thereafter the exposed cortex needs to be protected using an optically transparent artificial dura. This is a major disadvantage that limits repeated VSD imaging over the long term. To address this issue, we propose to use an atelocollagen membrane as the dura substitute. We fabricated a small cranial chamber device, which is a tubular structure equipped with a collagen membrane at one end of the tube. We implanted the device into rats and monitored neural activity in the frontal cortex 1 week following surgery. The results indicate that the collagen membrane was chemically transparent, allowing VSD staining across the membrane material. The membrane was also optically transparent enough to pass light; forelimb-evoked neural activity was successfully visualized through the artificial dura. Because of its ideal chemical and optical manipulation capability, this collagen membrane may be widely applicable in various implantable neural sensors. Full article
(This article belongs to the Special Issue Implantable Neural Sensors for the Brain Machine Interface)
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Review

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22 pages, 388 KiB  
Review
Emerging Encapsulation Technologies for Long-Term Reliability of Microfabricated Implantable Devices
by Seung-Hee Ahn, Joonsoo Jeong and Sung June Kim
Micromachines 2019, 10(8), 508; https://doi.org/10.3390/mi10080508 - 31 Jul 2019
Cited by 55 | Viewed by 5803
Abstract
The development of reliable long-term encapsulation technologies for implantable biomedical devices is of paramount importance for the safe and stable operation of implants in the body over a period of several decades. Conventional technologies based on titanium or ceramic packaging, however, are not [...] Read more.
The development of reliable long-term encapsulation technologies for implantable biomedical devices is of paramount importance for the safe and stable operation of implants in the body over a period of several decades. Conventional technologies based on titanium or ceramic packaging, however, are not suitable for encapsulating microfabricated devices due to their limited scalability, incompatibility with microfabrication processes, and difficulties with miniaturization. A variety of emerging materials have been proposed for encapsulation of microfabricated implants, including thin-film inorganic coatings of Al2O3, HfO2, SiO2, SiC, and diamond, as well as organic polymers of polyimide, parylene, liquid crystal polymer, silicone elastomer, SU-8, and cyclic olefin copolymer. While none of these materials have yet been proven to be as hermetic as conventional metal packages nor widely used in regulatory approved devices for chronic implantation, a number of studies have demonstrated promising outcomes on their long-term encapsulation performance through a multitude of fabrication and testing methodologies. The present review article aims to provide a comprehensive, up-to-date overview of the long-term encapsulation performance of these emerging materials with a specific focus on publications that have quantitatively estimated the lifetime of encapsulation technologies in aqueous environments. Full article
(This article belongs to the Special Issue Implantable Neural Sensors for the Brain Machine Interface)
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