Implantable neurotechnologies: a review of integrated circuit neural amplifiers

Kian Ann Ng, Elliot Greenwald, Yong Ping Xu, Nitish V. Thakor

Research output: Contribution to journalReview articlepeer-review

45 Scopus citations

Abstract

Neural signal recording is critical in modern day neuroscience research and emerging neural prosthesis programs. Neural recording requires the use of precise, low-noise amplifier systems to acquire and condition the weak neural signals that are transduced through electrode interfaces. Neural amplifiers and amplifier-based systems are available commercially or can be designed in-house and fabricated using integrated circuit (IC) technologies, resulting in very large-scale integration or application-specific integrated circuit solutions. IC-based neural amplifiers are now used to acquire untethered/portable neural recordings, as they meet the requirements of a miniaturized form factor, light weight and low power consumption. Furthermore, such miniaturized and low-power IC neural amplifiers are now being used in emerging implantable neural prosthesis technologies. This review focuses on neural amplifier-based devices and is presented in two interrelated parts. First, neural signal recording is reviewed, and practical challenges are highlighted. Current amplifier designs with increased functionality and performance and without penalties in chip size and power are featured. Second, applications of IC-based neural amplifiers in basic science experiments (e.g., cortical studies using animal models), neural prostheses (e.g., brain/nerve machine interfaces) and treatment of neuronal diseases (e.g., DBS for treatment of epilepsy) are highlighted. The review concludes with future outlooks of this technology and important challenges with regard to neural signal amplification.

Original languageEnglish (US)
Pages (from-to)45-62
Number of pages18
JournalMedical and Biological Engineering and Computing
Volume54
Issue number1
DOIs
StatePublished - Jan 1 2016

Keywords

  • Central nervous system
  • Integrated circuits
  • Neural recording amplifier
  • Peripheral nervous system
  • VLSI

ASJC Scopus subject areas

  • Biomedical Engineering
  • Computer Science Applications

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