Cited by 600Neuroscience and Neural EngineeringEEG and Brain-Computer InterfacesAnalog and Mixed-Signal Circuit Design

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Failure mode analysis of silicon-based intracortical microelectrode arrays in non-human primates

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Barrese, James C, Rao, Naveen, Paroo, Kaivon, Triebwasser, Corey, Vargas-Irwin, Carlos, Franquemont, Lachlan, Donoghue, John P·2013·Journal of Neural Engineering

DOI 10.1088/1741-2560/10/6/066014PMC PMC4868924

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Abstract

OBJECTIVE: Brain-computer interfaces (BCIs) using chronically implanted intracortical microelectrode arrays (MEAs) have the potential to restore lost function to people with disabilities if they work reliably for years. Current sensors fail to provide reliably useful signals over extended periods of time for reasons that are not clear. This study reports a comprehensive retrospective analysis from a large set of implants of a single type of intracortical MEA in a single species, with a common set of measures in order to evaluate failure modes. APPROACH: Since 1996, 78 silicon MEAs were implanted in 27 monkeys (Macaca mulatta). We used two approaches to find reasons for sensor failure. First, we classified the time course leading up to complete recording failure as acute (abrupt) or chronic (progressive). Second, we evaluated the quality of electrode recordings over time based on signal features and electrode impedance. Failure modes were divided into four categories: biological, material, mechanical, and unknown. MAIN RESULTS: Recording duration ranged from 0 to 2104 days (5.75 years), with a mean of 387 days and a median of 182 days (n = 78). Sixty-two arrays failed completely with a mean time to failure of 332 days (median = 133 days) while nine array experiments were electively terminated for experimental reasons (mean = 486 days). Seven remained active at the close of this study (mean = 753 days). Most failures (56%) occurred within a year of implantation, with acute mechanical failures the most common class (48%), largely because of connector issues (83%). Among grossly observable biological failures (24%), a progressive meningeal reaction that separated the array from the parenchyma was most prevalent (14.5%). In the absence of acute interruptions, electrode recordings showed a slow progressive decline in spike amplitude, noise amplitude, and number of viable channels that predicts complete signal loss by about eight years. Impedance measurements showed systematic early increases, which did not appear to affect recording quality, followed by a slow decline over years. The combination of slowly falling impedance and signal quality in these arrays indicates that insulating material failure is the most significant factor. SIGNIFICANCE: This is the first long-term failure mode analysis of an emerging BCI technology in a large series of non-human primates. The classification system introduced here may be used to standardize how neuroprosthetic failure modes are evaluated. The results demonstrate the potential for these arrays to record for many years, but achieving reliable sensors will require replacing connectors with implantable wireless systems, controlling the meningeal reaction, and improving insulation materials. These results will focus future research in order to create clinical neuroprosthetic sensors, as well as valuable research tools, that are able to safely provide reliable neural signals for over a decade.

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Authors: Barrese, J. C., Rao, N., Paroo, K., Triebwasser, C., Vargas-Irwin, C., Franquemont, L., & Donoghue, J. P.
Affiliations: Brown University (US)
Corresponding author: Barrese, James C
Rao, Naveen
Paroo, Kaivon
Triebwasser, Corey
Vargas-Irwin, Carlos
Franquemont, Lachlan
Donoghue, John P
ORCID: Vargas-Irwin, Carlos
Donoghue, John P
Venue: Journal of Neural Engineering
Publisher: IOP Publishing
Published: 2013-11-12
Volume: 10
Issue: 6
Pages: 066014
ISSN: 1741-2552 (ISSN-L)
1741-2560
DOI: 10.1088/1741-2560/10/6/066014
PMC: PMC4868924
OpenAlex: W1999169980
Cited by: 600
References: 42
Citations by year: 2026: 39 · 2025: 40 · 2024: 43 · 2023: 49 · 2022: 38 · 2021: 63 · 2020: 68 · 2019: 53 · 2018: 67 · 2017: 47 · 2016: 34 · 2015: 28 · 2014: 28 · 2013: 1
FWCI: 14.88
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Licence: iopscience.iop.org/info/page/text-and-data-mining (tdm)
iopscience.iop.org/page/copyright (vor)
Locations: Journal of Neural Engineering (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
Funders: National Institute of Neurological Disorders and Stroke (R01NS025074)
Topics: Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
Physical Sciences › Engineering › Electrical and Electronic Engineering › Analog and Mixed-Signal Circuit Design
Keywords: intracortical microelectrode arrays, failure mode analysis, brain-computer interface, chronic implantation, non-human primates, rhesus monkeys, silicon microelectrodes, electrode impedance, meningeal reaction, connector failure, neuroprosthetics, chronic neural recording, recording duration
MeSH terms: Animals, Cerebral Cortex, Electrodes, Implanted, Female, Macaca mulatta, Male, Microelectrodes, Silicon, Equipment Failure Analysis

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Failure mode analysis of silicon-based intracortical microelectrode arrays in non-human primates

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