The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.
Failure mode analysis of silicon-based intracortical microelectrode arrays in non-human primates
Open accessAbstract
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“Previous demonstrations of intracortical insertion of MEAs showed injury and neuronal loss at the implantation location99, as well as signal instabilities contributing to signal loss and performance decline over time100,101.”
From The speech neuroprosthesis (2024) · cites this paper as [100]
In the citing paper
“In spite of the formidable results of using UEA/USEA technologies described above, most penetrating microelectrode arrays currently have maximum in vivo lifetimes of several months or a few years (Suner et al 2005, Prasad et al 2012, Barrese et al 2013).”
From Clinical applications of penetrating neural interfaces and Utah Electrode Array technologies (2016) · cites this paper as Barrese et al 2013
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Neuronal ensemble control of prosthetic devices by a human with tetraplegia
Hochberg, L. R., Serruya, M. D., Friehs, G. M., Mukand, J. A., Saleh, M., Caplan, A. H., Branner, A., Chen, D., Penn, R. D., & Donoghue, J. P. (2006) · Nature · doi:10.1038/nature04970 · Cited by 3,295
Self-citationReach and grasp by people with tetraplegia using a neurally controlled robotic arm
Hochberg, L. R., Bacher, D., Jarosiewicz, B., Masse, N. Y., Simeral, J. D., Vogel, J., Haddadin, S., Liu, J., Cash, S. S., van der Smagt, P., et al. (2012) · Nature · doi:10.1038/nature11076 · Cited by 2,719
Self-citationResponse of brain tissue to chronically implanted neural electrodes
Polikov, V. S., Tresco, P. A., & Reichert, W. M. (2005) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2005.08.015 · Cited by 1,896
Biran, R., Martin, D. C., & Tresco, P. A. (2005) · Experimental Neurology · doi:10.1016/j.expneurol.2005.04.020 · Cited by 893
Brain responses to micro-machined silicon devices
Szarowski, D. H., Andersen, M. D., Retterer, S. T., Spence, A. J., Isaacson, M. S., Craighead, H. G., Turner, J. N., & Shain, W. G. (2003) · Brain Research · doi:10.1016/s0006-8993(03)03023-3 · Cited by 811
Chronic recording capability of the Utah Intracortical Electrode Array in cat sensory cortex
Rousche, P. J., & Normann, R. A. (1998) · Journal of Neuroscience Methods · doi:10.1016/s0165-0270(98)00031-4 · Cited by 646
Cerebral Astrocyte Response to Micromachined Silicon Implants
Turner, J. N., Shain, W. G., Szarowski, D. H., Andersen, M., Martins, S., Isaacson, M. S., & Craighead, H. G. (1999) · Experimental Neurology · doi:10.1006/exnr.1998.6983 · Cited by 603
Single-neuron dynamics in human focal epilepsy
Truccolo, W., Donoghue, J., Hochberg, L. R., Eskandar, E. N., Madsen, J. R., Anderson, W. S., Brown, E. N., Halgren, E., & Cash, S. S. (2011) · Nature Neuroscience · doi:10.1038/nn.2782 · Cited by 528
Self-citationFactors influencing the biocompatibility of insertable silicon microshafts in cerebral cortex
Edell, D. J., Toi, V. V., McNeil, V. M., & Clark, L. D. (1992) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.141202 · Cited by 481
McConnell, G. C., Rees, H. D., Levey, A. I., Gutekunst, C.-A., Gross, R. E., & Bellamkonda, R. V. (2009) · Journal of Neural Engineering · doi:10.1088/1741-2560/6/5/056003 · Cited by 480
Research works printed but not linked: 2
- McConnell G C, 2009, J. Neural Eng., 6
- Prasad A, 2012, J. Neural Eng., 9
Cited by
Sorted by citations
Items 201–300 of 599
Second Harmonic Generation Imaging of Collagen in Chronically Implantable Electrodes in Brain Tissue
Esquibel, C. R., Wendt, K. D., Lee, H. C., Gaire, J., Shoffstall, A. J., Urdaneta, M. E., Chacko, J. V., Brodnick, S. K., Otto, K. J., Capadona, J. R., et al. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.00095 · Cited by 34
Development and Characterization of a Sucrose Microneedle Neural Electrode Delivery System
Apollo, N. V., Jiang, J. L., Cheung, W., Baquier, S. H., Lai, A., Mirebedini, A., Foroughi, J., Wallace, G. G., Shivdasani, M. N., Prawer, S., et al. (2017) · Advanced Biosystems · doi:10.1002/adbi.201700187 · Cited by 34
Gilmour, A. D., Woolley, A. J., Poole-Warren, L. A., Thomson, C. E., & Green, R. A. (2016) · Biomaterials · doi:10.1016/j.biomaterials.2016.03.011 · Cited by 34
Overcoming failure: improving acceptance and success of implanted neural interfaces
Dalrymple, A. N., Jones, S. T., Fallon, J. B., Shepherd, R. K., & Weber, D. J. (2025) · Bioelectronic Medicine · doi:10.1186/s42234-025-00168-7 · Cited by 38
Magnetically Inserted Neural Electrodes: Tissue Response and Functional Lifetime
Dryg, I., Ward, M. P., Qing, K. Y., Mei, H., Schaffer, J. E., & Irazoqui, P. P. (2015) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2015.2399856 · Cited by 33
Zhang, M., Schwemmer, M. A., Ting, J. E., Majstorovic, C., Friedenberg, D. A., Bockbrader, M. A., Mysiw, W. J., Rezai, A. R., Annetta, N. V., Bouton, C. E., et al. (2018) · Bioelectronic Medicine · doi:10.1186/s42234-018-0011-x · Cited by 33
The role of inflammation on the functionality of intracortical microelectrodes
Gaire, J., Lee, H. C., Hilborn, N., Ward, R., Regan, M., & Otto, K. J. (2018) · Journal of Neural Engineering · doi:10.1088/1741-2552/aae4b6 · Cited by 35
Sommakia, S., Gaire, J., Rickus, J. L., & Otto, K. J. (2014) · Frontiers in Neuroengineering · doi:10.3389/fneng.2014.00033 · Cited by 32
Demonstration of a Robust All-Silicon-Carbide Intracortical Neural Interface
Bernardin, E. K., Frewin, C. L., Everly, R., Ul‐Hassan, J., & Saddow, S. E. (2018) · Micromachines · doi:10.3390/mi9080412 · Cited by 35
Automated reactive accelerated aging for rapid in vitro evaluation of neural implant performance
Street, M. G., Welle, C. G., & Takmakov, P. A. (2018) · Review of Scientific Instruments · doi:10.1063/1.5024686 · Cited by 31
Intracortical Microelectrode Array Unit Yield under Chronic Conditions: A Comparative Evaluation
Usoro, J. O., Sturgill, B. S., Musselman, K. C., Capadona, J. R., & Pancrazio, J. J. (2021) · Micromachines · doi:10.3390/mi12080972 · Cited by 34
Stocking, K. C., Vazquez, A. L., & Kozai, T. D. Y. (2019) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2018.2889832 · Cited by 29
Amorphous Silicon Carbide Platform for Next Generation Penetrating Neural Interface Designs
Deku, F., Frewin, C. L., Stiller, A. M., Cohen, Y., Aqeel, S., Joshi‐Imre, A., Black, B., Gardner, T. J., Pancrazio, J. J., & Cogan, S. F. (2018) · Micromachines · doi:10.3390/mi9100480 · Cited by 30
Understanding the Role of Innate Immunity in the Response to Intracortical Microelectrodes
Hermann, J. K., & Capadona, J. R. (2018) · Critical Reviews in Biomedical Engineering · doi:10.1615/critrevbiomedeng.2018027166 · Cited by 31
DARPA investment in peripheral nerve interfaces for prosthetics, prescriptions, and plasticity
Naufel, S. N., Knaack, G. L., Miranda, R. A., Best, T. K., Fitzpatrick, K., Emondi, A. A., Gieson, E. J. V., & McClure‐Begley, T. D. (2019) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2019.108539 · Cited by 30
NeuroRoots, a bio-inspired, seamless Brain Machine Interface device for long-term recordingPreprint
Ferro, M. D., Proctor, C. M., Gonzalez, A., Zhao, E. T., Slézia, A., Pas, J., Dijk, G., Donahue, M. J., Williamson, A., Malliaras, G. G., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/460949 · Cited by 32
Haghi, B., Aflalo, T., Kellis, S., Guan, C., Gámez, J., Huang, A. Y., Pouratian, N., Andersen, R. A., & Emami, A. (2024) · Nature Biomedical Engineering · doi:10.1038/s41551-024-01297-1 · Cited by 36
Bjånes, D. A., Kellis, S., Nickl, R., Baker, B., Aflalo, T., Bashford, L., Chivukula, S., Fifer, M. S., Osborn, L. E., Christie, B., et al. (2025) · Acta Biomaterialia · doi:10.1016/j.actbio.2025.02.030 · Cited by 37
Even-Chen, N., Stavisky, S. D., Pandarinath, C., Nuyujukian, P., Blabe, C. H., Hochberg, L. R., Henderson, J. M., & Shenoy, K. V. (2017) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2017.2776204 · Cited by 31
Nano functional neural interfaces
Wang, Y., Zhu, H., Yang, H., Argall, A. D., Luan, L., Xie, C., & Guo, L. (2018) · Nano Research · doi:10.1007/s12274-018-2127-4 · Cited by 30
Longitudinal neural and vascular structural dynamics produced by chronic microelectrode implantation
Welle, C. G., Gao, Y., Ye, M., Lozzi, A., Boretsky, A. R., Abliz, E., & Hammer, D. X. (2020) · Biomaterials · doi:10.1016/j.biomaterials.2020.119831 · Cited by 27
Chen, K., Cambi, F., & Kozai, T. D. Y. (2023) · Biomaterials · doi:10.1016/j.biomaterials.2023.122210 · Cited by 27
Bedell, H. W., Song, S., Li, X., Molinich, E., Lin, S., Stiller, A. M., Danda, V. R., Ecker, M., Shoffstall, A. J., Voit, W. E., et al. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00772 · Cited by 29
Dunlap, C. F., Colachis, S. C., Meyers, E., Bockbrader, M. A., & Friedenberg, D. A. (2020) · Frontiers in Neurorobotics · doi:10.3389/fnbot.2020.558987 · Cited by 30
CMOS stimulating chips capable of wirelessly driving 473 electrodes for a cortical vision prosthesis
Wong, Y. T., Feleppa, T., Mohan, A., Browne, D., Szlawski, J., Rosenfeld, J. V., & Lowery, A. (2019) · Journal of Neural Engineering · doi:10.1088/1741-2552/ab021b · Cited by 27
Flexible Polymer Electrodes for Stable Prosthetic Visual Perception in Mice
Orlemann, C., Boehler, C., Kooijmans, R. N., Li, B., Asplund, M., & Roelfsema, P. R. (2024) · Advanced Healthcare Materials · doi:10.1002/adhm.202304169 · Cited by 26
Enhancing biocompatibility of the brain-machine interface: A review
Villa, J., Cury, J., Kessler, L., Tan, X., & Richter, C. (2024) · Bioactive Materials · doi:10.1016/j.bioactmat.2024.08.034 · Cited by 31
Neural vs Neuromorphic Interfaces: Where Are We Standing?
Rana, D., Babushkina, N., Gini, M., Cáceres, A., Li, H., Maybeck, V., Criscuolo, V., Mayer, D., Ienca, M., Musall, S., et al. (2025) · Chemical Reviews · doi:10.1021/acs.chemrev.4c00862 · Cited by 29
Davis, K., Meschede-Krasa, B., Cajigas, I., Prins, N. W., Alver, C. G., Gallo, S., Bhatia, S., Abel, J. H., Naeem, J., Fisher, L., et al. (2022) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-022-01026-2 · Cited by 31
Song, S., Regan, B., Ereifej, E. S., Chan, E. R., & Capadona, J. R. (2022) · Cells · doi:10.3390/cells11152348 · Cited by 28
Structural analysis of explanted microelectrode arrays
Gilgunn, P. J., Ong, X. C., Flesher, S. N., Schwartz, A. B., & Gaunt, R. A. (2013) · International IEEE/EMBS Conference on Neural Engineering · doi:10.1109/ner.2013.6696035 · Cited by 27
Mols, K., Musa, S., Nuttin, B., Lagae, L., & Bonin, V. (2017) · Scientific Reports · doi:10.1038/s41598-017-15121-1 · Cited by 26
Neural engineering: the process, applications, and its role in the future of medicine
Ereifej, E. S., Shell, C. E., Schofield, J. S., Charkhkar, H., Cuberovic, I., Dorval, A. D., Graczyk, E. L., Kozai, T. D. Y., Otto, K. J., Tyler, D. J., et al. (2019) · Journal of Neural Engineering · doi:10.1088/1741-2552/ab4869 · Cited by 30
Approaches to a cortical vision prosthesis: implications of electrode size and placement
Christie, B. P., Ashmont, K. R., House, P. A., & Greger, B. (2016) · Journal of Neural Engineering · doi:10.1088/1741-2560/13/2/025003 · Cited by 26
Čvančara, P., Valle, G., Müller, M., Bartels, I., Guiho, T., Hiairrassary, A., Petrini, F. M., Raspopović, S., Strauss, I., Granata, G., et al. (2023) · npj Flexible Electronics · doi:10.1038/s41528-023-00284-x · Cited by 27
In vivo microelectrode arrays for neuroscience
Williams, N. P., Vöröslakos, M., Shi, D., Pwint, M. Y., Lanzio, V., Mao, H., Zolotavin, P., Yoon, E., Stieglitz, T., Xie, C., et al. (2025) · Nature Reviews Methods Primers · doi:10.1038/s43586-025-00399-7 · Cited by 30
A Framework for Optimizing Co-adaptation in Body-Machine Interfaces
Santis, D. D. (2021) · Frontiers in Neurorobotics · doi:10.3389/fnbot.2021.662181 · Cited by 27
Urdaneta, M. E., Kunigk, N. G., Currlin, S., Delgado, F., Fried, S. I., & Otto, K. J. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.908858 · Cited by 24
A Single Electronic Tattoo for Multisensory Integration
Wang, Z., Zhou, Z. J., Li, C., Liu, X., Zhang, Y., Pei, M., Zhou, Z. Y., Cui, D., Hu, D., Chen, F., et al. (2023) · Small Methods · doi:10.1002/smtd.202201566 · Cited by 27
The History and Horizons of Microscale Neural Interfaces
Kozai, T. D. Y. (2018) · Micromachines · doi:10.3390/mi9090445 · Cited by 29
Murphy, B. A., Miller, J. P., Gunalan, K., & Ajiboye, A. B. (2016) · PLoS ONE · doi:10.1371/journal.pone.0150359 · Cited by 25
Implantable Neural Microelectrodes: How to Reduce Immune Response
Xiang, Y., Zhao, Y., Cheng, T., Sun, S., Wang, J., & Pei, R. (2024) · ACS Biomaterials Science & Engineering · doi:10.1021/acsbiomaterials.4c00238 · Cited by 25
Building an adaptive interface via unsupervised tracking of latent manifolds
Rizzoglio, F., Casadio, M., Santis, D. D., & Mussa-Ivaldi, F. A. (2021) · Neural Networks · doi:10.1016/j.neunet.2021.01.009 · Cited by 25
Insertion mechanics of amorphous SiC ultra-micro scale neural probes
Geramifard, N., Dousti, B., Nguyen, C. K., Abbott, J., Cogan, S. F., & Varner, V. D. (2022) · Journal of Neural Engineering · doi:10.1088/1741-2552/ac5bf4 · Cited by 24
Fiáth, R., Hofer, K. T., Csikós, V., Horváth, D., Nánási, T., Tóth, K., Pothof, F., Böhler, C., Asplund, M., Ruther, P., et al. (2018) · Biomedizinische Technik/Biomedical Engineering · doi:10.1515/bmt-2017-0154 · Cited by 25
Liu, S., Moncion, C., Zhang, J., Balachandar, L., Kwaku, D., Riera, J. J., Volakis, J. L., & Chae, J. (2019) · ACS Sensors · doi:10.1021/acssensors.9b01491 · Cited by 24
Chakraborty, B., Joshi‐Imre, A., & Cogan, S. F. (2021) · Journal of Biomedical Materials Research Part B Applied Biomaterials · doi:10.1002/jbm.b.34906 · Cited by 24
Electrode sharpness and insertion speed reduce tissue damage near high-density penetrating arrays
McNamara, I., Wellman, S. M., Li, L., Eles, J. R., Savya, S. P., Sohal, H. S., Angle, M. R., & Kozai, T. D. Y. (2024) · Journal of Neural Engineering · doi:10.1088/1741-2552/ad36e1 · Cited by 24
Ghane-Motlagh, B., Javanbakht, T., Shoghi, F., Wilkinson, K. J., Martel, R., & Sawan, M. (2016) · Materials Science and Engineering C · doi:10.1016/j.msec.2016.06.045 · Cited by 23
Placing Sites on the Edge of Planar Silicon Microelectrodes Enhances Chronic Recording Functionality
Lee, H. C., Gaire, J., Roysam, B., & Otto, K. J. (2017) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2017.2715811 · Cited by 23
Hermann, J. K., Lin, S., Soffer, A., Wong, C., Ali, A., Chang, J. B., Sunil, S., Sudhakar, S., Tomaszewski, W. H., Protasiewicz, G., et al. (2018) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2018.00113 · Cited by 23
Schulte, J., Vajari, D. A., & Stieglitz, T. (2023) · Advanced Functional Materials · doi:10.1002/adfm.202310130 · Cited by 23
Rocha, D., Lopes, P. A., Peixoto, P., de Almeida, A. T., & Tavakoli, M. (2025) · Advanced Functional Materials · doi:10.1002/adfm.202417053 · Cited by 22
Design of Ceramic Packages for Ultrasonically Coupled Implantable Medical Devices
Shen, K., & Maharbiz, M. M. (2019) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2019.2957732 · Cited by 23
Commonly Overlooked Factors in Biocompatibility Studies of Neural Implants
Kumosa, L. S. (2023) · Advanced Science · doi:10.1002/advs.202205095 · Cited by 21
Flexible multichannel electrodes for acute recording in nonhuman primates
Wang, Y., Wang, Q., Zheng, R., Xu, X., Yang, X., Gui, Q., Yang, X., Wang, Y., Cui, H., & Pei, W. (2023) · Microsystems & Nanoengineering · doi:10.1038/s41378-023-00550-y · Cited by 22
Ferro, M. D., Proctor, C. M., Gonzalez, A., Jayabal, S., Zhao, E. T., Gagnon, M., Slézia, A., Pas, J., Dijk, G., Donahue, M. J., et al. (2024) · AIP Advances · doi:10.1063/5.0216979 · Cited by 20
Advances in Penetrating Multichannel Microelectrodes Based on the Utah Array Platform
Leber, M., Körner, J., Reiche, C. F., Yin, M., Bhandari, R., Franklin, R. K., Negi, S., & Solzbacher, F. (2019) · Advances in experimental medicine and biology · doi:10.1007/978-981-13-2050-7_1 · Cited by 24
Advanced Electrical and Optical Microsystems for Biointerfacing
Obaid, S. N., Chen, Z., & Lu, L. (2020) · Advanced Intelligent Systems · doi:10.1002/aisy.202000091 · Cited by 21
Lifetime engineering of bioelectronic implants with mechanically reliable thin film encapsulations
Niemiec, M., & Kim, K. (2023) · Progress in Biomedical Engineering · doi:10.1088/2516-1091/ad0b19 · Cited by 22
Pun, T. K., Khoshnevis, M., Hosman, T., Wilson, G. H., Kapitonava, A., Kamdar, F. B., Henderson, J. M., Simeral, J. D., Vargas-Irwin, C. E., Harrison, M. T., et al. (2024) · Communications Biology · doi:10.1038/s42003-024-06784-4 · Cited by 26
Self-citationEffects of neuronal cell adhesion molecule L1 and nanoparticle surface modification on microglia
Kushwah, N. S., Woeppel, K. M., Dhawan, V., Shi, D., & Cui, X. T. (2022) · Acta Biomaterialia · doi:10.1016/j.actbio.2022.06.038 · Cited by 22
Gregory, B. A., Thompson, C. H., Salatino, J. W., Railing, M. J., Zimmerman, A. F., Gupta, B., Williams, K., Beatty, J. A., Cox, C. L., & Purcell, E. K. (2023) · Acta Biomaterialia · doi:10.1016/j.actbio.2023.07.027 · Cited by 24
Soft, wireless and subdermally implantable recording and neuromodulation tools
Cai, L., & Gutruf, P. (2021) · Journal of Neural Engineering · doi:10.1088/1741-2552/abe805 · Cited by 23
Brandman, D. M., & Hochberg, L. R. (2016) · Wiley eBooks · doi:10.1002/9781118816028.ch9 · Cited by 23
Liquid Crystalline Polymers: Opportunities to Shape Neural Interfaces
Rihani, R. T., Tasnim, N., Javed, M., Usoro, J. O., D'Souza, T. M., Ware, T. H., & Pancrazio, J. J. (2021) · Neuromodulation Technology at the Neural Interface · doi:10.1111/ner.13364 · Cited by 20
Conformable neural interface based on off-stoichiometry thiol-ene-epoxy thermosets
Borda, E., Medagoda, D. I., Leccardi, M. J. I. A., Zollinger, E. G., & Ghezzi, D. (2022) · Biomaterials · doi:10.1016/j.biomaterials.2022.121979 · Cited by 20
Firing-rate-modulated spike detection and neural decoding co-design
Zhang, Z., & Constandinou, T. G. (2023) · Journal of Neural Engineering · doi:10.1088/1741-2552/accece · Cited by 20
Emerging Penetrating Neural Electrodes: In Pursuit of Large Scale and Longevity
Luan, L., Yin, R., Zhu, H., & Xie, C. (2023) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-090622-050507 · Cited by 23
Quantitative simulation of extracellular single unit recording from the surface of cortex
Hill, M., Rios, E., Sudhakar, S., Roossien, D. H., Caldwell, C. M., Cai, D., Ahmed, O. J., Lempka, S. F., & Chestek, C. A. (2018) · Journal of Neural Engineering · doi:10.1088/1741-2552/aacdb8 · Cited by 19
Hoeferlin, G. F., Grabinski, S. E., Druschel, L. N., Duncan, J. L., Burkhart, G., Weagraff, G. R., Lee, A. H., Hong, C., Bambroo, M., Olivares, H., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-56979-4 · Cited by 21
A Continuous, Impedimetric Parylene Flow Sensor
Hudson, T. Q., & Meng, E. F. (2021) · Journal of Microelectromechanical Systems · doi:10.1109/jmems.2021.3067573 · Cited by 19
An RF-Ultrasound Relay for Adaptive Wireless Powering Across Tissue Interfaces
So, E., Yeon, P., Chichilnisky, E. J., & Arbabian, A. (2022) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2022.3171233 · Cited by 19
Calibration-Free and Hardware-Efficient Neural Spike Detection for Brain Machine Interfaces
Zhang, Z., Feng, P., Oprea, A., & Constandinou, T. G. (2023) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2023.3278531 · Cited by 20
Plasticity and Recovery after Dorsal Column Spinal Cord Injury in Nonhuman Primates
Reed, J. L., Liao, C., Qi, H., & Kaas, J. H. (2016) · Journal of Experimental Neuroscience · doi:10.4137/jen.s40197 · Cited by 19
A novel microwire interface for small diameter peripheral nerves in a chronic, awake murine model
Falcone, J., Liu, T., Goldman, L., Pogue David, D., Rieth, L. W., Bouton, C. E., Straka, M., & Sohal, H. S. (2020) · Journal of Neural Engineering · doi:10.1088/1741-2552/ab9b6d · Cited by 19
Debnath, S., Prins, N. W., Pohlmeyer, E. A., Mylavarapu, R. V., Geng, S., Sanchez, J. C., & Prasad, A. (2018) · Biomedical Physics & Engineering Express · doi:10.1088/2057-1976/aada67 · Cited by 18
Evaluation methods for long-term reliability of polymer-based implantable biomedical devices
Lee, D. H., Kim, C. H., Youn, J., & Jeong, J. (2021) · Biomedical Engineering Letters · doi:10.1007/s13534-021-00188-7 · Cited by 18
Ahmadi, N., Adiono, T., Purwarianti, A., Constandinou, T. G., & Bouganis, C.-S. (2022) · IEEE Access · doi:10.1109/access.2022.3159225 · Cited by 18
A model of space-fractional-order diffusion in the glial scar
Prodanov, D., & Delbeke, J. (2016) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2016.04.031 · Cited by 18
Mahajan, S., Hermann, J. K., Bedell, H. W., Sharkins, J. A., Chen, L., Chen, K., Meade, S. M., Smith, C. S., Rayyan, J., Feng, H., et al. (2020) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2020.00416 · Cited by 17
Pikov, V., McCreery, D. B., & Han, M. (2020) · Journal of Neural Engineering · doi:10.1088/1741-2552/abca13 · Cited by 18
Bouton, C. E. (2020) · Handbook of clinical neurology · doi:10.1016/b978-0-444-63934-9.00022-6 · Cited by 18
Recording of pig neuronal activity in the comparative context of the awake human brain
Dobariya, A., Ahmadieh, T. Y. E., Good, L. B., Hernandez-Reynoso, A. G., Jakkamsetti, V., Brown, R., Dunbar, M. L., Ding, K., Luna, J., Kallem, R. R., et al. (2022) · Scientific Reports · doi:10.1038/s41598-022-19688-2 · Cited by 17
Hoeferlin, G. F., Bajwa, T. S., Olivares, H., Zhang, J., Druschel, L. N., Sturgill, B. S., Sobota, M., Boucher, P., Duncan, J., Hernandez-Reynoso, A. G., et al. (2023) · Micromachines · doi:10.3390/mi14101902 · Cited by 16
Chen, K., Forrest, A. M., Burgos, G.-G., & Kozai, T. D. Y. (2024) · Journal of Neural Engineering · doi:10.1088/1741-2552/ad5049 · Cited by 16
Interfacing Neuron-Motor Pathways with Stretchable and Biocompatible Electrode Arrays
Jiang, Z., Zhu, M. J., & Chen, X. (2024) · Accounts of Chemical Research · doi:10.1021/acs.accounts.4c00215 · Cited by 18
Electrochemical impedance spectroscopy in vivo for neurotechnology and bioelectronics
Hazelgrove, B., Matter, L., Raos, B. J., Harland, B. C., Cheng, L. K., Asplund, M., & Svirskis, D. M. (2025) · Nature Reviews Electrical Engineering · doi:10.1038/s44287-024-00126-6 · Cited by 16
Local Field Potential Analysis for Closed-Loop Neuromodulation
Maling, N., & McIntyre, C. C. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-802452-2.00005-6 · Cited by 17
Miniature electroparticle-cuff for wireless peripheral neuromodulation
Hernandez-Reynoso, A. G., Nandam, S., O’Brien, J. M., Kanneganti, A., Cogan, S. F., Freeman, D. K., & Romero‐Ortega, M. I. (2019) · Journal of Neural Engineering · doi:10.1088/1741-2552/ab1c36 · Cited by 16
Dubaniewicz, M. T., Eles, J. R., Lam, S., Song, S., Cambi, F., Sun, D., Wellman, S. M., & Kozai, T. D. Y. (2021) · Journal of Neural Engineering · doi:10.1088/1741-2552/abe8f1 · Cited by 17
Implanting mechanics of PEG/DEX coated flexible neural probe: impacts of fabricating methods
Zhang, W., Zhou, X., He, Y., Xu, L., & Xie, J. (2021) · Biomedical Microdevices · doi:10.1007/s10544-021-00552-5 · Cited by 18
Golabchi, A., Wu, B., Du, Z. J., & Cui, X. T. (2025) · Advanced NanoBiomed Research · doi:10.1002/anbr.202400114 · Cited by 16
Franklin, M. E., Bennett, C., Arboite, M., Álvarez-Ciara, A., Corrales, N., Verdelus, J., Dietrich, W. D., Keane, R. W., Vaccari, J. P. D. R., & Prasad, A. (2023) · Biomaterials · doi:10.1016/j.biomaterials.2023.122102 · Cited by 17
Devices for the electrical stimulation of the olfactory system: A review
Lipp, C., Laamari, L., Bertsch, A., Podlesek, D., Bensafi, M., Hummel, T. R., & Brugger, J. (2024) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2024.117063 · Cited by 15
Jiang, J., Willett, F. R., & Taylor, D. M. (2014) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2014.6944265 · Cited by 16
Ferroni, C. G., Maranesi, M., Livi, A., Lanzilotto, M., & Bonini, L. (2017) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2017.00084 · Cited by 16
A Flexible a-SiC-Based Neural Interface Utilizing Pyrolyzed-Photoresist Film (C) Active Sites
Feng, C., Frewin, C. L., Tanjil, M. R., Everly, R., Bieber, J. A., Kumar, A., Wang, M. C., & Saddow, S. E. (2021) · Micromachines · doi:10.3390/mi12070821 · Cited by 15
Yu, X. P., Su, J., Guo, J. Y., Zhang, X., Li, R. H., Chai, X., Chen, Y., Zhang, D. G., Wang, J., Sui, X., et al. (2019) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2019.108450 · Cited by 16
Advances in flexible high-density microelectrode arrays for brain-computer interfaces
Ban, S., Chong, D., Kwon, J., Lee, S., Huang, Y., Yoo, S., & Yeo, W. (2025) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2025.118102 · Cited by 15
Metadata
- 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
- 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
- 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
- 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
