Tissue response to a chronically implantable wireless intracortical visual prosthesis (Gennaris array)
Abstract
OBJECTIVE: Cortical vision prostheses aim to restore visual percepts to those who have lost sight by delivering electrical stimulation to the visual cortex. These devices need to be implanted intracranially using subdural or intracortical microelectrodes, and should preferably dispense with the need of transcranial wiring. The risks of cortical tissue injury from mechanical trauma, material biocompatibility, heat generation, electrical stimulation and long-term immune responses need to be evaluated. In this paper, we investigate the biological response to a wireless cortical vision prosthesis (Gennaris array), by characterizing the histological changes that occur following chronic electrical stimulation. APPROACH: Ten arrays (7 active, 3 passive) were implanted in three sheep using a pneumatic insertor. Each device consisted of a wireless receiver and Application Specific Integrated Circuit encased in a ceramic box, and could deliver electrical stimulation through one of 43 electrodes. MAIN RESULTS: Stimulation was delivered through seven of these devices for up to 3 months and each device was treated as independent for further analysis. Cumulatively, over 2700 h of stimulation were achieved without any observable adverse health effects. Histology showed that the devices and implantation procedure were well tolerated by the brain with a similar tissue response to the more common Utah arrays. However, voltage transients across the stimulating electrodes were not measured so exact charge injection could not be verified. SIGNIFICANCE: This work represents one of the first long-term tests of a fully implantable cortical vision prosthesis. The results indicate that long-term stimulation through wireless arrays can be achieved without induction of widespread tissue damage.
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GENNARIS consists of 11 modules with 43 electrodes each.
“The GENNARIS (Monash Vision Group) consists of 11 modules with 43 electrodes each (figure 6(d)) [106].”
From Advances in visual prostheses: engineering and biological challenges (2022) · cites this paper as [106]
The GENNARIS system uses inductive power transfer from a single transmitter coil to transmit data and power to 11 implanted receivers with 43 electrodes each.
“The GENNARIS system (Monash Vision Group) uses inductive power transfer from a single transmitter coil to transmit data and power to 11 implanted receiver with 43 electrodes each [106].”
From Advances in visual prostheses: engineering and biological challenges (2022) · cites this paper as [106]
Cites
Fiji: an open-source platform for biological-image analysis
Schindelin, J., Arganda-Carreras, I., Frise, E., Kaynig, V., Longair, M., Pietzsch, T., Preibisch, S., Rueden, C., Saalfeld, S., Schmid, B., et al. (2012) · Nature Methods · doi:10.1038/nmeth.2019 · Cited by 66,890 · see citing works
Response 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 · see citing works
The sensations produced by electrical stimulation of the visual cortex
Brindley, G. S., & Lewin, W. S. (1968) · The Journal of Physiology · doi:10.1113/jphysiol.1968.sp008519 · Cited by 1,170 · cited 2× · see citing works
“For these patients, the lateral geniculate nucleus (LGN) (Pezaris and Reid 2007) or the visual cortex have been shown to be viable locations for intervention with electrical stimulation (Brindley and Lewin 1968, Rosenfeld and Wong 2017).”
BackgroundBi, A., Cui, J., Ma, Y.-P., Olshevskaya, E. V., Pu, M., Dizhoor, A. M., & Pan, Z. (2006) · Neuron · doi:10.1016/j.neuron.2006.02.026 · Cited by 774 · see citing works
Schmidt, E. M., Bak, M. J., Hambrecht, F. T., Kufta, C. V., O'Rourke, D. K., & Vallabhanath, P. (1996) · Brain · doi:10.1093/brain/119.2.507 · Cited by 672 · see citing works
Maynard, E. M., Nordhausen, C. T., & Normann, R. A. (1997) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/s0013-4694(96)95176-0 · Cited by 640 · see citing works
Failure mode analysis of silicon-based intracortical microelectrode arrays in non-human primates
Barrese, J. C., Rao, N., Paroo, K., Triebwasser, C., Vargas-Irwin, C., Franquemont, L., & Donoghue, J. P. (2013) · Journal of Neural Engineering · doi:10.1088/1741-2560/10/6/066014 · Cited by 600 · see citing works
Artificial Vision for the Blind by Connecting a Television Camera to the Visual Cortex
Dobelle, W. H. (2000) · ASAIO Journal · doi:10.1097/00002480-200001000-00002 · Cited by 584 · see citing works
Fully Implanted Brain–Computer Interface in a Locked-In Patient with ALS
Vansteensel, M. J., Pels, E. G. M., Bleichner, M. G., Branco, M. P., Denison, T., Freudenburg, Z. V., Gosselaar, P., Leinders, S., Ottens, T. H., Van Den Boom, M. A., et al. (2016) · New England Journal of Medicine · doi:10.1056/nejmoa1608085 · Cited by 578 · see citing works
A neural interface for a cortical vision prosthesis
Normann, R. A., Maynard, E. M., Rousche, P. J., & Warren, D. J. (1999) · Vision Research · doi:10.1016/s0042-6989(99)00040-1 · Cited by 411 · see citing works
Veraart, C., Raftopoulos, C., Mortimer, J. T., Delbeke, J., Pins, D., Michaux, G., Vanlierde, A., Parrini, S., & Wanet-Defalque, M.-C. (1998) · Brain Research · doi:10.1016/s0006-8993(98)00977-9 · Cited by 407 · see citing works
Rose, T. L., & Robblee, L. S. (1990) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.61038 · Cited by 359 · see citing works
Chestek, C. A., Gilja, V., Nuyujukian, P., Foster, J. D., Fan, J. M., Kaufman, M. T., Churchland, M. M., Rivera-Alvidrez, Z., Cunningham, J. P., Ryu, S. I., et al. (2011) · Journal of Neural Engineering · doi:10.1088/1741-2560/8/4/045005 · Cited by 350 · see citing works
An implantable wireless neural interface for recording cortical circuit dynamics in moving primates
Borton, D. A., Yin, M., Aceros, J. C., & Nurmikko, A. V. (2013) · Journal of Neural Engineering · doi:10.1088/1741-2560/10/2/026010 · Cited by 318 · see citing works
A method for pneumatically inserting an array of penetrating electrodes into cortical tissue
Rousche, P. J., & Normann, R. A. (1992) · Annals of Biomedical Engineering · doi:10.1007/bf02368133 · Cited by 305 · see citing works
Visual sensations produced by intracortical microstimulation of the human occipital cortex
Bak, M., Girvin, J. P., Hambrecht, F. T., Kufta, C. V., Loeb, G. E., & Schmidt, E. M. (1990) · Medical & Biological Engineering & Computing · doi:10.1007/bf02442682 · Cited by 299 · see citing works
A fully organic retinal prosthesis restores vision in a rat model of degenerative blindness
Maya‐Vetencourt, J. F., Ghezzi, D., Antognazza, M. R., Colombo, E., Mete, M., Feyen, P., Desii, A., Buschiazzo, A., Paolo, M. D., Marco, S. D., et al. (2017) · Nature Materials · doi:10.1038/nmat4874 · Cited by 290 · see citing works
Potter, K. A., Buck, A. C., Self, W. K., & Capadona, J. R. (2012) · Journal of Neural Engineering · doi:10.1088/1741-2560/9/4/046020 · Cited by 239 · see citing works
Zhou, A., Santacruz, S. R., Johnson, B. C., Alexandrov, G., Moin, A., Burghardt, F., Rabaey, J. M., Carmena, J. M., & Muller, R. (2018) · Nature Biomedical Engineering · doi:10.1038/s41551-018-0323-x · Cited by 233 · see citing works
Lewis, P. M., Ackland, H. M., Lowery, A. J., & Rosenfeld, J. V. (2015) · Brain Research · doi:10.1016/j.brainres.2014.11.020 · Cited by 228 · see citing works
Self-citationWagstyl, K., Larocque, S., Cucurull, G., Lepage, C., Cohen, J. P., Bludau, S., Palomero-Gallagher, N., Lewis, L. B., Funck, T., Spitzer, H., et al. (2020) · PLOS Biology · doi:10.1371/journal.pbio.3000678 · Cited by 218 · see citing works
Retinal Prostheses: Current Clinical Results and Future Needs
Weiland, J. D., Cho, A. K., & Humayun, M. S. (2011) · Ophthalmology · doi:10.1016/j.ophtha.2011.08.042 · Cited by 196 · see citing works
Demonstration of artificial visual percepts generated through thalamic microstimulation
Pezaris, J. S., & Reid, R. C. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0608563104 · Cited by 195 · see citing works
Rousche, P. J., & Normann, R. A. (1999) · IEEE Transactions on Rehabilitation Engineering · doi:10.1109/86.750552 · Cited by 187 · see citing works
Bio-heat transfer model of deep brain stimulation-induced temperature changes
Elwassif, M. M., Kong, Q., Vázquez, M., & Bikson, M. (2006) · Journal of Neural Engineering · doi:10.1088/1741-2560/3/4/008 · Cited by 162 · see citing works
Barrese, J. C., Aceros, J., & Donoghue, J. P. (2016) · Journal of Neural Engineering · doi:10.1088/1741-2560/13/2/026003 · Cited by 161 · see citing works
McCreery, D. B., Pikov, V., & Troyk, P. R. (2010) · Journal of Neural Engineering · doi:10.1088/1741-2560/7/3/036005 · Cited by 137 · see citing works
A Wireless Implantable Multichannel Microstimulating System-on-a-Chip With Modular Architecture
Ghovanloo, M., & Najafi, K. (2007) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2007.903970 · Cited by 137 · see citing works
Sillay, K. A., Rutecki, P. A., Cicora, K., Worrell, G. A., Drazkowski, J. F., Shih, J. J., Sharan, A. D., Morrell, M. J., Williams, J. C., & Wingeier, B. (2013) · Brain stimulation · doi:10.1016/j.brs.2013.02.001 · Cited by 134 · see citing works
A Highly Flexible System for Microstimulation of the Visual Cortex: Design and Implementation
Coulombe, J., Sawan, M., & Gervais, J.-F. (2007) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2007.916026 · Cited by 129 · see citing works
An autonomous implantable computer for neural recording and stimulation in unrestrained primates
Mavoori, J., Jackson, A., Diorio, C., & Fetz, E. E. (2005) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2005.04.017 · Cited by 122 · see citing works
Lewis, P. M., & Rosenfeld, J. V. (2016) · Brain Research · doi:10.1016/j.brainres.2015.08.038 · Cited by 107 · see citing works
Self-citationRobblee, L. S., McHardy, J., Agnew, W. F., & Bullara, L. A. (1983) · Journal of Neuroscience Methods · doi:10.1016/0165-0270(83)90062-6 · Cited by 95 · see citing works
Neural decoding using gyral and intrasulcal electrocorticograms
Yanagisawa, T., Hirata, M., Saitoh, Y., Kato, A., Shibuya, D., Kamitani, Y., & Yoshimine, T. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.12.069 · Cited by 94 · see citing works
Davis, T. S., Parker, R. A., House, P. A., Bagley, E. E., Wendelken, S., Normann, R. A., & Greger, B. E. (2012) · Journal of Neural Engineering · doi:10.1088/1741-2560/9/6/065003 · Cited by 91 · see citing works
Torab, K., Davis, T. S., Warren, D. J., House, P. A., Normann, R. A., & Greger, B. (2011) · Journal of Neural Engineering · doi:10.1088/1741-2560/8/3/035001 · Cited by 90 · see citing works
Phosphene induction and the generation of saccadic eye movements by striate cortex
Tehovnik, E. J., Slocum, W. M., Carvey, C. E., & Schiller, P. H. (2005) · Journal of Neurophysiology · doi:10.1152/jn.00736.2004 · Cited by 87 · see citing works
Optogenetic approaches to retinal prosthesis
Barrett, J. M., Palmini, R. B., & Degenaar, P. A. (2014) · Visual Neuroscience · doi:10.1017/s0952523814000212 · Cited by 81 · see citing works
Neurobionics and the brain–computer interface: current applications and future horizons
Rosenfeld, J. V., & Wong, Y. T. (2017) · The Medical Journal of Australia · doi:10.5694/mja16.01011 · Cited by 79 · see citing works
The cortical visual areas of the sheep.
Clarke, P. G. H., & Whitteridge, D. (1976) · The Journal of Physiology · doi:10.1113/jphysiol.1976.sp011335 · Cited by 78 · see citing works
The effects of chronic intracortical microstimulation on neural tissue and fine motor behavior
Rajan, A. T., Boback, J. L., Dammann, J. F., Tenore, F. V., Wester, B. A., Otto, K. J., Gaunt, R. A., & Bensmaia, S. J. (2015) · Journal of Neural Engineering · doi:10.1088/1741-2560/12/6/066018 · Cited by 76 · see citing works
Saturation in phosphene size with increasing current levels delivered to human visual cortex
Bosking, W. H., Sun, P., Ozker, M., Pei, X., Foster, B. L., Beauchamp, M. S., & Yoshor, D. (2017) · The Journal of Neuroscience · doi:10.1523/jneurosci.2896-16.2017 · Cited by 75 · cited 1× · see citing works
“…studies in non-human primates have explored how different stimulation parameters and electrode configurations can be used to alter phosphene characteristics such as shape, brightness, longevity and color (Bak et al 1990, Tehovnik et al 2005, Torab et al 2011, Davis et al 2012, Bosking et al 2017).”
BackgroundNaito, J. (1989) · The Journal of Comparative Neurology · doi:10.1002/cne.902840203 · Cited by 73 · see citing works
Black, B., Kanneganti, A., Joshi‐Imre, A., Rihani, R. T., Chakraborty, B., Abbott, J., Pancrazio, J. J., & Cogan, S. F. (2018) · Journal of Neurophysiology · doi:10.1152/jn.00181.2018 · Cited by 62 · see citing works
Elwassif, M. M., Datta, A., Rahman, A., & Bikson, M. (2012) · Journal of Neural Engineering · doi:10.1088/1741-2560/9/4/046009 · Cited by 61 · see citing works
Huang, M. E., Harvey, R. L., Stoykov, M. E., Ruland, S. D., Weinand, M. E., Lowry, D. W., & Levy, R. M. (2008) · Topics in Stroke Rehabilitation · doi:10.1310/tsr1502-160 · Cited by 60 · see citing works
The effect of chronic intracortical microstimulation on the electrode–tissue interface
Chen, K. H., Dammann, J. F., Boback, J. L., Tenore, F. V., Otto, K. J., Gaunt, R. A., & Bensmaia, S. J. (2014) · Journal of Neural Engineering · doi:10.1088/1741-2560/11/2/026004 · Cited by 59 · see citing works
Humayun, M. S., de Juan, E., & Dagnelie, G. (2016) · Ophthalmology · doi:10.1016/j.ophtha.2016.06.044 · Cited by 55 · see citing works
Diamond Devices for High Acuity Prosthetic Vision
Ahnood, A., Hamish Meffin, A., Garrett, D. J., Fox, K. E., Ganesan, K., Stacey, A. D., Apollo, N. V., Wong, Y. T., Lichter, S. G., Kentler, W. G., et al. (2016) · Advanced Biosystems · doi:10.1002/adbi.201600003 · Cited by 55 · see citing works
Goss-Varley, M., Dona, K. R., McMahon, J. A., Shoffstall, A. J., Ereifej, E. S., Lindner, S. C., & Capadona, J. R. (2017) · Scientific Reports · doi:10.1038/s41598-017-15623-y · Cited by 55 · see citing works
A CMOS retinal neurostimulator capable of focussed, simultaneous stimulation
Dommel, N., Wong, Y. T., Lehmann, T., Dodds, C. W. D., Lovell, N. H., & Suaning, G. J. (2009) · Journal of Neural Engineering · doi:10.1088/1741-2560/6/3/035006 · Cited by 54 · see citing works
Long-term stability of sensitivity to intracortical microstimulation of somatosensory cortex
Callier, T., Schluter, E. W., Tabot, G. A., Miller, L. E., Tenore, F. V., & Bensmaı̈a, S. J. (2015) · Journal of Neural Engineering · doi:10.1088/1741-2560/12/5/056010 · Cited by 48 · see citing works
Brunton, E. K., Winther-Jensen, B., Wang, C., Yan, E. B., Hagh Gooie, S., Lowery, A. J., & Rajan, R. (2015) · Frontiers in Neuroscience · doi:10.3389/fnins.2015.00265 · Cited by 46 · see citing works
Lead Fractures in Deep Brain Stimulation during Long-Term Follow-Up
Fernández, F. S., Vega, M. A. Á., Ramos, A. A., et al. (2009) · Parkinson s Disease · doi:10.4061/2010/409356 · Cited by 40 · see citing works
Ewing, S. G., Porr, B., Riddell, J. S., Winter, C., & Grace, A. A. (2013) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2012.12.008 · Cited by 38 · see citing works
High channel count single-unit recordings from nonhuman primate frontal cortex
Mitz, A. R., Bartolo, R., Saunders, R. C., Browning, P. G. F., TALBOT, T. L., & Averbeck, B. B. (2017) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2017.07.001 · Cited by 37 · see citing works
Restoration of vision using wireless cortical implants: The Monash Vision Group project
Lowery, A. J., Rosenfeld, J. V., Lewis, P., Browne, D. C., Mohan, A., Brunton, E., Yan, E. B., Maller, J. J., Mann, C., Rajan, R., et al. (2015) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2015.7318543 · Cited by 35 · see citing works
The ovine motor cortex: A review of functional mapping and cytoarchitecture
John, S. E., Lovell, T. J. H., Opie, N. L., et al. (2017) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2017.06.002 · Cited by 30 · see citing works
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 · see citing works
Visual Sensation by Electrical Stimulation Using a New Direct Optic Nerve Electrode Device
Nishida, K., Sakaguchi, H., Kamei, M., Cecilia-Gonzalez, C., Terasawa, Y., Vélez-Montoya, R., Fujikado, T., Sánchez-Fontán, R., Ozawa, M., Quiroz-Mercado, H., et al. (2015) · Brain stimulation · doi:10.1016/j.brs.2015.03.001 · Cited by 26 · see citing works
Brain mapping: the (un)folding of striate cortex
Schira, M. M., Tyler, C. W., & Rosa, M. G. P. (2012) · Current Biology · doi:10.1016/j.cub.2012.11.003 · Cited by 22 · see citing works
Spectral distribution of local field potential responses to electrical stimulation of the retina
Wong, Y. T., Halupka, K., Kameneva, T., Cloherty, S. L., Grayden, D. B., Burkitt, A. N., Meffin, H., & Shivdasani, M. N. (2016) · Journal of Neural Engineering · doi:10.1088/1741-2560/13/3/036003 · Cited by 16 · see citing works
Gerboni, G., John, S. E., Rind, G. S., Ronayne, S. M., May, C. N., Oxley, T. J., Grayden, D. B., Opie, N. L., & Wong, Y. T. (2018) · Biomedical Physics & Engineering Express · doi:10.1088/2057-1976/aad714 · Cited by 14 · see citing works
Optimising electrode surface area to minimize power consumption in a cortical penetrating prosthesis
Brunton, E., Rajan, R., & Lowery, A. J. (2013) · International IEEE/EMBS Conference on Neural Engineering · doi:10.1109/ner.2013.6696224 · Cited by 7 · see citing works
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Sorted by citations
Bioengineering strategies for restoring vision
Cehajic-Kapetanovic, J., Singh, M. S., Zrenner, E., & MacLaren, R. E. (2022) · Nature Biomedical Engineering · doi:10.1038/s41551-021-00836-4 · Cited by 79 · see citing works
Challenges for Large-Scale Cortical Interfaces
Nurmikko, A. (2020) · Neuron · doi:10.1016/j.neuron.2020.10.015 · Cited by 68 · see citing works
Advances in visual prostheses: engineering and biological challenges
Borda, E., & Ghezzi, D. (2022) · Progress in Biomedical Engineering · doi:10.1088/2516-1091/ac812c · Cited by 44 · see citing works
Brain-Machine Interfaces to Assist the Blind
Ptito, M., Bleau, M., Djerourou, I., Paré, S., Schneider, F. C., & Chebat, D.-R. (2021) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2021.638887 · Cited by 45 · see citing works
“Safety tests on experimental animals have confirmed the production of phosphenes, and histological examination reveals minimal damage to the cortex after implantation and that longterm stimulation is possible without adverse events (Lowery et al., 2017; Rosenfeld et al., 2020).”
BackgroundRobot Bionic Vision Technologies: A Review
Zhang, H., & Lee, S. (2022) · Applied Sciences · doi:10.3390/app12167970 · Cited by 37 · see citing works
Liu, X., Chen, P., Ding, X., Liu, A., Li, P., Sun, C., & Guan, H. (2022) · Annals of Translational Medicine · doi:10.21037/atm-22-2858 · Cited by 28 · see citing works
“The formation of phosphenes has been validated in safety studies on experimental animals, and a histological investigation revealed little damage to the cortex following implantation, indicating that long-term stimulation is achievable without any deleterious effects (59,82).”
BackgroundMicrostimulation-evoked neural responses in visual cortex are depth dependent
Allison-Walker, T., Hagan, M. A., Price, N. S. C., & Wong, Y. T. (2021) · Brain stimulation · doi:10.1016/j.brs.2021.04.020 · Cited by 22 · see citing works
Intracortical current steering shifts the location of evoked neural activity
Meikle, S. J., Hagan, M. A., Price, N. S. C., & Wong, Y. T. (2022) · Journal of Neural Engineering · doi:10.1088/1741-2552/ac77bf · Cited by 19 · see citing works
“This slight bias in neural activity also occurred in the baseline firing rates and was likely caused by neuronal damage during electrode insertion such that neurons closer to the tip had less trauma [1, 19, 20].”
InfluentialBioinspired and biointegrated vision for artificial sight convergence
Yang, Y., Wang, Y., Zhu, C., Xie, Z., Qin, Z., Wang, Z., & Chai, Y. (2025) · Nature Reviews Bioengineering · doi:10.1038/s44222-025-00324-3 · Cited by 18 · see citing works
“Pre-clinical experiments have started but long-term biocompatibility still needs to be evaluated 129 .”
Neurophysiological considerations for visual implants
Meikle, S. J., & Wong, Y. T. (2022) · Brain Structure and Function · doi:10.1007/s00429-021-02417-2 · Cited by 15 · see citing works
Visual cortical prosthesis: an electrical perspective
Pio‐Lopez, L., Poulkouras, R., & Depannemaecker, D. (2021) · Journal of Medical Engineering & Technology · doi:10.1080/03091902.2021.1907468 · Cited by 14 · see citing works
Barbruni, G. L., Rodino, F., Ros, P. M., Demarchi, D., Ghezzi, D., & Carrara, S. (2024) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2024.3357626 · Cited by 14 · see citing works
“WPT enabled the progress from a few tens of channels of the first implants [11], [12] to several hundreds of the last few years [13], [14].”
BackgroundThe role of the visual field size in artificial vision
Ghezzi, D. (2023) · Journal of Neural Engineering · doi:10.1088/1741-2552/acc7cd · Cited by 10 · see citing works
Layer-dependent stability of intracortical recordings and neuronal cell loss
Urdaneta, M. E., Kunigk, N. G., Peñaloza-Aponte, J. D., Currlin, S., Malone, I. G., Fried, S. I., & Otto, K. J. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1096097 · Cited by 9 · see citing works
“In addition, using standard histological techniques, groups have shown qualitative differences in FBR markers across representative (superficial, middle, and deep) cortical depths (Kozai et al., 2014; Nolta et al., 2015; Rosenfeld et al., 2020).”
MethodResultRocca, A., Lehner, C., Wekesa, E., Luna, E., Fernández-Cornejo, V., Abarca-Olivas, J., Soto‐Sánchez, C., Fernández-Jover, E., & González-López, P. (2023) · Journal of neurosurgery · doi:10.3171/2023.8.jns23772 · Cited by 9 · see citing works
Cortical layering disrupts multi-electrode current steering
Meikle, S. J., Hagan, M. A., Price, N. S. C., & Wong, Y. T. (2023) · Journal of Neural Engineering · doi:10.1088/1741-2552/acdaf7 · Cited by 7 · see citing works
NeurostimML: a machine learning model for predicting neurostimulation-induced tissue damage
Li, Y., Frederick, R. A., George, D., Cogan, S. F., Pancrazio, J. J., Bleris, L. G., & Hernandez-Reynoso, A. G. (2024) · Journal of Neural Engineering · doi:10.1088/1741-2552/ad593e · Cited by 7 · see citing works
“Several experimental studies have systematically investigated the relationship between stimulation parameters and the potential for tissue damage [12, 18, 19].”
BackgroundOptimal placement of high-channel visual prostheses in human retinotopic visual cortex
van Hoof, R., Lozano, A., Wang, F., Klink, P. C., Roelfsema, P. R., & Goebel, R. (2025) · Journal of Neural Engineering · doi:10.1088/1741-2552/adaeef · Cited by 6 · see citing works
“Visual prostheses that interface directly with the brain may one day be a realistic treat-ment option for blindness that results from damage to the early visual pathways (Normann et al 2009, Roelfsema 2020, Rosenfeld et al 2020, Fernández et al 2021).”
Tackling visual impairment: emerging avenues in ophthalmology
Lin, F., Su, Y., Zhao, C., Akter, F., Yao, S., Huang, S., Shao, X., & Yao, Y. (2025) · Frontiers in Medicine · doi:10.3389/fmed.2025.1567159 · Cited by 5 · see citing works
Neurosurgery and the Brain-Computer Interface
Rosenfeld, J. V. (2024) · Advances in experimental medicine and biology · doi:10.1007/978-3-031-64892-2_32 · Cited by 4 · see citing works
Neural activity shaping in visual prostheses with deep learning
Castro, D., Grayden, D. B., Hamish Meffin, A., & Spencer, M. (2024) · Journal of Neural Engineering · doi:10.1088/1741-2552/ad6186 · Cited by 4 · see citing works
“In this study, we consider a square MEA with an 8-by-8 matrix of electrodes which is within the range of existing retinal implants (Luo and Da Cruz 2016, Rosenfeld et al 2020, Fernández et al 2021, Petoe et al 2021).”
Szlawski, J., Feleppa, T., Mohan, A., et al. (2022) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2022.3173682 · Cited by 4 · see citing works
Microelectrode Arrays, Implants, and Organs-on-a-Chip
Pasquarelli, A. (2021) · Learning materials in biosciences · doi:10.1007/978-3-030-76469-2_11 · Cited by 3 · see citing works
Visual Prostheses in the Era of Artificial Intelligence Technology
Sarbout, I., Gungor, A., Ounissi, M., Zaher, S., Ptito, M., Kupers, R., Racoceanu, D., & Milea, D. (2025) · Eye and Brain · doi:10.2147/eb.s524322 · Cited by 3 · see citing works
“Initial animal tests indicated a good safety profile, 44 encouraging the group to apply for funding to perform a clinical trial with a 73 electrodes device.”
Filling in the Visual Gaps: Shifting Cortical Activity using Current Steering
Meikle, S. J., Hagan, M. A., Price, N. S. C., & Wong, Y. T. (2021) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc46164.2021.9629693 · Cited by 2 · see citing works
“When implanting multishank electrode arrays, pneumatic tools are used for rapid insertion into the brain to overcome the ‘bed of nails’ effect [1, 8].”
BackgroundMethodInfluentialElectrical stimulation thresholds differ between V1 and V2
Meikle, S. J., Allison-Walker, T., Hagan, M. A., Price, N. S. C., & Wong, Y. T. (2023) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc40787.2023.10340103 · Cited by 2 · see citing works
“In the field of cortical sensorimotor stimulation, visual prostheses are one of the most developed devices, with several groups working to commercialize an end-user product [13-15].”
BackgroundBionic eye: An iconic innovation
Suvvari, T. K., Madhu, M., & Nagendra, S. (2021) · TNOA Journal of Ophthalmic Science and Research · doi:10.4103/tjosr.tjosr_168_20 · Cited by 2 · see citing works
Object recognition from sparse simulated phosphenes and curved segments
Scialom, E., Ernst, U. A., Rotermund, D., & Herzog, M. H. (2025) · Vision Research · doi:10.1016/j.visres.2025.108718 · Cited by 3 · see citing works
Neurosurgical Considerations for the Brain Computer Interface
Rosenfeld, J. V., Wong, Y. T., Szlawski, J., & Gutman, M. (2022) · Handbook of Neuroengineering · doi:10.1007/978-981-15-2848-4_38-1 · Cited by 1 · see citing works
A Special issue on Multidisciplinary research to promote the applications in Biological sciences
Manikandan, G. E. D. M. (2022) · International Journal of Life Science and Pharma Research · doi:10.22376/ijpbs/ijlpr/sp22/2022.1-154 · Cited by 1 · see citing works
Minimizing the number of phosphenes required for object recognition under prosthetic visionPreprint
Scialom, E., Ernst, U. A., Rotermund, D., & Herzog, M. H. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.09.26.614440 · Cited by 1 · see citing works
Neurosurgical Considerations for the Brain Computer Interface
Rosenfeld, J. V., Wong, Y. T., Szlawski, J., & Gutman, M. (2023) · Handbook of Neuroengineering · doi:10.1007/978-981-16-5540-1_38
Brain-Computer Interfaces for Vision Recovery in Precortical Vision Loss
Yang, C., Guo, A., & Lin, K. (2026) · Eye and Brain · doi:10.2147/eb.s561691
“…78 the PRIMA subretinal implant designed for central vision loss caused by AMD, manufactured by Science Corporation; 79,80 the Gennaris TM Bionic Vision System ® which utilizes nanowire technology to generate uniquely high-resolution phosphenes; 81 and the Orion ® , manufactured by Second Sight.”
Scialom, E., Lonnqvist, B., Bornet, A., & Herzog, M. H. (2026) · Journal of Neural Engineering · doi:10.1088/1741-2552/ae9227
“Specifically, excessive electrode stimulation can lead to increased tissue damage compared to passive electrodes (Rosenfeld et al 2020).”
- Authors
- Rosenfeld, J. V., Wong, Y. T., Yan, E., Szlawski, J., Mohan, A., Clark, J. C., Rosa, M., & Lowery, A.
- Affiliations
- Monash University (AU)
- Australian Research Council (AU)
- Austin Hospital Pathology
- Corresponding author
- Rosenfeld, Jeffrey V
- Wong, Yan T
- Yan, Edwin
- Szlawski, Julian
- Mohan, Anand
- Rosa, Marcello
- Lowery, Arthur
- Venue
- Journal of Neural Engineering
- Publisher
- IOP Publishing
- Published
- 2020-07-08
- Volume
- 17
- Issue
- 4
- Pages
- 046001
- ISSN
- 1741-2552 (ISSN-L)
- 1741-2560
- OpenAlex
- W3036770533
- Semantic Scholar
- 6ee8d7de51a401adfe87b7ff3160eb3ce627917d
- Cited by
- 35
- References
- 64
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 5 · 2023: 6 · 2022: 9 · 2021: 7 · 2020: 1
- FWCI
- 2.63
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Journal of Neural Engineering (publishedVersion)
- PubMed (publishedVersion)
- Funders
- MTPconnect (BioMedTech Horizons)
- National Health and Medical Research Council (APP1075773)
- Australian Research Council’s Research in Bionic Vision Science and Technology Initiative (SRI 1000006)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Health Sciences › Medicine › Anesthesiology and Pain Medicine › Pain Management and Treatment
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Keywords
- wireless neural stimulation, chronic electrical stimulation, tissue reaction, histology, biocompatibility, sheep model, charge injection, visual cortex stimulation, implantable microelectrodes
- MeSH terms
- Animals, Electric Stimulation, Electrodes, Implanted, Microelectrodes, Sheep, Visual Cortex, Prosthesis Implantation, Visual Prosthesis
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