Flexible, foldable, actively multiplexed, high-density electrode array for mapping brain activity in vivo
Open accessAbstract
Arrays of electrodes for recording and stimulating the brain are used throughout clinical medicine and basic neuroscience research, yet are unable to sample large areas of the brain while maintaining high spatial resolution because of the need to individually wire each passive sensor at the electrode-tissue interface. To overcome this constraint, we developed new devices that integrate ultrathin and flexible silicon nanomembrane transistors into the electrode array, enabling new dense arrays of thousands of amplified and multiplexed sensors that are connected using fewer wires. We used this system to record spatial properties of cat brain activity in vivo, including sleep spindles, single-trial visual evoked responses and electrographic seizures. We found that seizures may manifest as recurrent spiral waves that propagate in the neocortex. The developments reported here herald a new generation of diagnostic and therapeutic brain-machine interface devices.
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Compared with rigid electrodes based on silicon wafers and rigid packaging, flexible electrodes are more biocompatible and can adapt to complex tissue geometries.
“Compared to commercially available rigid electrodes based on silicon wafers and rigid packaging, flexible electrodes are also more biocompatible (details described in section 2) and can adapt to the complex tissue geometries of the human body,[293–295] such as sulci in the cerebral cortex,[296,297] bundled peripheral nerves,[298] and stretching motions on the skin.[299]”
From Flexible Electronics and Devices as Human–Machine Interfaces for Medical Robotics (2022) · cites this paper as [296]
The Abstract (page not provided) says flexible, non-penetrating subdural arrays minimize irritation and injury to brain tissue compared with penetrating arrays. Electrode array fabrication and testing (page not provided) shows that this flexible device can fold to access cortical sulci. The paper does not establish a comparison with commercially available silicon-wafer electrodes and rigid packaging, or show that flexible electrodes adapt to complex tissue geometries throughout the human body. (LLM, conf=0.86)
Experimental — accuracy not yet measuredUltrathin film electrode arrays are a promising and widely adopted option for electrocorticography electrodes on the cortex surface, owing to high recording density in a non-penetrating fashion.
“Referring to another brain (ECoG) recording, ultrathin film electrode arrays are a promising and widely adopted option for electrodes used on the surface of the cortex, owing to its high recording density in a non-penetrating fashion.[296,343–346]”
From Flexible Electronics and Devices as Human–Machine Interfaces for Medical Robotics (2022) · cites this paper as [296]
The Abstract (page not provided) describes flexible, non-penetrating subdural arrays as capable of high-resolution ECoG recording, and the fabrication section describes the paper’s ultrathin, high-resolution device. It does not establish that ultrathin, high-density arrays were widely adopted; the Abstract instead says clinically used subdural electrodes were larger and more widely spaced. (LLM, conf=0.86)
Experimental — accuracy not yet measuredFlexible transistors can incorporate some on-site intelligence, but their level of maturity is not yet sufficient to meet the foreseen processing complexity or the strict requirements for clinical use.
“Despite the fact that some on-site intelligence can be incorporated with the use of flexible transistors (Viventi et al. 2011), the level of maturity of such technologies is not yet sufficient to meet neither the foreseen processing complexity nor the strict requirements for clinical use.”
From Realizing flexible bioelectronic medicines for accessing the peripheral nerves – technology considerations (2018) · cites this paper as Viventi et al. 2011
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Cites
The Elements of Statistical Learning
Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics · doi:10.1007/978-0-387-21606-5 · Cited by 24,162 · see citing works
Reducing the dimensionality of data with neural networks
Hinton, G. E., & Salakhutdinov, R. R. (2006) · Science · doi:10.1126/science.1127647 · Cited by 20,928 · see citing works
Estimating the Number of Clusters in a Data Set Via the Gap Statistic
Tibshirani, R., Walther, G., & Hastie, T. (2001) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00293 · Cited by 6,205 · see citing works
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 · 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
Dissolvable films of silk fibroin for ultrathin conformal bio-integrated electronics
Kim, D.-H., Viventi, J., Amsden, J. J., Xiao, J., Vigeland, L., Kim, Y.-S., Blanco, J. A., Panilaitis, B., Frechette, E. S., Contreras, D., et al. (2010) · Nature Materials · doi:10.1038/nmat2745 · Cited by 1,721 · see citing works
Self-citationSolid state electronic devices
Streetman, B. G. (1972) · CERN Document Server (European Organization for Nuclear Research) · Cited by 1,475 · see citing works
Llinás, R. R., Ribary, U., Jeanmonod, D., Kronberg, E., & Mitra, P. P. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.26.15222 · Cited by 1,395 · see citing works
An empirical evaluation of deep architectures on problems with many factors of variation
Larochelle, H., Erhan, D., Courville, A. C., Bergstra, J., & Bengio, Y. (2007) · International Conference on Machine Learning · doi:10.1145/1273496.1273556 · Cited by 1,024 · see citing works
Essen, D. C. V., Newsome, W. T., & Maunsell, J. H. R. (1984) · Vision Research · doi:10.1016/0042-6989(84)90041-5 · Cited by 938 · see citing works
Campbell, P. K., Jones, K. E., Huber, R. J., Horch, K. W., & Normann, R. A. (1991) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.83588 · Cited by 881 · see citing works
Learning-dependent increases in sleep spindle density
Gais, S., Mölle, M., Helms, K., & Born, J. (2002) · The Journal of Neuroscience · doi:10.1523/jneurosci.22-15-06830.2002 · Cited by 859 · see citing works
A 90-nm logic technology featuring strained-silicon
Thompson, S. E., Armstrong, M., Auth, C., Alavi, M., Buehler, M., Chau, R. S., Cea, S., Ghani, T., Glass, G., Hoffman, T., et al. (2004) · IEEE Transactions on Electron Devices · doi:10.1109/ted.2004.836648 · Cited by 673 · see citing works
Brodmann's Areas 17 and 18 Brought into Stereotaxic Space—Where and How Variable?
Amunts, K., Maliković, A., Mohlberg, H., Schormann, T., & Zilles, K. (2000) · NeuroImage · doi:10.1006/nimg.1999.0516 · Cited by 640 · see citing works
High-frequency oscillations and seizure generation in neocortical epilepsy
Worrell, G. A., Parish, L. M., Cranstoun, S. D., Jonas, R., Baltuch, G. H., & Litt, B. (2004) · Brain · doi:10.1093/brain/awh149 · Cited by 537 · see citing works
Self-citationRetinotopic organization of areas 18 and 19 in the cat
Tusa, R. J., Rosenquist, A. C., & Palmer, L. A. (1979) · The Journal of Comparative Neurology · doi:10.1002/cne.901850405 · Cited by 531 · see citing works
Self-citationSpatiotemporal evolution of ventricular fibrillation
Witkowski, F. X., Leon, L. J., Penkoske, P. A., Giles, W. R., Spano, M. L., Ditto, W. L., & Winfree, A. T. (1998) · Nature · doi:10.1038/32170 · Cited by 484 · see citing works
Sleep spindle activity is associated with the integration of new memories and existing knowledge
Tamminen, J., Payne, J. D., Stickgold, R., Wamsley, E. J., & Gaskell, M. G. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.3028-10.2010 · Cited by 478 · see citing works
Fried, I., Mukamel, R., & Kreiman, G. (2011) · Neuron · doi:10.1016/j.neuron.2010.11.045 · Cited by 459 · see citing works
Worrell, G. A., Gardner, A. B., Stead, S. M., Hu, S., Goerss, S., Cascino, G. J., Meyer, F. B., Marsh, R. W., & Litt, B. (2008) · Brain · doi:10.1093/brain/awn006 · Cited by 455 · see citing works
Self-citationInference of hand movements from local field potentials in monkey motor cortex
Mehring, C., Rickert, J., Vaadia, E., de Oliveira, S. C., Aertsen, A., & Rotter, S. (2003) · Nature Neuroscience · doi:10.1038/nn1158 · Cited by 435 · see citing works
A Conformal, Bio-Interfaced Class of Silicon Electronics for Mapping Cardiac Electrophysiology
Viventi, J., Kim, D., Moss, J. D., Kim, Y., Blanco, J. A., Annetta, N. V., Hicks, A., Xiao, J., Huang, Y., Callans, D. J., et al. (2010) · Science Translational Medicine · doi:10.1126/scitranslmed.3000738 · Cited by 419 · see citing works
Self-citationSpiral Waves in Disinhibited Mammalian Neocortex
Huang, X., Troy, W. C., Yang, Q., Ma, H., Laing, C. R., Schiff, S. J., & Wu, J. (2004) · Journal of Neuroscience · doi:10.1523/jneurosci.2705-04.2004 · Cited by 388 · see citing works
Self-citationLong-term asynchronous decoding of arm motion using electrocorticographic signals in monkey
Chao (2010) · Frontiers in Neuroengineering · doi:10.3389/fneng.2010.00003 · Cited by 337 · see citing works
Selecting the signals for a brain–machine interface
Andersen, R. A., Musallam, S., & Pesaran, B. (2004) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2004.10.005 · Cited by 329 · see citing works
Spatial spectral analysis of human electrocorticograms including the alpha and gamma bands
Freeman, W., Rogers, L. J., Holmes, M., & Silbergeld, D. L. (2000) · Journal of Neuroscience Methods · doi:10.1016/s0165-0270(99)00160-0 · Cited by 323 · see citing works
Visual stimuli induce waves of electrical activity in turtle cortex
Prechtl, J. C., Cohen, L. B., Pesaran, B., Mitra, P. P., & Kleinfeld, D. (1997) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.94.14.7621 · Cited by 321 · see citing works
Microseizures and the spatiotemporal scales of human partial epilepsy
Stead, M., Bower, M. R., Brinkmann, B. H., Lee, K. H., Marsh, W. R., Meyer, F. B., Litt, B., Gompel, J. J. V., & Worrell, G. A. (2010) · Brain · doi:10.1093/brain/awq190 · Cited by 311 · see citing works
Self-citationSpiral Wave Dynamics in Neocortex
Huang, X., Xu, W., Liang, J., Takagaki, K., Gao, X., & Wu, J. (2010) · Neuron · doi:10.1016/j.neuron.2010.11.007 · Cited by 309 · see citing works
Self-citationSekitani, T., Takamiya, M., Noguchi, Y., Nakano, S., Kato, Y., Sakurai, T., & Someya, T. (2007) · Nature Materials · doi:10.1038/nmat1903 · Cited by 306 · see citing works
Decoding spoken words using local field potentials recorded from the cortical surface
Kellis, S., Miller, K., Thomson, K., Brown, R., House, P., & Greger, B. (2010) · Journal of Neural Engineering · doi:10.1088/1741-2560/7/5/056007 · Cited by 235 · see citing works
Reassessment of brain elasticity for analysis of biomechanisms of hydrocephalus
Taylor, Z. A., & Miller, K. (2004) · Journal of Biomechanics · doi:10.1016/j.jbiomech.2003.11.027 · Cited by 235 · see citing works
Small focal cortical dysplasia lesions are located at the bottom of a deep sulcus
Besson, P., Andermann, F., Dubeau, F., & Bernasconi, N. (2008) · Brain · doi:10.1093/brain/awn224 · Cited by 198 · see citing works
Heterogeneous neuronal firing patterns during interictal epileptiform discharges in the human cortex
Keller, C. J., Truccolo, W., Gale, J. T., Eskandar, E. N., Thesen, T., Carlson, C., Devinsky, O., Kuzniecky, R., Doyle, W., Madsen, J. R., et al. (2010) · Brain · doi:10.1093/brain/awq112 · Cited by 190 · see citing works
Stimulus feature selectivity in excitatory and inhibitory neurons in primary visual cortex
Cardin, J. A., Palmer, L. A., & Contreras, D. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.1692-07.2007 · Cited by 185 · see citing works
Self-citationBiocompatibility of silicon‐based electrode arrays implanted in feline cortical tissue
Schmidt, S., Horch, K., & Normann, R. A. (1993) · Journal of Biomedical Materials Research · doi:10.1002/jbm.820271106 · Cited by 182 · see citing works
ECoG factors underlying multimodal control of a brain-computer interface
Wilson, J. A., Felton, E. A., Garell, P. C., Schalk, G., & Williams, J. C. (2006) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2006.875570 · Cited by 164 · see citing works
Microphysiology of Epileptiform Activity in Human Neocortex
Schevon, C. A., Ng, S. K., Cappell, J., Goodman, R. R., McKhann, G. M., Waziri, A. E., Branner, A., Sosunov, A. A., Schroeder, C. E., & Emerson, R. G. (2008) · Journal of Clinical Neurophysiology · doi:10.1097/wnp.0b013e31818e8010 · Cited by 162 · see citing works
Spatial characterization of interictal high frequency oscillations in epileptic neocortex
Schevon, C. A., Trevelyan, A. J., Schroeder, C. E., Goodman, R. R., McKhann, G. M., & Emerson, R. G. (2009) · Brain · doi:10.1093/brain/awp222 · Cited by 150 · see citing works
Griffith, R. W., & Humphrey, D. R. (2006) · Neuroscience Letters · doi:10.1016/j.neulet.2006.07.018 · Cited by 147 · see citing works
Blanco, J. A., Stead, M., Krieger, A. Μ., et al. (2010) · Journal of Neurophysiology · doi:10.1152/jn.01082.2009 · Cited by 147 · see citing works
Self-citationRapid Communication with a “P300” Matrix Speller Using Electrocorticographic Signals (ECoG)
Brunner, P., Ritaccio, A. L., Emrich, J. F., Bischof, H., & Schalk, G. (2011) · Frontiers in Neuroscience · doi:10.3389/fnins.2011.00005 · Cited by 133 · see citing works
Pre-ictal and ictal neurovascular and metabolic coupling surrounding a seizure focus
Zhao, M., Nguyen, J., Ma, H.-T., Nishimura, N., Schaffer, C., & Schwartz, T. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.2597-11.2011 · Cited by 120 · see citing works
Fox, P. T., Huang, A. Y., Parsons, L. M., Xiong, J., Zamarripa, F., Rainey, L., & Lancaster, J. L. (2001) · NeuroImage · doi:10.1006/nimg.2000.0659 · Cited by 112 · see citing works
Characterization of flexible ECoG electrode arrays for chronic recording in awake rats
Yeager, J. D., Phillips, D. J., Rector, D. M., & Bahr, D. F. (2008) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2008.06.024 · Cited by 109 · see citing works
Human cortical prostheses: lost in translation?
Ryu, S. I., & Shenoy, K. V. (2009) · Neurosurgical Focus · doi:10.3171/2009.4.focus0987 · Cited by 104 · 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
Margalit, E., Weiland, J. D., Clatterbuck, R. E., Fujii, G. Y., Maia, M., Tameesh, M., Torres, G. F., D’Anna, S. A., Desai, S., Piyathaisere, D. V., et al. (2003) · Journal of Neuroscience Methods · doi:10.1016/s0165-0270(02)00345-x · Cited by 92 · see citing works
Cardin, J. A., Palmer, L. A., & Contreras, D. (2008) · Neuron · doi:10.1016/j.neuron.2008.05.002 · Cited by 90 · see citing works
Self-citationBranco, D. M., Coelho, T. M., Branco, B. D. M., Schmidt, L. P., Calcagnotto, M. E., Portuguez, M. W., Neto, E. P., Paglioli, E., Palmini, A., Lima, J. V., et al. (2003) · Journal of Clinical Neurophysiology · doi:10.1097/00004691-200302000-00002 · Cited by 83 · see citing works
Flexible biomedical microdevices with double-sided electrode arrangements for neural applications
Stieglitz, T. (2001) · Sensors and Actuators A Physical · doi:10.1016/s0924-4247(01)00520-9 · Cited by 75 · see citing works
Kellis, S., House, P. A., Thomson, K. E., Brown, R. B., & Greger, B. E. (2009) · Neurosurgical FOCUS · doi:10.3171/2009.4.focus0974 · Cited by 75 · see citing works
Yu, Z., Graudejus, O., Tsay, C., Lacour, S. P., Wagner, S., & Morrison, B. (2009) · Journal of Neurotrauma · doi:10.1089/neu.2008.0810 · Cited by 74 · see citing works
Stable Rotating Waves in Two-Dimensional Discrete Active Media
Paullet, J. E., & Ermentrout, B. (1994) · SIAM Journal on Applied Mathematics · doi:10.1137/s0036139993250683 · Cited by 72 · see citing works
Stieglitz, T., & Gross, M. (2002) · Sensors and Actuators B Chemical · doi:10.1016/s0925-4005(01)01021-8 · Cited by 65 · see citing works
Studies of stimulus parameters for seizure disruption using neural network simulations
Anderson, W. S., Kudela, P., Cho, J., Bergey, G. K., & Franaszczuk, P. J. (2007) · Biological Cybernetics · doi:10.1007/s00422-007-0166-0 · Cited by 45 · see citing works
Properties of the flash visual evoked potential recorded in the cat primary visual cortex
Padnick, L. B., & Linsenmeier, R. A. (1999) · Vision Research · doi:10.1016/s0042-6989(99)00016-4 · Cited by 19 · see citing works
Kitzmiller, J. P., Hansford, D. J., Fortin, L. D., Obrietan, K. H., Bergdall, V. K., & Beversdorf, D. Q. (2007) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2007.01.004 · Cited by 10 · see citing works
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- [23]23. Ball T, et al. Towards an implantable brain-machine interface based on epicortical field potentials. Biomed Tech (Berlin). 2004; 38:756-759.
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Hammock, M. L., Chortos, A., Tee, B. C. ‐., Tok, J. B. ‐., & Bao, Z. (2013) · Advanced Materials · doi:10.1002/adma.201302240 · Cited by 2,396 · see citing works
The rise of plastic bioelectronics
Someya, T., Bao, Z., & Malliaras, G. G. (2016) · Nature · doi:10.1038/nature21004 · Cited by 1,884 · see citing works
Lab-on-Skin: A Review of Flexible and Stretchable Electronics for Wearable Health Monitoring
Liu, Y., Pharr, M., & Salvatore, G. A. (2017) · ACS Nano · doi:10.1021/acsnano.7b04898 · Cited by 1,725 · see citing works
Pan, L., Chortos, A., Yu, G., Wang, Y., Isaacson, S., Allen, R., Shi, Y., Dauskardt, R., & Bao, Z. (2014) · Nature Communications · doi:10.1038/ncomms4002 · Cited by 1,519 · see citing works
Multifunctional wearable devices for diagnosis and therapy of movement disorders
Son, D., Lee, J., Qiao, S., Ghaffari, R., Kim, J., Lee, J. E., Song, C., Kim, S. J., Lee, D. J., Jun, S. W., et al. (2014) · Nature Nanotechnology · doi:10.1038/nnano.2014.38 · Cited by 1,462 · see citing works
Self-citationStretchable silicon nanoribbon electronics for skin prosthesis
Kim, J., Lee, M., Shim, H. J., Ghaffari, R., Cho, H. R., Son, D., Jung, Y. H., Soh, M., Choi, C., Jung, S., et al. (2014) · Nature Communications · doi:10.1038/ncomms6747 · Cited by 1,435 · see citing works
Self-citationA soft, wearable microfluidic device for the capture, storage, and colorimetric sensing of sweat
Koh, A., Kang, D., Xue, Y., Lee, S., Pielak, R. M., Kim, J., Hwang, T., Min, S., Banks, A., Bastien, P., et al. (2016) · Science Translational Medicine · doi:10.1126/scitranslmed.aaf2593 · Cited by 1,308 · see citing works
Self-citationRecent Advances in Flexible and Stretchable Bio‐Electronic Devices Integrated with Nanomaterials
Choi, S., Lee, H., Ghaffari, R., Hyeon, T., & Kim, D. (2016) · Advanced Materials · doi:10.1002/adma.201504150 · Cited by 1,104 · see citing works
Self-citationNeuroGrid: recording action potentials from the surface of the brain
Khodagholy, D., Gelinas, J. N., Thesen, T., Doyle, W., Devinsky, O., Malliaras, G. G., & Buzsáki, G. (2015) · Nature Neuroscience · doi:10.1038/nn.3905 · Cited by 938 · see citing works
A transparent bending-insensitive pressure sensor
Lee, S., Reuveny, A., Reeder, J., Lee, S., Jin, H., Liu, Q., Yokota, T., Sekitani, T., Isoyama, T., Abe, Y., et al. (2016) · Nature Nanotechnology · doi:10.1038/nnano.2015.324 · Cited by 833 · see citing works
Flexible and Stretchable Electronics for Biointegrated Devices
Kim, D.-H., Ghaffari, R., Lu, N., & Rogers, J. A. (2012) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-071811-150018 · Cited by 749 · see citing works
Self-citationNovel electrode technologies for neural recordings
Hong, G., & Lieber, C. M. (2019) · Nature Reviews Neuroscience · doi:10.1038/s41583-019-0140-6 · Cited by 695 · see citing works
Electronic skins and machine learning for intelligent soft robots
Shih, B., Shah, D., Li, J., Thuruthel, T. G., Park, Y.-L., Iida, F., Bao, Z., Kramer-Bottiglio, R., & Tolley, M. T. (2020) · Science Robotics · doi:10.1126/scirobotics.aaz9239 · Cited by 715 · see citing works
Neural recording and modulation technologies
Chen, R., Canales, A., & Anikeeva, P. (2017) · Nature Reviews Materials · doi:10.1038/natrevmats.2016.93 · Cited by 655 · see citing works
Flexible Hybrid Electronics for Digital Healthcare
Ma, Y., Zhang, Y., Cai, S., Han, Z., Liu, X., Wang, F., Cao, Y., Wang, Z., Li, H., Chen, Y., et al. (2020) · Advanced Materials · doi:10.1002/adma.201902062 · Cited by 620 · see citing works
Flexible Electronics and Devices as Human–Machine Interfaces for Medical Robotics
Heng, W., Solomon, S., & Gao, W. (2022) · Advanced Materials · doi:10.1002/adma.202107902 · Cited by 609 · see citing works
Park, D.-W., Schendel, A. A., Mikael, S., Brodnick, S. K., Richner, T. J., Ness, J. P., Hayat, M. R., Atry, F., Frye, S. T., Pashaie, R., et al. (2014) · Nature Communications · doi:10.1038/ncomms6258 · Cited by 565 · see citing works
Yu, K. J., Kuzum, D., Hwang, S.-W., Kim, B. H., Juul, H., Kim, N. H., Won, S. M., Chiang, K., Trumpis, M., Richardson, A. G., et al. (2016) · Nature Materials · doi:10.1038/nmat4624 · Cited by 523 · see citing works
Self-citationNext-generation probes, particles, and proteins for neural interfacing
Rivnay, J., Wang, H., Fenno, L., Deisseroth, K., & Malliaras, G. G. (2017) · Science Advances · doi:10.1126/sciadv.1601649 · Cited by 514 · see citing works
Materials for flexible bioelectronic systems as chronic neural interfaces
Song, E., Li, J., Won, S. M., Bai, W., & Rogers, J. A. (2020) · Nature Materials · doi:10.1038/s41563-020-0679-7 · Cited by 498 · see citing works
Self-citationUltraflexible, large-area, physiological temperature sensors for multipoint measurements
Yokota, T., Inoue, Y., Terakawa, Y., Reeder, J., Kaltenbrunner, M., Ware, T., Yang, K., Mabuchi, K., Murakawa, T., Sekino, M., et al. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1515650112 · Cited by 382 · see citing works
Wireless and battery-free technologies for neuroengineering
Won, S. M., Cai, L., Gutruf, P., & Rogers, J. A. (2021) · Nature Biomedical Engineering · doi:10.1038/s41551-021-00683-3 · Cited by 360 · see citing works
Self-citationZhang, Y., Wang, S., Li, X., Fan, J. A., Xu, S., Song, Y. M., Choi, K., Yeo, W., Lee, W., Nazaar, S. N., et al. (2014) · Advanced Functional Materials · doi:10.1002/adfm.201302957 · Cited by 354 · see citing works
Self-citationSoft Materials in Neuroengineering for Hard Problems in Neuroscience
Jeong, J.-W., Shin, G., Park, S. I., Yu, K. J., Xu, L., & Rogers, J. A. (2015) · Neuron · doi:10.1016/j.neuron.2014.12.035 · Cited by 333 · see citing works
Self-citationEnergy autonomous electronic skin
García Núñez, C., Manjakkal, L., & Dahiya, R. (2019) · npj Flexible Electronics · doi:10.1038/s41528-018-0045-x · Cited by 332 · see citing works
Consciousness in humans and non-human animals: recent advances and future directions
Boly, M., Seth, A. K., Wilke, M., Ingmundson, P., Baars, B., Laureys, S., Edelman, D. B., & Tsuchiya, N. (2013) · Frontiers in Psychology · doi:10.3389/fpsyg.2013.00625 · Cited by 291 · see citing works
Fang, H., Yu, K. J., Gloschat, C., Yang, Z., Song, E., Chiang, C.-H., Zhao, J., Won, S. M., Xu, S., Trumpis, M., et al. (2017) · Nature Biomedical Engineering · doi:10.1038/s41551-017-0038 · Cited by 278 · see citing works
Self-citationEEG-Based Brain-Computer Interfaces: A Thorough Literature Survey
Hwang, H.-J., Kim, S., Choi, S., & Im, C.-H. (2013) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2013.780869 · Cited by 257 · see citing works
Zhou, T., Hong, G., Fu, T.-M., Yang, X., Schuhmann, T. G., Viveros, R. D., & Lieber, C. M. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1705509114 · Cited by 227 · see citing works
Zhang, M., Tang, Z., Liu, X., & Van der Spiegel, J. (2020) · Nature Electronics · doi:10.1038/s41928-020-0390-3 · Cited by 231 · see citing works
Self-citationChiang, C.-H., Won, S. M., Orsborn, A. L., Yu, K. J., Trumpis, M., Bent, B., Wang, C., Xue, Y., Min, S., Woods, V., et al. (2020) · Science Translational Medicine · doi:10.1126/scitranslmed.aay4682 · Cited by 211 · see citing works
Self-citationLi, Q., Nan, K., Le Floch, P., Lin, Z., Sheng, H., Blum, T. S., & Liu, J. (2019) · Nano Letters · doi:10.1021/acs.nanolett.9b02512 · Cited by 224 · see citing works
Herbert, R., Kim, J.-H., Kim, Y., Lee, H., & Yeo, W.-H. (2018) · Materials · doi:10.3390/ma11020187 · Cited by 220 · see citing works
Self-citationFlexible Neural Electrode Array Based-on Porous Graphene for Cortical Microstimulation and Sensing
Lu, Y., Lyu, H., Richardson, A. G., Lucas, T. H., & Kuzum, D. (2016) · Scientific Reports · doi:10.1038/srep33526 · Cited by 213 · see citing works
Recent advances in neurotechnologies with broad potential for neuroscience research
Vázquez-Guardado, A., Yang, Y., Bandodkar, A. J., & Rogers, J. A. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-00739-8 · Cited by 202 · see citing works
Self-citationRecent Advances in Materials, Devices, and Systems for Neural Interfaces
Won, S. M., Song, E., Zhao, J., Li, J., Rivnay, J., & Rogers, J. A. (2018) · Advanced Materials · doi:10.1002/adma.201800534 · Cited by 206 · see citing works
Self-citationAutomated long-term recording and analysis of neural activity in behaving animals
Dhawale, A. K., Poddar, R., Wolff, S. B., Normand, V. A., Kopelowitz, E., & Ölveczky, B. P. (2017) · eLife · doi:10.7554/elife.27702 · Cited by 159 · see citing works
Implantable neurotechnologies: a review of micro- and nanoelectrodes for neural recording
Patil, A. C., & Thakor, N. V. (2016) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-015-1430-4 · Cited by 175 · see citing works
Kim, D., Wang, S., Keum, H., Ghaffari, R., Kim, Y., Tao, H., Panilaitis, B., Li, M., Kang, Z., Omenetto, F., et al. (2012) · Small · doi:10.1002/smll.201200933 · Cited by 170 · see citing works
Self-citationSasaki, M., Karikkineth, B. C., Nagamine, K., Kaji, H., Torimitsu, K., & Nishizawa, M. (2014) · Advanced Healthcare Materials · doi:10.1002/adhm.201400209 · Cited by 169 · see citing works
Kwon, K. Y., Sirowatka, B., Weber, A., & Li, W. (2013) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2013.2282318 · Cited by 166 · see citing works
Mesh electronics: a new paradigm for tissue-like brain probes
Hong, G., Yang, X., Zhou, T., & Lieber, C. M. (2018) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2017.11.007 · Cited by 159 · see citing works
Human brain mapping with multithousand-channel PtNRGrids resolves spatiotemporal dynamics
Tchoe, Y., Bourhis, A. M., Cleary, D. R., Stedelin, B., Lee, J., Tonsfeldt, K. J., Brown, E. C., Siler, D. A., Paulk, A. C., Yang, J. C., et al. (2022) · Science Translational Medicine · doi:10.1126/scitranslmed.abj1441 · Cited by 135 · see citing works
Translating the Brain-Machine Interface
Thakor, N. V. (2013) · Science Translational Medicine · doi:10.1126/scitranslmed.3007303 · Cited by 128 · see citing works
Nason, S. R., Vaskov, A. K., Willsey, M. S., Welle, E. J., An, H., Vu, P. P., Bullard, A. J., Nu, C. S., Kao, J. C., Shenoy, K. V., et al. (2020) · Nature Biomedical Engineering · doi:10.1038/s41551-020-0591-0 · Cited by 113 · see citing works
Xiang, Z., Yen, S., Sheshadri, S., Wang, J., Lee, S., Liu, Y., Liao, L., Thakor, N. V., & Lee, C. (2016) · Advanced Materials · doi:10.1002/adma.201503423 · Cited by 116 · see citing works
Conformable hybrid systems for implantable bioelectronic interfaces
Fallegger, F., Schiavone, G., & Lacour, S. P. (2020) · Advanced Materials · doi:10.1002/adma.201903904 · Cited by 113 · see citing works
Electronics for the Human Body
Rogers, J. A. (2015) · JAMA · doi:10.1001/jama.2014.17915 · Cited by 91 · see citing works
Self-citationHigh-resolution neural recordings improve the accuracy of speech decoding
Duraivel, S., Rahimpour, S., Chiang, C.-H., Trumpis, M., Wang, C., Barth, K., Harward, S. C., Lad, S. P., Friedman, A. H., Southwell, D. G., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-42555-1 · Cited by 75 · see citing works
Self-citationChallenges for Large-Scale Cortical Interfaces
Nurmikko, A. (2020) · Neuron · doi:10.1016/j.neuron.2020.10.015 · Cited by 68 · see citing works
Zhu, B., Shin, U., & Shoaran, M. (2021) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2021.3112756 · Cited by 67 · see citing works
Conductively coupled flexible silicon electronic systems for chronic neural electrophysiology
Li, J., Song, E., Chiang, C.-H., Yu, K. J., Koo, J., Du, H., Zhong, Y., Hill, M., Wang, C., Zhang, J., et al. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1813187115 · Cited by 65 · see citing works
Self-citationTrindade, A. J., Guilhabert, B., Massoubre, D., Zhu, D., Laurand, N., Gu, E., Watson, I. M., Humphreys, C. J., & Dawson, M. D. (2013) · Applied Physics Letters · doi:10.1063/1.4851875 · Cited by 64 · see citing works
Giagka, V., & Serdijn, W. A. (2018) · Bioelectronic Medicine · doi:10.1186/s42234-018-0010-y · Cited by 58 · see citing works
Flexible wireless powered drug delivery system for targeted administration on cerebral cortex
Sung, S. H., Kim, Y. S., Joe, D. J., Mun, B. H., You, B. K., Keum, D. H., Hahn, S. K., Berggren, M., Kim, D., & Lee, K. J. (2018) · Nano Energy · doi:10.1016/j.nanoen.2018.06.015 · Cited by 55 · see citing works
Self-citationRecording and decoding for neural prostheses
Warren, D. J., Kellis, S., Nieveen, J. G., Wendelken, S. M., Dantas, H., Davis, T. S., Hutchinson, D. T., Normann, R. A., Clark, G. A., & Mathews, V. J. (2016) · Proceedings of the IEEE · doi:10.1109/jproc.2015.2507180 · Cited by 52 · see citing works
High-density mapping of primate digit representations with a 1152-channel µECoG array
Kaiju, T., Inoue, M., Hirata, M., & Suzuki, T. (2021) · Journal of Neural Engineering · doi:10.1088/1741-2552/abe245 · Cited by 42 · see citing works
The Layer 7 Cortical Interface: A Scalable and Minimally Invasive Brain–Computer Interface Platform
Hettick, M., Ho, E., Poole, A. J., Monge, M., Papageorgiou, D., Takahashi, K., LaMarca, M., Trietsch, D., Reed, K., Murphy, M., et al. (2022) · doi:10.1101/2022.01.02.474656 · Cited by 31 · see citing works
Large-scale, closed-loop interrogation of neural circuits underlying cognition.
Khodagholy, D., Ferrero, J. J., Park, J., Zhao, Z., & Gelinas, J. N. (2022) · Trends in Neurosciences · doi:10.1016/j.tins.2022.10.003 · Cited by 27 · see citing works
Recent advances in recording and modulation technologies for next-generation neural interfaces.
Hong, J.-W., Yoon, C., Jo, K., Won, J. H., & Park, S. (2021) · iScience · doi:10.1016/j.isci.2021.103550 · Cited by 25 · see citing works
Thukral, A., Ershad, F., Enan, N., Rao, Z., & Yu, C. (2018) · IEEE Nanotechnology Magazine · doi:10.1109/mnano.2017.2781290 · Cited by 19 · see citing works
Macroporous nanowire nanoelectronic scaffolds for synthetic tissues
Tian, B., Liu, J., Dvir, T., Jin, L., Tsui, J. H., Qing, Q., Suo, Z., Langer, R., Kohane, D. S., & Lieber, C. M. (2012) · Nature Materials · doi:10.1038/nmat3404 · Cited by 20 · see citing works
Lau, A. H. Y., Chik, G. K. K., Zhang, Z., Leung, T. K. W., & Chan, P. K. L. (2020) · Advanced Intelligent Systems · doi:10.1002/aisy.202000005 · Cited by 18 · see citing works
High-Density, Actively Multiplexed µECoG Array on Reinforced Silicone Substrate
Rachinskiy, I., Wong, L., Chiang, C.-H., Wang, C., Trumpis, M., Ogren, J. I., Hu, Z., McLaughlin, B., & Viventi, J. (2022) · Frontiers in Nanotechnology · doi:10.3389/fnano.2022.837328 · Cited by 14 · see citing works
Self-citationNeurophysiological 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
Thin-film, high-density micro-electrocorticographic decoding of a human cortical gyrus
Muller, L., Felix, S., Shah, K. G., Lee, K., Pannu, S., & Chang, E. F. (2016) · 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2016.7591001 · Cited by 15 · see citing works
Walker, R. M., Rieth, L., Iyer, S. S., Bajwa, A. A., Silver, J., Ahmed, T., Tasneem, N., Sharma, M., & Gardner, A. T. (2017) · 2017 IEEE 60th International Midwest Symposium on Circuits and Systems (MWSCAS) · doi:10.1109/mwscas.2017.8053106 · Cited by 7 · see citing works
- Authors
- Viventi, J., Kim, D.-H., Vigeland, L., Frechette, E. S., Blanco, J. A., Kim, Y.-S., Avrin, A. E., Tiruvadi, V. R., Hwang, S.-W., Vanleer, A. C., Wulsin, D. F., Davis, K., Gelber, C. E., Palmer, L., Van der Spiegel, J., Wu, J., Xiao, J., Huang, Y., Contreras, D., Rogers, J. A., & Litt, B.
- Affiliations
- New York University (US)
- Seoul National University (KR)
- University of Pennsylvania (US)
- Hospital of the University of Pennsylvania (US)
- United States Naval Academy (US)
- University of Illinois Urbana-Champaign (US)
- Tsinghua University (CN)
- University of Colorado Boulder (US)
- Northwestern University (US)
- Corresponding author
- Rogers, John A
- Litt, Brian
- ORCID
- Venue
- Nature Neuroscience
- Published
- 2011-11-13
- Volume
- 14
- Issue
- 12
- Pages
- 1599-1605
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- PMC
- PMC3235709
- OpenAlex
- W2105425384
- Semantic Scholar
- bbd162eb8f4aaccb5db074efe5f0e6eb421af799
- Cited by
- 1,136
- References
- 58
- Citations by year
- 2026: 46 · 2025: 67 · 2024: 56 · 2023: 56 · 2022: 65 · 2021: 92 · 2020: 96 · 2019: 94 · 2018: 97 · 2017: 103 · 2016: 88 · 2015: 89 · 2014: 78 · 2013: 73 · 2012: 36
- FWCI
- 24.56
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- Seoul National University Open Repository (Seoul National University) (submittedVersion)
- Funders
- National Science Foundation (DE-FG02-07ER46453, DE-FG02-07ER46471, 0328162)
- U.S. Department of Energy (DE‐FG02‐, FG02-07ER46453, DEFG0207ER46471, DEFG0207ER46453, FG02-07ER46471)
- National Institutes of Health (5r01ns048598-04, 5r01ns041811-10)
- National Heart, Lung, and Blood Institute (T32HL007954)
- National Eye Institute (R01EY020765, T32EY007035)
- National Institute of Neurological Disorders and Stroke (R01 NS-041811, R01-NS048598, R01 NS 48598)
- Division of Materials Research
- National Center for Research Resources (S10RR031724)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Physical Sciences › Engineering › Biomedical Engineering › Analog and Mixed-Signal Circuit Design
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- flexible electrode arrays, multi-electrode recording, sleep spindles, visual evoked potentials, electrographic seizures, epileptic activity, brain-computer interface, neural tissue damage
- MeSH terms
- Animals, Brain Mapping, Cats, Electric Stimulation, Electrodes, Implanted, Electroencephalography, Electronics, Evoked Potentials, Visual, Microelectrodes, Numerical Analysis, Computer-Assisted, Photic Stimulation, Seizures, Visual Cortex, Brain Waves
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