Multiplexed, High Density Electrophysiology with Nanofabricated Neural Probes
Open accessAbstract
Extracellular electrode arrays can reveal the neuronal network correlates of behavior with single-cell, single-spike, and sub-millisecond resolution. However, implantable electrodes are inherently invasive, and efforts to scale up the number and density of recording sites must compromise on device size in order to connect the electrodes. Here, we report on silicon-based neural probes employing nanofabricated, high-density electrical leads. Furthermore, we address the challenge of reading out multichannel data with an application-specific integrated circuit (ASIC) performing signal amplification, band-pass filtering, and multiplexing functions. We demonstrate high spatial resolution extracellular measurements with a fully integrated, low noise 64-channel system weighing just 330 mg. The on-chip multiplexers make possible recordings with substantially fewer external wires than the number of input channels. By combining nanofabricated probes with ASICs we have implemented a system for performing large-scale, high-density electrophysiology in small, freely behaving animals that is both minimally invasive and highly scalable.
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Some neural interface devices have been fabricated with high electrode densities, but their designs have limited their use to specific central nervous system structures such as cortical grey matter or hippocampal slices.
“Some neural interface devices have been fabricated with high electrode densities; however, their designs have limited the use of these arrays to specific central nervous system structures, such as cortical grey matter (6.25 electrodes/mm 2 [12,13]; >150 electrodes/mm 2 [17,18]) or hippocampal slices (<11 electrodes/mm 2 [19]).”
From A new high-density (25 electrodes/mm<sup>2</sup>) penetrating microelectrode array for recording and stimulating sub-millimeter neuroanatomical structures (2013) · cites this paper as [17]
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Cites
Receptive fields of single neurones in the cat's striate cortex
Hubel, D. H., & Wiesel, T. N. (1959) · The Journal of Physiology · doi:10.1113/jphysiol.1959.sp006308 · Cited by 4,653 · see citing works
Theta oscillations in the hippocampus
Buzsáki, G. (2002) · Neuron · doi:10.1016/s0896-6273(02)00586-x · Cited by 3,332 · see citing works
Large-scale recording of neuronal ensembles
Buzsáki, G. (2004) · Nature Neuroscience · doi:10.1038/nn1233 · Cited by 1,875 · see citing works
Modulation of visual responses by behavioral state in mouse visual cortex
Niell, C. M., & Stryker, M. P. (2010) · Neuron · doi:10.1016/j.neuron.2010.01.033 · Cited by 1,483 · cited 1× · see citing works
“For example, silicon probes containing dozens of recording sites on a thin penetrating shaft have yielded important insights into the function of the hippocampus [12] and visual cortex [13,14].”
BackgroundIntracellular Features Predicted by Extracellular Recordings in the Hippocampus In Vivo
Henze, D. A., Borhegyi, Z., Csicsvari, J., Mamiya, A., Harris, K. D., & Buzsáki, G. (2000) · Journal of Neurophysiology · doi:10.1152/jn.2000.84.1.390 · Cited by 942 · see citing works
Barthó, P., Hirase, H., Monconduit, L., Zugaro, M. B., Harris, K. D., & Buzsáki, G. (2004) · Journal of Neurophysiology · doi:10.1152/jn.01170.2003 · Cited by 888 · see citing works
Organization of cell assemblies in the hippocampus
Harris, K. D., Csicsvari, J., Hirase, H., Dragoi, G., & Buzsáki, G. (2003) · Nature · doi:10.1038/nature01834 · Cited by 869 · see citing works
Multiple neural spike train data analysis: state-of-the-art and future challenges
Brown, E. N., Kass, R. E., & Mitra, P. P. (2004) · Nature Neuroscience · doi:10.1038/nn1228 · Cited by 857 · see citing works
Tungsten Microelectrode for Recording from Single Units
Hubel, D. H. (1957) · Science · doi:10.1126/science.125.3247.549 · Cited by 852 · see citing works
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 798 · see citing works
Gray, C. M., Maldonado, P., Wilson, M., & McNaughton, B. L. (1995) · Journal of Neuroscience Methods · doi:10.1016/0165-0270(95)00085-2 · Cited by 746 · see citing works
Chronic, multisite, multielectrode recordings in macaque monkeys
Nicolelis, M. A. L., Dimitrov, D., Carmena, J. M., Crist, R., Lehew, G., Kralik, J. D., & Wise, S. P. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1934665100 · Cited by 740 · see citing works
A synaptic organizing principle for cortical neuronal groups
Perin, R., Berger, T. K., & Markram, H. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1016051108 · Cited by 718 · see citing works
How advances in neural recording affect data analysis
Stevenson, I. H., & Kording, K. P. (2011) · Nature Neuroscience · doi:10.1038/nn.2731 · Cited by 564 · see citing works
Basal forebrain activation enhances cortical coding of natural scenes
Goard, M. J., & Dan, Y. (2009) · Nature Neuroscience · doi:10.1038/nn.2402 · Cited by 558 · see citing works
Hazan, L., Zugaro, M. B., & Buzsáki, G. (2006) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2006.01.017 · Cited by 492 · see citing works
Das, A., & Gilbert, C. D. (1995) · Nature · doi:10.1038/375780a0 · Cited by 446 · see citing works
Massively Parallel Recording of Unit and Local Field Potentials With Silicon-Based Electrodes
Csicsvari, J., Henze, D. A., Jamieson, B., Harris, K. D., Sirota, A., Barthó, P., Wise, K. D., & Buzsáki, G. (2003) · Journal of Neurophysiology · doi:10.1152/jn.00116.2003 · Cited by 402 · see citing works
Drake, K. L., Wise, K. D., Farraye, J., Anderson, D. J., & BeMent, S. L. (1988) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.7273 · Cited by 364 · see citing works
Pettersen, K. H., Devor, A., Ulbert, I., Dale, A. M., & Einevoll, G. T. (2006) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2005.12.005 · Cited by 350 · see citing works
Biran, R., Martin, D. C., & Tresco, P. A. (2007) · Journal of Biomedical Materials Research Part A · doi:10.1002/jbm.a.31138 · Cited by 336 · see citing works
Microelectrodes, Microelectronics, and Implantable Neural Microsystems
Wise, K. D., Sodagar, A. M., Yao, Y., Gulari, M. N., Perlin, G. E., & Najafi, K. (2008) · Proceedings of the IEEE · doi:10.1109/jproc.2008.922564 · Cited by 336 · see citing works
The Design of Integrated Circuits to Observe Brain Activity
Harrison, R. R. (2008) · Proceedings of the IEEE · doi:10.1109/jproc.2008.922581 · Cited by 330 · see citing works
Self-citationUsing noise signature to optimize spike-sorting and to assess neuronal classification quality
Pouzat, C., Mazor, O., & Laurent, G. (2002) · Journal of Neuroscience Methods · doi:10.1016/s0165-0270(02)00276-5 · Cited by 310 · see citing works
Ludwig, K. A., Langhals, N. B., Joseph, M. D., Richardson-Burns, S. M., Hendricks, J. L., & Kipke, D. R. (2011) · Journal of Neural Engineering · doi:10.1088/1741-2560/8/1/014001 · Cited by 283 · see citing works
Polytrodes: High-Density Silicon Electrode Arrays for Large-Scale Multiunit Recording
Blanche, T. J., Spacek, M. A., Hetke, J. F., & Swindale, N. V. (2005) · Journal of Neurophysiology · doi:10.1152/jn.01023.2004 · Cited by 282 · see citing works
Self-citationHow silent is the brain: is there a “dark matter” problem in neuroscience?
Shoham, S., O’Connor, D. H., & Segev, R. (2006) · Journal of Comparative Physiology A · doi:10.1007/s00359-006-0117-6 · Cited by 238 · see citing works
Recording spikes from a large fraction of the ganglion cells in a retinal patch
Segev, R., Goodhouse, J., Puchalla, J., & Berry, M. J. (2004) · Nature Neuroscience · doi:10.1038/nn1323 · Cited by 221 · see citing works
Implant Size and Fixation Mode Strongly Influence Tissue Reactions in the CNS
Thelin, J., Jörntell, H., Psouni, E., Garwicz, M., Schouenborg, J., Danielsen, N., & Linsmeier, C. E. (2011) · PLoS ONE · doi:10.1371/journal.pone.0016267 · Cited by 188 · see citing works
Coherent gamma oscillations couple the amygdala and striatum during learning
Popescu, A. T., Popa, D., & Paré, D. (2009) · Nature Neuroscience · doi:10.1038/nn.2305 · Cited by 187 · see citing works
A 32-site neural recording probe fabricated by DRIE of SOI substrates
Peter Norlin, A., Kindlundh, M., Mouroux, A., Yoshida, K., & Hofmann, U. (2002) · Journal of Micromechanics and Microengineering · doi:10.1088/0960-1317/12/4/312 · Cited by 184 · see citing works
A wireless multi-channel neural amplifier for freely moving animals
Szuts, T. A., Fadeyev, V., Kachiguine, S., Sher, A., Grivich, M., Agrochão, M., Hottowy, P., Dąbrowski, W., Lubenov, E. V., Siapas, A. G., et al. (2011) · Nature Neuroscience · doi:10.1038/nn.2730 · Cited by 183 · see citing works
OlssonIII, R. H., Buhl, D. L., Sirota, A. M., Buzsaki, G., & Wise, K. D. (2005) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2005.847540 · Cited by 181 · see citing works
Silicon ribbon cables for chronically implantable microelectrode arrays
Hetke, J. F., Lund, J. L., Najafi, K., Wise, K. D., & Anderson, D. J. (1994) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.284959 · Cited by 174 · see citing works
Review of signal distortion through metal microelectrode recording circuits and filters
Nelson, M. J., Pouget, P., Nilsen, E. A., Patten, C. D., & Schall, J. D. (2008) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2007.12.010 · Cited by 167 · see citing works
Scaling limitations of silicon multichannel recording probes
Najafi, K., Ji, J., & Wise, K. D. (1990) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.43605 · Cited by 163 · see citing works
Miranda, H. C., Gilja, V., Chestek, C. A., Shenoy, K. V., & Meng, T. H. Y. (2010) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2010.2044573 · Cited by 161 · see citing works
Reverse engineering the mouse brain
O’Connor, D. H., Huber, D., & Svoboda, K. (2009) · Nature · doi:10.1038/nature08539 · Cited by 137 · see citing works
Hutzler, M., Lambacher, A., Eversmann, B., Jenkner, M., Thewes, R., & Fromherz, P. (2006) · Journal of Neurophysiology · doi:10.1152/jn.00347.2006 · Cited by 128 · see citing works
Fidelity of the Ensemble Code for Visual Motion in Primate Retina
Frechette, E. S., Sher, A., Grivich, M. I., Petrusca, D., Litke, A. M., & Chichilnisky, E. J. (2005) · Journal of Neurophysiology · doi:10.1152/jn.01175.2004 · Cited by 125 · see citing works
Herwik, S., Kisban, S., Aarts, A. A. A., Seidl, K., Girardeau, G., Benchenane, K., Zugaro, M. B., Wiener, S. I., Paul, O., Neves, H. P., et al. (2009) · Journal of Micromechanics and Microengineering · doi:10.1088/0960-1317/19/7/074008 · Cited by 113 · see citing works
Chen, Y., Lai, H.-Y., Lin, S.-H., Chao, W.-H., Chao, W.-H., Liao, C., Tsang, S., Chen, Y., & Lin, S.-Y. (2009) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2009.05.010 · Cited by 110 · see citing works
Large-scale neural ensemble recording in the brains of freely behaving mice
Lin, L., Chen, G., Xie, K., Zaia, K. A., Zhang, S., & Tsien, J. Z. (2006) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2005.12.032 · Cited by 108 · see citing works
A Wireless Implantable Microsystem for Multichannel Neural Recording
Sodagar, A. M., Wise, K. D., & Najafi, K. (2009) · IEEE Transactions on Microwave Theory and Techniques · doi:10.1109/tmtt.2009.2029957 · Cited by 90 · see citing works
Recent Progress in Neural Probes Using Silicon MEMS Technology
Ruther, P., Herwik, S., Kisban, S., Seidl, K., & Paul, O. (2010) · IEEJ Transactions on Electrical and Electronic Engineering · doi:10.1002/tee.20566 · Cited by 82 · see citing works
Implantable multichannel electrode array based on soi technology
Cheung, K. C., Djupsund, K., Dan, Y., & Lee, L. P. (2003) · Journal of Microelectromechanical Systems · doi:10.1109/jmems.2003.809962 · Cited by 81 · see citing works
Du, J., Riedel-Kruse, I. H., Nawroth, J. C., Roukes, M. L., Laurent, G., & Masmanidis, S. C. (2008) · Journal of Neurophysiology · doi:10.1152/jn.90992.2008 · Cited by 80 · see citing works
Self-citationThe Lantern: An ultra-light micro-drive for multi-tetrode recordings in mice and other small animals
Battaglia, F. P., Kalenscher, T., Cabral, H., Winkel, J., Bos, J. J., Manuputy, R., van Lieshout, T., Pinkse, F. A., Beukers, H., & Pennartz, C. M. A. (2008) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2008.12.024 · Cited by 51 · see citing works
A 3-D 160-Site Microelectrode Array for Cochlear Nucleus Mapping
Merriam, M. E., Dehmel, S., Srivannavit, O., Shore, S. E., & Wise, K. D. (2010) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2010.2088122 · Cited by 30 · see citing works
Wiring Nanoscale Biosensors with Piezoelectric Nanomechanical Resonators
Sadek, A. S., Karabalin, R. B., Du, J., Roukes, M. L., Christof Koch, A., & Masmanidis, S. C. (2010) · Nano Letters · doi:10.1021/nl100245z · Cited by 25 · see citing works
Self-citationSilicon Microelectrodes with Flexible Integrated Cables for Neural Implant Applications
Yao, Y., Gulari, M. N., Casey, B., Wiler, J. A., & Wise, K. D. (2007) · International IEEE/EMBS Conference on Neural Engineering · doi:10.1109/cne.2007.369693 · Cited by 24 · see citing works
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The origin of extracellular fields and currents — EEG, ECoG, LFP and spikes
Buzsáki, G., Anastassiou, C. A., & Koch, C. (2012) · Nature Reviews Neuroscience · doi:10.1038/nrn3241 · Cited by 4,225 · see citing works
Modelling and analysis of local field potentials for studying the function of cortical circuits
Einevoll, G. T., Kayser, C., Logothetis, N. K., & Panzeri, S. (2013) · Nature Reviews Neuroscience · doi:10.1038/nrn3599 · Cited by 857 · see citing works
Spike sorting for large, dense electrode arrays
Rossant, C., Kadir, S., Goodman, D. F. M., Schulman, J., Hunter, M. L. D., Saleem, A. B., Grosmark, A., Belluscio, M., Denfield, G. H., Ecker, A. S., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4268 · Cited by 760 · see citing works
Revealing neuronal function through microelectrode array recordings
Obien, M. E. J., Deligkaris, K., Bullmann, T., Bakkum, D. J., & Frey, U. (2015) · Frontiers in Neuroscience · doi:10.3389/fnins.2014.00423 · Cited by 705 · see citing works
A Fully Automated Approach to Spike Sorting
Chung, J. E., Magland, J. F., Barnett, A. H., Tolosa, V., Tooker, A., Lee, K. Y., Shah, K. G., Felix, S. H., Frank, L. M., & Greengard, L. (2017) · Neuron · doi:10.1016/j.neuron.2017.08.030 · Cited by 477 · see citing works
Nanotools for Neuroscience and Brain Activity Mapping
Alivisatos, A. P., Andrews, A. M., Boyden, E. S., Chun, M., Church, G. M., Deisseroth, K. A., Donoghue, J. P., Fraser, S. E., Lippincott‐Schwartz, J., Looger, L. L., et al. (2013) · ACS Nano · doi:10.1021/nn4012847 · Cited by 353 · see citing works
Self-citationChallenges and opportunities for large-scale electrophysiology with Neuropixels probes
Steinmetz, N. A., Koch, C., Harris, K. D., & Carandini, M. (2018) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2018.01.009 · Cited by 331 · see citing works
Tools for Probing Local Circuits: High-Density Silicon Probes Combined with Optogenetics
Buzsáki, G., Stark, E., Berényi, A., Khodagholy, D., Kipke, D. R., Yoon, E., & Wise, K. D. (2015) · Neuron · doi:10.1016/j.neuron.2015.01.028 · Cited by 328 · see citing works
Large-scale, high-density (up to 512 channels) recording of local circuits in behaving animals
Berényi, A., Somogyvári, Z., Nagy, A. J., Roux, L., Long, J. D., Fujisawa, S., Stark, E., Leonardo, A. M., Harris, T. D., & Buzsáki, G. (2013) · Journal of Neurophysiology · doi:10.1152/jn.00785.2013 · Cited by 299 · 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
An Implantable 455-Active-Electrode 52-Channel CMOS Neural Probe
Lopez, C. M., Andrei, A., Mitra, S., Welkenhuysen, M., Eberle, W., Bartic, C., Puers, R., Yazicioglu, R. F., & Gielen, G. G. E. (2014) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2013.2284347 · Cited by 264 · see citing works
Locomotion Enhances Neural Encoding of Visual Stimuli in Mouse V1
Dadarlat, M. C., & Stryker, M. P. (2017) · The Journal of Neuroscience · doi:10.1523/jneurosci.2728-16.2017 · Cited by 205 · see citing works
Close-Packed Silicon Microelectrodes for Scalable Spatially Oversampled Neural Recording
Scholvin, J., Kinney, J. P., Bernstein, J. G., Moore-Kochlacs, C., Kopell, N., Fonstad, C. G., & Boyden, E. S. (2015) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2015.2406113 · Cited by 203 · see citing works
Panier, T., Romano, S. A., Olive, R., Pietri, T., Sumbre, G., Candelier, R., & Debrégeas, G. (2013) · Frontiers in Neural Circuits · doi:10.3389/fncir.2013.00065 · Cited by 201 · see citing works
A Neural Probe With Up to 966 Electrodes and Up to 384 Configurable Channels in 0.13 $\mu$m SOI CMOS
López, C. M., Putzeys, J., Raducanu, B. C., Ballini, M., Wang, S., Andrei, A., Rochus, V., Vandebriel, R., Severi, S., Hoof, C. A. V., et al. (2017) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2016.2646901 · Cited by 198 · see citing works
Reconfigurable nanophotonic silicon probes for sub-millisecond deep-brain optical stimulation
Mohanty, A., Li, Q., Tadayon, M. A., Roberts, S. P., Bhatt, G. R., Shim, E., Ji, X., Cardenas, J., Miller, S. A., Kepecs, A., et al. (2020) · Nature Biomedical Engineering · doi:10.1038/s41551-020-0516-y · Cited by 189 · see citing works
Flexible, Penetrating Brain Probes Enabled by Advances in Polymer Microfabrication
Weltman, A., Yoo, J. J., & Meng, E. F. (2016) · Micromachines · doi:10.3390/mi7100180 · Cited by 180 · see citing works
Neural Dust: An Ultrasonic, Low Power Solution for Chronic Brain-Machine Interfaces
Seo, D., Carmena, J. M., Rabaey, J. M., Alon, E., & Maharbiz, M. M. (2013) · arXiv · doi:10.48550/arxiv.1307.2196 · Cited by 172 · see citing works
Shin, H., Son, Y., Chae, U., Kim, J., Choi, N., Lee, H. J., Woo, J., Cho, Y., Yang, S. H., Lee, C. J., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-11628-5 · Cited by 169 · see citing works
Implantable aptamer–field-effect transistor neuroprobes for in vivo neurotransmitter monitoring
Zhao, C., Cheung, K. M., Huang, I.-W., Yang, H., Nakatsuka, N., Liu, W., Cao, Y. F., Man, T., Weiss, P. S., Monbouquette, H. G., et al. (2021) · Science Advances · doi:10.1126/sciadv.abj7422 · Cited by 169 · see citing works
Time Multiplexed Active Neural Probe with 1356 Parallel Recording Sites
Raducanu, B. C., Yazıcıoğlu, R. F., López, C. M., Ballini, M., Putzeys, J., Wang, S., Andrei, A., Rochus, V., Welkenhuysen, M., Helleputte, N. V., et al. (2017) · Sensors · doi:10.3390/s17102388 · Cited by 166 · see citing works
Patel, P. R., Na, K., Zhang, H., Kozai, T. D. Y., Kotov, N. A., Yoon, E., & Chestek, C. A. (2015) · Journal of Neural Engineering · doi:10.1088/1741-2560/12/4/046009 · Cited by 160 · see citing works
Automated 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
Model validation of untethered, ultrasonic neural dust motes for cortical recording
Seo, D., Carmena, J. M., Rabaey, J. M., Maharbiz, M. M., & Alon, E. (2015) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2014.07.025 · Cited by 158 · see citing works
Nanofabricated Neural Probes for Dense 3-D Recordings of Brain Activity
Rios, G., Lubenov, E. V., Chi, D., Roukes, M. L., & Siapas, A. G. (2016) · Nano Letters · doi:10.1021/acs.nanolett.6b02673 · Cited by 157 · see citing works
Luan, L., Robinson, J. T., Aazhang, B., Chi, T., Yang, K., Li, X., Rathore, H., Singer, A., Yellapantula, S., Fan, Y., et al. (2020) · Neuron · doi:10.1016/j.neuron.2020.10.011 · Cited by 150 · see citing works
A very large-scale microelectrode array for cellular-resolution electrophysiology
Tsai, D., Sawyer, D., Bradd, A., Yuste, R., & Shepard, K. L. (2017) · Nature Communications · doi:10.1038/s41467-017-02009-x · Cited by 150 · see citing works
Wark, H. A. C., Sharma, R., Mathews, K. S., Fernandez, E., Yoo, J., Christensen, B., Tresco, P., Rieth, L., Solzbacher, F., Normann, R. A., et al. (2013) · Journal of Neural Engineering · doi:10.1088/1741-2560/10/4/045003 · Cited by 148 · see citing works
Brain activity mapping at multiple scales with silicon microprobes containing 1,024 electrodes
Shobe, J. L., Claar, L. D., Parhami, S., Bakhurin, K. I., & Masmanidis, S. C. (2015) · Journal of Neurophysiology · doi:10.1152/jn.00464.2015 · Cited by 146 · see citing works
Self-citationNanofabricated Ultraflexible Electrode Arrays for High‐Density Intracortical Recording
Wei, X., Luan, L., Zhao, Z., Li, X., Zhu, H., Potnis, O., & Xie, C. (2018) · Advanced Science · doi:10.1002/advs.201700625 · Cited by 146 · see citing works
Frequency Dependence of Signal Power and Spatial Reach of the Local Field Potential
Łęski, S., Lindén, H., Tetzlaff, T., Pettersen, K. H., & Einevoll, G. T. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003137 · Cited by 145 · see citing works
Optimal Electrode Size for Multi-Scale Extracellular-Potential Recording From Neuronal Assemblies
Viswam, V., Obien, M. E. J., Franke, F., Frey, U., & Hierlemann, A. R. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00385 · Cited by 136 · see citing works
Nanostructures: a platform for brain repair and augmentation
Vidu, R., Rahman, M., Mahmoudi, M., Enăchescu, M., Potecă, T. D., & Opriș, I. C. (2014) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2014.00091 · Cited by 132 · see citing works
A 75-µW, 16-Channel Neural Spike-Sorting Processor With Unsupervised Clustering
Karkare, V., Gibson, S., & Markovic, D. M. (2013) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2013.2264616 · Cited by 130 · see citing works
Lazaro, M. T., Taxidis, J., Shuman, T., Bachmutsky, I., Ikrar, T., Santos, R., Marcello, G. M., Mylavarapu, A., Chandra, S., Foreman, A., et al. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.05.006 · Cited by 125 · see citing works
Self-citationThe sifting of visual information in the superior colliculus
Lee, K. H., Tran, A., Turan, Z., & Meister, M. (2020) · eLife · doi:10.7554/elife.50678 · Cited by 117 · see citing works
Does Impedance Matter When Recording Spikes With Polytrodes?
Neto, J. P., Baião, P., Lopes, G., Frazão, J., Nogueira, J., Fortunato, E. M. C., Barquinha, P. M. C., & Kampff, A. R. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00715 · Cited by 103 · see citing works
Recent advances in silicon-based neural microelectrodes and microsystems: a review
Fekete, Z. (2015) · Sensors and Actuators B Chemical · doi:10.1016/j.snb.2015.03.055 · Cited by 99 · see citing works
Dorigo, D. D., Moranz, C., Graf, H., Marx, M., Wendler, D., Shui, B., Herbawi, A. S., Kuhl, M., Ruther, P., Paul, O., et al. (2018) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2018.2873180 · Cited by 94 · see citing works
Ito, S., Feldheim, D. A., & Litke, A. M. (2017) · The Journal of Neuroscience · doi:10.1523/jneurosci.3689-16.2017 · Cited by 92 · see citing works
Validating silicon polytrodes with paired juxtacellular recordings: method and dataset
Neto, J. P., Lopes, G., Frazão, J., Nogueira, J., Lacerda, P., Baião, P., Aarts, A. A. A., Andrei, A., Musa, S., Fortunato, E. M. C., et al. (2016) · Journal of Neurophysiology · doi:10.1152/jn.00103.2016 · Cited by 91 · see citing works
Kirchgessner, M. A., Franklin, A. D., & Callaway, E. M. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2002080117 · Cited by 87 · see citing works
Open source silicon microprobes for high throughput neural recording
Yang, L., Lee, K., Villagracia, J., & Masmanidis, S. C. (2019) · Journal of Neural Engineering · doi:10.1088/1741-2552/ab581a · Cited by 86 · see citing works
Self-citationSung, C., Jeon, W., Nam, K. S., Kim, Y., Butt, H., & Park, S. (2020) · Journal of Materials Chemistry B · doi:10.1039/d0tb00872a · Cited by 85 · see citing works
In vivo optogenetic identification and manipulation of GABAergic interneuron subtypes
Roux, L., Stark, E., Sjulson, L., & Buzsáki, G. (2014) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2013.12.013 · Cited by 83 · see citing works
Fiáth, R., Raducanu, B. C., Musa, S., Andrei, A., López, C. M., Hoof, C. A. V., Ruther, P., Aarts, A. A. A., Horváth, D., & Ulbert, I. (2018) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2018.01.060 · Cited by 81 · see citing works
Shim, E., Chen, Y., Masmanidis, S. C., & Li, M. (2016) · Scientific Reports · doi:10.1038/srep22693 · Cited by 80 · see citing works
Self-citationNewman, J. P., Zeller-Townson, R., Fong, M., Desai, S. A., Gross, R. E., & Potter, S. M. (2013) · Frontiers in Neural Circuits · doi:10.3389/fncir.2012.00098 · Cited by 73 · see citing works
22.7 A 966-electrode neural probe with 384 configurable channels in 0.13µm SOI CMOS
López, C. M., Mitra, S., Putzeys, J., Raducanu, B., Ballini, M., Andrei, A., Severi, S., Welkenhuysen, M., Hoof, C. A. V., Musa, S., et al. (2016) · Digest of technical papers/Digest of technical papers - IEEE International Solid-State Circuits Conference · doi:10.1109/isscc.2016.7418072 · Cited by 68 · see citing works
Nanoelectronic Coating Enabled Versatile Multifunctional Neural Probes
Zhao, Z., Luan, L., Wei, X., Zhu, H., Li, X., Lin, S. Q., Siegel, J. J., Chitwood, R. A., & Xie, C. (2017) · Nano Letters · doi:10.1021/acs.nanolett.7b00956 · Cited by 65 · see citing works
Translational Neuroelectronics
Jastrzebska‐Perfect, P., Chowdhury, S., Spyropoulos, G. D., Zhao, Z., Cea, C., Gelinas, J. N., & Khodagholy, D. (2020) · Advanced Functional Materials · doi:10.1002/adfm.201909165 · Cited by 64 · see citing works
New approaches for CMOS-based devices for large-scale neural recording
Ruther, P., & Paul, O. (2014) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2014.10.007 · Cited by 61 · see citing works
Flexible and Implantable Polyimide Aptamer-Field-Effect Transistor Biosensors
Zhao, C., Man, T., Cao, Y. F., Weiss, P. S., Monbouquette, H. G., & Andrews, A. M. (2022) · ACS Sensors · doi:10.1021/acssensors.2c01909 · Cited by 60 · see citing works
Nanowire electrodes for high-density stimulation and measurement of neural circuits
Robinson, J. T., Jorgolli, M., & Park, H. (2013) · Frontiers in Neural Circuits · doi:10.3389/fncir.2013.00038 · Cited by 60 · see citing works
Neural Probes for Chronic Applications
Kook, G., Lee, S., Lee, H., Cho, I., & Lee, H. J. (2016) · Micromachines · doi:10.3390/mi7100179 · Cited by 58 · see citing works
Distinct “driving” versus “modulatory” influences of different visual corticothalamic pathways
Kirchgessner, M. A., Franklin, A. D., & Callaway, E. M. (2021) · Current Biology · doi:10.1016/j.cub.2021.09.025 · Cited by 55 · see citing works
Kim, H. W., Kim, J., Kim, J. Y., Kim, K., Lee, J. Y., Kim, T., Cho, S., An, J. B., Kim, H. J., Sun, L., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-59303-2 · Cited by 52 · see citing works
Neural ensemble communities: open-source approaches to hardware for large-scale electrophysiology
Siegle, J. H., Hale, G., Newman, J. P., & Voigts, J. (2014) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2014.11.004 · Cited by 52 · see citing works
Coordinated neuronal ensembles in primary auditory cortical columns
See, J. Z., Atencio, C. A., Sohal, V. S., & Schreiner, C. E. (2018) · eLife · doi:10.7554/elife.35587 · Cited by 52 · see citing works
Time multiplexed active neural probe with 678 parallel recording sites
Raducanu, B. C., Yazıcıoğlu, R. F., López, C. M., Ballini, M., Putzeys, J., Wang, S., Andrei, A., Welkenhuysen, M., Helleputte, N. V., Musa, S., et al. (2016) · European Solid-State Device Research Conference · doi:10.1109/essderc.2016.7599667 · Cited by 51 · see citing works
Electrophysiology Read-Out Tools for Brain-on-Chip Biotechnology
Forró, C., Caron, D., Angotzi, G. N., Gallo, V., Berdondini, L., Santoro, F., Palazzolo, G., & Panuccio, G. (2021) · Micromachines · doi:10.3390/mi12020124 · Cited by 50 · see citing works
Emergence of Slow-Switching Assemblies in Structured Neuronal Networks
Schaub, M. T., Billeh, Y. N., Anastassiou, C. A., Koch, C., & Barahona, M. (2015) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004196 · Cited by 49 · see citing works
Seidl, K., Schwaerzle, M., Ulbert, I., Neves, H. P., Paul, O., & Ruther, P. (2012) · Journal of Microelectromechanical Systems · doi:10.1109/jmems.2012.2206564 · Cited by 47 · see citing works
Shanks, J. A., Ito, S., Schaevitz, L. R., Yamada, J., Chen, B., Litke, A. M., & Feldheim, D. A. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.4599-15.2016 · Cited by 46 · see citing works
Divergence in Population Coding for Space between Dorsal and Ventral CA1
Chockanathan, U., & Padmanabhan, K. (2021) · eNeuro · doi:10.1523/eneuro.0211-21.2021 · Cited by 42 · see citing works
MANTA—an open-source, high density electrophysiology recording suite for MATLAB
Englitz, B., David, S. V., Sorenson, M. D., & Shamma, S. (2013) · Frontiers in Neural Circuits · doi:10.3389/fncir.2013.00069 · Cited by 41 · see citing works
Opto‐electro‐thermal optimization of photonic probes for optogenetic neural stimulation
Dong, N., Palmini, R. B., Soltan, A., Ponon, N. K., O'Neil, A., Travelyan, A., Maaskant, P. P., Degenaar, P. A., & Sun, X. (2018) · Journal of Biophotonics · doi:10.1002/jbio.201700358 · Cited by 41 · see citing works
Inter-laminar microcircuits across neocortex: repair and augmentation
Opriș, I. C. (2013) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2013.00080 · Cited by 40 · see citing works
Park, S., Na, K., Vöröslakos, M., Song, H., Slager, N., Oh, S., Seymour, J. P., Buzsáki, G., & Yoon, E. (2021) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2021.3093542 · Cited by 40 · see citing works
An implantable 455-active-electrode 52-channel CMOS neural probe
López, C. M., Andrei, A., Mitra, S., Welkenhuysen, M., Eberle, W., Bartic, C., Puers, R., Yazıcıoğlu, R. F., & Gielen, G. E. (2013) · Digest of technical papers/Digest of technical papers - IEEE International Solid-State Circuits Conference · doi:10.1109/isscc.2013.6487738 · Cited by 39 · see citing works
Marques–Smith, A., Neto, J. P., Lopes, G., Nogueira, J., Calcaterra, L., Frazão, J., Kim, D., Phillips, M. G., Dimitriadis, G., & Kampff, A. R. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/370080 · Cited by 39 · see citing works
McBride, E. G., Lee, S.-Y. J., & Callaway, E. M. (2019) · Current Biology · doi:10.1016/j.cub.2019.03.065 · Cited by 38 · see citing works
Schwartz, Z. P., Buran, B. N., & David, S. V. (2019) · Journal of Neurophysiology · doi:10.1152/jn.00595.2019 · Cited by 37 · see citing works
Biocompatible reference electrodes to enhance chronic electrochemical signal fidelity in vivo
Seaton, B. T., & Heien, M. L. (2021) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-021-03640-w · Cited by 36 · see citing works
Chik, G. K. K., Xiao, N., Ji, X., Tsang, A. C. O., Leung, G., Zhang, S., Tin, C., & Chan, P. K. L. (2022) · Advanced Materials Technologies · doi:10.1002/admt.202200143 · Cited by 32 · see citing works
Fiáth, R., Beregszászi, P., Horváth, D., Wittner, L., Aarts, A. A. A., Ruther, P., Neves, H. P., Bokor, H., Acsády, L., & Ulbert, I. (2016) · Journal of Neurophysiology · doi:10.1152/jn.00318.2016 · Cited by 32 · see citing works
High‐density implantable neural electrodes and chips for massive neural recordings
Wang, L., Suo, Y., Wang, J., Wang, X., Xue, K., An, J., Sun, X., Chen, Q., Tang, X., Zhao, Y., et al. (2024) · Brain‐X · doi:10.1002/brx2.65 · Cited by 31 · see citing works
CHIME: CMOS-Hosted in vivo Microelectrodes for Massively Scalable Neuronal Recordings
Köllő, M., Rácz, R., Hanna, M.-E., Obaid, A., Angle, M. R., Wray, W., Kong, Y., Hierlemann, A. R., Müller, J., Melosh, N. A., et al. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.00834 · Cited by 31 · see citing works
CMOS Neural Probe With 1600 Close-Packed Recording Sites and 32 Analog Output Channels
Herbawi, A. S., Christ, O., Kiessner, L., Mottaghi, S., Hofmann, U., Paul, O., & Ruther, P. (2018) · Journal of Microelectromechanical Systems · doi:10.1109/jmems.2018.2872619 · Cited by 30 · see citing works
New Perspectives on Neuroengineering and Neurotechnologies: NSF-DFG Workshop Report
Moritz, C. T., Ruther, P., Goering, S., Stett, A., Ball, T., Burgard, W., Chudler, E. H., & Rao, R. P. N. (2016) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2016.2543662 · Cited by 29 · see citing works
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 29 · see citing works
Zhao, Z., Gong, R., Zheng, L., & Wang, J. (2016) · Sensors · doi:10.3390/s16111851 · Cited by 29 · see citing works
Crosstalk in polymer microelectrode arrays
Qiang, Y., Gu, W., Liu, Z., Liang, S., Ryu, J. H., Seo, K. J., Liu, W., & Fang, H. (2021) · Nano Research · doi:10.1007/s12274-021-3442-8 · Cited by 28 · see citing works
Perna, A., Angotzi, G. N., Berdondini, L., & Ribeiro, J. F. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1275908 · Cited by 28 · see citing works
Physical principles for scalable neural recording
Marblestone, A. H., Zamft, B. M., Maguire, Y. G., Shapiro, M. G., Cybulski, T. R., Glaser, J. I., Amodei, D., Stranges, P. B., Kalhor, R., Dalrymple, D., et al. (2013) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2013.00137 · Cited by 27 · see citing works
Chamanzar, M., Denman, D. J., Blanche, T. J., & Maharbiz, M. M. (2015) · IEEE International Conference on Micro Electro Mechanical Systems (MEMS) · doi:10.1109/memsys.2015.7051049 · Cited by 26 · see citing works
Self-citationMultilayer 3D electrodes for neural implants
Leccardi, M. J. I. A., Vagni, P., & Ghezzi, D. (2018) · Journal of Neural Engineering · doi:10.1088/1741-2552/aae191 · Cited by 26 · see citing works
Jones, R. T., Barth, A. M., Ormiston, L. D., & Módy, I. (2015) · Epilepsia · doi:10.1111/epi.13218 · Cited by 25 · see citing works
A low-cost, scalable, current-sensing digital headstage for high channel count μ ECoG
Trumpis, M., Insanally, M. N., Zou, J., Elsharif, A., Ghomashchi, A., Artan, N. S., Froemke, R. C., & Viventi, J. (2017) · Journal of Neural Engineering · doi:10.1088/1741-2552/aa5a82 · Cited by 25 · see citing works
Hoseini, M. S., Higashikubo, B. T., Cho, F. S., Chang, A. H., Clemente-Perez, A., Lew, I., Ciesielska, A., Stryker, M. P., & Paz, J. T. (2021) · eLife · doi:10.7554/elife.61437 · Cited by 24 · see citing works
Zhang, F., Aghagolzadeh, M., & Oweiss, K. G. (2012) · Journal of Signal Processing Systems · doi:10.1007/s11265-012-0670-x · Cited by 23 · see citing works
Ritter, L. M., Golshani, P., Takahashi, K. U., Dufour, S., Valiante, T. A., & Kokaia, M. (2014) · Epilepsia · doi:10.1111/epi.12804 · Cited by 23 · see citing works
Angotzi, G. N., Malerba, M., Boi, F., Miele, E., Maccione, A., Amin, H., Crepaldi, M., & Berdondini, L. (2018) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2018.2792046 · Cited by 23 · see citing works
Statistically Reconstructed Multiplexing for Very Dense, High-Channel-Count Acquisition Systems
Tsai, D., Yuste, R., & Shepard, K. L. (2017) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2017.2750484 · Cited by 23 · see citing works
A nanofabricated optoelectronic probe for manipulating and recording neural dynamics
Li, B., Lee, K., Masmanidis, S. C., & Li, M. (2018) · Journal of Neural Engineering · doi:10.1088/1741-2552/aabc94 · Cited by 22 · see citing works
Self-citationWhy not record from every electrode with a CMOS scanning probe?Preprint
Dimitriadis, G., Neto, J. P., Aarts, A. A. A., Andrei, A., Ballini, M., Battaglia, F. P., Calcaterra, L., Chen, S., David, F., Fiáth, R., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/275818 · Cited by 22 · see citing works
3D probe array integrated with a front-end 100-channel neural recording ASIC
Cheng, M., Yao, L., Tan, K. L., Lim, R., Li, P., & Chen, W. (2014) · Journal of Micromechanics and Microengineering · doi:10.1088/0960-1317/24/12/125010 · Cited by 20 · see citing works
Sim, S., Shin, H., Bae, K., Han, H., Kang, Y., Woo, J., Cho, Y., Cho, I., & Kim, J. (2023) · Sensors and Actuators B Chemical · doi:10.1016/j.snb.2023.134124 · Cited by 19 · see citing works
Variability of acute extracellular action potential measurements with multisite silicon probes
Scott, K. M., Du, J., Lester, H. A., & Masmanidis, S. C. (2012) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2012.08.005 · Cited by 19 · see citing works
Self-citationSecondary auditory cortex mediates a sensorimotor mechanism for action timing
Cook, J. R., Li, H., Nguyen, B., Huang, H.-H., Mahdavian, P., Kirchgessner, M. A., Strassmann, P., Engelhardt, M. D., Callaway, E. M., & Jin, X. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01025-5 · Cited by 19 · see citing works
- Authors
- Du, J., Blanche, T. J., Harrison, R. R., Lester, H. A., & Masmanidis, S. C.
- Affiliations
- California Institute of Technology (US)
- University of California, Berkeley (US)
- Intan Technologies (United States) (US)
- Corresponding author
- Masmanidis, Sotiris C.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2011-10-12
- Volume
- 6
- Issue
- 10
- Pages
- e26204
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC3192171
- OpenAlex
- W2081826483
- Cited by
- 231
- References
- 51
- Citations by year
- 2026: 6 · 2025: 15 · 2024: 6 · 2023: 14 · 2022: 10 · 2021: 21 · 2020: 19 · 2019: 14 · 2018: 19 · 2017: 19 · 2016: 28 · 2015: 19 · 2014: 16 · 2013: 20 · 2012: 5
- FWCI
- 5.43
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- CaltechAUTHORS (California Institute of Technology) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- eScholarship (California Digital Library) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- Figshare (submittedVersion, cc-by)
- Funders
- California Institute of Technology
- National Institutes of Health (5r21ns066260-02, DA017279)
- Kavli Nanoscience Institute, California Institute of Technology
- National Institute on Drug Abuse (R01DA017279, DA017279)
- National Institute of Neurological Disorders and Stroke (R21 NS066260, 5R21NS066260)
- 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
- neural probes, extracellular recording, application-specific integrated circuits, silicon neural probe, implanted electrodes, freely moving animals
- MeSH terms
- Animals, Behavior, Animal, Electrodes, Male, Mice, Inbred C57BL, Neurons, Signal Processing, Computer-Assisted, Silicon, Temperature, Molecular Probes, Nanotechnology, Nanostructures, Mice, Electrophysiological Phenomena
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