Abstract
Active high-density electrode arrays realized with complementary metal–oxide–semiconductor (CMOS) technology provide electrophysiological recordings from several thousands of closely spaced microelectrodes. This has drastically advanced the spatiotemporal recording resolution of conventional multielectrode arrays (MEAs). Thus, today’s electrophysiology in neuronal cultures can exploit label-free electrical readouts from a large number of single neurons within the same network. This provides advanced capabilities to investigate the properties of self-assembling neuronal networks, to advance studies on neurotoxicity and neurodevelopmental alterations associated with human brain diseases, and to develop cell culture models for testing drug- or cell-based strategies for therapies.
Here, after introducing the reader to this neurotechnology, we summarize the results of different recent studies demonstrating the potential of active high-density electrode arrays for experimental applications. We also discuss ongoing and possible future research directions that might allow for moving these platforms forward for screening applications.
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References
Alagapan, S., Franca, E., Pan, L., Leondopulos, S., Wheeler, B. C., & DeMarse, T. B. (2016). Structure, function, and propagation of information across living two, four, and eight node degree topologies. Frontiers in Bioengineering and Biotechnology, 4, 15.
Amin, H., Maccione, A., Marinaro, F., Zordan, S., Nieus, T., & Berdondini, L. (2016). Electrical responses and spontaneous activity of human iPS-derived neuronal networks characterized for 3-month culture with 4096-electrode arrays. Frontiers in Neuroscience, 10, 121.
Amin, H., Maccione, A., Zordan, S., Nieus, T., & Berdondini, L. (2015). High-density MEAs reveal lognormal firing patterns in neuronal networks for short and long term recordings. In 2015 7th international IEEE/EMBS conference on neural engineering (NER), pp. 1000–1003.
Amin, H., Marinaro, F., De Pietri Tonelli, D., & Berdondini, L. (2017a). Developmental excitatory-to-inhibitory GABA-polarity switch is disrupted in 22q11.2 deletion syndrome: A potential target for clinical therapeutics. Scientific Reports, 7, 15752.
Amin, H., Nieus, T., Lonardoni, D., Maccione, A., & Berdondini, L. (2017b). High-resolution bioelectrical imaging of Aβ-induced network dysfunction on CMOS-MEAs for neurotoxicity and rescue studies. Scientific Reports, 7, 2460.
Angotzi, G. N., Malerba, M., Boi, F., Miele, E., Maccione, A., Amin, H., et al. (2018). A synchronous neural recording platform for multiple high-resolution CMOS probes and passive electrode arrays. IEEE Transactions on Biomedical Circuits and Systems, 12, 532–542.
Berdondini, L., Imfeld, K., Maccione, A., Tedesco, M., Neukom, S., Koudelka-Hep, M., et al. (2009). Active pixel sensor array for high spatio-temporal resolution electrophysiological recordings from single cell to large scale neuronal networks. Lab on a Chip, 9, 2644–2651.
Berdondini, L., Overstolz, T., de Rooij, N. F., Koudelka-Hep, M., Wany, M., Seitz, P. (2001). High-density microelectrode arrays for electrophysiological activity imaging of neuronal networks. In ICECS 2001. 8th IEEE international conference on electronics, circuits and systems (Cat. No.01EX483), pp. 1239–1242.
Berdondini, L., van der Wal, P. D., Guenat, O., de Rooij, N. F., Koudelka-Hep, M., Seitz, P., et al. (2005). High-density electrode array for imaging in vitro electrophysiological activity. Biosensors & Bioelectronics, 21, 167–174.
Bisio, M., Bosca, A., Pasquale, V., Berdondini, L., & Chiappalone, M. (2014). Emergence of bursting activity in connected neuronal sub-populations. PLoS One, 9, e107400.
Borst, A., & Theunissen, F. E. (1999). Information theory and neural coding. Nature Neuroscience, 2, 947–957.
Bosi, S., Rauti, R., Laishram, J., Turco, A., Lonardoni, D., Nieus, T., et al. (2015). From 2D to 3D: Novel nanostructured scaffolds to investigate signalling in reconstructed neuronal networks. Scientific Reports, 5, 9562.
Brunel, N. (2000). Phase diagrams of sparsely connected networks of excitatory and inhibitory spiking neurons. Neurocomputing, 32–33, 307–312.
Buonomano, D. V., & Maass, W. (2009). State-dependent computations: Spatiotemporal processing in cortical networks. Nature Reviews Neuroscience, 10, 113–125.
Carvalho-de-Souza, J. L., Treger, J. S., Dang, B., Kent, S. B. H., Pepperberg, D. R., & Bezanilla, F. (2015). Photosensitivity of neurons enabled by cell-targeted gold nanoparticles. Neuron, 86, 207–217.
Charkhkar, H., Meyyappan, S., Matveeva, E., Moll, J. R., McHail, D. G., Peixoto, N., et al. (2015). Amyloid beta modulation of neuronal network activity in vitro. Brain Research, 1629, 1–9.
Corner, M. A., van Pelt, J., Wolters, P. S., Baker, R. E., & Nuytinck, R. H. (2002). Physiological effects of sustained blockade of excitatory synaptic transmission on spontaneously active developing neuronal networks—an inquiry into the reciprocal linkage between intrinsic biorhythms and neuroplasticity in early ontogeny. Neuroscience and Biobehavioral Reviews, 26, 127–185.
Dante, S., Petrelli, A., Petrini, E. M., Marotta, R., Maccione, A., Alabastri, A., et al. (2017). Selective targeting of neurons with inorganic nanoparticles: Revealing the crucial role of nanoparticle surface charge. ACS Nano, 11, 6630–6640.
Dipalo, M., Amin, H., Lovato, L., Moia, F., Caprettini, V., Messina, G. C., et al. (2017). Intracellular and extracellular recording of spontaneous action potentials in mammalian neurons and cardiac cells with 3D plasmonic nanoelectrodes. Nano Letters, 17, 3932–3939.
Dranias, M. R., Ju, H., Rajaram, E., & VanDongen, A. M. J. (2013). Short-term memory in networks of dissociated cortical neurons. The Journal of Neuroscience, 33, 1940–1953.
Duan, X., Gao, R., Xie, P., Cohen-Karni, T., Qing, Q., Choe, H. S., et al. (2012). Intracellular recordings of action potentials by an extracellular nanoscale field-effect transistor. Nature Nanotechnology, 7, 174–179.
Eckmann, J.-P., Jacobi, S., Marom, S., Moses, E., & Zbinden, C. (2008). Leader neurons in population bursts of 2D living neural networks. New Journal of Physics, 10, 015011.
Effenberger, F., Jost, J., & Levina, A. (2015). Self-organization in balanced state networks by STDP and homeostatic plasticity. PLoS Computational Biology, 11, e1004420.
Fossum, E. R. (1997). CMOS image sensors: Electronic camera-on-a-chip. IEEE Transactions on Electron Devices, 44, 1689–1698.
Frey, U., Sedivy, J., Heer, F., Pedron, R., Ballini, M., Mueller, J., et al. (2010). Switch-matrix-based high-density microelectrode array in CMOS technology. IEEE Journal of Solid-State Circuits, 45, 467–482.
Fromherz, P. (2003). Semiconductor chips with ion channels, nerve cells and brain. Physica E: Low-Dimensional Systems and Nanostructures, 16, 24–34.
Gandolfo, M., Maccione, A., Tedesco, M., Martinoia, S., & Berdondini, L. (2010). Tracking burst patterns in hippocampal cultures with high-density CMOS-MEAs. Journal of Neural Engineering, 7, 056001.
Grattarola, M., & Massobrio, G. (1998). Bioelectronics handbook : MOSFETs, biosensors, and neurons. New York: McGraw-Hill.
Hafizovic, S., Heer, F., Ugniwenko, T., Frey, U., Blau, A., Ziegler, C., et al. (2007). A CMOS-based microelectrode array for interaction with neuronal cultures. Journal of Neuroscience Methods, 164, 93–106.
Hierlemann, A., Frey, U., Hafizovic, S., & Heer, F. (2011). Growing cells atop microelectronic chips: Interfacing electrogenic cells in vitro with CMOS-based microelectrode arrays. Proceedings of the IEEE, 99, 252–284.
Hilgen, G., Sorbaro, M., Pirmoradian, S., Muthmann, J.-O., Kepiro, I. E., Ullo, S., et al. (2017). Unsupervised spike sorting for large-scale, high-density multielectrode arrays. Cell Reports, 18, 2521–2532.
Huang, C., Resnik, A., Celikel, T., & Englitz, B. (2016). Adaptive spike threshold enables robust and temporally precise neuronal encoding. PLoS Computational Biology, 12, e1004984.
Imfeld, K., Neukom, S., Maccione, A., Bornat, Y., Martinoia, S., Farine, P.-A., et al. (2008). Large-scale, high-resolution data acquisition system for extracellular recording of electrophysiological activity. IEEE Transactions on Biomedical Engineering, 55, 2064–2073.
Jimbo, Y., & Kawana, A. (1992). Electrical stimulation and recording from cultured neurons using a planar electrode array. Bioelectrochemistry and Bioenergetics, 29, 193–204.
Jun, J. J., Steinmetz, N. A., Siegle, J. H., Denman, D. J., Bauza, M., Barbarits, B., et al. (2017). Fully integrated silicon probes for high-density recording of neural activity. Nature, 551, 232–236. https://doi.org/10.1038/nature24636
Kamioka, H., Maeda, E., Jimbo, Y., Robinson, H. P., & Kawana, A. (1996). Spontaneous periodic synchronized bursting during formation of mature patterns of connections in cortical cultures. Neuroscience Letters, 206, 109–112.
Kayser, C., Wilson, C., Safaai, H., Sakata, S., & Panzeri, S. (2015). Rhythmic auditory cortex activity at multiple timescales shapes stimulus-response gain and background firing. The Journal of Neuroscience, 35, 7750–7762.
Keefer, E. W., Norton, S. J., Boyle, N. A. J., Talesa, V., & Gross, G. W. (2001). Acute toxicity screening of novel AChE inhibitors using neuronal networks on microelectrode arrays. Neurotoxicology, 22, 3–12.
Kermany, E., Gal, A., Lyakhov, V., Meir, R., Marom, S., & Eytan, D. (2010). Tradeoffs and constraints on neural representation in networks of cortical neurons. The Journal of Neuroscience, 30, 9588–9596.
Kotov, N. A., Winter, J. O., Clements, I. P., Jan, E., Timko, B. P., Campidelli, S., et al. (2009). Nanomaterials for neural interfaces. Advanced Materials, 21, 3970–4004.
Kumar, S. S., Wülfing, J., Okujeni, S., Boedecker, J., Riedmiller, M., & Egert, U. (2016). Autonomous optimization of targeted stimulation of neuronal networks. PLoS Computational Biology, 12, e1005054.
Lin, I.-C., Okun, M., Carandini, M., & Harris, K. D. (2015). The nature of shared cortical variability. Neuron, 87, 644–656. https://doi.org/10.1016/j.neuron.2015.06.035
Lonardoni, D., Amin, H., Di Marco, S., Maccione, A., Berdondini, L., & Nieus, T. (2017). Recurrently connected and localized neuronal communities initiate coordinated spontaneous activity in neuronal networks. PLoS Computational Biology, 13, e1005672.
Lonardoni, D., Di Marco, S., Amin, H., Maccione, A., Berdondini, L., Nieus, T. (2015). High-density MEA recordings unveil the dynamics of bursting events in cell cultures. In 2015 37th annual international conference of the IEEE engineering in medicine and biology society (EMBC), pp. 3763–3766.
Luccioli, S., Ben-Jacob, E., Barzilai, A., Bonifazi, P., & Torcini, A. (2014). Clique of functional hubs orchestrates population bursts in developmentally regulated neural networks. PLoS Computational Biology, 10, e1003823.
Luczak, A., & MacLean, J. N. (2012). Default activity patterns at the neocortical microcircuit level. Frontiers in Integrative Neuroscience, 6, 30.
Maccione, A., Gandolfo, M., Tedesco, M., Nieus, T., Imfeld, K., Martinoia, S., et al. (2010). Experimental investigation on spontaneously active hippocampal cultures recorded by means of high-density MEAs: Analysis of the spatial resolution effects. Frontiers in Neuroengineering, 3, 4.
Maccione, A., Gandolfo, M., Zordan, S., Amin, H., Di Marco, S., Nieus, T., et al. (2015). Microelectronics, bioinformatics and neurocomputation for massive neuronal recordings in brain circuits with large scale multielectrode array probes. Brain Research Bulletin, 119, 118–126.
Maccione, A., Garofalo, M., Nieus, T., Tedesco, M., Berdondini, L., & Martinoia, S. (2012). Multiscale functional connectivity estimation on low-density neuronal cultures recorded by high-density CMOS micro electrode arrays. Journal of Neuroscience Methods, 207, 161–171.
Malerba, M., Amin, H., Angotzi, G. N., Maccione, A., & Berdondini, L. (2018). Fabrication of multielectrode arrays for neurobiology applications. Methods in Molecular Biology, 1771, 147–157.
Masquelier, T., & Deco, G. (2013). Network bursting dynamics in excitatory cortical neuron cultures results from the combination of different adaptive mechanism. PLoS One, 8, e75824.
Merscher, S., Funke, B., Epstein, J. A., Heyer, J., Puech, A., Lu, M. M., et al. (2001). TBX1 is responsible for cardiovascular defects in velo-cardio-facial/DiGeorge syndrome. Cell, 104, 619–629.
Müller, J., Ballini, M., Livi, P., Chen, Y., Radivojevic, M., Shadmani, A., et al. (2015). High-resolution CMOS MEA platform to study neurons at subcellular, cellular, and network levels. Lab on a Chip, 15, 2767–2780.
Muthmann, J.-O., Amin, H., Sernagor, E., Maccione, A., Panas, D., Berdondini, L., et al. (2015). Spike detection for large neural populations using high density multielectrode arrays. Frontiers in Neuroinformatics, 9, 28.
Nel, A. E., Mädler, L., Velegol, D., Xia, T., Hoek, E. M. V., Somasundaran, P., et al. (2009). Understanding biophysicochemical interactions at the nano-bio interface. Nature Materials, 8, 543–557.
Nieus, T., D’Andrea, V., Amin, H., Di Marco, S., Safaai, H., Maccione, A., et al. (2018). State-dependent representation of stimulus-evoked activity in high-density recordings of neural cultures. Scientific Reports, 8, 5578.
Nieus, T., Di Marco, S., Maccione, A., Amin, H., Berdondini, L. (2015). Investigating cell culture dynamics combining high density recordings with dimensional reduction techniques. In 2015 37th annual international conference of the IEEE engineering in medicine and biology society (EMBC), pp. 3759–3762.
Novellino, A., Scelfo, B., Palosaari, T., Price, A., Sobanski, T., Shafer, T. J., et al. (2011). Development of micro-electrode array based tests for neurotoxicity: Assessment of interlaboratory reproducibility with neuroactive chemicals. Frontiers in Neuroengineering, 4, 4.
Orlandi, J. G., Soriano, J., Alvarez-Lacalle, E., Teller, S., & Casademunt, J. (2013). Noise focusing and the emergence of coherent activity in neuronal cultures. Nature Physics, 9, 582–590.
Panzeri, S., Safaai, H., De Feo, V., & Vato, A. (2016). Implications of the dependence of neuronal activity on neural network states for the design of brain-machine interfaces. Frontiers in Neuroscience, 10, 165. https://doi.org/10.3389/fnins.2016.00165
Pasquale, V., Martinoia, S., & Chiappalone, M. (2017). Stimulation triggers endogenous activity patterns in cultured cortical networks. Scientific Reports, 7, 9080.
Pasquale, V., Massobrio, P., Bologna, L. L., Chiappalone, M., & Martinoia, S. (2008). Self-organization and neuronal avalanches in networks of dissociated cortical neurons. Neuroscience, 153, 1354–1369.
Pastore, V. P., Massobrio, P., Godjoski, A., & Martinoia, S. (2018). Identification of excitatory-inhibitory links and network topology in large-scale neuronal assemblies from multi-electrode recordings. PLoS Computational Biology, 14, e1006381.
Pauwelyn, T., Miccoli, B., Velnayagam, A., Jan Boom, R., Skolimowski, M., Vrouwe, E., et al. (2018). High-throughput CMOS MEA system with integrated microfluidics for cardiotoxicity studies. Frontiers in Cellular Neuroscience. https://doi.org/10.3389/conf.fncel.2018.38.00009
Pimashkin, A., Kastalskiy, I., Simonov, A., Koryagina, E., Mukhina, I., & Kazantsev, V. (2011). Spiking signatures of spontaneous activity bursts in hippocampal cultures. Frontiers in Computational Neuroscience, 5, 46.
Pine, J. (2006). A history of MEA development. In Advances in network electrophysiology (pp. 3–23). New York: Springer.
Pulizzi, R., Musumeci, G., Van den Haute, C., Van De Vijver, S., Baekelandt, V., & Giugliano, M. (2016). Brief wide-field photostimuli evoke and modulate oscillatory reverberating activity in cortical networks. Scientific Reports, 6, 24701.
Raducanu, B. C., Yazicioglu. R. F., Lopez, C. M., Ballini, M., Putzeys, J., & Wang, S., et al. (2016). Time multiplexed active neural probe with 678 parallel recording sites. In 2016 46th European solid-state device research conference (ESSDERC), pp. 385–388.
Rey, H. G., Pedreira, C., & Quian Quiroga, R. (2015). Past, present and future of spike sorting techniques. Brain Research Bulletin, 119, 106–117.
Ritter, P., Born, J., Brecht, M., Dinse, H. R., Heinemann, U., Pleger, B., et al. (2015). State-dependencies of learning across brain scales. Frontiers in Computational Neuroscience, 9, 1.
Robinette, B. L., Harrill, J. A., Mundy, W. R., & Shafer, T. J. (2011). In vitro assessment of developmental neurotoxicity: Use of microelectrode arrays to measure functional changes in neuronal network ontogeny. Frontiers in Neuroengineering, 4, 1.
Robinson, J. T., Jorgolli, M., Shalek, A. K., Yoon, M.-H., Gertner, R. S., & Park, H. (2012). Vertical nanowire electrode arrays as a scalable platform for intracellular interfacing to neuronal circuits. Nature Nanotechnology, 7, 180–184.
Safaai, H., Neves, R., Eschenko, O., Logothetis, N. K., & Panzeri, S. (2015). Modeling the effect of locus coeruleus firing on cortical state dynamics and single-trial sensory processing. Proceedings of the National Academy of Sciences, 112, 12834–12839.
Sakmann, B., & Neher, E. (1984). Patch clamp techniques for studying ionic channels in excitable membranes. Annual Review of Physiology. https://doi.org/10.1146/annurev.ph.46.030184.002323
Schroeter, M. S., Charlesworth, P., Kitzbichler, M. G., Paulsen, O., & Bullmore, E. T. (2015). Emergence of rich-club topology and coordinated dynamics in development of hippocampal functional networks in vitro. The Journal of Neuroscience, 35, 5459–5470.
Schwartz, A. B., Cui, X. T., Weber, D. J., & Moran, D. W. (2006). Brain-controlled interfaces: Movement restoration with neural prosthetics. Neuron, 52, 205–220.
Segev, R., & Ben-Jacob, E. (2001). Spontaneous synchronized bursting in 2D neural networks. Physica A: Statistical Mechanics and its Applications, 302, 64–69.
Seu, G. P., Angotzi, G. N., Boi, F., Raffo, L., Berdondini, L., & Meloni, P. (2018). Exploiting all programmable SoCs in neural signal analysis: A closed-loop control for large-scale CMOS multielectrode arrays. IEEE Transactions on Biomedical Circuits and Systems, 12, 839–850.
Soloperto, A., Bisio, M., Palazzolo, G., Chiappalone, M., Bonifazi, P., & Difato, F. (2016). Modulation of neural network activity through single cell ablation: An in vitro model of minimally invasive neurosurgery. Molecules, 21, 1018.
Spira, M. E., & Hai, A. (2013). Multi-electrode array technologies for neuroscience and cardiology. Nature Nanotechnology, 8, 83–94.
Stett, A., Egert, U., Guenther, E., Hofmann, F., Meyer, T., Nisch, W., et al. (2003). Biological application of microelectrode arrays in drug discovery and basic research. Analytical and Bioanalytical Chemistry, 377, 486–495.
Suresh, J., Radojicic, M., Pesce, L. L., Bhansali, A., Wang, J., Tryba, A. K., et al. (2016). Network burst activity in hippocampal neuronal cultures: The role of synaptic and intrinsic currents. Journal of Neurophysiology, 115, 3073–3089.
Tsai, D., Sawyer, D., Bradd, A., Yuste, R., & Shepard, K. L. (2017). A very large-scale microelectrode array for cellular-resolution electrophysiology. Nature Communications, 8, 1802.
Van Pelt, J., Wolters, P. S., Corner, M. A., Rutten, W. L. C., & Ramakers, G. J. A. (2004). Long-term characterization of firing dynamics of spontaneous bursts in cultured neural networks. IEEE Transactions on Biomedical Engineering, 51, 2051–2062.
Vasilaki, E., & Giugliano, M. (2014). Emergence of connectivity motifs in networks of model neurons with short- and long-term plastic synapses. PLoS One, 9, e84626.
Vassallo, A., Chiappalone, M., De Camargos Lopes, R., Scelfo, B., Novellino, A., Defranchi, E., et al. (2017). A multi-laboratory evaluation of microelectrode array-based measurements of neural network activity for acute neurotoxicity testing. Neurotoxicology, 60, 280–292.
Wagenaar, D., Pine, J., & Potter, S. (2006). An extremely rich repertoire of bursting patterns during the development of cortical cultures. BMC Neuroscience, 7, 11.
Weihberger, O., Okujeni, S., Mikkonen, J. E., & Egert, U. (2013). Quantitative examination of stimulus-response relations in cortical networks in vitro. Journal of Neurophysiology, 109, 1764–1774.
Womelsdorf, T., Schoffelen, J.-M., Oostenveld, R., Singer, W., Desimone, R., Engel, A. K., et al. (2007). Modulation of neuronal interactions through neuronal synchronization. Science, 316, 1609–1612.
Xie, C., Lin, Z., Hanson, L., Cui, Y., & Cui, B. (2012). Intracellular recording of action potentials by nanopillar electroporation. Nature Nanotechnology, 7, 185–190.
Yuan, X., Hierlemann, A., & Frey, U. (2018). Dual-mode microelectrode array with 20k-electrodes and high SNR for high-throughput extracellular recording and stimulation. Frontiers in Cellular Neuroscience. https://doi.org/10.3389/conf.fncel.2018.38.00088
Acknowledgements
We acknowledge the financial support of the Seventh Framework Programme for Research of The European Commission (SI-CODE FET-Open grant FP7–284553, NAMASEN FP7-264872 Marie-Curie Initial Training Network). We thank all collaborators and former members of the NetS3 laboratory, in particular, A. Maccione, T. Nieus, and A. Simi for their contributions to studies on neuronal cell cultures and active high-density MEAs. Finally, we are grateful for the support of Marina Nanni in cell culture preparations.
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Lonardoni, D. et al. (2019). Active High-Density Electrode Arrays: Technology and Applications in Neuronal Cell Cultures. In: Chiappalone, M., Pasquale, V., Frega, M. (eds) In Vitro Neuronal Networks. Advances in Neurobiology, vol 22. Springer, Cham. https://doi.org/10.1007/978-3-030-11135-9_11
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