nach oben

Neuroinformatics

Erschienen in:

04.07.2019 | Software Original Article

MEAnalyzer – a Spike Train Analysis Tool for Multi Electrode Arrays

verfasst von: Raha M. Dastgheyb, Seung-Wan Yoo, Norman J. Haughey

Erschienen in: Neuroinformatics | Ausgabe 1/2020

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Despite a multitude of commercially available multi-electrode array (MEA) systems that are each capable of rapid data acquisition from cultured neurons or slice cultures, there is a general lack of available analysis tools. These analysis gaps restrict the efficient extraction of meaningful physiological features from data sets, and limit interpretation of how experimental manipulations modify neural network activity. Here, we present the development of a user-friendly, publicly-available software called MEAnalyzer. This software contains several spike train analysis methods including relevant statistical calculations, periodicity analysis, functional connectivity analysis, and advanced data visualizations in a user-friendly graphical user interface that requires no coding from the user. Widespread availability of this user friendly and mathematically advanced program will stimulate and enhance the use of MEA technologies.

Vorheriger Artikel Fully-Automated Identification of Imaging Biomarkers for Post-Operative Cerebellar Mutism Syndrome Using Longitudinal Paediatric MRI

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Nur mit Berechtigung zugänglich

Bokil, H., Andrews, P., Kulkarni, J. E., Mehta, S., & Mitra, P. P. (2010). Chronux: A platform for analyzing neural signals. Journal of Neuroscience Methods, 192(1), 146–151. https://doi.org/10.1016/j.jneumeth.2010.06.020.CrossRefPubMedPubMedCentral

Bologna, L. L., Pasquale, V., Garofalo, M., Gandolfo, M., Baljon, P. L., Maccione, A., Martinoia, S., & Chiappalone, M. (2010). Investigating neuronal activity by SPYCODE multi-channel data analyzer. Neural Networks, 23(6), 685–697. https://doi.org/10.1016/j.neunet.2010.05.002.CrossRefPubMed

Bongard, M., Micol, D., & Fernandez, E. (2014). NEV2lkit: A new open source tool for handling neuronal event files from multi-electrode recordings. International Journal of Neural Systems, 24(4), 1450009. https://doi.org/10.1142/S0129065714500099.CrossRefPubMed

Bower, J. M., & Beeman, D. (2007). Constructing realistic neural simulations with GENESIS. Methods in Molecular Biology, 401, 103–125. https://doi.org/10.1007/978-1-59745-520-6_7.CrossRefPubMed

Bradley, J. A., Luithardt, H. H., Metea, M. R., & Strock, C. J. (2018). In vitro screening for seizure liability using microelectrode Array technology. Toxicological Sciences, 163, 240–253. https://doi.org/10.1093/toxsci/kfy029.CrossRefPubMed

Brodlie, K. W., Carpenter, L. A., Earnshaw, R. A., Gallop, J. R., Hubbold, R. J., Mumford, A. M., et al. (2012). Scientific visualization: Techniques and applications. Springer Science & Business Media.

Cajigas, I., Malik, W. Q., & Brown, E. N. (2012). nSTAT: Open-source neural spike train analysis toolbox for Matlab. Journal of Neuroscience Methods, 211(2), 245–264. https://doi.org/10.1016/j.jneumeth.2012.08.009.CrossRefPubMedPubMedCentral

Canepari, M., Bove, M., Maeda, E., Cappello, M., & Kawana, A. (1997). Experimental analysis of neuronal dynamics in cultured cortical networks and transitions between different patterns of activity. Biological Cybernetics, 77(2), 153–162. https://doi.org/10.1007/s004220050376.CrossRefPubMed

Chaudhuri, A. D., Dastgheyb, R. M., Yoo, S. W., Trout, A., Talbot, C. C., Jr., Hao, H., et al. (2018). TNFalpha and IL-1beta modify the miRNA cargo of astrocyte shed extracellular vesicles to regulate neurotrophic signaling in neurons. Cell Death & Disease, 9(3), 363. https://doi.org/10.1038/s41419-018-0369-4.CrossRef

Chiappalone, M., Bove, M., Vato, A., Tedesco, M., & Martinoia, S. (2006). Dissociated cortical networks show spontaneously correlated activity patterns during in vitro development. Brain Research, 1093, 41–53. https://doi.org/10.1016/j.brainres.2006.03.049.CrossRefPubMed

Cotterill, E., Charlesworth, P., Thomas, C. W., Paulsen, O., & Eglen, S. J. (2016). A comparison of computational methods for detecting bursts in neuronal spike trains and their application to human stem cell-derived neuronal networks. Journal of Neurophysiology, 116(2), 306–321. https://doi.org/10.1152/jn.00093.2016.CrossRefPubMedPubMedCentral

de Korte, T., Guilbot, S., Printemps, R., Hautefeuille, L., Le Grand, M., Wilbers, R., et al. (2017). Assessment of compound effects on electrophysiology of hiPSC-derived ventricular cardiomyocytes using patch clamp and multielectrode Array (MEA) analysis. Journal of Pharmacological and Toxicological Methods, 88, 196–196. https://doi.org/10.1016/j.vascn.2017.09.092.CrossRef

Delorme, A., & Thorpe, S. J. (2003). SpikeNET: An event-driven simulation package for modelling large networks of spiking neurons. Network, 14(4), 613–627.CrossRef

Earnshaw, R., & Wiseman, N. (2012). An introductory guide to scientific visualization. Springer Science & Business Media.

Egert, U., Knott, T., Schwarz, C., Nawrot, M., Brandt, A., Rotter, S., & Diesmann, M. (2002). MEA-tools: An open source toolbox for the analysis of multi-electrode data with MATLAB. Journal of Neuroscience Methods, 117(1), 33–42. https://doi.org/10.1016/S0165-0270(02)00045-6.CrossRefPubMed

Georgiadis, V., Stephanou, A., Townsend, P. A., & Jackson, T. R. (2015). MultiElec: A MATLAB based application for MEA data analysis. PLoS One, 10(6), e0129389. https://doi.org/10.1371/journal.pone.0129389.CrossRefPubMedPubMedCentral

Gerstein, G. L. (2000). Cross-correlation measures of unresolved multi-neuron recordings. Journal of Neuroscience Methods, 100(1–2), 41–51.CrossRef

Goldberg, D. H., Victor, J. D., Gardner, E. P., & Gardner, D. (2009). Spike train analysis toolkit: Enabling wider application of information-theoretic techniques to neurophysiology. Neuroinformatics, 7(3), 165–178. https://doi.org/10.1007/s12021-009-9049-y.CrossRefPubMedPubMedCentral

Gross, G. W., & Schwalm, F. U. (1994). A closed flow chamber for long-term multichannel recording and optical monitoring. Journal of Neuroscience Methods, 52(1), 73–85. https://doi.org/10.1016/0165-0270(94)90059-0.CrossRefPubMed

Harris, K. D., Quiroga, R. Q., Freeman, J., & Smith, S. L. (2016). Improving data quality in neuronal population recordings. Nature Neuroscience, 19(9), 1165–1174. https://doi.org/10.1038/nn.4365.CrossRefPubMedPubMedCentral

Hazan, L., Zugaro, M., & Buzsaki, G. (2006). Klusters, NeuroScope, NDManager: A free software suite for neurophysiological data processing and visualization. Journal of Neuroscience Methods, 155(2), 207–216. https://doi.org/10.1016/j.jneumeth.2006.01.017.CrossRefPubMed

Hines, M. L., & Carnevale, N. T. (1997). The NEURON simulation environment. Neural Computation, 9(6), 1179–1209.CrossRef

Hodgkin, A. L., & Huxley, A. F. (1945). Resting and action potentials in single nerve fibres. The Journal of Physiology, 104(2), 176–195.CrossRef

Huang, Y., Li, X., Li, Y., Xu, Q., Lu, Q., & Liu, Q. (2008). An integrative analysis platform for multiple neural spike train data. Journal of Neuroscience Methods, 172(2), 303–311. https://doi.org/10.1016/j.jneumeth.2008.04.026.CrossRefPubMed

Jefferys, J. G. R., & Haas, H. L. (1982). Synchronized bursting of Ca1 hippocampal pyramidal cells in the absence of synaptic transmission. Nature, 300(5891), 448–450. https://doi.org/10.1038/300448a0.CrossRefPubMed

Johnson, D. H. (1978). The relationship of post-stimulus time and interval histograms to the timing characteristics of spike trains. Biophysical Journal, 22(3), 413–430. https://doi.org/10.1016/S0006-3495(78)85496-4.CrossRefPubMedPubMedCentral

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(2–3), 109–112.CrossRef

Knox, C. K. (1981). Detection of neuronal interactions using correlation-analysis. Trends in Neurosciences, 4(9), 222–225. https://doi.org/10.1016/0166-2236(81)90070-9.CrossRef

Kwon, K. Y., Eldawlatly, S., & Oweiss, K. (2012). NeuroQuest: A comprehensive analysis tool for extracellular neural ensemble recordings. Journal of Neuroscience Methods, 204(1), 189–201. https://doi.org/10.1016/j.jneumeth.2011.10.027.CrossRefPubMed

Latora, V., & Marchiori, M. (2001). Efficient behavior of small-world networks. Physical Review Letters, 87(19). https://doi.org/10.1103/PhysRevLett.87.198701.

Lidierth, M. (2009). sigTOOL: A MATLAB-based environment for sharing laboratory-developed software to analyze biological signals. Journal of Neuroscience Methods, 178(1), 188–196. https://doi.org/10.1016/j.jneumeth.2008.11.004.CrossRefPubMed

Llinas, R. R. (1988). The intrinsic electrophysiological properties of mammalian neurons - insights into central nervous-system function. Science, 242(4886), 1654–1664. https://doi.org/10.1126/science.3059497.CrossRefPubMed

Maeda, E., Robinson, H. P. C., & Kawana, A. (1995). The mechanisms of generation and propagation of synchronized bursting in developing networks of cortical-neurons. The Journal of Neuroscience, 15(10), 6834–6845.CrossRef

Mahmud, M., Bertoldo, A., Girardi, S., Maschietto, M., & Vassanelli, S. (2012). SigMate: A Matlab-based automated tool for extracellular neuronal signal processing and analysis. Journal of Neuroscience Methods, 207(1), 97–112. https://doi.org/10.1016/j.jneumeth.2012.03.009.CrossRefPubMed

Mahmud, M., Pulizzi, R., Vasilaki, E., & Giugliano, M. (2014). QSpike tools: A generic framework for parallel batch preprocessing of extracellular neuronal signals recorded by substrate microelectrode arrays. Frontiers in Neuroinformatics, 8, 26. https://doi.org/10.3389/fninf.2014.00026.CrossRefPubMedPubMedCentral

Meier, R., Egert, U., Aertsen, A., & Nawrot, M. P. (2008). FIND--a unified framework for neural data analysis. Neural Networks, 21(8), 1085–1093. https://doi.org/10.1016/j.neunet.2008.06.019.CrossRefPubMed

Micallef, J. (1987). Encapsulation, reusability and extensibility in object-oriented programming languages.

Miller, S. J., Philips, T., Kim, N., Dastgheyb, R., Chen, Z., Hsieh, Y. C., Daigle, J. G., Datta, M., Chew, J., Vidensky, S., Pham, J. T., Hughes, E. G., Robinson, M. B., Sattler, R., Tomer, R., Suk, J. S., Bergles, D. E., Haughey, N., Pletnikov, M., Hanes, J., & Rothstein, J. D. (2019). Molecularly defined cortical astroglia subpopulation modulates neurons via secretion of Norrin. Nature Neuroscience, 22, 741–752. https://doi.org/10.1038/s41593-019-0366-7.CrossRefPubMedPubMedCentral

Novak, J. L., & Wheeler, B. C. (1988). Multisite hippocampal slice recording and stimulation using a 32 element microelectrode Array. Journal of Neuroscience Methods, 23(2), 149–159. https://doi.org/10.1016/0165-0270(88)90187-2.CrossRefPubMed

Novellino, A., Chiappalone, M., Maccione, A., & Martinoia, S. (2009). Neural signal manager: A collection of classical and innovative tools for multi-channel spike train analysis. International Journal of Adaptive Control and Signal Processing, 23(11), 999–1013. https://doi.org/10.1002/acs.1076.CrossRef

Pastore, V. P., Poli, D., Godjoski, A., Martinoia, S., & Massobrio, P. (2016). ToolConnect: A functional connectivity toolbox for in vitro networks. Frontiers in Neuroinformatics, 10, 13. https://doi.org/10.3389/fninf.2016.00013.CrossRefPubMedPubMedCentral

Pine, J. (1980). Recording action-potentials from cultured neurons with extracellular micro-circuit electrodes. Journal of Neuroscience Methods, 2(1), 19–31. https://doi.org/10.1016/0165-0270(80)90042-4.CrossRefPubMed

Poli, D., Pastore, V. P., & Massobrio, P. (2015). Functional connectivity in in vitro neuronal assemblies. Front Neural Circuits, 9, 57. https://doi.org/10.3389/fncir.2015.00057.CrossRefPubMedPubMedCentral

Potter, S. M., & DeMarse, T. B. (2001). A new approach to neural cell culture for long-term studies. Journal of Neuroscience Methods, 110(1–2), 17–24.CrossRef

Salinas, E., & Sejnowski, T. J. (2001). Correlated neuronal activity and the flow of neural information. Nature Reviews. Neuroscience, 2(8), 539–550. https://doi.org/10.1038/35086012.CrossRefPubMedPubMedCentral

Schofield, P. N., Bubela, T., Weaver, T., Brown, S. D., Hancock, J. M., Einhorn, D., et al. (2009). Post-publication sharing of data and tools. Nature, 461(7261), 171–173. https://doi.org/10.1038/461171a.CrossRefPubMedPubMedCentral

Snyder, D. L. (1991). Random point processes in time and space. In M. I. Miller, & D. L. Snyder (Eds.), (2nd ed. / ed.). In New York :: Springer-Verlag.

Somerville, J., Stuart, L., Sernagor, E., & Borisyuk, R. (2010). iRaster: A novel information visualization tool to explore spatiotemporal patterns in multiple spike trains. Journal of Neuroscience Methods, 194(1), 158–171. https://doi.org/10.1016/j.jneumeth.2010.09.009.CrossRefPubMed

Spira, M. E., & Hai, A. (2013). Multi-electrode array technologies for neuroscience and cardiology. Nature Nanotechnology, 8(2), 83–94. https://doi.org/10.1038/nnano.2012.265.CrossRefPubMed

Teeters, J. L., Godfrey, K., Young, R., Dang, C., Friedsam, C., Wark, B., Asari, H., Peron, S., Li, N., Peyrache, A., Denisov, G., Siegle, J. H., Olsen, S. R., Martin, C., Chun, M., Tripathy, S., Blanche, T. J., Harris, K., Buzsáki, G., Koch, C., Meister, M., Svoboda, K., & Sommer, F. T. (2015). Neurodata without Borders: Creating a common data format for neurophysiology. Neuron, 88(4), 629–634. https://doi.org/10.1016/j.neuron.2015.10.025.CrossRefPubMed

Thomas, C. A., Jr., Springer, P. A., Loeb, G. E., Berwald-Netter, Y., & Okun, L. M. (1972). A miniature microelectrode array to monitor the bioelectric activity of cultured cells. Experimental Cell Research, 74(1), 61–66.CrossRef

Vato, A., Bonzano, L., Chiappalone, M., Cicero, S., Morabito, F., Novellino, A., & Stillo, G. (2004). Spike manager: A new tool for spontaneous an evoked neuronal networks activity characterization. Neurocomputing, 58, 1153–1161. https://doi.org/10.1016/j.neucom.2004.01.180.CrossRef

Wagenaar, D., DeMarse, T. B., & Potter, S. M. (2005). MeaBench: A toolset for multi-electrode data acquisition and on-line analysis. 2005 2nd Internatinoal Ieee/Embs Conference on Neural. Engineering, 518–521.

Welch, P. D. (1967). Use of Fast Fourier Transform for Estimation of Power Spectra - a Method Based on Time Averaging over Short Modified Periodograms. Ieee Transactions on Audio and Electroacoustics, Au15(2), 70-&, https://doi.org/10.1109/Tau.1967.1161901.CrossRef

Wiegner, A. W., & Wierzbicka, M. M. (1987). A method for assessing significance of peaks in cross-correlation histograms. Journal of Neuroscience Methods, 22(2), 125–131.CrossRef

Wiener, N. (1949). Extrapolation, interpolation, and smoothing of stationary time series, with engineering applications. Cambridge: Technology Press of the Massachusetts Institute of Technology.CrossRef

Titel: MEAnalyzer – a Spike Train Analysis Tool for Multi Electrode Arrays
verfasst von: Raha M. Dastgheyb
Seung-Wan Yoo
Norman J. Haughey
Publikationsdatum: 04.07.2019
Verlag: Springer US
Erschienen in: Neuroinformatics / Ausgabe 1/2020
Print ISSN: 1539-2791
Elektronische ISSN: 1559-0089
DOI: https://doi.org/10.1007/s12021-019-09431-0

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Weitere Artikel der Ausgabe 1/2020

Cellular Automata Tractography: Fast Geodesic Diffusion MR Tractography and Connectivity Based Segmentation on the GPU

A Comprehensive Framework to Capture the Arcana of Neuroimaging Analysis

A Data Structure for Real-Time Aggregation Queries of Big Brain Networks

Hierarchical Structured Sparse Learning for Schizophrenia Identification

Fully-Automated Identification of Imaging Biomarkers for Post-Operative Cerebellar Mutism Syndrome Using Longitudinal Paediatric MRI

DisConICA: a Software Package for Assessing Reproducibility of Brain Networks and their Discriminability across Disorders