Quantitative differences in developmental profiles of spontaneous activity in cortical and hippocampal cultures

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• 作者：Paul Charlesworth (1) (2)
  Ellese Cotterill (3)
  Andrew Morton (1) (4)
  Seth GN Grant (5)
  Stephen J Eglen (3)
  
  1. Genes to Cognition Programme ; Wellcome Trust Sanger Institute ; Genome Campus ; CB10 1SA ; Hinxton ; UK
  2. Current address ; Department of Physiology ; Development and Neuroscience ; Physiological Laboratory ; Downing Street ; Cambridge ; CB2 3EG ; UK
  3. Cambridge Computational Biology Institute ; University of Cambridge ; Wilberforce Road ; Cambridge ; CB3 0WA ; UK
  4. Current address ; Centre for Integrative Physiology ; University of Edinburgh School of Biomedical Sciences ; EH8 9XD ; Edinburgh ; UK
  5. Centre for Clinical Brain Sciences and Centre for Neuroregeneration ; Chancellors Building ; Edinburgh University ; 49 Little France Crescent ; Edinburgh ; EH16 4SB ; UK
  
• 关键词：Multielectrode array ; Spontaneous activity ; Cortex ; Hippocampus ; Principal component analysis ; Support vector machine ; Classification tree
• 刊名：Neural Development
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：10
• 期：1
• 全文大小：799 KB
• 参考文献：1. Blankenship AG, Feller MB. Mechanisms underlying spontaneous patterned activity in developing neural circuits. Nat Rev Neurosci. 2010; 11:18鈥?9. CrossRef
  2. Leinekugel X, Khazipov R, Cannon R, Hirase H, Ben-Ari Y, Buzs谩ki G. Correlated bursts of activity in the neonatal hippocampus / in vivo. Science. 2002; 296:2049鈥?2. CrossRef
  3. Khazipov R, Sirota A, Leinekugel X, Holmes GL, Ben-Ari Y, Buzs谩ki G. Early motor activity drives spindle bursts in the developing somatosensory cortex. Nature. 2004; 432:758鈥?1. CrossRef
  4. Hanganu IL, Ben-Ari Y, Khazipov R. Retinal waves trigger spindle bursts in the neonatal rat visual cortex. J Neurosci. 2006; 26:6728鈥?6. CrossRef
  5. Seelke AMH, Blumberg MS. Developmental appearance and disappearance of cortical events and oscillations in infant rats. Brain Res. 2010; 1324:34鈥?2. CrossRef
  6. Colonnese MT, Khazipov R. Slow activity transients鈥?in infant rat visual cortex: a spreading synchronous oscillation patterned by retinal waves. J Neurosci. 2010; 30:4325鈥?7. CrossRef
  7. Johnstone AFM, Gross GW, Weiss DG, Schroeder OHU, Gramowski A, Shafer TJ. Microelectrode arrays: a physiologically based neurotoxicity testing platform for the 21st century. Neurotoxicology. 2010; 31:331鈥?0. CrossRef
  8. Wagenaar DA, Pine J, Potter SM. An extremely rich repertoire of bursting patterns during the development of cortical cultures. BMC Neurosci. 2006; 7:11. CrossRef
  9. Rolston JD, Wagenaar DA, Potter SM. Precisely timed spatiotemporal patterns of neural activity in dissociated cortical cultures. Neuroscience. 2007; 148:294鈥?03. CrossRef
  10. Soriano J, Rodr铆guez Mart铆nez M, Tlusty T, Moses E. Development of input connections in neural cultures. Proc Natl Acad Sci USA. 2008; 105:13758鈥?3. CrossRef
  11. Gullo F, Manfredi I, Lecchi M, Casari G, Wanke E, Becchetti A. Multi-electrode array study of neuronal cultures expressing nicotinic / 尾2-V287L subunits, linked to autosomal dominant nocturnal frontal lobe epilepsy. An / in vitro model of spontaneous epilepsy. Front Neural Circuits. 2014; 8:87. CrossRef
  12. Lisman JE. Bursts as a unit of neural information: making unreliable synapses reliable. Trends Neurosci. 1997; 20:38鈥?3. CrossRef
  13. Eytan D, Marom S. Dynamics and effective topology underlying synchronization in networks of cortical neurons. J Neurosci. 2006; 26:8465鈥?6. CrossRef
  14. Cutts CS, Eglen SJ. Detecting pairwise correlations in spike trains: an objective comparison of methods and application to the study of retinal waves. J Neurosci. 2014; 34:14288鈥?03. CrossRef
  15. Wong RO, Meister M, Shatz CJ. Transient period of correlated bursting activity during development of the mammalian retina. Neuron. 1993; 11:923鈥?8. CrossRef
  16. Godfrey KB, Eglen SJ. Theoretical models of spontaneous activity generation and propagation in the developing retina. Mol Biosyst. 2009; 5:1527鈥?5. CrossRef
  17. Buzs谩ki G. Theta oscillations in the hippocampus. Neuron. 2002; 33:325鈥?0. CrossRef
  18. James G, Witten D, Hastie T, Tibshirani R. An Introduction to Statistical Learning: With Applications in R. New York: Springer; 2014.
  19. Ito S, Yeh FC, Hiolski E, Rydygier P, Gunning DE, Hottowy P, et al. Large-scale, high-resolution multielectrode-array recording depicts functional network differences of cortical and hippocampal cultures. PLoS One. 2014; 9:e105324. CrossRef
  20. Okamoto K, Ishikawa T, Abe R, Ishikawa D, Kobayashi C, Mizunuma M, et al. / Ex vivo cultured neuronal networks emit / in vivo-like spontaneous activity. J Physiol Sci. 2014; 64:421鈥?1. CrossRef
  21. Maccione A, Hennig MH, Gandolfo M, Muthmann O, van Coppenhagen J, Eglen SJ, et al. Following the ontogeny of retinal waves pan-retinal recordings of population dynamics in the neonatal mouse. J Physiol. 2013; 592:1545鈥?3. CrossRef
  22. Gramowski A, J眉gelt K, Weiss DG, Gross GW. Substance identification by quantitative characterization of oscillatory activity in murine spinal cord networks on microelectrode arrays. Eur J Neurosci. 2004; 19:2815鈥?5. CrossRef
  23. Mack CM, Lin BJ, Turner JD, Johnstone AFM, Burgoon LD, Shafer TJ. Burst and principal components analyses of MEA data for 16 chemicals describe at least three effects classes. Neurotoxicology. 2014; 40:75鈥?5. CrossRef
  24. MacLaren EJ, Charlesworth P, Coba MP, Grant SGN. Knockdown of mental disorder susceptibility genes disrupts neuronal network physiology / in vitro. Mol Cell Neurosci. 2011; 47:93鈥?. CrossRef
  25. Mann EO, Kohl MM, Paulsen O. Distinct roles of GABA_A and GABA_B receptors in balancing and terminating persistent cortical activity. J Neurosci. 2009; 29:7513鈥?8.
  26. Mao BQ, Hamzei-Sichani F, Aronov D, Froemke RC, Yuste R. Dynamics of spontaneous activity in neocortical slices. Neuron. 2001; 32:883鈥?8. CrossRef
  27. Potter SM, DeMarse TB. A new approach to neural cell culture for long-term studies. J Neurosci Methods. 2001; 110:17鈥?4. CrossRef
  28. Carpenter AE, Jones TR, Lamprecht MR, Clarke C, Kang IH, Friman O, et al. CellProfiler: image analysis software for identifying and quantifying cell phenotypes. Genome Biol. 2006; 7:R100. CrossRef
  29. Nex Technologies. NeuroExplorer Manual. 2012. [http://www.neuroexplorer.com/downloads/NeuroExplorerManual.pdf ]
  30. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Series B Stat Methodol. 1995; 57:289鈥?00.
  31. R Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria; 2014. [http://www.r-project.org ]
  32. Eglen SJ, Weeks M, Jessop M, Simonotto J, Jackson T, Sernagor E. A data repository and analysis framework for spontaneous neural activity recordings in developing retina. Gigascience. 2014; 3:3. CrossRef
  33. Genes to Cognition: Hippocampus vs Cortex project. [http://github.com/sje30/g2chvc]
  
• 刊物主题：Neurosciences; Developmental Biology;
• 出版者：BioMed Central
• ISSN：1749-8104

文摘

Background Neural circuits can spontaneously generate complex spatiotemporal firing patterns during development. This spontaneous activity is thought to help guide development of the nervous system. In this study, we had two aims. First, to characterise the changes in spontaneous activity in cultures of developing networks of either hippocampal or cortical neurons dissociated from mouse. Second, to assess whether there are any functional differences in the patterns of activity in hippocampal and cortical networks. Results We used multielectrode arrays to record the development of spontaneous activity in cultured networks of either hippocampal or cortical neurons every 2 or 3 days for the first month after plating. Within a few days of culturing, networks exhibited spontaneous activity. This activity strengthened and then stabilised typically around 21 days in vitro. We quantified the activity patterns in hippocampal and cortical networks using 11 features. Three out of 11 features showed striking differences in activity between hippocampal and cortical networks: (1) interburst intervals are less variable in spike trains from hippocampal cultures; (2) hippocampal networks have higher correlations and (3) hippocampal networks generate more robust theta-bursting patterns. Machine-learning techniques confirmed that these differences in patterning are sufficient to classify recordings reliably at any given age as either hippocampal or cortical networks. Conclusions Although cultured networks of hippocampal and cortical networks both generate spontaneous activity that changes over time, at any given time we can reliably detect differences in the activity patterns. We anticipate that this quantitative framework could have applications in many areas, including neurotoxicity testing and for characterising the phenotype of different mutant mice. All code and data relating to this report are freely available for others to use.