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Classification of pseudocalcium visual responses from mouse retinal ganglion cells

Published online by Cambridge University Press:  10 November 2021

H. Shabani ,
Mahdi Sadeghi Open the ORCID record for Mahdi Sadeghi [Opens in a new window] ,
E. Zrenner ,
D.L. Rathbun Open the ORCID record for D.L. Rathbun [Opens in a new window]  and
Z. Hosseinzadeh
H. Shabani
Affiliation:
Institute for Ophthalmic Research, Centre for Ophthalmology, Eberhard Karls University, Tübingen, Germany
Mahdi Sadeghi
Affiliation:
Institute for Ophthalmic Research, Centre for Ophthalmology, Eberhard Karls University, Tübingen, Germany
E. Zrenner
Affiliation:
Institute for Ophthalmic Research, Centre for Ophthalmology, Eberhard Karls University, Tübingen, Germany Werner Reichardt Centre for Integrative Neuroscience (CIN), Tübingen, Germany
D.L. Rathbun*
Affiliation:
Institute for Ophthalmic Research, Centre for Ophthalmology, Eberhard Karls University, Tübingen, Germany Department of Ophthalmology, Detroit Institute of Ophthalmology, Henry Ford Health System, Detroit, Michigan
Z. Hosseinzadeh*
Affiliation:
Department of Molecular and Cellular Mechanisms of Neurodegeneration, Paul Flechsig Institute for Brain Research, University of Leipzig, Leipzig, Germany
*
Corresponding author: D.L. Rathbun,e-mail: [email protected]; Z. Hosseinzadeh, e-mail: [email protected]
Corresponding author: D.L. Rathbun,e-mail: [email protected]; Z. Hosseinzadeh, e-mail: [email protected]
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Abstract

Recently, a detailed catalog of 32 retinal ganglion cell (RGC) visual response patterns in mouse has emerged. However, the 10,000 samples required for this catalog—based on fluorescent signals from a calcium indicator dye—are much harder to acquire from the extracellular spike train recordings underlying our bionic vision research. Therefore, we sought to convert spike trains into pseudocalcium signals so that our data could be directly matched to the 32 predefined, calcium signal-based groups. A microelectrode array (MEA) was used to record spike trains from mouse RGCs of 29 retinas. Visual stimuli were adapted from the Baden et al. study; including moving bars, full-field contrast and temporal frequency chirps, and black–white and UV-green color flashes. Spike train histograms were converted into pseudocalcium traces with an OGB-1 convolution kernel. Response features were extracted using sparse principal components analysis to match each RGC to one of the 32 RGC groups. These responses mapped onto of the 32 previously described groups; however, some of the groups remained unmatched. Thus, adaptation of the Baden et al. methodology for MEA recordings of spike trains instead of calcium recordings was partially successful. Different classification methods, however, will be needed to define clear RGC groups from MEA data for our bionic vision research. Nevertheless, others may pursue a pseudocalcium approach to reconcile spike trains with calcium signals. This work will help to guide them on the limitations and potential pitfalls of such an approach.

Keywords

pseudocalciumcalcium kernelcalcium tracechirp
Type
Research Article
Information
Visual Neuroscience , Volume 38 , 2021 , E016
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Copyright
© The Author(s), 2021. Published by Cambridge University Press

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Footnotes

This is an updated version of the original article. For details please see the notice at https://doi.org/10.1017/S0952523822000037.

References

Ayton, L.N., Barnes, N., Dagnelie, G., Fujikado, T., Goetz, G., Hornig, R., Jones, B.W., Muqit, M.M.K., Rathbun, D.L., Stingl, K., Weiland, J.D. & Petoe, M.A. (2020). An update on retinal prostheses. Clinical Neurophysiology 131, 1383–1398.CrossRefGoogle ScholarPubMed
Baden, T., Berens, P., Franke, K., Román Rosón, M., Bethge, M. & Euler, T. (2016). The functional diversity of retinal ganglion cells in the mouse. Nature 529, 345–350.CrossRefGoogle ScholarPubMed
Bae, J.A., Mu, S., Kim, J.S., Turner, N.L., Tartavull, I., Kemnitz, N., Jordan, C.S., Norton, A.D., Silversmith, W.M., Prentki, R., Sorek, M, David, C., Jones, D.L., Bland, D., Sterling, A.L.R., Park, J., Briggman, K.L., Seung, H.S. & EYEWIRERS. (2018). Digital museum of retinal ganglion cells with dense anatomy and physiology. Cell 173, 1293–1306.e19.CrossRefGoogle ScholarPubMed
Barlow, H.B., Hill, R.M. & Levick, W.R. (1964). Retinal ganglion cells responding selectively to direction and speed of image motion in the rabbit. The Journal of Physiology 173, 377–407.CrossRefGoogle ScholarPubMed
Barlow, H.B. & Levick, W.R. (1965). The mechanism of directionally selective units in rabbit’s retina. The Journal of Physiology 178, 477–504.CrossRefGoogle ScholarPubMed
Boycott, B.B. & Wässle, H. (1974). The morphological types of ganglion cells of the domestic cat’s retina. The Journal of Physiology 240, 397–419.CrossRefGoogle ScholarPubMed
Briggman, K.L., Helmstaedter, M. & Denk, W. (2011). Wiring specificity in the direction-selectivity circuit of the retina. Nature 471, 183–188.CrossRefGoogle ScholarPubMed
Carcieri, S.M., Jacobs, A.L. & Nirenberg, S. (2003). Classification of retinal ganglion cells: A statistical approach. Journal of Neurophysiology 90, 1704–1713.CrossRefGoogle ScholarPubMed
Demchinsky, A.M., Shaimov, T.B., Goranskaya, D.N., Moiseeva, I.V., Kuznetsov, D.I., Kuleshov, D.S. & Polikanov, D.V. (2019). The first deaf-blind patient in Russia with Argus II retinal prosthesis system: What he sees and why. Journal of Neural Engineering 16, 025002.CrossRefGoogle Scholar
Deneux, T., Kaszas, A., Szalay, G., Katona, G., Lakner, T., Grinvald, A., Rózsa, B. & Vanzetta, I. (2016). Accurate spike estimation from noisy calcium signals for ultrafast three-dimensional imaging of large neuronal populations in vivo. Nature Communications 7, 12190.CrossRefGoogle ScholarPubMed
Enroth-Cugell, C. & Robson, J.G. (1966). The contrast sensitivity of retinal ganglion cells of the cat. The Journal of Physiology 187, 517–552.CrossRefGoogle ScholarPubMed
Farrow, K. & Masland, R.H. (2011). Physiological clustering of visual channels in the mouse retina. Journal of Neurophysiology 105, 1516–1530.CrossRefGoogle ScholarPubMed
Greenberg, D.S., Houweling, A.R. & Kerr, J.N.D. (2008). Population imaging of ongoing neuronal activity in the visual cortex of awake rats. Nature Neuroscience 11, 749–751.CrossRefGoogle ScholarPubMed
Grewe, B.F., Langer, D., Kasper, H., Kampa, B.M. & Helmchen, F. (2010). High-speed in vivo calcium imaging reveals neuronal network activity with near-millisecond precision. Nature Methods 7, 399–405.CrossRefGoogle ScholarPubMed
Grienberger, C. & Konnerth, A. (2012). Imaging calcium in neurons. Neuron 73, 862–885.CrossRefGoogle ScholarPubMed
Ho, E., Smith, R., Goetz, G., Lei, X., Galambos, L., Kamins, T.I., Harris, J., Mathieson, K., Palanker, D. & Sher, A. (2018). Spatiotemporal characteristics of retinal response to network-mediated photovoltaic stimulation. Journal of Neurophysiology 119, 389–400.CrossRefGoogle ScholarPubMed
Hosseinzadeh, Z., Jalligampala, A., Zrenner, E. & Rathbun, D.L. (2017). The spatial extent of epiretinal electrical stimulation in the healthy mouse retina. Neurosignals 25, 15–25.CrossRefGoogle ScholarPubMed
Hosseinzadeh, Z., Rathbun, D.L. & Zrenner, E. (2019). Selective activation of ON and OFF RGC input in mouse retina stimulated. Investigative Ophthalmology & Visual Science 60, 4989.Google Scholar
Jalligampala, A., Sekhar, S., Zrenner, E. & Rathbun, D.L. (2017). Optimal voltage stimulation parameters for network-mediated responses in wild type and rd10 mouse retinal ganglion cells. Journal of Neural Engineering 14, 026004.CrossRefGoogle ScholarPubMed
Jouty, J., Hilgen, G., Sernagor, E. & Hennig, M.H. (2018). Non-parametric physiological classification of retinal ganglion cells in the mouse retina. Frontiers in Cellular Neuroscience 12, 481.CrossRefGoogle ScholarPubMed
Kuffler, S.W. (1953). Discharge patterns and functional organization of mammalian retina. Journal of Neurophysiology 16, 37–68.CrossRefGoogle ScholarPubMed
Nakajima, R. & Baker, B.J. (2018). Mapping of excitatory and inhibitory postsynaptic potentials of neuronal populations in hippocampal slices using the GEVI, ArcLight. Journal of Physics D: Applied Physics 51, 504003.CrossRefGoogle ScholarPubMed
Perry, V.H. & Cowey, A. (1984). Retinal ganglion cells that project to the superior colliculus and pretectum in the macaque monkey. Neuroscience 12, 1125–1137.CrossRefGoogle Scholar
Rathbun, D.L., Ghorbani, N., Shabani, H., Zrenner, E. & Hosseinzadeh, Z. (2018). Spike-triggered average electrical stimuli as input filters for bionic vision-a perspective. Journal of Neural Engineering 15, 063002.CrossRefGoogle ScholarPubMed
Rheaume, B.A., Jereen, A., Bolisetty, M., Sajid, M.S., Yang, Y., Renna, K., Sun, L., Robson, P. & Trakhtenberg, E.F. (2018). Single cell transcriptome profiling of retinal ganglion cells identifies cellular subtypes. Nature Communications 9, 2759.CrossRefGoogle ScholarPubMed
Sekhar, S., Jalligampala, A., Zrenner, E. & Rathbun, D.L. (2016). Tickling the retina: Integration of subthreshold electrical pulses can activate retinal neurons. Journal of Neural Engineering 13, 046004.CrossRefGoogle ScholarPubMed
Sekhar, S., Jalligampala, A., Zrenner, E. & Rathbun, D.L. (2017). Correspondence between visual and electrical input filters of ON and OFF mouse retinal ganglion cells. Journal of Neural Engineering 14, 046017.CrossRefGoogle Scholar
Shew, W.L., Bellay, T. & Plenz, D. (2010). Simultaneous multi-electrode array recording and two-photon calcium imaging of neural activity. Journal of Neuroscience Methods 192, 75–82.CrossRefGoogle ScholarPubMed
Tran, N.M., Shekhar, K., Whitney, I.E., Jacobi, A., Benhar, I., Hong, G., Yan, W., Adiconis, X., Arnold, M.E., Lee, J.M., Levin, J.Z., Lin, D., Wang, C., Lieber, C.M., Regev, A., He, Z. & Sanes, J.R. (2019). Single-cell profiles of retinal ganglion cells differing in resilience to injury reveal neuroprotective genes. Neuron 104, 1039–1055.e12.CrossRefGoogle ScholarPubMed
Wässle, H. (2004). Parallel processing in the mammalian retina. Nature Reviews. Neuroscience 5, 747–757.CrossRefGoogle ScholarPubMed
Williamson, R.S., Sahani, M. & Pillow, J.W. (2015). The equivalence of information-theoretic and likelihood-based methods for neural dimensionality reduction. PLoS Computational Biology 11, e1004141.CrossRefGoogle ScholarPubMed
Zrenner, E. (2002). Will retinal implants restore vision? Science 295, 1022–1025.CrossRefGoogle ScholarPubMed