Skip to main content
SpringerLink
Log in

A Conductance-Based Neuronal Network Model for Color Coding in the Primate Foveal Retina

  • Conference paper
  • First Online:
Natural and Artificial Computation for Biomedicine and Neuroscience (IWINAC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10337))

Abstract

Descriptive models of the retina have been essential to understand how retinal neurons convert visual stimuli into a neural response. With recent advancements of neuroimaging techniques, availability of an increasing amount of physiological data and current computational capabilities, we now have powerful resources for developing biologically more realistic models of the brain. In this work, we implemented a two-dimensional network model of the primate retina that uses conductance-based neurons. The model aims to provide neuroscientists who work in visual areas beyond the retina with a realistic retinal model whose parameters have been carefully tuned based on data from the primate fovea and whose response at every stage of the model adequately reproduces neuronal behavior. We exhaustively benchmarked the model against well-established visual stimuli, showing spatial and temporal responses of the model neurons to light flashes, which can be disk- or ring-shaped, and to sine-wave gratings of varying spatial frequency. The model describes the red-green and blue-yellow color opponency of retinal cells that connect to parvocellular and koniocellular cells in the Lateral Geniculate Nucleus (LGN), respectively. The model was implemented in the widely used neural simulation tool NEST and the code has been released as open source software.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Arman, A.C., Sampath, A.P.: Dark-adapted response threshold of OFF ganglion cells is not set by OFF bipolar cells in the mouse retina. J. Neurophysiol. 107(10), 2649–2659 (2012)

    Article  Google Scholar 

  2. Benardete, E.A., Kaplan, E.: The receptive field of the primate P retinal ganglion cell, i: linear dynamics. Vis. Neurosci. 14(01), 169–185 (1997)

    Article  Google Scholar 

  3. Berry, M.J., Brivanlou, I.H., Jordan, T.A., Meister, M.: Anticipation of moving stimuli by the retina. Nature 398(6725), 334–338 (1999)

    Article  Google Scholar 

  4. Croner, L.J., Kaplan, E.: Receptive fields of P and M ganglion cells across the primate retina. Vis. Res. 35(1), 7–24 (1995)

    Article  Google Scholar 

  5. Crook, J.D., Davenport, C.M., Peterson, B.B., Packer, O.S., Detwiler, P.B., Dacey, D.M.: Parallel ON and OFF cone bipolar inputs establish spatially coextensive receptive field structure of blue-yellow ganglion cells in primate retina. J. Neurosci. 29(26), 8372–8387 (2009)

    Article  Google Scholar 

  6. Demb, J.B., Singer, J.H.: Intrinsic properties and functional circuitry of the AII amacrine cell. Vis. Neurosci. 29(01), 51–60 (2012)

    Article  Google Scholar 

  7. Destexhe, A., Mainen, Z.F., Sejnowski, T.J., et al.: Synaptic currents, neuromodulation, and kinetic models. Handb. Brain Theory Neural Netw. 66, 617–648 (1995)

    Google Scholar 

  8. Enroth-Cugell, C., Robson, J.G.: The contrast sensitivity of retinal ganglion cells of the cat. J. Physiol. 187(3), 517–552 (1966)

    Article  Google Scholar 

  9. Github: code repository. https://github.com/pablomc88

  10. van Hateren, H.: A cellular and molecular model of response kinetics and adaptation in primate cones and horizontal cells. J. Vis. 5(4), 5–5 (2005)

    Article  Google Scholar 

  11. Hennig, M.H., Funke, K., Wörgötter, F.: The influence of different retinal subcircuits on the nonlinearity of ganglion cell behavior. J. Neurosci. 22(19), 8726–8738 (2002)

    Google Scholar 

  12. Hennig, M.H., Wörgötter, F.: Effects of fixational eye movements on retinal ganglion cell responses: a modelling study. Front. Comput. Neurosci. 1, 1–12 (2007)

    Article  Google Scholar 

  13. Hill, S., Tononi, G.: Modeling sleep and wakefulness in the thalamocortical system. J. Neurophysiol. 93(3), 1671–1698 (2005)

    Article  Google Scholar 

  14. Izhikevich, E.M., Edelman, G.M.: Large-scale model of mammalian thalamocortical systems. Proc. Nat. Acad. Sci. 105(9), 3593–3598 (2008)

    Article  Google Scholar 

  15. Kaplan, E., Benardete, E.: The dynamics of primate retinal ganglion cells. Prog. Brain Res. 134, 17–34 (2001)

    Article  Google Scholar 

  16. Kolb, H., Fernandez, E., Nelson, R., Jones, B.W.: Webvision: The Organization of the Retina and Visual System. National Library of Medicine, Bethesda (2011). Copyright

    Google Scholar 

  17. Lee, B.B., Shapley, R.M., Hawken, M.J., Sun, H.: Spatial distributions of cone inputs to cells of the parvocellular pathway investigated with cone-isolating gratings. JOSA A 29(2), A223–A232 (2012)

    Article  Google Scholar 

  18. MacNeil, M.A., Masland, R.H.: Extreme diversity among amacrine cells: implications for function. Neuron 20(5), 971–982 (1998)

    Article  Google Scholar 

  19. Manookin, M.B., Beaudoin, D.L., Ernst, Z.R., Flagel, L.J., Demb, J.B.: Disinhibition combines with excitation to extend the operating range of the OFF visual pathway in daylight. J. Neurosci. 28(16), 4136–4150 (2008)

    Article  Google Scholar 

  20. Martínez-Cañada, P., Morillas, C., Pino, B., Ros, E., Pelayo, F.: A computational framework for realistic retina modeling. Int. J. Neural Syst. 26(07), 1650030 (2016)

    Article  Google Scholar 

  21. Martínez-Cañada, P., Morillas, C., Pino, B., Pelayo, F.: Towards a generic simulation tool of retina models. In: Ferrández Vicente, J.M., Álvarez-Sánchez, J.R., de la Paz López, F., Toledo-Moreo, F.J., Adeli, H. (eds.) IWINAC 2015. LNCS, vol. 9107, pp. 47–57. Springer, Cham (2015). doi:10.1007/978-3-319-18914-7_6

    Chapter  Google Scholar 

  22. Masland, R.H.: The fundamental plan of the retina. Nat. Neurosci. 4(9), 877–886 (2001)

    Article  Google Scholar 

  23. Momiji, H., Hankins, M.W., Bharath, A.A., Kennard, C.: A numerical study of red-green colour opponent properties in the primate retina. Eur. J. Neurosci. 25(4), 1155–1165 (2007)

    Article  Google Scholar 

  24. Nawy, S., Jahr, C.E.: Suppression by glutamate of cGMP-activated conductance in retinal bipolar cells. Nature 346(6281), 269 (1990)

    Article  Google Scholar 

  25. Plesser, H.E., Austvoll, K.: Specification and generation of structured neuronal network models with the NEST topology module. BMC Neurosci. 10(suppl 1), P56 (2009)

    Article  Google Scholar 

  26. Plesser, H.E., Diesmann, M., Gewaltig, M.O., Morrison, A.: NEST: the Neural Simulation Tool. In: Jaeger, D., Jung, R. (eds.) Encyclopedia of Computational Neuroscience. Springer, Heidelberg (2015). www.springerreference.com/docs/html/chapterdbid/348323.html

  27. Publio, R., Oliveira, R.F., Roque, A.C.: A computational study on the role of gap junctions and rod Ih conductance in the enhancement of the dynamic range of the retina. PLoS ONE 4(9), e6970 (2009)

    Article  Google Scholar 

  28. Smith, R.G.: Simulation of an anatomically defined local circuit: the cone-horizontal cell network in cat retina. Vis. Neurosci. 12(03), 545–561 (1995)

    Article  Google Scholar 

  29. Snellman, J., Kaur, T., Shen, Y., Nawy, S.: Regulation of ON bipolar cell activity. Prog. Retinal Eye Res. 27(4), 450–463 (2008)

    Article  Google Scholar 

  30. Tailby, C., Szmajda, B., Buzas, P., Lee, B., Martin, P.: Transmission of blue (S) cone signals through the primate lateral geniculate nucleus. J. Physiol. 586(24), 5947–5967 (2008)

    Article  Google Scholar 

  31. Tranchina, D., Gordon, J., Shapley, R.: Retinal light adaptation-evidence for a feedback mechanism. Nature 310(5975), 314–316 (1984)

    Article  Google Scholar 

  32. Vardi, N., Zhang, L.L., Payne, J.A., Sterling, P.: Evidence that different cation chloride cotransporters in retinal neurons allow opposite responses to GABA. J. Neurosci. 20(20), 7657–7663 (2000)

    Google Scholar 

  33. Wang, X.J., Rinzel, J.: Alternating and synchronous rhythms in reciprocally inhibitory model neurons. Neural Comput. 4(1), 84–97 (1992)

    Article  Google Scholar 

  34. Wohrer, A., Kornprobst, P.: Virtual retina: a biological retina model and simulator, with contrast gain control. J. Comput. Neurosci. 26(2), 219–249 (2009)

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgments

This work was supported by the Spanish National Grant TIN2016-81041-R and the research project P11-TIC-7983 of Junta of Andalucia (Spain), co-financed by the European Regional Development Fund (ERDF). P. Martínez-Cañada was supported by the PhD scholarship FPU13/01487, awarded by the Government of Spain, FPU program.

Author information

Authors and Affiliations

  1. Department of Computer Architecture and Technology, University of Granada, Granada, Spain

    Pablo Martínez-Cañada, Christian Morillas & Francisco Pelayo

  2. Centro de Investigación en Tecnologías de la Información y de las Comunicaciones (CITIC), University of Granada, Granada, Spain

    Pablo Martínez-Cañada, Christian Morillas & Francisco Pelayo

Authors
  1. Pablo Martínez-Cañada
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Christian Morillas
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Francisco Pelayo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Pablo Martínez-Cañada .

Editor information

Editors and Affiliations

  1. Departamento de Electrónica, Tecnología de Computadoras y Proyectos, Universidad Politécnica de Cartagena, Cartagena, Spain

    José Manuel Ferrández Vicente

  2. Departamento de Inteligencia Articial, Universidad Nacional de Educación a Distancia, Madrid, Spain

    José Ramón Álvarez-Sánchez

  3. Departamento de Inteligencia Articial, Universidad Nacional de Educación a Distancia, Madrid, Spain

    Félix de la Paz López

  4. Departamento de Electrónica, Tecnología de Computadoras y Proyectos, Universidad Politécnica de Cartagena, Cartagena, Spain

    Javier Toledo Moreo

  5. The Ohio State University, Columbus, Ohio, USA

    Hojjat Adeli

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Martínez-Cañada, P., Morillas, C., Pelayo, F. (2017). A Conductance-Based Neuronal Network Model for Color Coding in the Primate Foveal Retina. In: Ferrández Vicente, J., Álvarez-Sánchez, J., de la Paz López, F., Toledo Moreo, J., Adeli, H. (eds) Natural and Artificial Computation for Biomedicine and Neuroscience. IWINAC 2017. Lecture Notes in Computer Science(), vol 10337. Springer, Cham. https://doi.org/10.1007/978-3-319-59740-9_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-59740-9_7

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59739-3

  • Online ISBN: 978-3-319-59740-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation