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Coordinated dynamic encoding in the retina using opposing forms of plasticity

Nature Neuroscience volume 14, pages 1317–1322 (2011)Cite this article

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Abstract

The range of natural inputs encoded by a neuron often exceeds its dynamic range. To overcome this limitation, neural populations divide their inputs among different cell classes, as with rod and cone photoreceptors, and adapt by shifting their dynamic range. We report that the dynamic behavior of retinal ganglion cells in salamanders, mice and rabbits is divided into two opposing forms of short-term plasticity in different cell classes. One population of cells exhibited sensitization—a persistent elevated sensitivity following a strong stimulus. This newly observed dynamic behavior compensates for the information loss caused by the known process of adaptation occurring in a separate cell population. The two populations divide the dynamic range of inputs, with sensitizing cells encoding weak signals and adapting cells encoding strong signals. In the two populations, the linear, threshold and adaptive properties are linked to preserve responsiveness when stimulus statistics change, with one population maintaining the ability to respond when the other fails.

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Figure 1: Adaptation and sensitization in separate neural populations.
Figure 2: Sensitizing and adapting populations encode common stimulus features.
Figure 3: Improvement of discriminability in a combined population of sensitizing and adapting cells.
Figure 4: Sensitizing cells specialize to encode weak signals; adapting cells encode strong signals.
Figure 5: Sensitizing and adapting cells increase information transmission using opposing changes in firing rate.
Figure 6: Model of sensitization.

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References

  1. Laughlin, S. A simple coding procedure enhances a neuron's information capacity. Z. Naturforsch. C. 36, 910–912 (1981).

    Article  CAS  Google Scholar 

  2. DeWeese, M. & Zador, A. Asymmetric dynamics in optimal variance adaptation. Neural Comput. 10, 1179–1202 (1998).

    Article  Google Scholar 

  3. Wark, B., Fairhall, A. & Rieke, F. Timescales of inference in visual adaptation. Neuron 61, 750–761 (2009).

    Article  CAS  Google Scholar 

  4. Fairhall, A.L., Lewen, G.D., Bialek, W. & de Ruyter van Steveninck, R.R. Efficiency and ambiguity in an adaptive neural code. Nature 412, 787–792 (2001).

    Article  CAS  Google Scholar 

  5. Nagel, K.I. & Doupe, A.J. Temporal processing and adaptation in the songbird auditory forebrain. Neuron 51, 845–859 (2006).

    Article  CAS  Google Scholar 

  6. Maravall, M., Petersen, R.S., Fairhall, A.L., Arabzadeh, E. & Diamond, M.E. Shifts in coding properties and maintenance of information transmission during adaptation in barrel cortex. PLoS Biol. 5, e19 (2007).

    Article  Google Scholar 

  7. Smirnakis, S.M., Berry, M.J., Warland, D.K., Bialek, W. & Meister, M. Adaptation of retinal processing to image contrast and spatial scale. Nature 386, 69–73 (1997).

    Article  CAS  Google Scholar 

  8. Frazor, R.A. & Geisler, W.S. Local luminance and contrast in natural images. Vision Res. 46, 1585–1598 (2006).

    Article  Google Scholar 

  9. Baccus, S.A. & Meister, M. Fast and slow contrast adaptation in retinal circuitry. Neuron 36, 909–919 (2002).

    Article  CAS  Google Scholar 

  10. Rieke, F. & Rudd, M.E. The challenges natural images pose for visual adaptation. Neuron 64, 605–616 (2009).

    Article  CAS  Google Scholar 

  11. Solomon, S.G., Peirce, J.W., Dhruv, N.T. & Lennie, P. Profound contrast adaptation early in the visual pathway. Neuron 42, 155–162 (2004).

    Article  CAS  Google Scholar 

  12. Snippe, H.P. & van Hateren, J.H. Recovery from contrast adaptation matches ideal-observer predictions. J. Opt. Soc. Am. A Opt. Image Sci. Vis. 20, 1321–1330 (2003).

    Article  CAS  Google Scholar 

  13. Brown, S.P. & Masland, R.H. Spatial scale and cellular substrate of contrast adaptation by retinal ganglion cells. Nat. Neurosci. 4, 44–51 (2001).

    Article  CAS  Google Scholar 

  14. Pinsker, H.M., Hening, W.A., Carew, T.J. & Kandel, E.R. Long-term sensitization of a defensive withdrawal reflex in Aplysia. Science 182, 1039–1042 (1973).

    Article  CAS  Google Scholar 

  15. Segev, R., Puchalla, J. & Berry, M.J. Functional organization of ganglion cells in the salamander retina. J. Neurophysiol. 95, 2277–2292 (2006).

    Article  Google Scholar 

  16. Huberman, A.D. et al. Architecture and activity-mediated refinement of axonal projections from a mosaic of genetically identified retinal ganglion cells. Neuron 59, 425–438 (2008).

    Article  CAS  Google Scholar 

  17. Dayan, P. & Abbott, L.F. Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems 460 (MIT Press, 2009).

  18. Abbott, L.F. & Dayan, P. The effect of correlated variability on the accuracy of a population code. Neural Comput. 11, 91–101 (1999).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  20. Srinivasan, M.V., Laughlin, S.B. & Dubs, A.T. Predictive coding: a fresh view of inhibition in the retina. Proc. R. Soc. Lond. B Biol. Sci. 216, 427–459 (1982).

    Article  CAS  Google Scholar 

  21. Chander, D. & Chichilnisky, E.J. Adaptation to temporal contrast in primate and salamander retina. J. Neurosci. 21, 9904–9916 (2001).

    Article  CAS  Google Scholar 

  22. Mennerick, S. & Matthews, G. Ultrafast exocytosis elicited by calcium current in synaptic terminals of retinal bipolar neurons. Neuron 17, 1241–1249 (1996).

    Article  CAS  Google Scholar 

  23. Field, G.D. & Rieke, F. Nonlinear signal transfer from mouse rods to bipolar cells and implications for visual sensitivity. Neuron 34, 773–785 (2002).

    Article  CAS  Google Scholar 

  24. Reinagel, P. & Reid, R.C. Temporal coding of visual information in the thalamus. J. Neurosci. 20, 5392–5400 (2000).

    Article  CAS  Google Scholar 

  25. Wessel, R., Koch, C. & Gabbiani, F. Coding of time-varying electric field amplitude modulations in a wave-type electric fish. J. Neurophysiol. 75, 2280–2293 (1996).

    Article  CAS  Google Scholar 

  26. Butts, D.A. How much information is associated with a particular stimulus? Network 14, 177–187 (2003).

    Article  Google Scholar 

  27. Kim, K.J. & Rieke, F. Slow Na+ inactivation and variance adaptation in salamander retinal ganglion cells. J. Neurosci. 23, 1506–1516 (2003).

    Article  CAS  Google Scholar 

  28. Manookin, M.B. & Demb, J.B. Presynaptic mechanism for slow contrast adaptation in mammalian retinal ganglion cells. Neuron 50, 453–464 (2006).

    Article  CAS  Google Scholar 

  29. Rieke, F. Temporal contrast adaptation in salamander bipolar cells. J. Neurosci. 21, 9445–9454 (2001).

    Article  CAS  Google Scholar 

  30. Brainard, D.H. The psychophysics toolbox. Spat. Vis. 10, 433–436 (1997).

    Article  CAS  Google Scholar 

  31. Pello, D.G. The VideoToolbox software for visual psychophysics: transforming numbers into movies. Spat. Vis. 10, 437–442 (1997).

    Article  Google Scholar 

  32. Chichilnisky, E.J. A simple white noise analysis of neuronal light responses. Network 12, 199–213 (2001).

    Article  CAS  Google Scholar 

  33. Olveczky, B.P., Baccus, S.A. & Meister, M. Segregation of object and background motion in the retina. Nature 423, 401–408 (2003).

    Article  Google Scholar 

  34. Gollisch, T. & Meister, M. Rapid neural coding in the retina with relative spike latencies. Science 319, 1108–1111 (2008).

    Article  CAS  Google Scholar 

  35. Strong, S., Koberle, R. & de Ruyter van Steveninck, R. Entropy and information in neural spike trains. Phys. Rev. Lett. 80, 197–200 (1998).

    Article  CAS  Google Scholar 

  36. Baccus, S.A. Timing and computation in inner retinal circuitry. Annu. Rev. Physiol. 69, 271–290 (2007).

    Article  CAS  Google Scholar 

  37. Maguire, G., Maple, B., Lukasiewicz, P. & Werblin, F. Gamma-aminobutyrate type B receptor modulation of L-type calcium channel current at bipolar cell terminals in the retina of the tiger salamander. Proc. Natl. Acad. Sci. USA 86, 10144–10147 (1989).

    Article  CAS  Google Scholar 

  38. Li, G.-L., Vigh, J. & von Gersdorff, H. Short-term depression at the reciprocal synapses between a retinal bipolar cell terminal and amacrine cells. J. Neurosci. 27, 7377–7385 (2007).

    Article  CAS  Google Scholar 

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Acknowledgements

We thank E. Knudsen and W.T. Newsome for comments on the manuscript; D. Baylor, R.W. Tsien, B. Wandell, P. Jadzinsky, A.L. Fairhall, F. Rieke, D.S. Fisher and K.D. Miller for discussions; and Y. Ozuysal and A. Huberman for technical assistance. This work was supported by grants from the US National Eye Institute, Pew Charitable Trusts, McKnight Endowment Fund for Neuroscience, Karl Kirchgessner Foundation and Alfred P. Sloan Foundation (S.A.B.); and by the Stanford Medical Scientist Training Program and a US National Science Foundation Integrative Graduate Education and Research Traineeship (D.B.K.). Rabbit experiments were performed in the laboratory of M. Meister at Harvard University.

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Authors and Affiliations

  1. Neuroscience Program, Stanford University School of Medicine, Stanford, California, USA

    David B Kastner

  2. Department of Neurobiology, Stanford University School of Medicine, Stanford, California, USA

    Stephen A Baccus

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  1. David B Kastner
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  2. Stephen A Baccus
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Contributions

D.B.K. and S.A.B. designed the study, D.B.K. performed the experiments and analysis, and D.B.K. and S.A.B. wrote the manuscript.

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Correspondence to Stephen A Baccus.

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Kastner, D., Baccus, S. Coordinated dynamic encoding in the retina using opposing forms of plasticity. Nat Neurosci 14, 1317–1322 (2011). https://doi.org/10.1038/nn.2906

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