Abstract
Many experiments showed that the retina processes information before transmitting them to the visual cortex. We propose a model to elucidate the predictive effect of the amacrine cells and ganglion cells in the retina. We generate the input signals with OU (Ornstein-Uhlenbeck) and HMM (Hidden Markov model) process, and compare the mutual information calculated from the simulations with those of the moving bar experiments on bullfrog retina mounted on a multi-electrode array, illustrating that the model agrees with the experiments.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Jessell, T., Siegelbaum, S., Hudspeth, A.J.: Learning and memory. In: Kandel, E.R., Schwartz, J.H., Jessell, T.M. (eds.) Principles of Neural Science, vol. 4, pp. 1227–1246. McGraw-hill, New York (2000)
Berry II, M.J., et al.: Anticipation of moving stimuli by the retina. Nature 398(6725), 334 (1999)
Palmer, S.E., Marre, O., Berry, M.J., Bialek, W.: Predictive information in a sensory population. Proc. Natl. Acad. Sci. U.S.A. 112(22), 6908–6913 (2015)
Mi, Y., Fung, C.C.A., Wong, K.Y.M., Wu, S.: Spike Frequency Adaptation Implements Anticipative Tracking in Continuous Attractor Neural Networks. In: NIPS, pp. 505–513 (2014)
Nijhawan, R., Wu, S.: Compensating time delays with neural predictions: are predictions sensory or motor? Philos. Trans. Royal Soc. A 367(1891), 1063–1078 (2009)
Chen, K.S., Chen, C.C., Chan, C.K.: Characterization of predictive behavior of a retina by mutual information. Front. Comput. Neurosci. 11, 66 (2017)
Chen, Y.: Anticipative Responses of a Retina to a Stochastically Moving Bar. Master thesis, National Tsing Hua University (2018)
Fung, C.C.A., Wong, K.Y.M., Wang, H., Wu, S.: Dynamical synapses enhance neural information processing: gracefulness, accuracy, and mobility. Neural Comput. 24(5), 1147–1185 (2012)
Marre, O., Botella-Soler, V., Simmons, K.D., Mora, T., Tkačik, G., Berry II, M.J.: High accuracy decoding of dynamical motion from a large retinal population. PLOS Comput. Biol. 11(7), e1004304 (2015)
Briggman, K.L., Helmstaedter, M., Denk, W.: Wiring specificity in the direction-selectivity circuit of the retina. Nature 471(7337), 183 (2011)
Euler, T., Detwiler, P.B., Denk, W.: Directionally selective calcium signals in dendrites of starburst amacrine cells. Nature 418(6900), 845 (2002)
Wei, W., Hamby, A.M., Zhou, K., Feller, M.B.: Development of asymmetric inhibition underlying direction selectivity in the retina. Nature 469(7330), 402 (2011)
Fried, S.I., Münch, T.A., Werblin, F.S.: Mechanisms and circuitry underlying directional selectivity in the retina. Nature 420(6914), 411 (2002)
Masland, R.H.: The neuronal organization of the retina. Neuron 76(2), 266–280 (2012)
Venkataramani, S., Taylor, W.R.: Orientation selectivity in rabbit retinal ganglion cells is mediated by presynaptic inhibition. J. Neurosci. 30(46), 15664–15676 (2010)
Manu, M., Baccus, S.A.: Disinhibitory gating of retinal output by transmission from an amacrine cell. Proc. Natl. Acad. Sci. U.S.A. 108(45), 18447–18452 (2011)
Baden, T., Berens, P., Franke, K., Rosón, M.R., Bethge, M., Euler, T.: The functional diversity of retinal ganglion cells in the mouse. Nature 529(7586), 345 (2016)
Zhang, A.J., Wu, S.M.: Responses and receptive fields of amacrine cells and ganglion cells in the salamander retina. Vision Res. 50(6), 614–622 (2010)
Hosoya, T., Baccus, S.A., Meister, M.: Dynamic predictive coding by the retina. Nature 436, 71–77 (2005)
de Vries, S.E., Baccus, S.A., Meister, M.: The projective field of a retinal amacrine cell. J. Neurosci. 31(23), 8595–8604 (2011)
Lin, B., Wang, S.W., Masland, R.H.: Retinal ganglion cell type, size, and spacing can be specified independent of homotypic dendritic contacts. Neuron 43(4), 475–485 (2004)
Vaney, D.I., Sivyer, B., Taylor, W.R.: Direction selectivity in the retina: symmetry and asymmetry in structure and function. Nat. Rev. Neurosci. 13(3), 194 (2012)
Dong, W., Sun, W., Zhang, Y., Chen, X., He, S.: Dendritic relationship between starburst amacrine cells and direction-selective ganglion cells in the rabbit retina. J. Physiol. 556(1), 11–17 (2004)
Fung, C.C.A., Wong, K.Y.M., Mao, H.Z., Wu, S.: Fluctuation-response relation unifies dynamical behaviors in neural fields. Phys. Rev. E 92(2), 022801 (2015)
Pang, J.J., Gao, F., Wu, S.M.: Light-evoked excitatory and inhibitory synaptic inputs to ON and OFF \(\alpha \) ganglion cells in the mouse retina. J. Neurosci. 23(14), 6063–6073 (2003)
Acknowledgements
This work is supported by the Research Grants Council of Hong Kong (grant numbers 16322616 and 16306817).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Yan, M., Chen, Y., Chan, C.K., Wong, K.Y.M. (2018). Modelling Predictive Information of Stochastic Dynamics in the Retina. In: Cheng, L., Leung, A., Ozawa, S. (eds) Neural Information Processing. ICONIP 2018. Lecture Notes in Computer Science(), vol 11307. Springer, Cham. https://doi.org/10.1007/978-3-030-04239-4_22
Download citation
DOI: https://doi.org/10.1007/978-3-030-04239-4_22
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-04238-7
Online ISBN: 978-3-030-04239-4
eBook Packages: Computer ScienceComputer Science (R0)