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Modelling Predictive Information of Stochastic Dynamics in the Retina

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Neural Information Processing (ICONIP 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11307))

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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.

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Acknowledgements

This work is supported by the Research Grants Council of Hong Kong (grant numbers 16322616 and 16306817).

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Correspondence to Min Yan .

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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

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  • DOI: https://doi.org/10.1007/978-3-030-04239-4_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04238-7

  • Online ISBN: 978-3-030-04239-4

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