Modelling Predictive Information of Stochastic Dynamics in the Retina

Min Yan; Yiko Chen; C. K. Chan; K. Y.Michael Wong

doi:10.1007/978-3-030-04239-4_22

Modelling Predictive Information of Stochastic Dynamics in the Retina

Min Yan, Yiko Chen, C. K. Chan, K. Y.Michael Wong

Department of Physics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Neural Information Processing - 25th International Conference, ICONIP 2018, Proceedings
Editors	Seiichi Ozawa, Andrew Chi Sing Leung, Long Cheng
Publisher	Springer Verlag
Pages	246-257
Number of pages	12
ISBN (Print)	9783030042387
DOIs	https://doi.org/10.1007/978-3-030-04239-4_22
State	Published - 2018
Event	25th International Conference on Neural Information Processing, ICONIP 2018 - Siem Reap, Cambodia Duration: 13 Dec 2018 → 16 Dec 2018

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11307 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	25th International Conference on Neural Information Processing, ICONIP 2018
Country/Territory	Cambodia
City	Siem Reap
Period	13/12/18 → 16/12/18

Keywords

Amacrine cells
Direction selectivity
Ganglion cells
Predictive information
Retina

Access to Document

10.1007/978-3-030-04239-4_22

Cite this

Yan, M., Chen, Y., Chan, C. K., & Wong, K. Y. M. (2018). Modelling Predictive Information of Stochastic Dynamics in the Retina. In S. Ozawa, A. C. S. Leung, & L. Cheng (Eds.), Neural Information Processing - 25th International Conference, ICONIP 2018, Proceedings (pp. 246-257). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11307 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-04239-4_22

Yan, Min ; Chen, Yiko ; Chan, C. K. et al. / Modelling Predictive Information of Stochastic Dynamics in the Retina. Neural Information Processing - 25th International Conference, ICONIP 2018, Proceedings. editor / Seiichi Ozawa ; Andrew Chi Sing Leung ; Long Cheng. Springer Verlag, 2018. pp. 246-257 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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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.",

keywords = "Amacrine cells, Direction selectivity, Ganglion cells, Predictive information, Retina",

author = "Min Yan and Yiko Chen and Chan, {C. K.} and Wong, {K. Y.Michael}",

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Yan, M, Chen, Y, Chan, CK & Wong, KYM 2018, Modelling Predictive Information of Stochastic Dynamics in the Retina. in S Ozawa, ACS Leung & L Cheng (eds), Neural Information Processing - 25th International Conference, ICONIP 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11307 LNCS, Springer Verlag, pp. 246-257, 25th International Conference on Neural Information Processing, ICONIP 2018, Siem Reap, Cambodia, 13/12/18. https://doi.org/10.1007/978-3-030-04239-4_22

Modelling Predictive Information of Stochastic Dynamics in the Retina. / Yan, Min; Chen, Yiko; Chan, C. K. et al.
Neural Information Processing - 25th International Conference, ICONIP 2018, Proceedings. ed. / Seiichi Ozawa; Andrew Chi Sing Leung; Long Cheng. Springer Verlag, 2018. p. 246-257 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11307 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 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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Yan M, Chen Y, Chan CK, Wong KYM. Modelling Predictive Information of Stochastic Dynamics in the Retina. In Ozawa S, Leung ACS, Cheng L, editors, Neural Information Processing - 25th International Conference, ICONIP 2018, Proceedings. Springer Verlag. 2018. p. 246-257. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-04239-4_22

Modelling Predictive Information of Stochastic Dynamics in the Retina

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