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Special Issue: Neural Coding 2018

1 Institute of Physiology CAS, Czech Republic
2 Department of Mathematics, University of Torino, Italy
3 Institute for Stochastics, Johannes Kepler University Linz, Austria

The special issue is available from: https://www.aimspress.com/newsinfo/1269.html.
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References

1. G. Ascione and E. Pirozzi, On a stochastic neuronal model integrating correlated inputs, Math. Biosci. Eng., 16 (2019), 5206–5225.

2. A. Di Crescenzo and F. Travaglino, Probabilistic analysis of systems alternating for state-dependent dichotomous noise, Math. Biosci. Eng., 16 (2019), 6386–6405.

3. P. E. Greenwood and L. M. Ward, Rapidly forming, slowly evolving, spatial patterns from quasicycle Mexican Hat coupling, Math. Biosci. Eng., 16 (2019), 6769–6793.

4. J. Ito, E. Lucrezia, G. Palm and S. Grün, Detection and evaluation of bursts in terms of novelty and surprise, Math. Biosci. Eng., 16 (2019), 6990–7008.

5. D. Fasoli and S. Panzeri, Mathematical studies of the dynamics of finite-size binary neural networks: A review of recent progress, Math. Biosci. Eng., 16 (2019), 8025–8059.

6. A. Civallero and C. Zucca, The Inverse First Passage time method for a two dimensional Ornstein Uhlenbeck process with neuronal application, Math. Biosci. Eng., 16 (2019), 8162–8178.

© 2019 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

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