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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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Citation: Lubomir Kostal, Laura Sacerdote, Massimiliano Tamborrino. Special Issue: Neural Coding 2018. Mathematical Biosciences and Engineering, 2019, 16(6): 8214-8216. doi: 10.3934/mbe.2019415

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.

 

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