| CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY |
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Information Capacity and Transmission in a Courbage–Nekorkin–Vdovin Map-Based Neuron Model |
| Yuan Yue1,2, Yu-Jiang Liu1, Ya-Lei Song1, Yong Chen3, Lian-Chun Yu1** |
1Institute of Theoretical Physics, Lanzhou University, Lanzhou 730000
2School of Mathematics and Computer Science, Northwest University for Nationalities, Lanzhou 730000
3School of Physics and Nuclear Energy Engineering, Beihang University, Beijing 100191
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| Cite this article: |
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Yuan Yue, Yu-Jiang Liu, Ya-Lei Song et al 2017 Chin. Phys. Lett. 34 048701 |
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Abstract The map-based neuron models have received attention as valid phenomenological neuron models due to their computational efficiency and flexibility to generate rich patterns. Here we evaluate the information capacity and transmission of the Courbage–Nekorkin–Vdovin (CNV) map-based neuron model with a bursting and tonic firing mode in response to external pulse inputs, in both temporal and rate coding schemes. We find that for both firing modes, the CNV model could capture the essential behavior of the stochastic Hodgkin–Huxley model in information transmission for the temporal coding scheme, with regard to the dependence of total entropy, noise entropy, information rate, and coding efficiency on the strength of the input signal. However, in tonic firing mode, it fails to replicate the input strength-dependent information rate in the rate coding scheme. Our results suggest that the CNV map-based neuron model could capture the essential behavior of information processing of typical conductance-based neuron models.
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Received: 18 September 2016
Published: 21 March 2017
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| PACS: |
87.19.lo
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(Information theory)
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87.19.ls
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(Encoding, decoding, and transformation)
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87.19.lc
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(Noise in the nervous system)
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87.19.ll
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(Models of single neurons and networks)
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| Fund: Supported by the National Natural Science Foundation of China under Grant Nos 11564034, 11105062 and 61562075, and the Fundamental Research Funds for the Central Universities under Grant Nos lzujbky-2015-119 and 31920130008. |
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