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Books on the topic 'Neurons Models'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Gerstner, Wulfram. Spiking neuron models: Single neurons, populations, plasticity. Cambridge, U.K: Cambridge University Press, 2002.

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2

An introduction to the mathematics of neurons. Cambridge: Cambridge University Press, 1986.

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3

Borkowski, Lech S. Nonlinear dynamics of Hodgkin-Huxley neurons. Poznań: Wydawn. Nauk. UAM, 2010.

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4

Bielecki, Andrzej. Models of Neurons and Perceptrons: Selected Problems and Challenges. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-90140-4.

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5

Mira, José, and Alberto Prieto, eds. Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45720-8.

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6

John, Milton. Dynamics of small neural populations. Providence, R.I: American Mathematical Society, 1996.

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7

John, Milton. Dynamics of small neural populations. Providence, R.I: American Mathematical Society, 1996.

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8

Friesen, W. Otto. NeuroDynamix: Computer models for neurophysiology. New York: Oxford University Press, 1994.

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9

1973-, Friesen Jonathon A., ed. NeuroDynamix: Computer-based neuronal models for neurophysiology. Oxford: Oxford University Press, 1994.

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10

An introduction to the mathematics of neurons: Modeling in the frequency domain. 2nd ed. Cambridge, U.K: Cambridge University Press, 1997.

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11

Pacut, Andrzej. Stochastic modeling at diverse scales: From Poisson to network neurons. Warszawa: Oficyna Wydawnicza Politechniki Warszawskiej, 2000.

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12

Richard, Durbin, Miall Christopher, Mitchison Graeme, and King's College (University of Cambridge). Research Centre., eds. The Computing neuron. Wokingham, England: Addison-Wesley Pub. Co., 1989.

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13

D, Nozdrachev A., ed. Informat͡s︡ionnye kharakteristiki sistem neĭronov. Leningrad: "Nauka," Leningradskoe otd-nie, 1990.

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14

Tuckwell, Henry C. Introduction to theoretical neurobiology. Cambridge [Cambridgeshire]: Cambridge University Press, 1988.

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15

Idan, Segev, Rinzel John, and Shepherd Gordon M. 1933-, eds. The theoretical foundation of dendritic function: Selected papers of Wilfrid Rall with commentaries. Cambridge, Mass: MIT Press, 1995.

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16

Korogod, Serge. Electrical dynamics of the dendritic space. Cambridge: Cambridge University Press, 2009.

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17

Zmysłowski, Wojciech. Algorytmy formowania sygnału sterującego w sieciach motoneuronów alfa, komórek Renshawa, interneuronów lalN i neuronów C₃-C₄ PN. Warszawa: Polska Akademia Nauk, Instytut Biocybernetyki i Inżynierii Biomedycznej, 1989.

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18

Dynamical systems in neuroscience: The geometry of excitability and bursting. Cambridge, Mass: MIT Press, 2007.

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19

Spikes, decisions, and actions: The dynamical foundations of neuroscience. Oxford: Oxford University Press, 1999.

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20

N, Reeke George, ed. Modeling in the neurosciences: From biological systems to neuromimetic robotics. 2nd ed. Boca Raton, Fla: Taylor & Francis, 2005.

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21

Greenwood, Priscilla E., and Lawrence M. Ward. Stochastic Neuron Models. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-26911-5.

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22

Stress, the aging brain, and the mechanisms of neuron death. Cambridge, Mass: MIT Press, 1992.

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23

Brette, Romain, and Alain Destexhe. Handbook of neural activity measurement. Cambridge: Cambridge University Press, 2012.

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24

International School of Biophysics (1997 Casamicciola Terme, Italy). Chaos and noise in biology and medicine: Proceedings of the International School of Biophysics, Casamicciola, Napoli, Italy, 19-24 May 1997. Singapore: World Scientific, 1998.

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25

Trappenberg, Thomas P. Fundamentals of computational neuroscience. 2nd ed. Oxford: Oxford University Press, 2010.

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26

Fundamentals of computational neuroscience. 2nd ed. Oxford: Oxford University Press, 2010.

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27

The correlative brain: Theory and experiment in neural interaction. Berlin: Springer-Verlag, 1990.

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28

Trappenberg, Thomas P. Fundamentals of computational neuroscience. 2nd ed. Oxford: Oxford University Press, 2010.

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29

Suzanne, Tyc-Dumont, ed. Le neurone computationnel: Histoire d'un siècle de recherches. Paris: CNRS, 2005.

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30

Żochowski, Michał. Synchrony in biological and physical systems: An experimental and theoretical study. Warszawa: Polska Akademia Nauk, Instytut Biocybernetyki i Inżynierii Biomedycznej, 2000.

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31

Kochendörfer, Günter. Neuronale Modelle des Sprachverstehens. Freiburg (Breisgau): HochschulVerlag, 1997.

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32

1951-, Miles Richard, ed. Neuronal networks of the hippocampus. Cambridge: Cambridge University Press, 1991.

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33

Gerstner, Wulfram, and Werner M. Kistler. Spiking Neuron Models: Single Neurons, Populations, Plasticity. Cambridge University Press, 2012.

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34

Gerstner, Wulfram, and Werner M. Kistler. Spiking Neuron Models: Single Neurons, Populations, Plasticity. Cambridge University Press, 2002.

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35

Gerstner, Wulfram, Werner M. Kistler, Richard Naud, and Liam Paninski. Neuronal Dynamics: From Single Neurons to Networks and Models of Cognition. Cambridge University Press, 2014.

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36

Gerstner, Wulfram, Werner M. Kistler, Richard Naud, and Liam Paninski. Neuronal Dynamics: From Single Neurons to Networks and Models of Cognition. Cambridge University Press, 2014.

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37

Neuronal Dynamics: From Single Neurons to Networks and Models of Cognition. Cambridge University Press, 2014.

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38

Sampath, Gopalan, and S. K. Srinivasan. Stochastic Models for Spike Trains of Single Neurons. Springer London, Limited, 2013.

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39

Greenwood, Priscilla E., and Lawrence M. Ward. Stochastic Neuron Models. Springer London, Limited, 2016.

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40

Stochastic Neuron Models. Springer, 2016.

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41

Cauchi, Ruben. Drosophila Melanogaster Models of Motor Neuron Disease. Nova Science Publishers, Incorporated, 2013.

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42

Bielecki, Andrzej. Models of Neurons and Perceptrons: Selected Problems and Challenges. Springer, 2019.

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43

Bielecki, Andrzej. Models of Neurons and Perceptrons: Selected Problems and Challenges. Springer, 2018.

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44

Gerstner, Wulfram, and Werner M. Kistler. Spiking Neuron Models. Cambridge University Press, 2002.

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45

Spiking Neuron Models. Cambridge University Press, 2002.

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46

Gerstner, Wulfram, and Werner M. Kistler. Spiking Neuron Models. Cambridge University Press, 2002.

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47

An Introduction to the Mathematics of Neurons. Cambridge University Press, 1986.

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48

Saraga, Fernanda. Use of compartmental models to predict physiological properties of hippocampal inhibitory neurons. 2006.

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49

Rigatos, Gerasimos G. Advanced Models of Neural Networks: Nonlinear Dynamics and Stochasticity in Biological Neurons. Springer, 2014.

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50

Rigatos, Gerasimos G. Advanced Models of Neural Networks: Nonlinear Dynamics and Stochasticity in Biological Neurons. Springer, 2016.

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