[1] | Eric R Kandel, James H Schwartz, and Thomas M Jessell. Principles of Neural Science, volume 4. 2000. [ bib | DOI | http ] |
[2] | Peter Dayan and L F Abbott. Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems. 2001. [ bib | DOI ] |
[3] | Mark F Bear, Barry W Connors, and Michael A Paradiso. Neuroscience: Exploring the brain (3rd ed.). 2007. [ bib | http ] |
[4] | Wulfram Gerstner and Werner M Kistler. Spiking Neuron Models: Single Neurons, Populations, Plasticity. 2002. [ bib | DOI ] |
[5] | F. Rieke, D. Warland, R. De Ruyter Van Steveninck, and W. Bialek. Spikes: Exploring the Neural Code, volume 20. 1997. [ bib ] |
[6] | Stanley Jacobson and Elliott M Marcus. Neuroanatomy for the neuroscientist. 2008. [ bib | DOI | www: ] |
[7] | Areles Molleman. Patch Clamping: An Introductory Guide to Patch Clamp Electrophysiology. 2003. 2003. [ bib | DOI | http ] |
[8] | U Windhorst and H Johansson. Modern Techniques in Neuroscience Research. 1999. [ bib | http ] |
[9] | Eugene M Izhikevich. Dynamical Systems in Neuroscience. 2007. [ bib | DOI | .pdf ] |
[10] | L F Abbott and S B Nelson. Synaptic plasticity: taming the beast. Nat. Neurosci., 3 Suppl:1178-1183, 2000. [ bib | DOI ] |
[11] | Ami Citri, Ami Citri, Robert C Malenka, and Robert C Malenka. Synaptic plasticity: multiple forms, functions, and mechanisms. Neuropsychopharmacology, 33(1):18-41, 2008. [ bib | DOI | http ] |
[12] | H K Khalil. Nonlinear Systems, Third Edition. 2002. [ bib | DOI | http ] |
[13] | Steven H. Strogatz. Nonlinear Dynamics and Chaos. In Book, pages 1-505. 1994. [ bib | DOI ] |
[14] | R Rojas. Neural networks: a systematic introduction. 1996. [ bib | DOI | http ] |
[15] | J Hertz, A Krogh, and R G Palmer. Introduction to the Theory of Neural Computation, volume 1. 1991. [ bib | http ] |
[16] | Satish Kumar. Neural networks: a classroom approach. Tata McGraw-Hill Education, 2004. [ bib ] |
[17] | Elad Schneidman, Susanne Still, Michael J. Berry, and William Bialek. Network information and connected correlations. Phys. Rev. Lett., 91:238701, Dec 2003. [ bib | DOI | http ] |
[18] | Bruno B Averbeck, Peter E Latham, and Alexandre Pouget. Neural correlations, population coding and computation. Nat. Rev. Neurosci., 7(5):358-366, 2006. [ bib | DOI ] |
[19] | A Borst and F E Theunissen. Information theory and neural coding. Nat. Neurosci., 2(11):947-957, 1999. [ bib | DOI ] |
[20] | S Panzeri, S R Schultz, A Treves, and E T Rolls. Correlations and the encoding of information in the nervous system. Proc. Biol. Sci., 266(1423):1001-1012, 1999. [ bib | DOI ] |
[21] | David J C Mackay. Information Theory , Inference , and Learning Algorithms. Learning, 22(3):348-349, 2003. [ bib | DOI | http ] |
[22] | Paul C Bressloff. Spatiotemporal dynamics of continuum neural fields. Journal of Physics A: Mathematical and Theoretical, 45(3):033001, 2011. [ bib | DOI ] |
[23] | L. E. Reichl. A Modern Course in Statistical Physics, 2nd Edition, 1999. [ bib | DOI ] |
[24] | Franz Schwabl. Statistische Mechanik. 2006. [ bib | DOI | http ] |
[25] | Wulfram Gerstner, Werner M Kistler, Richard Naud, and Liam Paninski. Neuronal Dynamics - From Single Neurons to Networks and Models of Cognition. Cambridge University Press, Cambridge, new. edition, 2014. [ bib ] |
[26] | G Bard Ermentrout and David H Terman. Mathematical Foundations of Neuroscience -. Springer Science & Business Media, Berlin Heidelberg, 2010. aufl. edition, 2010. [ bib ] |
[27] | Jeffry S. Isaacson and Massimo Scanziani. How inhibition shapes cortical activity. Neuron, 72(2):231-243, 2011. [ bib | DOI | http ] |
[28] | Michael Okun and Ilan Lampl. Instantaneous correlation of excitation and inhibition during ongoing and sensory-evoked activities. Nature neuroscience, 11(5):535-537, 2008. [ bib | DOI ] |
[29] | M N Shadlen and W T Newsome. The variable discharge of cortical neurons: implications for connectivity, computation, and information coding. The Journal of neuroscience : the official journal of the Society for Neuroscience, 18(10):3870-3896, 1998. [ bib ] |
[30] | C van Vreeswijk and H Sompolinsky. Chaotic balanced state in a model of cortical circuits. Neural computation, 10(6):1321-1371, 1998. [ bib | DOI ] |
[31] | C van Vreeswijk and H Sompolinsky. Chaos in neuronal networks with balanced excitatory and inhibitory activity. Science (New York, N.Y.), 274(5293):1724-1726, 1996. [ bib | DOI ] |
[32] | Barry A. Cipra. An Introduction to the Ising Model. [ bib ] |
[33] | Elad Schneidman, Michael J Berry, Ronen Segev, and William Bialek. Weak pairwise correlations imply strongly correlated network states in a neural population. Nature, 440(7087):1007-1012, 2006. [ bib | DOI | arXiv ] |
[34] | Yair Shemesh, Yehezkel Sztainberg, Oren Forkosh, Tamar Shlapobersky, Alon Chen, and Elad Schneidman. High-order social interactions in groups of mice. eLife, 2013(2):1-19, 2013. [ bib | DOI ] |
[35] | Aonan Tang, David Jackson, Jon Hobbs, Wei Chen, Jodi L Smith, Hema Patel, Anita Prieto, Dumitru Petrusca, Matthew I Grivich, Alexander Sher, Pawel Hottowy, Wladyslaw Dabrowski, Alan M Litke, and John M Beggs. A maximum entropy model applied to spatial and temporal correlations from cortical networks in vitro. The Journal of neuroscience : the official journal of the Society for Neuroscience, 28(2):505-518, 2008. [ bib | DOI ] |
[36] | Gasper Tkacik, Elad Schneidman, Michael J. Berry, and William Bialek. Spin glass models for a network of real neurons. (1):1-15, 2009. [ bib | arXiv | http ] |
[37] | David Harris and Sarah Harris. Digital Design and Computer Architecture -. Morgan Kaufmann Publishers, San Francisco, 2007. [ bib ] |
[38] | Christopher M Bishop. Pattern Recognition and Machine Learning, volume 4. 2006. [ bib | DOI | arXiv | .pdf ] |
[39] | Tom M Mitchell. Machine Learning, volume 1. 1997. [ bib | DOI | http ] |
[40] | Simon Haykin. Neural Networks and Learning Machines, volume 3. 2008. [ bib | http ] |
[41] | Scholarpedia Computational Neuroscience. [ bib | http ] |
[42] | Scholarpedia Computational Intelligence. [ bib | http ] |
[43] | Andrew Ng. Machine Learning. [ bib | http ] |
[44] | Dario Floreano and Robert J. Wood. Science, technology and the future of small autonomous drones. Nature, 521(7553):460-466, 2015. [ bib | DOI | http ] |
[45] | Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. Deep learning. Nature, 521(7553):436-444, 2015. [ bib | DOI | http ] |
[46] | Michael L. Littman. Reinforcement learning improves behaviour from evaluative feedback. Nature, 521(7553):445-451, 2015. [ bib | DOI | http ] |
[47] | Daniela Rus and Michael T. Tolley. Design, fabrication and control of soft robots. Nature, 521(7553):467-475, 2015. [ bib | DOI | http ] |
[48] | S Russel. Ethics of artificial intelligence. Nature, 2015. [ bib ] |
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