Molter C, Salihoglu U, Bersini H. (2007). The road to chaos by time-asymmetric Hebbian learning in recurrent neural networks. Neural computation. 19 [PubMed]

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References and models cited by this paper

Amari S. (1972). Learning pattern sequences by self-organizing nets of threshold elements. IEEE Transactions on computers. 21

Amari S, Maginu K. (1988). Statistical neurodynamics of associative memory Neural Netw. 1

Amari SI. (1977). Neural theory of association and concept-formation. Biological cybernetics. 26 [PubMed]

Amit DJ. (1989). Modeling Brain Function: the World of Attractor Neural Networks.

Amit DJ. (1995). The Hebbian paradigm reintegrated: Local reverberations as internal representation Behav Brain Sci. 18

Amit DJ, Fusi S. (1994). Learning in neural networks with material synapses Neural Comput. 6

Amit DJ, Mongillo G. (2003). Spike-driven synaptic dynamics generating working memory states. Neural computation. 15 [PubMed]

Babloyantz A, Lourenço C. (1994). Computation with chaos: a paradigm for cortical activity. Proceedings of the National Academy of Sciences of the United States of America. 91 [PubMed]

Bersini H. (1998). The frustrated and compositional nature of chaos in small Hopfield networks. Neural networks : the official journal of the International Neural Network Society. 11 [PubMed]

Bersini H, Sener P. (2002). The connections between the frustrated chaos and the intermittency chaos in small Hopfield networks. Neural networks : the official journal of the International Neural Network Society. 15 [PubMed]

Bi G, Poo M. (1999). Distributed synaptic modification in neural networks induced by patterned stimulation. Nature. 401 [PubMed]

Bliss TV, Lomo T. (1973). Long-lasting potentiation of synaptic transmission in the dentate area of the anaesthetized rabbit following stimulation of the perforant path. The Journal of physiology. 232 [PubMed]

Brunel N, Amit D. (1994). Learning internal representations in an attractor neural network with analogue neurons Network. 6

Brunel N, Carusi F, Fusi S. (1998). Slow stochastic Hebbian learning of classes of stimuli in a recurrent neural network. Network (Bristol, England). 9 [PubMed]

Dauce E, Guillot A. (2002). Approche dynamique de la cognition artificielle.

Derrida B, Gardner E. (1989). Three unfinished works on the optimal storage capacity of networks J Physics A Math Gen. 22

Erdi P. (1996). The brain as a hermeneutic device. Bio Systems. 38 [PubMed]

Forrest B, Wallace D. (1995). Models of neural networks (2nd ed).

Franosch JM, Lingenheil M, van Hemmen JL. (2005). How a frog can learn what is where in the dark. Physical review letters. 95 [PubMed]

Freeman W. (2002). Biocomputing.

Freeman WJ, Skarda CH. (1987). How brains make chaos in order to make sense of the world Behav Brain Sci. 10

Fusi S. (2002). Hebbian spike-driven synaptic plasticity for learning patterns of mean firing rates. Biological cybernetics. 87 [PubMed]

Gardner E. (1987). Maximum storage capacity in neural networks Europhys Lett. 4

Grossberg S. (1992). Neural networks and natural intelligence.

Gutfreund Y, Zheng W, Knudsen EI. (2002). Gated visual input to the central auditory system. Science (New York, N.Y.). 297 [PubMed]

Hansel D, Sompolinsky H. (1996). Chaos and synchrony in a model of a hypercolumn in visual cortex. Journal of computational neuroscience. 3 [PubMed]

Hebb DO. (1949). The Organization Of Behavior.

Hopfield JJ. (1982). Neural networks and physical systems with emergent collective computational abilities. Proceedings of the National Academy of Sciences of the United States of America. 79 [PubMed]

Ikeda K, Matsumoto K, Otsuka K. (1989). Maxwell-Bloch turbulence Progress of Theoretical Physics. 99

Kaneko K. (1992). Pattern dynamics in spatiotemporal chaos Physica D. 34

Kaneko K, Tsuda I. (2003). Chaotic itinerancy. Chaos. 13

Kenet T, Bibitchkov D, Tsodyks M, Grinvald A, Arieli A. (2003). Spontaneously emerging cortical representations of visual attributes. Nature. 425 [PubMed]

Kohonen T. (1982). Self-organized formation of topology correct feature maps Biol Cybern. 43

Kuhn R, van_Hemmen J. (1995). Models of neural networks (2nd ed).

Levy WB, Steward O. (1983). Temporal contiguity requirements for long-term associative potentiation/depression in the hippocampus. Neuroscience. 8 [PubMed]

Llineas R. (2001). I of the vortex: From neurons to self.

Molter C, Bersini H. (2003). How chaos in small Hopfield networks makes sense of the world Proc Intl Joint Conf Neural Networks.

Molter C, Salihoglu U, Bersini H. (2005). Introduction of an Hebbian unsupervised learning algorithm to boost the encoding capacity of Hopfield networks Proc Intl Joint Conf Neural Networks.

Molter C, Salihoglu U, Bersini H. (2005). Learning cycles brings chaos in continuous Hopfield networks Proc Intl Joint Conf Neural Networks.

Nicolis JS, Tsuda I. (1985). Chaotic dynamics of information processing: the "magic number seven plus-minus two" revisited. Bulletin of mathematical biology. 47 [PubMed]

Omlin CW. (2001). Understanding and explaining DRN behaviour A field guide to dynamical recurrent networks.

Pasemann F. (2002). Complex dynamics and the structure of small neural networks. Network (Bristol, England). 13 [PubMed]

Piaget J. (1963). The psychology of intelligence.

Pomeau Y, Manneville P. (1980). Intermittent transition to turbulence in dissipative dynamical systems Comm Math Phys. 74

Rodriguez E et al. (1999). Perception's shadow: long-distance synchronization of human brain activity. Nature. 397 [PubMed]

Rossler OE. (1983). The chaotic hierarchy Zeitschrift Fur Naturforschug. 38a

Ruelle D, Eckmann J. (1985). Ergodic theory of chaos and strange attractors Rev Mod Phys. 57

Samuelides M, Quoy M, Dauce E, Doyon B, Cessac B. (1998). Self-organization and dynamics reduction in recurrent networks: stimulus presentation and learning. Neural Netw. 11

Schulten K, Domany E, van Hemmen JK. (1994). Models of neural networks II..

Sejnowski TJ. (1977). Storing covariance with nonlinearly interacting neurons. Journal of mathematical biology. 4 [PubMed]

Sompolinsky H, Amit DJ, Gutfreund H. (1987). Statistical mechanics of neural networks near saturation Ann Phys. 173

Sompolinsky H, Crisanti A, Sommers HJ. (1988). Chaos in random neural networks. Physical review letters. 61 [PubMed]

Sprott JC, Albers DJ, Dechert WD. (1998). Routes to chaos in neural networks with random weights Int J Bifurc Chaos. 8

Tsuda I. (1992). Dynamic link of memory-chaotic memory map in nonequilibrium neural networks Neural Netw. 5

Tsuda I. (2001). Toward an interpretation of dynamic neural activity in terms of chaotic dynamical systems. The Behavioral and brain sciences. 24 [PubMed]

Varela F, Rosch E, Thompson E. (1991). The embodied mind: Cognitive science and human experience.

Wolf A, Swift J, Swinney H, Vastano J. (1984). Determining Lyapunov exponents from a time series Physica D. 16

van Vreeswijk C, Sompolinsky H. (1996). Chaos in neuronal networks with balanced excitatory and inhibitory activity. Science (New York, N.Y.). 274 [PubMed]

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