Mean-field analysis of neuronal spike dynamics

References

• Marr D. Simple memory: a theory for archicortex. Phil. Trans. R. Soc. B 1971; 262: 24–81
   Web of Science ®Google Scholar
• Kohonen T. Associative Memory. Springer, Berlin 1977
   Google Scholar
• Hopfield J J. Neural networks and physical systems with emergent collective computational abilities. Proc. Natl. Acad. Sci. USA 1982; 79: 2554–8
   PubMed Web of Science ®Google Scholar
• Amit D J. Modeling Brain Function. Cambridge University Press, Cambridge 1989
   Google Scholar
• Sompolinsky H, Golomb D, Kleinfeld D. Global processing of visual stimuli in a neural network of coupled oscillators. Proc. Natl. Acad. Sci. USA 1990; 87: 7200–4
   PubMed Web of Science ®Google Scholar
• Sompolinsky H, Golomb D, Kleinfeld D. Cooperative dynamics in visual processing. Phys. Rev. A 1991; 43: 6990–7011
   PubMed Web of Science ®Google Scholar
• von der Malsburg C, Schneider W. A neural cocktail-party processor. Biol. Cybern. 1986; 54: 29–40
   PubMed Web of Science ®Google Scholar
• Gray C M, Konig P, Engel A K, Singer W. Oscillatory responses in cat visual cortex exhibit intercolumnar synchronization which reflects global stimulus properties. Nature 1989; 338: 334–7
   PubMed Web of Science ®Google Scholar
• Eckhorn R, Bauer R, Jordan W, Brosch M, Kruse W, Munk M, Reitbaeck H J. Coherent oscillations-a mechanism of feature linking in the visual cortex; multiple electrode and correlation analysis in the cat. Biol. Cybern. 1988; 60: 121–30
   PubMed Web of Science ®Google Scholar
• Tovee M J, Rolls E T, Treves A, Bellis R P. Information encoding and the responses of single neurons in the primate temporal visual cortex. J. Neurophysiol. 1993, in press
   PubMed Web of Science ®Google Scholar
• Tuckwell H J. Introduction to Theoretical Neurobiology. Cambridge University Press, Cambridge 1988
   Google Scholar
• McGregor R J. Neural and Brain Modelling. Academic, New York 1987
   Google Scholar
• Mahowald M, Douglas R. A silicon neuron. Nature 1991; 354: 515–8
   PubMed Web of Science ®Google Scholar
• Horner H, Bormann D, Frick M, Kinzelbach H, Schmidt A. Transients and basins of attractions in neural network models. Z. Phys. B 1989; 76: 381–98
   Google Scholar
• Mirollo R E, Strogatz S H. Synchronization of pulse-coupled biological oscillators. SIAM J. Appl. Math. 1990; 50: 1645–62
   Web of Science ®Google Scholar
• Kuramoto Y. Collective synchronization of pulse coupled oscillators and excitable units. Physica 1991; 50D: 15–30
   Google Scholar
• Bush P C, Douglas R J. Synchronization of bursting action potential discharge in a model of neocortical neurons. Neural Comput. 1991; 3: 19–30
   PubMedGoogle Scholar
• Abbott L F, Van Vreeswijk C. Asynchronous states in networks of pulse-coupled oscillators. Brandeis University. 1992, Preprint
   Google Scholar
• Treves A, Rolls E T, Tovee M. On the time required for recurrent processing in the bra. Oxford University. 1992, Preprint
   Google Scholar
• Brown D A, Gähwiler B H, Griffith W H, Halliwell J V. Membrane currents in hippocampal neurons. Prog. Brain Res. 1990; 83: 141–60
   PubMed Web of Science ®Google Scholar
• Jack J J B, Noble D, Tsien R W. Electric Current Flow in Excitable Cells. Clarendon, Oxford 1985
   Google Scholar
• McCormick D A, Connors B W, Lighthall J W, Prince D A. Comparative electrophysiology of pyramidal and sparsely spiny stellate neurons of the neocortex. J. Neurophysiol. 1985; 54: 782–806
   PubMed Web of Science ®Google Scholar
• Connors B W, Malenka R C, Silva L R. Two inhibitory postsynaptic potentials, and GABAA and GABAB receptor-mediated responses in neocortex of rat and car. J. Physiol. 1985; 406: 443–68
   Google Scholar
• Mason A, Larkman A. Correlations between morphology and electrophysiology of pyramidal neurons in slices of rat visual cortex. II Electrophysiology. J. Neurosci. 1990; 10: 1415
   PubMed Web of Science ®Google Scholar
• Frolov A A, Medvedev A V. Substantiation of the ‘point approximation’ for describing the total electrical activity of the brain with the use of a simulation model. Biophysics 1986; 31: 332–6
   Google Scholar
• Amit D J, Tsodyks M V. Quantitative study of attractor neural network retrieving at low spike rates: I. Substrate-spikes, rates and neuronal gain. Network 1991; 2: 259–73
   Web of Science ®Google Scholar
• Wilson H R, Cowan J D. Excitatory and inhibitory interactions in localized populations of model neurons. Biophys. J. 1974; 12: 1–24
   Web of Science ®Google Scholar
• Abbott L F. Realistic synaptic inputs for model neural networks. Network 1991; 2: 245–58
   Web of Science ®Google Scholar
• Van Vreeswijk C, Abbott L F. Self-sustained firing in populations of integrate and fire neurons. Brandeis University. 1991, Preprint
   Google Scholar
• Treves A, Rolls E T. What determines the capacity of autoassociative memories in the brain?. Network 1991; 2: 371–97
   Web of Science ®Google Scholar
• Treves A. Graded-response neurons and information encodings in autoassociative memories. Phys. Rev. A 1990; 42: 2418–30
   PubMed Web of Science ®Google Scholar
• Hansel D, Sompolinsky H. Synchronization and computation in a chaotic neural network. Phys. Rev. Lett. 1992; 68: 718–21
   PubMed Web of Science ®Google Scholar