Koulakov AA (2001) Properties of synaptic transmission and the global stability of working memory states, Network.47, 47-74.
Koulakov_Network_2001.pdf
Koulakov AA and Chklovskii DB (2001). Orientation preference patterns in mammalian visual cortex: A wire length minimization approach. Neuron 29: 519–527.
Koulakov_Chklovskii_Neuron_2001.pdf
Kretzberg J, Sejnowski TJ, Warzecha A.-K and Egelhaaf M (2003).Variability of Postsynaptic Responses Depends Non-Linearly on the Number of Synaptic Inputs, Neurocomputing, (52-54) 313-320.
Kretzberg_etal_Neurocomp_2003.pdf
Kretzberg J, Sejnowski TJ, Warzecha A.-K and Egelhaaf M (2002). Variability of Postsynaptic Responses to Spike-Mediated and Graded Synaptic Input, Society for Neuroscience Abstracts, 28.
Kretzberg_etal_SFNabs_2002.pdf
Lee T-W, Wachtler T and Sejnowski TJ (1999). The spectral independent components of natural scenes. Institute for Neural Computation at UCSD Technical Report Series INC-9901, September 1999.
Lee_Wachtler_Sejnowski_TechReport_1999.pdf
Lee T-W, Wachtler T and Sejnowski TJ (2001). Color opponency constitutes a sparse representation for the chromatic structure of natural scenes. Leen, T.K., Dietterich, T.G. and Tresp, V.; (Eds.), Advances in Neural Information Processing Systems, 13, MIT Press, Cambridge, MA.866-872.
Lee_Wachtler_Sejnwoski_NIPS_2001.pdf
Lee T-W, Wachtler T and Sejnowski TJ (2002). Color opponency is an efficient representation of spectral properties in natural scenes. Vision Res., 42, 2095-2103.
Lee_Wachtler_Sejnwoski_VisionRes_2002.pdf
Lee T-W, Wachtler T and Sejnowski TJ (2000). The spectral independent components of natural scenes. Lecture Notes in Computer Science, 1811, 527-534.
Lee_Wachtler_Sejnwoski_LNCS_2000.pdf
Lewicki, MS and Sejnowski TJ (1997). Bayesian Unsupervised Learning of Higher Order Structure. Mozer, M.; Jordan, M. I.; Petsche, T.; (Eds.), Advances in Neural Information Processing Systems, 9, MIT Press, Cambridge, MA. 529-535.
Lewicki_Sejnowski_AdavNeuralInfoProcSys_1997.pdf
Lewicki MS and Sejnowski TJ (2000). Learning overcomplete representations. Neural Comput., 12, 337-365.
Lewicki_Sejnowski_NeuralComp_2000.pdf
Maass W and Zador A (1998). Computing with dynamic synapses. NIPS 10.
Maass_Zador_NIPS_1998.pdf
Maass W and Zador A (1999). Dynamic stochastic synapses as computational elements. Neural Computation, 11:903-917.
Maass_Zador_NeuralComp_1999.pdf
Mainen Z, Carnevale N, Zador A, Claiborne B and Brown T (1996). Electrotonic structure of hippocampal CA1 pyramidal neurons based on three-dimensional reconstructions. J. Neurophysiol. 76:1904-1923.
Mainen_etal_JNeurophysiol_1996.pdf
Marnellos G, Deblandre G, Mjolsness E and Kintner C (2000). Delta-Notch lateral inhibitory patterning in the emergence of ciliated cells in Xenopus: experimental observations and a gene-network model. In: Proceedings of the Pacific Symposium on Biocomputing (R. Altman, A.K. Dunker, L. Hunter, K. Lauderdale and T.E. Klein, eds.), 5:329-340.
Marnellos_etal_PacificSympBiocomp_2000.pdf
Marnellos G and Mjolsness E (1996). Comparison of simulated annealing with genetic algorithms in biological problems that use recurrent neural nets. In: Proceedings of the 18th Annual Conference of the Cognitive Science Society. G.W.Cottrell, ed., Lawrence Erlbaum Associates.
Marnellos_Mjolsness_Proc18thAnnualConfCogSciSoc_1996.pdf
Marnellos G and Mjolsness E (1997). A computational model of early neurogenesis in Drosophila. Technical report CS97-523, Department of Computer Science and Engineering, UCSD.
Marnellos_Mjosness_TechReport_Computational_1997.pdf
Marnellos G and Mjolsness E (1997). Optimization in biological models that use recurrent neural nets. Technical report CS97-524, Department of Computer Science and Engineering, UCSD.
Marnellos_Mjolsness_TechReport_Optimization_1997.pdf
Marnellos G and Mjolsness E (1998). A gene network approach to modeling early neurogenesis in drosophila. In: Proceedings of the Pacific Symposium on Biocomputing (R. Altman, A.K. Dunker, L. Hunter and T.E. Klein, eds.), 3:30-41.
Marnellos_Mjolsness_ProcPacificSympBiocomp_1998.pdf
Marnellos G and Mjolsness E (1998). A gene network model of resource allocation to growth and reproduction. In: Artificial Life VI, Proceedings of the Sixth International Conference on Artificial Life (C. Adami, R.K. Belew, H. Kitano and C.E. Taylor, eds.), MIT Press, 433-437.
Marnellos_Mjolsness_ArtificialLife_1998.pdf
Marnellos G and Mjolsness E (1998). Probing the dynamics of cell differentiation in a model of Drosophila neurogenesis. In: Artificial Life VI, Proceedings of the Sixth International Conference on Artificial Life (C. Adami, R.K. Belew, H. Kitano and C.E. Taylor, eds.), MIT Press, 161-170.
Marnellos_Mjolsness_ArtificialLifConf_1998.pdf