6. Destexhe, A., Contreras, D., <strong>Sejnowski</strong>, T. J. and Steriade, M., A model of spindlerhythmicity in the isolated thalamic reticular nucleus, Institute for Neural ComputationTechnical Report Series, INC-9308, (November 1993).7. Stensmo, M. and <strong>Sejnowski</strong>, T. J., A mixture model diagnosis system, Institute forNeural Computation Technical Report Series, INC-9401, (December, 1994).8. Bell, A. J., Mainen, Z. F., Tsodyks, M. and <strong>Sejnowski</strong>, T. J., 'Balancing' of conductancesmay explain irregular cortical spiking, Institute for Neural Computation TechnicalReport Series, INC-9502, (February, 1995).9. Goodhill, G. J., Finch, S., and <strong>Sejnowski</strong>, T. J., Quantifying neighbourhood preservationin topographic mappings, Institute for Neural Computation Technical Report Series,INC-9505, (November 1995).10. Ghahremani, D., Makeig, S., Jung, T-P, Bell, A. J., and <strong>Sejnowski</strong>, T. J., Independentcomponent analysis of simulated EEG using a three-shell spherical head model,Institute for Neural Computation Technical Report Series, INC-9601, (May 1996).11. Makeig, S., Jung, T-P. Ghahremani, D., and <strong>Sejnowski</strong>, T. J., Independent componentanalysis of simulated ERP data, Institute for Neural Computation Technical ReportSeries, INC-9606, (October 1996).Book Chapters:1. <strong>Sejnowski</strong>, T. J., Skeleton filters in the brain, in Parallel Models of Associative Memory,G. E. Hinton and J. A. Anderson (Eds.), Lawrence Erlbaum Associates, Hillsdale, NewJersey, 189-212 (1981).2. Hinton, G. E. and <strong>Sejnowski</strong>, T. J., Learning in Boltzmann machines, Cognitiva 85,Paris, 284-290 (June 4-7 1985).3. Hinton, G. E. and <strong>Sejnowski</strong>, T. J., Learning and relearning in Boltzmann machines. In:McClelland, J. and Rumelhart, D. (Eds.) Explorations in the Microstructure of Cognition1: Foundations, Cambridge: MIT Press, 282-317 (1986).4. <strong>Sejnowski</strong>, T. J., Open questions about computation in cerebral cortex. In: McClelland,J. and Rumelhart, D. (Eds.) Explorations in the Microstructure of Cognition 2:Applications, Cambridge: MIT Press, 372-389 (1986).5. <strong>Sejnowski</strong>, T. J., Higher-order Boltzmann machines. In: Neural Networks forComputing, J. Denker (Ed). New York: American Institute of Physics, 398-403 (1986).6. Qian, N. and <strong>Sejnowski</strong>, T. J., Electro-diffusion model of electrical conduction inneuronal processes. In: C. D. Woody, J. L. McGaugh, and D. L. Alkon, CellularMechanisms of Conditioning and Behavioral Plasticity, London: Pergammon, 237-244(1988).7. <strong>Sejnowski</strong>, T. J. and Hinton, G. E., Separating figure from ground with a Boltzmannmachine. In: Arbib, M. and Hanson, A. R. (Eds.) Vision, Brain and CooperativeComputation, Cambridge: MIT Press, 703-724 (1987).
8. Lehky, S. and <strong>Sejnowski</strong>, T. J., Neural network models of visual processing, Societyfor Neuroscience Short Course on Computational Neuroscience, 102-123 (1987).9. <strong>Sejnowski</strong>, T. J. and Rosenberg, C. R., Learning and Representation in ConnectionistModels. In: M. S. Gazzaniga (Ed). Perspectives in Memory Research, Cambridge: MITPress, 135-178 (1988).10. Churchland, P. S. and <strong>Sejnowski</strong>, T. J., Neural representations and neuralcomputation, In: L. Nadel (Ed). Neural Connections and Mental Computation,Cambridge: MIT Press, 15-48 (1988).11. Churchland, P. S., Koch, C. and <strong>Sejnowski</strong>, T. J., What is computational neuroscience?In: E. Schwartz (Ed). Computational Neuroscience, Cambridge: MIT Press, 46-55(1988).12. <strong>Sejnowski</strong>, T. J., Neural network learning algorithms. In: R. Eckmiller and C. von derMalsburg (Eds.) Neural Computers, Berlin: Springer-Verlag, 291-300 (1988).13. Lehky, S. R. and <strong>Sejnowski</strong>, T. J., Neural network model for the cortical representationof surface curvature from images of shaded surfaces. In: J. Lund (Ed). SensoryProcessing in the Mammalian Brain: Neural Substrates and Experimental Strategies,Oxford: Oxford University Press, (1988).14. Qian, N. and <strong>Sejnowski</strong>, T. J., Learning to predict the secondary structure of globularproteins. In: Y. C. Lee (Ed). Evolution, Learning and Cognition, Singapore: WorldScientific, 257-276 (1988).15. <strong>Sejnowski</strong>, T. J. and Tesauro, G., The Hebb rule for synaptic plasticity: Algorithms andimplementations. In: J. Byrne and W. O. Berry (Eds.) Neural Models of Plasticity,New York: Academic Press, 94-103 (1988).16. <strong>Sejnowski</strong>, T. J., Koch, C. and Churchland, P. S., Computational neuroscience. In: G.Adelman, (Ed)., Encyclopedia of Neuroscience: Neuroscience Year, Boston: Birkhäuser,41-44 (1989).17. <strong>Sejnowski</strong>, T. J. and Tesauro, G., Building network learning algorithms from Hebbiansynapses. In: J. L. McGaugh, N. M. Weinberger and G. Lynch (Eds.) BrainOrganization and Memory: Cells, Systems and Circuits, New York: Oxford UniversityPress, 338-355 (1989).18. <strong>Sejnowski</strong>, T. J. and Stanton, P. K., Covariance storage in the hippocampus. In: S. F.Zornetzer, J. L. Davis and C. Lau (Eds.) An Introduction to Neural and ElectronicNetworks, New York: Academic Press, 365-377 (1989).19. <strong>Sejnowski</strong>, T. J., The Computer and the Brain revisited. In: J. R. Brink and C. Roland(Eds.) Computer and the Brain: Perspectives on Human and Artificial Intelligence,Amsterdam: Elsevier (1989).20. <strong>Sejnowski</strong>, T. J., Chattarji, S. and Stanton, P. K., Induction of synaptic plasticity byHebbian covariance in the hippocampus. In: R. M. Durbin, R. C. Miall and G. J.Mitchison (Eds.) The Computing Neuron, New York: Addison-Wesley, 105-124 (1989).
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