Book Chapters

  • Sompolinsky H. and White O.L., Theory of Large Recurrent Networks: from Spikes to Behavior, in Les Houches Lectures LXXX on Methods and models in neurophysics, Chow C., Gutkin B., Hansel D., Meunier C., and Dalibard J. (Editors), Chap. 8: 267-339, (Elsevier: London, 2005). ( pdf file)

  • Van Vreeswijk C. and Sompolinsky H., Irregular Activity in Large Networks of  Neurons. In Les Houches Lectures LXXX on Methods and models in neurophysics, Chow C., Gutkin B., Hansel D., Meunier C., and Dalibard J. (Editors), Chap. 9: 341-402, (Elsevier: London, 2005). ( pdf file)

  • Sompolinsky H. A Scientific Perspective on Human Choice, in Judaism, Science, and Moral Responsibility The Orthodox Forum, (Rowman & Littlefield Pubs,  2005), David Shatz and Yitzhak Berger (Editors). ( pdf file)

  • L.F. Abbott and Kanaka Rajan and Haim Sompolinsky, Interactions between Intrinsic and Stimulus Evoked Activity in Recurrent Neural Networks, in Neuronal Variability and Its Functional Significance (Dennis Glanzman and Mingzhou Ding, Eds. Oxford University Press, 2010)
     
  • Hansel D. and Sompolinsky H. Modeling Feature Selectivity in Local Cortical Circuits. in Methods in Neuronal Modeling: From Synapse to Networks. Koch C. and Segev I. Editors. MIT Press, Cambridge, MA. Chapter 13, 2nd Ed. (1998)
     
  • Sompolinsky H., Barkai N. and Seung H.S. On-Line Learning of Dichotomies: Algorithms and Learning Curves. in Neural Networks: The Statistical Mechanics Perspective. Oh J., Kwon C. and Cho S., editors. (World Scientific, Singapore, 1995)
     
  • Barkai N. and Sompolinsky H. Theory of Learning from Examples. International Joint Conference on Neural Networks. (IJCNN, Nagoya, 1993)
     
  • Sompolinsky H. Theoretical Issues in Learning from Examples. in Proceedings of the Third NEC Symposium on Computational Learning and Cognition. (SIAM 1993)
     
  • Kleinfeld D., Chiel H.J. and Sompolinsky H. Small Nervous Systems and Neural Network Models. in Non-Linear Dynamics and Neural Networks, Schuster H.G. and Singer W., editors. (VCH, Weinheim, 1991)
     
  • Sompolinsky H., Golomb D. and Kleinfeld D. Phase Coherence and Computation in a Neural Network of Coupled Oscillators. in Non-Linear Dynamics and Neural Networks, Schuster H.G and Singer W., editors. (VCH, Weinheim, 1991)
     
  • Kleinfeld D. and Sompolinsky H. Associative Network Models for Central Pattern Generators. in Methods in Neuronal Modeling: From Synapse to Networks, Koch C. and Segev I., editors., Ch. 7. (MIT Press, Cambridge, MA 1989)
    Sompolinsky H. The Theory of Neural Networks: The Hebb Rule and Beyond. Proceedings of Heidelberg Colloquium on Glassy Dynamics, 1986. (Springer-Verlag, 1987)
     
  • Sompolinsky H. and Zippelius A. A Study of Short-Range Spin Glasses. Proceedings of the Heidelberg Colloquium on Spin Glasses, June 1983. (Pringer-Verlag, 1984)