Center of Excellence for Learning in Education, Science and Technology A National Science Foundation Science of Learning Center

Books and Book Chapters 2011

  1. Carpenter, G.A. and Grossberg, S. (2011). Adaptive resonance theory. In Sammet and G. Webb (Eds.), Encyclopedia of machine learning, Part 2. Berlin: Springer, pp.22-35.
  2. Cutsuridis, V., Hussain, G., and Taylor, J.G. (2011). In Perception-action cycle: Models, architectures and hardware. Springer.
  3. Duncan, J. and Miller, E.K. (2011). Adaptive neural coding in frontal and parietal cortex. In Principles of frontal lobe function: Second edition.
  4. Eichenbaum, H. (2011). The paradoxical hippocampus: When forgetting helps learning. In N. Kapur, A. Pascual-Leone, and V. Ramachandran (Eds.), The paradoxical brain. Cambridge University Press, pp.379-396.
  5. Eichenbaum, H. and Fortin, N. (2011). The neurobiology of memory-based predictions. In M. Bar (Ed.), Predictions in the brain: Using our past to generate a future. New York: Oxford University Press, pp.271-282.
  6. Eichenbaum, H., Sauvage, M., Fortin, N., Robitsek, J.R., and Komorowski, R. (2011). Comparative analysis of episodic memory: Cognitive mechanisms and neural substrates. In E. Wasserman and T. Zentall (Eds.), Comparative cognition: Experimental explorations of animal intelligence, Volume II. Oxford University Press.
  7. Engel, A.K., Friston, K., Kelso, J.A.S., Koning, P., Kovacs, I., MacDonald, A., Miller, E.K., Phillips, W.A., Silverstein, S.M., Tallon-Baudry, C., Triesh, J. Uhlhaas, P. (2011). Coordination in behavior and cognition. In Dynamic coordination in the brain. MIT Press, pp.267-299.
  8. Grossberg, S. (2011). Visual motion perception. In V.S. Ramachandran (Ed.), Encyclopedia of human behavior (second edition). Oxford: Elsevier.
  9. Grossberg, S. (2011). Cortical and subcortical predictive dynamics and learning during perception, cognition, emotion, and action. In M. Bar (Ed.), Predictions in the brain: Using our past to generate a future. New York: Oxford University Press, pp.208-230.
  10. Grossberg, S. (2011). Foundations and new paradigms of brain computing: Past, present, and future. In R. Pirrone and F. Sorbello (Eds.), AI*IA 2011: Artificial intelligence around man and beyond. Berlin: Springer, pp.1-7.
  11. Léveillé J., Ames H., Chandler B., Gorchetchnikov A., Mingolla E., Patrick S., and Versace M. (2011). Learning in a distributed software architecture. In Lecture notes for computer sciences, social informatics, and telecommunications engineering (LNICST).
  12. Miller, E.K. and Buschman, T.J. (2011). Top-down control of attention by rhythmic neural computations. In Posner, M.I. (Ed.), Cognitive neuroscience of attention. New York: Guilford Press.
  13. Raudies, F. and Neumann, H. (2011). Modeling binocular and motion transparency processing by local center-surround interactions. In Pomplun, M. and Suzuki, J. (Ed.), Developing and applying biologically-inspired vision systems: Interdisciplinary concepts. IGI Global (in press).
  14. Versace, M. (2011). Open-source computer software for computational neuroscience: Bridging the gap between models and behavior. In T.S. Clary (Ed.), Horizons in computer science research. Nova Science Publishers, Inc..
  15. Versace, M. (2011). Silicon brains. In pp.