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Intercellular Communication

  • John Rinzel
Chapter
Part of the Interdisciplinary Applied Mathematics book series (IAM, volume 20)

Abstract

Orchestrating the activity of cell populations for physiological functioning of the brain, organs, and musculature depends on transmission of signals, learning and memory devices, and feedback control systems. By what biophysical mechanisms do cells communicate in order to coordinate their activity as local ensembles, as multimodal circuits, and across system levels? Here we only scratch the surface of this fascinating topic. We will focus on electrically active cells; for this, you can have in mind, for example, cardiac cells, many types of secretory cells, and neurons.

Keywords

Synaptic Input Intercellular Communication Tuning Curve Excitatory Input Electrical Coupling 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Suggestions for Further Reading

  1. •.
    Spikes, Fred Rieke, David Warland, Rob de Ruyter van Steveninck, and William Bialek. This influential book treats neuronal communication from a highly information-theoretic point of view (Rieke et al. 1997).Google Scholar
  2. •.
    Neural networks as spatio-temporal pattern-forming systems, Bard Ermentrout. This paper reviews pattern formation in neural networks, including the continuous networks discussed in this chapter (Ermentrout 1998).Google Scholar
  3. •.
    Mathematical Physiology, James Keener and James Sneyd. Keener and Sneyd treat some of the cellular level topics presented in this chapter, as well as many other topics in systems level physiology, from a more analytic perspective as opposed to the computational focus presented here (Keener and Sneyd 1998).Google Scholar
  4. •.
    Methods in Neuronal Modeling, Christof Koch and Idan Segev, editors. This is a compilation of chapters from various authors on a wide variety of topics related to neuronal modeling, both at the cell and at the network level (Koch and Segev 1998).Google Scholar
  5. •.
    Foundations of Cellular Neurophysiology, Daniel Johnston and Samuel Wu. Covers in more depth topics such as transmitter release, plasticity, elementary networks and extracellular electrical behavior (Johnston and Wu 1995).Google Scholar
  6. •.
    Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems, Peter Dayan and Larry Abbott. This book addresses neural coding issues with several different types of models (Dayan and Abbott 2001).Google Scholar
  7. •.
    Biophysics of Computation, Christof Koch. This book covers many aspects of cell-based neurophysiology from a modeling perspective (Koch 1999).Google Scholar

Copyright information

© Springer-Verlag New York, Inc. 2002

Authors and Affiliations

  • John Rinzel

There are no affiliations available

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