Mechanisms of Integration: What Parameters Control Output as Function of Input?

  • Theodore Holmes Bullock


With the goal of outlining a frame of reference for considering how organized constellations of neurons integrate and operate to achieve neural function, I define integration, recognize its several, widely disparate levels, and review the middle levels—between the molecular and membrane channel level on the basic side and the memory and motivation level on the cognitive side. It appears that the molecular and subcellular levels are more general and less diverse in different species and parts of the nervous system.

The cellular and even more the intercellular levels are so differentiated that many degrees of freedom are available with which the neuron or small assemblies of them can integrate their inputs to determine their outputs (Table 1). The locus concept—that parts of the neuron are quite different in capabilities—is an important preliminary to evaluating the list of variables by which neurons differ from one another in the ways they can integrate. This list of several scores of variables includes accommodation, proximal-distal asymmetry, after-potentials and rebound, plateau potentials, tendency to repetitive firing and plasticity of various properties. Combinations of characteristic values along each of these variables occur in almost unlimited permutations; each kind of neuron has a “personality” determined by its combination. As we learn in Chapter 3, neurons use not a single code, the frequency of impulses, but one or more than one of a list of several spike codes and many graded, subthreshold response codes.

A selection of the intercellular mechanisms is reviewed, including heterosynaptic facilitation, presynaptic modulation, pacemakers subject to influence by input, and synchrony of subthreshold activity among cells of a population. Several special aspects of neuronal integration are treated in Chapters 3–7, the origin of pattern in [61–1], page 496 of this volume and Section V, page 483 of this volume, and higher levels of integration in Sections II, III and IV.

As has happened many times before, we can expect to discover still more emergent properties and integrative mechanisms, including varying degrees of plasticity of them; this is especially true at the highest integrative levels in the brain. As has happened before, when these accumulate so that our picture of how neural assemblies operate has changed sufficiently, we will have undergone another quiet revolution in neuroscience.


Effective Connectivity Electrical Transmission Plateau Potential Repetitive Firing Squid Giant Axon 
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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Copyright information

© Springer Science+Business Media New York 1993

Authors and Affiliations

  • Theodore Holmes Bullock
    • 1
  1. 1.Department of Neurosciences 0201University of California, San DiegoLa JollaUSA

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