Neural Coding: Variability and Information
The application of Shannon’s Information Theory to the nervous system initially led to enormous discrepancies between estimates of the potential amount of information that might be transmitted and psychophysical estimates of the amount of information that human observers can discriminate. This chapter reviews the reasons for these discrepancies and their resolution based on the coding of steady vs. time varying signals, the role of variability in limiting information transfer but improving fidelity of transmission, the importance of precise timing vs. frequency codes in some sensory systems. Motor systems often function so as to minimize the variance in attaining an end point and neural data are consistent with a theory of how this minimization can be achieved.
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