Correlation coding
From Wikipedia, the free encyclopedia
The correlation coding model of neuronal firing claims that correlations between action potentials, or "spikes", within a spike train may carry additional information above and beyond the simple timing of the spikes. It has been theoretically demonstrated that correlation between spike trains can only reduce, and never increase, the total mutual information present in the two spike trains about a stimulus feature. [1] Any degree of correlation reduces the total entropy, and so correlations, following Fisher's Information Theorem, can only reduce information as they always reduce entropy.
However, this does not prevent correlations from carrying information not present in the average firing rate of two pairs of neurons. A good example of this exists in the pentobarbital-anesthetized marmoset auditory cortex, in which a pure tone causes an increase in the number of correlated spikes, but not an increase in the mean firing rate, of pairs of neurons. [2]
Contrast this with independent-spike coding.
[edit] See also
[edit] References
- Dayan P & Abbott LF. Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems. Cambridge, Massachusetts: The MIT Press; 2001. ISBN 0-262-04199-5
- Rieke F, Warland D, de Ruyter van Steveninck R, Bialek W. Spikes: Exploring the Neural Code. Cambridge, Massachusetts: The MIT Press; 1999. ISBN 0-262-68108-0