Correlation coding
Encyclopedia
The correlation coding model of neuron
al firing claims that correlations between action potential
s, 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. Any degree of correlation reduces the total entropy; thus, by Fisher's Information Theorem
, correlations can only reduce information.
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.
Contrast this with independent-spike coding
.
Neuron
A neuron is an electrically excitable cell that processes and transmits information by electrical and chemical signaling. Chemical signaling occurs via synapses, specialized connections with other cells. Neurons connect to each other to form networks. Neurons are the core components of the nervous...
al firing claims that correlations between action potential
Action potential
In physiology, an action potential is a short-lasting event in which the electrical membrane potential of a cell rapidly rises and falls, following a consistent trajectory. Action potentials occur in several types of animal cells, called excitable cells, which include neurons, muscle cells, and...
s, 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. Any degree of correlation reduces the total entropy; thus, by Fisher's Information Theorem
Fisher information
In mathematical statistics and information theory, the Fisher information is the variance of the score. In Bayesian statistics, the asymptotic distribution of the posterior mode depends on the Fisher information and not on the prior...
, correlations can only reduce information.
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.
Contrast this with independent-spike coding
Independent-spike coding
The independent-spike coding model of neuronal firing claims that each individual action potential, or "spike", is independent of each other spike within the spike train.Contrast this with correlation coding.-References:...
.
See also
- Rate coding
- Temporal codingTemporal codingThe temporal coding is a type of neural coding which relies on precise timing of action potentials or inter-spike intervals.Combined with traditional rate coding models, temporal coding can provide additional information with the same rate....
- Sparse codingSparse codingThe sparse code is a kind of neural code in which each item is encoded by the strong activation of a relatively small set of neurons. For each item to be encoded, this is a different subset of all available neurons....
- Independent-spike codingIndependent-spike codingThe independent-spike coding model of neuronal firing claims that each individual action potential, or "spike", is independent of each other spike within the spike train.Contrast this with correlation coding.-References:...
- Population codingPopulation codingPopulation coding is a means by which information is coded in a group of neurons. In population coding, each neuron has a distribution of responses over some set of inputs, and the responses of many neurons may be combined to determine some value about the inputs...