Population coding is the quantitative study of which algorithms or representations are used by the brain to combine together and evaluate the messages carried by different neurons. Here, we review an information-theory-based approach to population coding. We discuss how to quantify the information carried by a neural population and how to quantify the contribution of individual members of the population, or the interaction between them, to the overall information encoded by the considered group of neurons. We present examples of applications of this formalism to simultaneous recordings of multiple spike trains.
KeywordsMutual Information Spike Train Primary Visual Cortex Individual Neuron Noise Correlation
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