Shannon mutual information provides a measure of how much information is, on average, contained in a set of neural activities about a set of stimuli. It has been extensively used to study neural coding in different brain areas. To apply a similar approach to investigate single stimulus encoding, the authors need to introduce a quantity specific for a single stimulus.
Single Stimulus.

A scientific paper by Michele Bezzi
Accenture Technology Labs, Sophia Antipolis, France

This quantity has been defined in literature by four different measures, but none of them satisfies the same intuitive properties (non-negativity, additivity), that characterize mutual information. The authors present here a detailed analysis of the different meanings and properties of these four definitions and show that all these measures satisfy, at least, a weaker additivity condition, i.e. limited to the response set. This allows their use for analysing correlated coding, as illustrated in a toy-example from hippocampal place cells.
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