Incremental Mutual Information: A New Method for Characterizing the Strength and Dynamics of Connections in Neuronal Circuits is a 2010 paper by A. Singh and N. Lesica in PLoS Computational Biology that describes a method which can be used as an alternative to correlation analysis for some cases.*
What is the promise of Incremental Mutual Information (IMI), compared to correlation analysis and correlation functions? First, similar to mutual information, which I have discussed before, it also considers non-linear dependencies of neuronal activities. Second, “it has the potential to disambiguate statistical dependencies that reflect the connection between neurons from those caused by other sources (e.g. shared inputs or intrinsic cellular or network mechanisms) provided that the dependencies have appropriate timescales” (taken from the abstract). This sounds interesting, but we have to consider ‘appropriate timescales’ in more detail later.
A blog about neurophysiology 