Spontaneous Plasticity of Multineuronal Activity Patterns in Activated Hippocampal Networks
Figure 2
Diagram of entropy-based metrics to capture network activity patterns. (a) Shannon
index (SI) is calculated with the Shannon entropy equation and normalized with its maximum
and minimum values that can be taken through data shuffle with keeping the
total number of events constant, as shown in the schematics. (b) SI can take
different values depending on the pattern of activity, even when the numbers of
activity events and active cells are invariant. (c) Example of the normalized SI (NSI)
in multineuronal spike trains. A 1-minute window (shadow area) was placed at
any given time on a rastergram. Two histograms were made by projecting the dataset
to the vertical (right) and horizontal axes (bottom), so that NSIs evaluate the event dispersion in
terms of space and time ( and , resp.).