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Functional Holography is a method of analysis designed to extract the maximum amount of functional information about the dynamical network as a whole unit.
Itay Baruchi and his Ph.D. supervisor, Eshel Ben-Jacob, introduced the Functional Holography methodology. The FH analysis was devised to study the dynamics of task performing dynamical networks.
The new approach is based on the realization that task-performing networks follow some underlying principles that should be reflected and therefore be detected in their activity. Where the analysis is designed to decipher the existence of simple causal motives that are expected to be embedded in the observed complex activity of the networks are noticeable. Many studies have applied the FH analysis to modeled and real networks or complex data the characteristic geometrical and topological features are deciphered in the complex activity.