Estimating information in time-varying signals
Fig 2
Example biochemical reaction networks and their behavior.
Three example birth-death processes, specified by the reactions in the top row for each of the two possible inputs (u(1) in blue, u(2) in red), stylize simple behaviors of biochemical signaling networks. (A) Input is encoded in both the transient approach to steady state and the steady state value. (B) Input is encoded in the magnitude of the transient response which is subsequently adapted away. (C) Input is encoded only at the level of temporal correlations of the response trajectory. Bottom row shows example trajectories generated using the Stochastic Simulation Algorithm for the copy number of molecules, t ∈ [0, 2000], for each network and the two possible inputs (light blue, light red); while plotted as a connected line for clarity, each trajectory represents molecular counts and is thus a step-wise function taking on only integer or zero values. Dark blue, red lines show the conditional means over N = 1000 trajectory realizations.