Frequently, a common chemical entity triggers opposite cellular processes, which implies that the components of signalling networks must detect signals not only through their chemical natures, but also through their dynamic properties. To gain insights on the mechanisms of discrimination of the dynamic properties of cellular signals, we developed a computational stochastic model and investigated how three calcium ion (Ca(2+))-dependent enzymes (adenylyl cyclase (AC), phosphodiesterase 1 (PDE1), and calcineurin (CaN)) differentially detect Ca(2+) transients in a hippocampal dendritic spine. The balance among AC, PDE1 and CaN might determine the occurrence of opposite Ca(2+)-induced forms of synaptic plasticity, long-term potentiation (LTP) and long-term depression (LTD). CaN is essential for LTD. AC and PDE1 regulate, indirectly, protein kinase A, which counteracts CaN during LTP. Stimulations of AC, PDE1 and CaN with artificial and physiological Ca(2+) signals demonstrated that AC and CaN have Ca(2+) requirements modulated dynamically by different properties of the signals used to stimulate them, because their interactions with Ca(2+) often occur under kinetic control. Contrarily, PDE1 responds to the immediate amplitude of different Ca(2+) transients and usually with the same Ca(2+) requirements observed under steady state. Therefore, AC, PDE1 and CaN decode different dynamic properties of Ca(2+) signals.