Intrinsic modeling of time in NEF and SPA

Dear all
in comparison to simple connective network approaches (edges or links; nodes or units; activation spreading between neural layers) where time consonants needs to be defined explicitly ( e.g., time constant for decay of neural activation in nodes) this needs not to be done in the NEF approach.
Temporal changes of neural activations are an implicit feature in the NEF-SPA concept.
So, my question is:
What are the most important implicit processes in the NEF-SPA approach leading to the fact that we need not to include an external temporal processing in the NEF-SPA approach?
Which intrinsic processes within the NEF-SPA concept manage the temporal aspects of the NEF-SPA neural networks?
1 ) implicit time constants are used for modeling spike generation?
2 ) implicit time constants are used for modeling delay for forwarding neural signals to synaptic connections?
3 ) a set of time constants is used to model different types of synaptic connections at the level of the BG and Thalamus?
Could you help me to get a deeper insight in these NEF-SPA processes for modeling timing or time in the NEF-SPA concept?

Kind regards , Bernd