Just to help clarify, this is true, and is indeed a consequence of the filtering over time. When those two spikes are accumulated by leaky integration (a lowpass filter acting as the model for the postsynaptic current) they will sum to twice the value of a single spike with the same weight. This is assuming that the two spikes occur nearby in time relative to the time course of the synaptic filter (in other words, that the firing rate is high relative to the [reciprocal of the] time-constant \tau^{-1} used to model the exponential decay of the leak).
The interpretation of decoders as weights only holds roughly in the 1D case (after accounting for a possible change in sign for “on/off” neurons, a gain, and a bias current). In higher dimensions, the actual weight is a dot-product of a higher-dimensional decoder with a higher-dimensional encoder. This results in a conceptual distinction between the weight matrix and their factored forms used to understand the relevant computations. The course notes, and some of the Nengo notebook examples, are a good reference for understanding this in more detail.