There are not many free parameters in the framework described here. The amoeba example and the brain are at opposite ends of the evolutionary scale yet they differ remarkably little. The number of dimensions, [math]n[/math], and the number of stored contexts, [math]m[/math], are the key differences, with a greater complexity of paths through sensory+motivation space possible as these parameters increase. Evolution can work slowly, only adding dimensions when these help to distinguish contexts where different actions are required and increasing the length of paths through sensory+motivational space when these are beneficial for survival.
Plants fall somewhere between an amoeba and a brain. They have a motor system (as time-lapse photography illustrates vividly) and a sensory system - sensing cold, injury, light, lack of water - and they move through sensory+motivational space along well-adapted paths. For every living organism it would be instructive (in an ideal world, where this was simple to estimate) to plot the dimensionality of sensory+motivational space, [math]n[/math], through which a plant or animal moves and the number of separable sensory+motivational contexts they store, [math]m[/math]. As discussed elsewhere, autonomous robots could be added to the plot.