In addition to being psychologically motivated, this sort of gradient representation is also more compatible with machine learning algorithms and particularly with deep neural models that naturally operate with real-valued multidimensional word embeddings and hidden states.
establishing which of the above-mentioned strategies is optimal in terms of prediction accuracy is not straightforward.