I am glad that my question triggered this track of thoughts. I have been thinking about the same question as well. A hidden unit activation indicates a direction of variation. Visualization helps us investigate the "relative sensitivity" of that variation (or pattern in input) regarding each raw feature (pixel). If a pixel has high value in visualization image, it means that the direction of variation corresponding to that hidden unit is highly sensitive to that pixel. In other words, a little change in that pixel value, results in bigger jumps in the activation of the hidden unit. The activation itself, is the intensity of the corresponding pattern detected in the input space.