The computational details of the Gestalt Bubble model presented above are necessarily somewhat vague and speculative at this point. But the real significance of this model of perception is not in its computational details, but in the paradigmatic message behind the model, which is that spatial perception is exactly as it appears phenomenally, i.e. a reified three-dimensional spatial structure that contains more explicit spatial information than the two-dimensional retinal stimulus on which it is based. The Gestalt principles of emergence, reification, and multistability can be emulated in a computational model as a relaxation algorithm between local computational elements that interact with field-like influences. Whatever the neurophysiological reality behind this holistic emergent style of computation, the Gestalt Bubble model captures certain essential features of Gestalt perception, and these in turn offer clues as to the neurophysiological principles behind perceptual computation.

The three-dimensional spatial interpolation in the Gestalt Bubble model is exactly the kind of mechanism that is required to account for perceptual phenomena such as those shown below.