Neural Models for Part-Whole Hierarchies

We present a connectionist method for representing images that ex(cid:173) plicitly addresses their hierarchical nature. It blends data from neu(cid:173) roscience about whole-object viewpoint sensitive cells in inferotem(cid:173) poral cortex8 and attentional basis-field modulation in V43 with ideas about hierarchical descriptions based on microfeatures.5,11 The resulting model makes critical use of bottom-up and top-down pathways for analysis and synthesis.6 We illustrate the model with a simple example of representing information about faces. Images of objects constitute an important paradigm case of a representational hi(cid:173) erarchy, in which'wholes', such as faces, consist of'parts', such as eyes, noses and mouths.