A parallel-process model of mental rotation

Abstract

It is argued that some of the phenomena identified with analog processes by Shepard can be understood as resulting from a parallel-process algorithm running on a processor having many individual processing elements and a restricted communication structure. In particular, an algorithm has been developed and implemented which models human behavior on Shepard's object rotation and comparison task. The algorithm exhibits computation times which increase linearly with the angle of rotation. Shepard found a similar linear function in his experiments with human subjects. In addition, the intermediate states of the computation are such that if the rotation process were to be interrupted at any point, the object representation would correspond to that of the actual object at a position along the rotation trajectory. The computational model presented here is governed by three constraining assumptions: (a) that it be parallel: (b) that the communication between processors be restricted to immediate neighbors: (c) that the object representation be distributed across a large fraction of the available processors. A method of diagnosing the correct axis of rotation is also presented.