The role of the teacher in learning-based models of parietal area 7a

The back-propagation learning procedure can be used to train simulated neural networks to compute arbitrary functions. We have recently shown that when such a network is trained to carry out the transformation of stimulus location to head-centered coordinates that occurs in parietal area 7a, the response properties of certain units in the network closely resemble neurons found in area 7a. The back-propagation procedure requires the use of a teacher. Here we examine the effect of using different kinds of teachers. As long as the teacher represents information about stimulus location in head-centered coordinates, the trained network contains units of the kind found in area 7a. Differences in teacher format only effect the quantitative distribution of the different unit types. When the teacher does not represent stimulus location explicitly, the network does not contain units of the required kind.