Abstract

Correlation analyses of recent back‐propagation neural networks show that network results are due to imbalances in stimulus input. Conclusions concerning the effects of receptive field size, hemispheric specialization, and other issues of relevance to psychology cannot therefore be drawn until the dominating effects of low‐level correlations are removed. Statistical techniques for evaluating the stimulus materials for neural networks are introduced.