The Morton-Massaro law of information integration: implications for models of perception

Information integration may be studied by analyzing the effect of 2 or more sources (e.g., auditory and visual) on participants' responses. Experiments show that ratios of response probabilities often factorize into components selectively influenced by only 1 source (e.g., 1 component affected by the acoustic source and another 1 affected by the visual source). This is called the Morton-Massaro law (MML). This article identifies conditions in which the law is optimal and notes that it reflects an implicit assumption about the statistics of the environment. Adherence to the MML can be used to assess whether the assumption is being made, and analyses of natural stimuli can be used to determine whether the assumption is reasonable. Feed-forward and interactive models subject to a channel separability constraint are consistent with the law.