Combining Integral and Separable Subspaces

It is well known that pairs of dimensions that are processed holistically integral dimensions normally combine with a Euclidean metric, whereas pairs of dimensions that are processed analytically separable dimensions most often combine with a city-block metric. This paper extends earlier research regarding information integration in that it deals with complex stimuli consisting of both dimensional pairs previously identified as holistic, and dimensional pairs previously identified as analytical. The general pattern identified is that information integration can be more accurately described with a rule taking aspects of stimuli into consideration compared to a traditional rule. For example, it appears that combinations of analytical and holistic stimuli, are better described by treating the different subspaces individually and then combining these with addition, compared to any single Minkowskian rule, and much better compared to any of the Minkowskian rules traditionally used (i.e. the cityblock-, the Euclidean or the dominance-metrics).