The conventional interpretation of double dissociations is that they are almost irrefutable evidence of distinctions in both function and type of mental processes, or of separation of cognition into modules. We present a connectionist model that demonstrates apparent double dissociations within a single-route, single-mechanism network and argue that these apparent dissociations are simply the expected tails of a standard bell curve describing network performance. We conclude that within a connectionist model, the appearance of double dissociations may not be evidence for functional or mechanistic separation, and that similar caveats apply to the interpretation of double dissociations in human cognitive behaviour.

Children acquire noun inflections before they acquire verb inflections. Noun inflections are dso less affected by language disorders than verb inflections. We describe a single-system connectionist model of English noun and verb inflection which captures these facts of acquisition and atrophy, as well as other well-established developmental characteristics such as U-shaped learning and the ability to generalise to novel forms. The model makes the novel experimental prediction that irregular nouns are less affected by damage than irregular verbs, even though irregular nouns are harder to learn.

Traditionally, regularity in a data set is assessed by fitting a model to the data and examining the extent to which the variance accounted for by the model is large compared to the overall variance in the system. Such approaches, however, do not address the complementary question of how much regularity is present in the data, in the first place, and how much work is expected to be required to capture a particular amount of regularity. In this work we use the notion of Kolmogorov complexity to derive a measure of system regularity independent of any particular model. Thus, in our framework, the explanatory adequacy of a model can be readily quantified, so that one can examine the extent to which the model is satisfactory, or whether additional mechanisms need be postulated.