On defining and interpreting dissociations

A common assumption in cognitive neuropsychology is that a single (classical) dissociation will trump any accounts suggesting totally shared mechanisms, and this no matter how many observations of associations can be mustered (see e.g., Tree, 2011). Due to this special status of dissociations it seems reasonable to demand, as Geskin and Behrmann do (this issue), that dissociations between face and object recognition in developmental prosopagnosia (DP) must be demonstrated taking into account both accuracy and latency (RT), and these demonstrations ought to rest on data from assessments of face and non-face recognition that are matched in complexity and processing demands. Even though the latter condition may be hard to fulfil in reality (Robotham & Starrfelt, 2017), it is nevertheless the case that a dissociation demonstrated by contrasting performance on, for example, a difficult face recognition task and an easy object recognition task may reflect nothing besides a difference in task difficulty. A methodological issue not considered in great detail by Geskin and Behrmann, however, is how a dissociation is defined. They seem to adopt the common definition that a dissociation is established if a person performs abnormally on task X but within the normal range on task Y, with ‘normality’ being anchored by whether performance falls below or beyond 2 SDs (or 1.7) of the control mean. There are two problems with this approach. First, it implicitly assumes that failure to reject the null hypothesis regarding performance on task Y is proof of normality. This is a dubious assumption (Crawford, Garthwaite, & Gray, 2003), not least because studies in cognitive neuropsychology are typically characterized by low statistical power (few controls) which leaves plenty of room for Type 2 errors (false-negatives). Secondly, it does not take into consideration the difference in performance between tasks X and Y. In the extreme case, one could claim a dissociation if a person’s scores amounted to −2.01 SD on task X and −1.99 SD on task Y; a trivial difference of . 02 SD. To overcome these problems, Crawford et al. (2003) have suggested that a performance pattern must fulfil two criteria in order to be considered as a dissociation: 1) the person’s performance on task X must differ significantly from that of the normal population; and 2) the difference in performance of that person on tasks X and Y must differ significantly from the difference scores of the normal population on tasks X and Y. Crawford et al. have even developed computer programmes which can be used to assess whether a particular performance pattern qualifies as a dissociation when both criteria are taken into account (Crawford, Garthwaite, & Porter, 2010). In addition to testing whether a case’s scores on tasks X and Y differ significantly from the normal population by using the control participants’ mean and SD as sample statistics (rather than as population parameters), these tests estimate whether the case’s standardized difference between tasks X and Y differs significantly from the standardized differences in controls by taking into account the correlation between tasks X and Y in the control sample. If a dissociation is revealed, it may be either a strong dissociation or a putatively classical dissociation (Shallice, 1988). A strong dissociation refers to a performance pattern where an individual’s scores deviate significantly from the control sample on both tasks X and Y, and where the individual’s difference between tasks X and Y exceeds what can be expected in the normal population. In comparison, a