Dissociating visuo-spatial and verbal working memory: It's all in the features.

Echoing many of the themes of the seminal work of Atkinson and Shiffrin (The Psychology of Learning and Motivation, 2; 89-195, 1968), this paper uses the feature model (Nairne, Memory & Cognition, 16, 343-352, 1988; Nairne, Memory & Cognition, 18; 251-269, 1990; Neath & Nairne, Psychonomic Bulletin & Review, 2; 429-441, 1995) to account for performance in working-memory tasks. The Brooks verbal and visuo-spatial matrix tasks were performed alone, with articulatory suppression, or with a spatial suppression task; the results produced the expected dissociation. We used approximate Bayesian computation techniques to fit the feature model to the data and showed that the similarity-based interference process implemented in the model accounted for the data patterns well. We then fit the model to data from Guérard and Tremblay (2008, Journal of Experimental Psychology: Learning, Memory, and Cognition, 34, 556-569); the latter study produced a double dissociation while calling upon more typical order reconstruction tasks. Again, the model performed well. The findings show that a double dissociation can be modelled without appealing to separate systems for verbal and visuo-spatial processing. The latter findings are significant as the feature model had not been used to model this type of dissociation before; importantly, this is also the first time the model is quantitatively fit to data. For the demonstration provided here, modularity was unnecessary if two assumptions were made: (1) the main difference between spatial and verbal working-memory tasks is the features that are encoded; (2) secondary tasks selectively interfere with primary tasks to the extent that both tasks involve similar features. It is argued that a feature-based view is more parsimonious (see Morey, 2018, Psychological Bulletin, 144, 849-883) and offers flexibility in accounting for multiple benchmark effects in the field.