Abstract
The act of reaching for and acting upon an object involves two forms of selection: selection of the object as a target, and selection of the action to be performed. While these two forms of selection are logically dissociable, and are evidently subserved by separable neural pathways, they must also be closely coordinated. We examine the nature of this coordination by developing and analyzing a computational model of object and action selection first proposed by Ward [Ward, R. (1999). Interactions between perception and action systems: a model for selective action. In G. W. Humphreys, J. Duncan, & A. Treisman (Eds.), Attention, Space and Action: Studies in Cognitive Neuroscience. Oxford: Oxford University Press]. An interesting tenet of this account, which we explore in detail, is that the interplay between object and action selection depends critically on top-down inputs representing the current task set or plan of action. A concrete manifestation of this, established through a series of simulations, is that the impact of distractor objects on reaching times can vary depending on the nature of the current action plan. In order to test the model's predictions in this regard, we conducted two experiments, one involving direct object manipulation, the other involving tool-use. In both experiments we observed the specific interaction between task set and distractor type predicted by the model. Our findings provide support for the computational model, and more broadly for an interactive account of object and action selection.