Typical spatial descriptions, such as “The car is in front of the house,” describe the position of a located object (LO; e.g., the car) in space relative to a reference object (RO) whose location is known (e.g., the house). The orientation of the RO affects spatial language comprehension via the reference frame selection process. However, the effects of the LO's orientation on spatial language have not received great attention. This study explores whether the pure geometric information of the LO (e.g., (...) its orientation) affects spatial language comprehension using placing and production tasks. Our results suggest that the orientation of the LO influences spatial language comprehension even in the absence of functional relationships. (shrink)

The ability to judge spatial relations from perspectives that differ from one's current body orientation and location is important for many everyday activities. Despite considerable research on imaginal perspective taking, however, detailed computational accounts of the processes involved in this ability are missing. In this contribution, I introduce Smart (Spatial Memory Access by Reference Frame SelecTion) as a computational cognitive model of imaginal perspective taking processes. In assuming that imaginal perspective taking is governed by reference frame selection for memory access (...) and subsequent motor activation, Smart is able to explain and simulate key findings on human imaginal perspective taking. In addition to providing novel insight into the mechanisms underlying imaginal perspective taking, Smart also has several implications for our view on spatial memory, more generally. In particular, Smart supports the idea that enduring spatial representations are essentially orientation-free and that spatial representations are best viewed as flexible combinations of representation structures and reference frames. (shrink)

Previous studies have shown that multiple reference frames are available and compete for selection during the use of spatial terms such as “above.” However, the mechanisms that underlie the selection process are poorly understood. In the current paper we present two experiments and a comparison of three computational models of selection to shed further light on the nature of reference frame selection. The three models are drawn from different areas of human cognition, and we assess whether they may be applied (...) to a reference frame selection by examining their ability to account for both existing and new empirical data comprising acceptance rates, response times, and response time distributions. These three models are the competitive shunting model, the leaky competing accumulator model, and a lexical selection model. Model simulations show that only the LCA model satisfactorily accounts for the empirical observations. The key properties of this model that seem to drive its success are its bounded linear activation function, its number and type of processing stages, and its use of decay. Uncovering these critical properties has important implications for our understanding not only of spatial term use, in particular, but also of conflict and selection in human cognition more generally. (shrink)