“What” Effects on “Where”: Functional Influences on Spatial Relations

Abstract

Spatial relations indicate the location of an object by specifying its direction with respect to a reference object whose location is known. It has been largely assumed that specific features of these objects are generally ignored in descriptions of spatial location. Within such a view, spatial relations can be described in terms of geometric or topological features that are not dependent on object details such as function. We demonstrate in two experiments that a geometric feature (center of mass) is not sufficient. Using two different tasks, we show that the function of the reference object and its relationship with the other object significantly influence the way in which vertical spatial relations (“above” and “below”) are applied to spatial configurations.

Attentional Distribution and Spatial Language

“…This may be due to the simplification of the trajector and the center-of-mass deviant functional interaction. Since the data sets in [15] are considerably smaller than the data set from [12], it did not seem reasonable to further reduce the number of data points by employing a functional subset. In sum, across all three data sets, the focus only at function extension proposed in this article result in relatively bad GOF-values, except for the small functional subset.…”

“…In [15] experiments are presented that investigated the swedish spatial prepositions ovanför, över, nevanför and under (corresponding to the english prepositions above, over, below and under) with respect to their acceptability when influenced by a functional relationship between landmark and trajector. As the AVS simulations in [10] and Experiment 2 in [12] only consider above, we restricted our simulations to the corresponding swedish preposition ovanför.…”

“…We used the center of mass of the coin trajectors for the data from both [15] and [12]. This seems reasonable, because a coin is a small trajector and the functional interaction shown in Fig.…”

“…The AVS and its extensions were implemented in C++. 3 Each of the models was fit to three different data sets: (i) ratings for all three slot positions in [12,Experiment 2]; (ii) ratings for the piggy bank landmark in [15]; and (iii) ratings for the petrol can landmark in [15]. Using the RMSE of model ratings and empirical ratings as the criterion function, all models were fit using a variant of the Metropolis algorithm [17].…”

“…This model, called attentional vectorsum (AVS) model [10], computes acceptability ratings for how well a given spatial term such as above describes the spatial arrangement between two objects. In the light of evidence that functional relations between objects impact spatial language use [11,12], [13] proposed an extension of the AVS, henceforth called functional AVS (fAVS), that allows the computation of the acceptability ratings to be influenced by functional object relations.…”