Abstract

We examined how two distinct stimulus features, orientation and color, interact as contributions to global stimulus dissimilarity. Five subjects rated dissimilarity between pairs of bars (N = 30) varying in color (four cardinal hues, plus white) and orientation (six angles at 30° intervals). An exploratory analysis with individual-differences multidimensional scaling (MDS) resulted in a 5D solution, with two dimensions required to accommodate the circular sequence of the angular attribute, and red-green, blue-yellow and achromatic axes for the color attribute. Weights of the orientation subspace relative to the color subspace varied among the subjects, from a 0.32:0.61 ratio to 0.53:0.44, emphasis shifting between color and orientation. In addition to Euclidean metric, we modeled the interaction of color and orientation using Minkowski power metrics across a range of Minkowski exponents p, including the city-block (p = 1), Euclidean (p = 2) and Dominance metric (p → ∞) as special cases. For averaged data, p ~ 1.3 provided the best fit, i.e., intermediate between separable and integral features. For individual subjects, however, the metric exponent varied significantly from p = 0.7 to p = 3.1, indicating a subject-specific rule for combining color and orientation, as in Tversky and Gati's variable-weights model. No relationship was apparent between dimensional weights and individual p exponents. Factors affecting dimensional integrality are discussed, including possible underlying neural mechanisms where the interaction of the low-level vision attributes orientation and color might shift between uncorrelated (p = 1) or correlated (p ≥ 2) forms.

Highlights

  • Researchers in visual perception frequently ask observers whether two stimuli are different, or how different they are

  • The present study further explores the interaction of visual attributes in bimodal stimuli and extends Izmailov and Edrenkin’s (2010) path of research, with bar stimuli varying in color in addition to orientation

  • MULTIDIMENSIONAL SCALING (EUCLIDEAN METRIC) Analysis began with multidimensional scaling (MDS), in which a Euclidean geometrical model is used to account for the data, representing each stimulus as a point in a low-dimensional space

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Summary

Introduction

Researchers in visual perception frequently ask observers whether two stimuli are different, or how different they are. The total inter-stimulus dissimilarity is an aggregate of differences across multiple attributes, and the research question becomes one of how these differences interact. A research tradition beginning with Attneave (1950) has focused on the special case of “integral” dimensions, where the attributes on which the stimuli are parameterized can be replaced with oblique linear combinations, intrinsically as good as the original parameters, because the inter-stimulus dissimilarities remain the same. In Garner’s words (1974, 199), “[p]sychologically, if dimensions are integral, they are not really perceived as dimensions at all. .” That is, integral dimensions form a seamless Gestalt Dimensions exist for the experimenter [. . . ] but these are constructs [. . . ] and do not reflect the immediate perceptual experience of the subject in such experiments . . . .” That is, integral dimensions form a seamless Gestalt

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