The density effect in centroid estimation is blind to contrast polarity
Rashid, Jordan Ali; Chubb, Charles (2021), The density effect in centroid estimation is blind to contrast polarity, Dryad, Dataset, https://doi.org/10.7280/D10111
Human vision is highly efficient in estimating the centroids of spatially scattered items. However, the processes underlying this remarkable skill remain poorly understood. A salient fact is that in estimating the centroids of dot-clouds, observers underweight densely packed dots relative to isolated dots; thus, when an observer estimates the centroid of a dot cloud, the weight exerted on the subject’s response by a given dot tends to be suppressed by other dots near it. The current experiment sought to determine whether dots of contrast polarity equal vs. opposite to a given dot differ in how they alter the weight it exerts. Six observers were tested in a task that used brief (150 ms), Gaussian clouds that mixed 9 white and 9 black dots on a gray background. On each trial, the observer strove to mouse-click the centroid of the stimulus cloud weighting all dots equally. The model used to describe the results allows the weight exerted on the subject’s response by a given dot to depend on its peripherality in the stimulus cloud as well as on the density of same- and opposite-polarity dots surrounding it. For four observers, peripheral dots exerted lower influence than central dots on responses; the other two showed little effect of peripherality. For all observers, dots in high-density regions exerted less weight on responses than dots in low-density regions. Concerning the primary research question: dots of opposite vs. the same polarity as a given dot suppressed the weight it exerted with equal effectiveness. This suggests that the site of the interaction producing the density effect is a neural population that registers positive and negative contrast polarities in the same way.
See methods section of manuscript for details on data collection. The data file is a MATLAB data file organized into structures. There is a README text file included to explain each field of the structure.
See the README.txt in zip file.