Spatially Pooled Contrast Responses Predict Neural and Perceptual Similarity of Naturalistic Image Categories
Figure 3
Methods and experimental design.
(A), Experimental set-up of experiment 1 (EEG experiment). Subjects were presented with individual images of dead leaves while EEG was recorded. Single-image evoked responses (ERPs) were computed for each electrode, by averaging two repeated presentations of each individual image. Regression analyses of ERP amplitude on contrast statistics were performed at each time sample and electrode. (B), Representational dissimilarity matrices (RDMs) were computed at each sample of the ERP. A single RDM displays Euclidean distance (red = high, blue = low) between multiple-electrode patterns of ERP amplitude between all pairs of stimuli at a specific moment in time. The (cartoon) inset demonstrates how dissimilarities can cluster by category: all images from one category are in consecutive rows and can be ‘similarly dissimilar’ to other categories. (C), Experimental set-up of experiment 2 (behavioral experiment). On each trial, subjects were presented with a pair of stimuli for 50 ms, followed by a mask after an interval of 100 ms. Subjects were presented 8 times with all possible pairings of stimuli and were instructed to indicate whether stimuli were the same or different. (D), Cartoon example of leave-one-out classification based on contrast statistics. One stimulus is selected in turn, after which the median (thumbnail) of the remaining stimuli of its category is computed, as well as the median of other categories (here, just one). Classification accuracy reflects how many stimuli are closer to the median of other categories instead of its own category in terms of distance in image statistics.