Comparing explicit and implicit ensemble perception

Poster Presentation 43.316: Monday, May 22, 2023, 8:30 am – 12:30 pm, Banyan Breezeway
Session: Scene Perception: Spatiotemporal factors

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Shaul Hochstein1 (), Noam Khayat1, Marina Pavlovskaya1; 1ELSC Safra Center for Brain Research & Life Sciences Institute, Hebrew University, Jerusalem

Introduction. Visual scenes are too complex to immediately perceive all their details. As suggested by Gestalt psychologists, grouping similar scene elements expedites evaluating scene gist. Ensemble perception is efficient representation of similar object sets by their summary statistics, overcoming processing, attention and memory limits. Observers are better at perceiving image set means than remembering presence of particular set members. We previously found that ensemble perception occurs explicitly, when observers are asked to judge set mean, and automatically, implicitly, on-the-fly, trial-by-trial, when engaged in an orthogonal task. Ensemble perception includes low-level, (line orientation), and high-level, (category exemplar), variables. There is an inherent paradox in ensemble perception, as in categorization: Ensemble (or category) members share sufficient features to allow recognizing them as belonging to the same set (or category), but each one is different, or we would have a useless tautology. Methods. We now study relationships among these ensemble perception phenomena, testing explicit and implicit ensemble perception; for sets varying in circle size, line orientation, or disc brightness; and with spatial, temporal or spatio-temporal presentation. Following ensemble set presentation, 96 observers were asked if a test image, or which of 2, had been present in the set. Then, subsequent experiments asked the same observers to explicitly judge if the test image was larger, more clockwise, or brighter than the set mean, or which of two test images was closer to the mean. Results. Image presence followed a Gaussian dependence on (relative) distance from set mean, and explicit mean judgement had sigmoidal dependence on (relative) distance from mean. We directly compare these dependences, finding that explicit ensemble averaging is more precise than implicit mean perception – for each ensemble variable, presentation mode, and (1- or 2-image) testing mode. Conclusions. Implicit ensemble-statistics perception has lower precision than tasks requiring explicit ensemble integration.

Acknowledgements: supported by a grant from the Israel Science Foundation (ISF)