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Perceptual history biases in serial ensemble representation

Ensemble perception refers to the visual system's ability to efficiently represent groups of similar objects as a unified percept using their summary statistical information. Most studies focused on extraction of current trial averages, giving little attention to prior experience effects, altho...

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Autores principales: Khayat, Noam, Ahissar, Merav, Hochstein, Shaul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10029768/
https://www.ncbi.nlm.nih.gov/pubmed/36920389
http://dx.doi.org/10.1167/jov.23.3.7
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author Khayat, Noam
Ahissar, Merav
Hochstein, Shaul
author_facet Khayat, Noam
Ahissar, Merav
Hochstein, Shaul
author_sort Khayat, Noam
collection PubMed
description Ensemble perception refers to the visual system's ability to efficiently represent groups of similar objects as a unified percept using their summary statistical information. Most studies focused on extraction of current trial averages, giving little attention to prior experience effects, although a few recent studies found that ensemble mean estimations contract toward previously presented stimuli, with most of these focusing on explicit perceptual averaging of simultaneously presented item ensembles. Yet, the time element is crucial in real dynamic environments, where we encounter ensemble items over time, aggregating information until reaching summary representations. Moreover, statistical information of objects and scenes is learned over time and often implicitly and then used for predictions that shape perception, promoting environmental stability. Therefore, we now focus on temporal aspects of ensemble statistics and test whether prior information, beyond the current trial, biases implicit perceptual decisions. We designed methods to separate current trial biases from those of previously seen trial ensembles. In each trial, six circles of different sizes were presented serially, followed by two test items. Participants were asked to choose which was present in the sequence. Participants unconsciously rely on ensemble statistics, choosing stimuli closer to the ensemble mean. To isolate the influence of earlier trials, the two test items were sometimes equidistant from the current trial mean. Results showed membership judgment biases toward current trial mean, when informative (largest effect). On equidistant trials, judgments were biased toward previously experienced stimulus statistics. Comparison of similar conditions with a shifted stimulus distribution ruled out a bias toward an earlier, presession, prototypical diameter. We conclude that ensemble perception, even for temporally experienced ensembles, is influenced not only by current trial mean but also by means of recently seen ensembles and that these influences are somewhat correlated on a participant-by-participant basis.
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spelling pubmed-100297682023-03-22 Perceptual history biases in serial ensemble representation Khayat, Noam Ahissar, Merav Hochstein, Shaul J Vis Article Ensemble perception refers to the visual system's ability to efficiently represent groups of similar objects as a unified percept using their summary statistical information. Most studies focused on extraction of current trial averages, giving little attention to prior experience effects, although a few recent studies found that ensemble mean estimations contract toward previously presented stimuli, with most of these focusing on explicit perceptual averaging of simultaneously presented item ensembles. Yet, the time element is crucial in real dynamic environments, where we encounter ensemble items over time, aggregating information until reaching summary representations. Moreover, statistical information of objects and scenes is learned over time and often implicitly and then used for predictions that shape perception, promoting environmental stability. Therefore, we now focus on temporal aspects of ensemble statistics and test whether prior information, beyond the current trial, biases implicit perceptual decisions. We designed methods to separate current trial biases from those of previously seen trial ensembles. In each trial, six circles of different sizes were presented serially, followed by two test items. Participants were asked to choose which was present in the sequence. Participants unconsciously rely on ensemble statistics, choosing stimuli closer to the ensemble mean. To isolate the influence of earlier trials, the two test items were sometimes equidistant from the current trial mean. Results showed membership judgment biases toward current trial mean, when informative (largest effect). On equidistant trials, judgments were biased toward previously experienced stimulus statistics. Comparison of similar conditions with a shifted stimulus distribution ruled out a bias toward an earlier, presession, prototypical diameter. We conclude that ensemble perception, even for temporally experienced ensembles, is influenced not only by current trial mean but also by means of recently seen ensembles and that these influences are somewhat correlated on a participant-by-participant basis. The Association for Research in Vision and Ophthalmology 2023-03-15 /pmc/articles/PMC10029768/ /pubmed/36920389 http://dx.doi.org/10.1167/jov.23.3.7 Text en Copyright 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
spellingShingle Article
Khayat, Noam
Ahissar, Merav
Hochstein, Shaul
Perceptual history biases in serial ensemble representation
title Perceptual history biases in serial ensemble representation
title_full Perceptual history biases in serial ensemble representation
title_fullStr Perceptual history biases in serial ensemble representation
title_full_unstemmed Perceptual history biases in serial ensemble representation
title_short Perceptual history biases in serial ensemble representation
title_sort perceptual history biases in serial ensemble representation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10029768/
https://www.ncbi.nlm.nih.gov/pubmed/36920389
http://dx.doi.org/10.1167/jov.23.3.7
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