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An Electrophysiological Index of Perceptual Goodness
A traditional line of work starting with the Gestalt school has shown that patterns vary in strength and salience; a difference in “Perceptual goodness.” The Holographic weight of evidence model quantifies goodness of visual regularities. The key formula states that W = E/N, where E is number of hol...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5193141/ https://www.ncbi.nlm.nih.gov/pubmed/27702812 http://dx.doi.org/10.1093/cercor/bhw255 |
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author | Makin, Alexis D.J. Wright, Damien Rampone, Giulia Palumbo, Letizia Guest, Martin Sheehan, Rhiannon Cleaver, Helen Bertamini, Marco |
author_facet | Makin, Alexis D.J. Wright, Damien Rampone, Giulia Palumbo, Letizia Guest, Martin Sheehan, Rhiannon Cleaver, Helen Bertamini, Marco |
author_sort | Makin, Alexis D.J. |
collection | PubMed |
description | A traditional line of work starting with the Gestalt school has shown that patterns vary in strength and salience; a difference in “Perceptual goodness.” The Holographic weight of evidence model quantifies goodness of visual regularities. The key formula states that W = E/N, where E is number of holographic identities in a pattern and N is number of elements. We tested whether W predicts the amplitude of the neural response to regularity in an extrastriate symmetry-sensitive network. We recorded an Event Related Potential (ERP) generated by symmetry called the Sustained Posterior Negativity (SPN). First, we reanalyzed the published work and found that W explained most variance in SPN amplitude. Then in four new studies, we confirmed specific predictions of the holographic model regarding 1) the differential effects of numerosity on reflection and repetition, 2) the similarity between reflection and Glass patterns, 3) multiple symmetries, and 4) symmetry and anti-symmetry. In all cases, the holographic approach predicted SPN amplitude remarkably well; particularly in an early window around 300–400 ms post stimulus onset. Although the holographic model was not conceived as a model of neural processing, it captures many details of the brain response to symmetry. |
format | Online Article Text |
id | pubmed-5193141 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-51931412017-01-04 An Electrophysiological Index of Perceptual Goodness Makin, Alexis D.J. Wright, Damien Rampone, Giulia Palumbo, Letizia Guest, Martin Sheehan, Rhiannon Cleaver, Helen Bertamini, Marco Cereb Cortex Original Articles A traditional line of work starting with the Gestalt school has shown that patterns vary in strength and salience; a difference in “Perceptual goodness.” The Holographic weight of evidence model quantifies goodness of visual regularities. The key formula states that W = E/N, where E is number of holographic identities in a pattern and N is number of elements. We tested whether W predicts the amplitude of the neural response to regularity in an extrastriate symmetry-sensitive network. We recorded an Event Related Potential (ERP) generated by symmetry called the Sustained Posterior Negativity (SPN). First, we reanalyzed the published work and found that W explained most variance in SPN amplitude. Then in four new studies, we confirmed specific predictions of the holographic model regarding 1) the differential effects of numerosity on reflection and repetition, 2) the similarity between reflection and Glass patterns, 3) multiple symmetries, and 4) symmetry and anti-symmetry. In all cases, the holographic approach predicted SPN amplitude remarkably well; particularly in an early window around 300–400 ms post stimulus onset. Although the holographic model was not conceived as a model of neural processing, it captures many details of the brain response to symmetry. Oxford University Press 2016-12 2016-12-26 /pmc/articles/PMC5193141/ /pubmed/27702812 http://dx.doi.org/10.1093/cercor/bhw255 Text en © The Author 2016. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Articles Makin, Alexis D.J. Wright, Damien Rampone, Giulia Palumbo, Letizia Guest, Martin Sheehan, Rhiannon Cleaver, Helen Bertamini, Marco An Electrophysiological Index of Perceptual Goodness |
title | An Electrophysiological Index of Perceptual Goodness |
title_full | An Electrophysiological Index of Perceptual Goodness |
title_fullStr | An Electrophysiological Index of Perceptual Goodness |
title_full_unstemmed | An Electrophysiological Index of Perceptual Goodness |
title_short | An Electrophysiological Index of Perceptual Goodness |
title_sort | electrophysiological index of perceptual goodness |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5193141/ https://www.ncbi.nlm.nih.gov/pubmed/27702812 http://dx.doi.org/10.1093/cercor/bhw255 |
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