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Information and Perception of Meaningful Patterns
The visual system needs to extract the most important elements of the external world from a large flux of information in a short time for survival purposes. It is widely believed that in performing this task, it operates a strong data reduction at an early stage, by creating a compact summary of rel...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3716808/ https://www.ncbi.nlm.nih.gov/pubmed/23894422 http://dx.doi.org/10.1371/journal.pone.0069154 |
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author | Del Viva, Maria M. Punzi, Giovanni Benedetti, Daniele |
author_facet | Del Viva, Maria M. Punzi, Giovanni Benedetti, Daniele |
author_sort | Del Viva, Maria M. |
collection | PubMed |
description | The visual system needs to extract the most important elements of the external world from a large flux of information in a short time for survival purposes. It is widely believed that in performing this task, it operates a strong data reduction at an early stage, by creating a compact summary of relevant information that can be handled by further levels of processing. In this work we formulate a model of early vision based on a pattern-filtering architecture, partly inspired by high-speed digital data reduction in experimental high-energy physics (HEP). This allows a much stronger data reduction than models based just on redundancy reduction. We show that optimizing this model for best information preservation under tight constraints on computational resources yields surprisingly specific a-priori predictions for the shape of biologically plausible features, and for experimental observations on fast extraction of salient visual features by human observers. Interestingly, applying the same optimized model to HEP data acquisition systems based on pattern-filtering architectures leads to specific a-priori predictions for the relevant data patterns that these devices extract from their inputs. These results suggest that the limitedness of computing resources can play an important role in shaping the nature of perception, by determining what is perceived as “meaningful features” in the input data. |
format | Online Article Text |
id | pubmed-3716808 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-37168082013-07-26 Information and Perception of Meaningful Patterns Del Viva, Maria M. Punzi, Giovanni Benedetti, Daniele PLoS One Research Article The visual system needs to extract the most important elements of the external world from a large flux of information in a short time for survival purposes. It is widely believed that in performing this task, it operates a strong data reduction at an early stage, by creating a compact summary of relevant information that can be handled by further levels of processing. In this work we formulate a model of early vision based on a pattern-filtering architecture, partly inspired by high-speed digital data reduction in experimental high-energy physics (HEP). This allows a much stronger data reduction than models based just on redundancy reduction. We show that optimizing this model for best information preservation under tight constraints on computational resources yields surprisingly specific a-priori predictions for the shape of biologically plausible features, and for experimental observations on fast extraction of salient visual features by human observers. Interestingly, applying the same optimized model to HEP data acquisition systems based on pattern-filtering architectures leads to specific a-priori predictions for the relevant data patterns that these devices extract from their inputs. These results suggest that the limitedness of computing resources can play an important role in shaping the nature of perception, by determining what is perceived as “meaningful features” in the input data. Public Library of Science 2013-07-19 /pmc/articles/PMC3716808/ /pubmed/23894422 http://dx.doi.org/10.1371/journal.pone.0069154 Text en © 2013 Del Viva et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Del Viva, Maria M. Punzi, Giovanni Benedetti, Daniele Information and Perception of Meaningful Patterns |
title | Information and Perception of Meaningful Patterns |
title_full | Information and Perception of Meaningful Patterns |
title_fullStr | Information and Perception of Meaningful Patterns |
title_full_unstemmed | Information and Perception of Meaningful Patterns |
title_short | Information and Perception of Meaningful Patterns |
title_sort | information and perception of meaningful patterns |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3716808/ https://www.ncbi.nlm.nih.gov/pubmed/23894422 http://dx.doi.org/10.1371/journal.pone.0069154 |
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