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Predictive Coding: A Possible Explanation of Filling-In at the Blind Spot

Filling-in at the blind spot is a perceptual phenomenon in which the visual system fills the informational void, which arises due to the absence of retinal input corresponding to the optic disc, with surrounding visual attributes. It is known that during filling-in, nonlinear neural responses are ob...

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Detalles Bibliográficos
Autores principales: Raman, Rajani, Sarkar, Sandip
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4784844/
https://www.ncbi.nlm.nih.gov/pubmed/26959812
http://dx.doi.org/10.1371/journal.pone.0151194
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author Raman, Rajani
Sarkar, Sandip
author_facet Raman, Rajani
Sarkar, Sandip
author_sort Raman, Rajani
collection PubMed
description Filling-in at the blind spot is a perceptual phenomenon in which the visual system fills the informational void, which arises due to the absence of retinal input corresponding to the optic disc, with surrounding visual attributes. It is known that during filling-in, nonlinear neural responses are observed in the early visual area that correlates with the perception, but the knowledge of underlying neural mechanism for filling-in at the blind spot is far from complete. In this work, we attempted to present a fresh perspective on the computational mechanism of filling-in process in the framework of hierarchical predictive coding, which provides a functional explanation for a range of neural responses in the cortex. We simulated a three-level hierarchical network and observe its response while stimulating the network with different bar stimulus across the blind spot. We find that the predictive-estimator neurons that represent blind spot in primary visual cortex exhibit elevated non-linear response when the bar stimulated both sides of the blind spot. Using generative model, we also show that these responses represent the filling-in completion. All these results are consistent with the finding of psychophysical and physiological studies. In this study, we also demonstrate that the tolerance in filling-in qualitatively matches with the experimental findings related to non-aligned bars. We discuss this phenomenon in the predictive coding paradigm and show that all our results could be explained by taking into account the efficient coding of natural images along with feedback and feed-forward connections that allow priors and predictions to co-evolve to arrive at the best prediction. These results suggest that the filling-in process could be a manifestation of the general computational principle of hierarchical predictive coding of natural images.
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spelling pubmed-47848442016-03-23 Predictive Coding: A Possible Explanation of Filling-In at the Blind Spot Raman, Rajani Sarkar, Sandip PLoS One Research Article Filling-in at the blind spot is a perceptual phenomenon in which the visual system fills the informational void, which arises due to the absence of retinal input corresponding to the optic disc, with surrounding visual attributes. It is known that during filling-in, nonlinear neural responses are observed in the early visual area that correlates with the perception, but the knowledge of underlying neural mechanism for filling-in at the blind spot is far from complete. In this work, we attempted to present a fresh perspective on the computational mechanism of filling-in process in the framework of hierarchical predictive coding, which provides a functional explanation for a range of neural responses in the cortex. We simulated a three-level hierarchical network and observe its response while stimulating the network with different bar stimulus across the blind spot. We find that the predictive-estimator neurons that represent blind spot in primary visual cortex exhibit elevated non-linear response when the bar stimulated both sides of the blind spot. Using generative model, we also show that these responses represent the filling-in completion. All these results are consistent with the finding of psychophysical and physiological studies. In this study, we also demonstrate that the tolerance in filling-in qualitatively matches with the experimental findings related to non-aligned bars. We discuss this phenomenon in the predictive coding paradigm and show that all our results could be explained by taking into account the efficient coding of natural images along with feedback and feed-forward connections that allow priors and predictions to co-evolve to arrive at the best prediction. These results suggest that the filling-in process could be a manifestation of the general computational principle of hierarchical predictive coding of natural images. Public Library of Science 2016-03-09 /pmc/articles/PMC4784844/ /pubmed/26959812 http://dx.doi.org/10.1371/journal.pone.0151194 Text en © 2016 Raman, Sarkar 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 use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Raman, Rajani
Sarkar, Sandip
Predictive Coding: A Possible Explanation of Filling-In at the Blind Spot
title Predictive Coding: A Possible Explanation of Filling-In at the Blind Spot
title_full Predictive Coding: A Possible Explanation of Filling-In at the Blind Spot
title_fullStr Predictive Coding: A Possible Explanation of Filling-In at the Blind Spot
title_full_unstemmed Predictive Coding: A Possible Explanation of Filling-In at the Blind Spot
title_short Predictive Coding: A Possible Explanation of Filling-In at the Blind Spot
title_sort predictive coding: a possible explanation of filling-in at the blind spot
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4784844/
https://www.ncbi.nlm.nih.gov/pubmed/26959812
http://dx.doi.org/10.1371/journal.pone.0151194
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