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A dynamical framework to relate perceptual variability with multisensory information processing
Multisensory processing involves participation of individual sensory streams, e.g., vision, audition to facilitate perception of environmental stimuli. An experimental realization of the underlying complexity is captured by the “McGurk-effect”- incongruent auditory and visual vocalization stimuli el...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4977493/ https://www.ncbi.nlm.nih.gov/pubmed/27502974 http://dx.doi.org/10.1038/srep31280 |
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author | Thakur, Bhumika Mukherjee, Abhishek Sen, Abhijit Banerjee, Arpan |
author_facet | Thakur, Bhumika Mukherjee, Abhishek Sen, Abhijit Banerjee, Arpan |
author_sort | Thakur, Bhumika |
collection | PubMed |
description | Multisensory processing involves participation of individual sensory streams, e.g., vision, audition to facilitate perception of environmental stimuli. An experimental realization of the underlying complexity is captured by the “McGurk-effect”- incongruent auditory and visual vocalization stimuli eliciting perception of illusory speech sounds. Further studies have established that time-delay between onset of auditory and visual signals (AV lag) and perturbations in the unisensory streams are key variables that modulate perception. However, as of now only few quantitative theoretical frameworks have been proposed to understand the interplay among these psychophysical variables or the neural systems level interactions that govern perceptual variability. Here, we propose a dynamic systems model consisting of the basic ingredients of any multisensory processing, two unisensory and one multisensory sub-system (nodes) as reported by several researchers. The nodes are connected such that biophysically inspired coupling parameters and time delays become key parameters of this network. We observed that zero AV lag results in maximum synchronization of constituent nodes and the degree of synchronization decreases when we have non-zero lags. The attractor states of this network can thus be interpreted as the facilitator for stabilizing specific perceptual experience. Thereby, the dynamic model presents a quantitative framework for understanding multisensory information processing. |
format | Online Article Text |
id | pubmed-4977493 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-49774932016-08-22 A dynamical framework to relate perceptual variability with multisensory information processing Thakur, Bhumika Mukherjee, Abhishek Sen, Abhijit Banerjee, Arpan Sci Rep Article Multisensory processing involves participation of individual sensory streams, e.g., vision, audition to facilitate perception of environmental stimuli. An experimental realization of the underlying complexity is captured by the “McGurk-effect”- incongruent auditory and visual vocalization stimuli eliciting perception of illusory speech sounds. Further studies have established that time-delay between onset of auditory and visual signals (AV lag) and perturbations in the unisensory streams are key variables that modulate perception. However, as of now only few quantitative theoretical frameworks have been proposed to understand the interplay among these psychophysical variables or the neural systems level interactions that govern perceptual variability. Here, we propose a dynamic systems model consisting of the basic ingredients of any multisensory processing, two unisensory and one multisensory sub-system (nodes) as reported by several researchers. The nodes are connected such that biophysically inspired coupling parameters and time delays become key parameters of this network. We observed that zero AV lag results in maximum synchronization of constituent nodes and the degree of synchronization decreases when we have non-zero lags. The attractor states of this network can thus be interpreted as the facilitator for stabilizing specific perceptual experience. Thereby, the dynamic model presents a quantitative framework for understanding multisensory information processing. Nature Publishing Group 2016-08-09 /pmc/articles/PMC4977493/ /pubmed/27502974 http://dx.doi.org/10.1038/srep31280 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Thakur, Bhumika Mukherjee, Abhishek Sen, Abhijit Banerjee, Arpan A dynamical framework to relate perceptual variability with multisensory information processing |
title | A dynamical framework to relate perceptual variability with multisensory information processing |
title_full | A dynamical framework to relate perceptual variability with multisensory information processing |
title_fullStr | A dynamical framework to relate perceptual variability with multisensory information processing |
title_full_unstemmed | A dynamical framework to relate perceptual variability with multisensory information processing |
title_short | A dynamical framework to relate perceptual variability with multisensory information processing |
title_sort | dynamical framework to relate perceptual variability with multisensory information processing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4977493/ https://www.ncbi.nlm.nih.gov/pubmed/27502974 http://dx.doi.org/10.1038/srep31280 |
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