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Measuring multisensory integration: from reaction times to spike counts
A neuron is categorized as “multisensory” if there is a statistically significant difference between the response evoked, e.g., by a crossmodal stimulus combination and that evoked by the most effective of its components separately. Being responsive to multiple sensory modalities does not guarantee...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5465073/ https://www.ncbi.nlm.nih.gov/pubmed/28596602 http://dx.doi.org/10.1038/s41598-017-03219-5 |
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author | Colonius, Hans Diederich, Adele |
author_facet | Colonius, Hans Diederich, Adele |
author_sort | Colonius, Hans |
collection | PubMed |
description | A neuron is categorized as “multisensory” if there is a statistically significant difference between the response evoked, e.g., by a crossmodal stimulus combination and that evoked by the most effective of its components separately. Being responsive to multiple sensory modalities does not guarantee that a neuron has actually engaged in integrating its multiple sensory inputs: it could simply respond to the stimulus component eliciting the strongest response in a given trial. Crossmodal enhancement is commonly expressed as a proportion of the strongest mean unisensory response. This traditional index does not take into account any statistical dependency between the sensory channels under crossmodal stimulation. We propose an alternative index measuring by how much the multisensory response surpasses the level obtainable by optimally combining the unisensory responses, with optimality defined as probability summation under maximal negative stochastic dependence. The new index is analogous to measuring crossmodal enhancement in reaction time studies by the strength of violation of the “race model inequality’, a numerical measure of multisensory integration. Since the new index tends to be smaller than the traditional one, neurons previously labeled as “multisensory’ may lose that property. The index is easy to compute and it is sensitive to variability in data. |
format | Online Article Text |
id | pubmed-5465073 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-54650732017-06-14 Measuring multisensory integration: from reaction times to spike counts Colonius, Hans Diederich, Adele Sci Rep Article A neuron is categorized as “multisensory” if there is a statistically significant difference between the response evoked, e.g., by a crossmodal stimulus combination and that evoked by the most effective of its components separately. Being responsive to multiple sensory modalities does not guarantee that a neuron has actually engaged in integrating its multiple sensory inputs: it could simply respond to the stimulus component eliciting the strongest response in a given trial. Crossmodal enhancement is commonly expressed as a proportion of the strongest mean unisensory response. This traditional index does not take into account any statistical dependency between the sensory channels under crossmodal stimulation. We propose an alternative index measuring by how much the multisensory response surpasses the level obtainable by optimally combining the unisensory responses, with optimality defined as probability summation under maximal negative stochastic dependence. The new index is analogous to measuring crossmodal enhancement in reaction time studies by the strength of violation of the “race model inequality’, a numerical measure of multisensory integration. Since the new index tends to be smaller than the traditional one, neurons previously labeled as “multisensory’ may lose that property. The index is easy to compute and it is sensitive to variability in data. Nature Publishing Group UK 2017-06-08 /pmc/articles/PMC5465073/ /pubmed/28596602 http://dx.doi.org/10.1038/s41598-017-03219-5 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Colonius, Hans Diederich, Adele Measuring multisensory integration: from reaction times to spike counts |
title | Measuring multisensory integration: from reaction times to spike counts |
title_full | Measuring multisensory integration: from reaction times to spike counts |
title_fullStr | Measuring multisensory integration: from reaction times to spike counts |
title_full_unstemmed | Measuring multisensory integration: from reaction times to spike counts |
title_short | Measuring multisensory integration: from reaction times to spike counts |
title_sort | measuring multisensory integration: from reaction times to spike counts |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5465073/ https://www.ncbi.nlm.nih.gov/pubmed/28596602 http://dx.doi.org/10.1038/s41598-017-03219-5 |
work_keys_str_mv | AT coloniushans measuringmultisensoryintegrationfromreactiontimestospikecounts AT diederichadele measuringmultisensoryintegrationfromreactiontimestospikecounts |