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Individual Topographic Variability Is Inherent to Cortical Physiology but Task-Related Differences May Be Noise
The observation of highly variable sets of association neocortical areas across individuals, containing the estimated generators of Slow Potentials (SPs) and beta oscillations, lead to the persistence in individual analyses. This brought to notice an unexpected within individual topographic similari...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4444270/ https://www.ncbi.nlm.nih.gov/pubmed/26010428 http://dx.doi.org/10.1371/journal.pone.0128343 |
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author | Basile, Luis F. H. Sato, João R. Pasquini, Henrique A. Lozano, Mirna D. Nucci, Mariana P. Velasques, Bruna Ribeiro, Pedro Ramos, Renato T. Anghina, Renato |
author_facet | Basile, Luis F. H. Sato, João R. Pasquini, Henrique A. Lozano, Mirna D. Nucci, Mariana P. Velasques, Bruna Ribeiro, Pedro Ramos, Renato T. Anghina, Renato |
author_sort | Basile, Luis F. H. |
collection | PubMed |
description | The observation of highly variable sets of association neocortical areas across individuals, containing the estimated generators of Slow Potentials (SPs) and beta oscillations, lead to the persistence in individual analyses. This brought to notice an unexpected within individual topographic similarity between task conditions, despite our original interest in task-related differences. A recent related work explored the quantification of the similarity in beta topography between largely differing tasks. In this article, we used Independent Component Analysis (ICA) for the decomposition of beta activity from a visual attention task, and compared it with quiet resting, recorded by 128-channel EEG in 62 subjects. We statistically tested whether each ICA component obtained in one condition could be explained by a linear regression model based on the topographic patterns from the other condition, in each individual. Results were coherent with the previous report, showing a high topographic similarity between conditions. From an average of 12 beta component maps obtained for each task, over 80% were satisfactorily explained by the complementary task. Once more, the component maps including those considered unexplained, putatively “task-specific”, had their scalp distribution and estimated cortical sources highly variable across subjects. These findings are discussed along with other studies based on individual data and the present fMRI results, reinforcing the increasingly accepted view that individual variability in sets of active neocortical association areas is not noise, but intrinsic to cortical physiology. Actual ‘noise’, mainly stemming from group “brain averaging” and the emphasis on statistical differences as opposed to similarities, may explain the overall hardship in replication of the vast literature on supposed task-specific forms of activity, and the ever inconclusive status of a universal functional mapping of cortical association areas. A new hypothesis, that individuals may use the same idiosyncratic sets of areas, at least by their fraction of activity in the sub-delta and beta range, in various non-sensory-motor forms of conscious activities, is a corollary of the discussed variability. |
format | Online Article Text |
id | pubmed-4444270 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-44442702015-06-16 Individual Topographic Variability Is Inherent to Cortical Physiology but Task-Related Differences May Be Noise Basile, Luis F. H. Sato, João R. Pasquini, Henrique A. Lozano, Mirna D. Nucci, Mariana P. Velasques, Bruna Ribeiro, Pedro Ramos, Renato T. Anghina, Renato PLoS One Research Article The observation of highly variable sets of association neocortical areas across individuals, containing the estimated generators of Slow Potentials (SPs) and beta oscillations, lead to the persistence in individual analyses. This brought to notice an unexpected within individual topographic similarity between task conditions, despite our original interest in task-related differences. A recent related work explored the quantification of the similarity in beta topography between largely differing tasks. In this article, we used Independent Component Analysis (ICA) for the decomposition of beta activity from a visual attention task, and compared it with quiet resting, recorded by 128-channel EEG in 62 subjects. We statistically tested whether each ICA component obtained in one condition could be explained by a linear regression model based on the topographic patterns from the other condition, in each individual. Results were coherent with the previous report, showing a high topographic similarity between conditions. From an average of 12 beta component maps obtained for each task, over 80% were satisfactorily explained by the complementary task. Once more, the component maps including those considered unexplained, putatively “task-specific”, had their scalp distribution and estimated cortical sources highly variable across subjects. These findings are discussed along with other studies based on individual data and the present fMRI results, reinforcing the increasingly accepted view that individual variability in sets of active neocortical association areas is not noise, but intrinsic to cortical physiology. Actual ‘noise’, mainly stemming from group “brain averaging” and the emphasis on statistical differences as opposed to similarities, may explain the overall hardship in replication of the vast literature on supposed task-specific forms of activity, and the ever inconclusive status of a universal functional mapping of cortical association areas. A new hypothesis, that individuals may use the same idiosyncratic sets of areas, at least by their fraction of activity in the sub-delta and beta range, in various non-sensory-motor forms of conscious activities, is a corollary of the discussed variability. Public Library of Science 2015-05-26 /pmc/articles/PMC4444270/ /pubmed/26010428 http://dx.doi.org/10.1371/journal.pone.0128343 Text en © 2015 Basile 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 Basile, Luis F. H. Sato, João R. Pasquini, Henrique A. Lozano, Mirna D. Nucci, Mariana P. Velasques, Bruna Ribeiro, Pedro Ramos, Renato T. Anghina, Renato Individual Topographic Variability Is Inherent to Cortical Physiology but Task-Related Differences May Be Noise |
title | Individual Topographic Variability Is Inherent to Cortical Physiology but Task-Related Differences May Be Noise |
title_full | Individual Topographic Variability Is Inherent to Cortical Physiology but Task-Related Differences May Be Noise |
title_fullStr | Individual Topographic Variability Is Inherent to Cortical Physiology but Task-Related Differences May Be Noise |
title_full_unstemmed | Individual Topographic Variability Is Inherent to Cortical Physiology but Task-Related Differences May Be Noise |
title_short | Individual Topographic Variability Is Inherent to Cortical Physiology but Task-Related Differences May Be Noise |
title_sort | individual topographic variability is inherent to cortical physiology but task-related differences may be noise |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4444270/ https://www.ncbi.nlm.nih.gov/pubmed/26010428 http://dx.doi.org/10.1371/journal.pone.0128343 |
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