Cargando…
Revisiting Nonlinear Functional Brain Co-activations: Directed, Dynamic, and Delayed
The center stage of neuro-imaging is currently occupied by studies of functional correlations between brain regions. These correlations define the brain functional networks, which are the most frequently used framework to represent and interpret a variety of experimental findings. In the previous st...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8546168/ https://www.ncbi.nlm.nih.gov/pubmed/34712111 http://dx.doi.org/10.3389/fnins.2021.700171 |
_version_ | 1784590135653826560 |
---|---|
author | Cifre, Ignacio Miller Flores, Maria T. Penalba, Lucia Ochab, Jeremi K. Chialvo, Dante R. |
author_facet | Cifre, Ignacio Miller Flores, Maria T. Penalba, Lucia Ochab, Jeremi K. Chialvo, Dante R. |
author_sort | Cifre, Ignacio |
collection | PubMed |
description | The center stage of neuro-imaging is currently occupied by studies of functional correlations between brain regions. These correlations define the brain functional networks, which are the most frequently used framework to represent and interpret a variety of experimental findings. In the previous study, we first demonstrated that the relatively stronger blood oxygenated level dependent (BOLD) activations contain most of the information relevant to understand functional connectivity, and subsequent work confirmed that a large compression of the original signals can be obtained without significant loss of information. In this study, we revisit the correlation properties of these epochs to define a measure of nonlinear dynamic directed functional connectivity (nldFC) across regions of interest. We show that the proposed metric provides at once, without extensive numerical complications, directed information of the functional correlations, as well as a measure of temporal lags across regions, overall offering a different and complementary perspective in the analysis of brain co-activation patterns. In this study, we provide further details for the computations of these measures and for a proof of concept based on replicating existing results from an Autistic Syndrome database, and discuss the main features and advantages of the proposed strategy for the study of brain functional correlations. |
format | Online Article Text |
id | pubmed-8546168 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85461682021-10-27 Revisiting Nonlinear Functional Brain Co-activations: Directed, Dynamic, and Delayed Cifre, Ignacio Miller Flores, Maria T. Penalba, Lucia Ochab, Jeremi K. Chialvo, Dante R. Front Neurosci Neuroscience The center stage of neuro-imaging is currently occupied by studies of functional correlations between brain regions. These correlations define the brain functional networks, which are the most frequently used framework to represent and interpret a variety of experimental findings. In the previous study, we first demonstrated that the relatively stronger blood oxygenated level dependent (BOLD) activations contain most of the information relevant to understand functional connectivity, and subsequent work confirmed that a large compression of the original signals can be obtained without significant loss of information. In this study, we revisit the correlation properties of these epochs to define a measure of nonlinear dynamic directed functional connectivity (nldFC) across regions of interest. We show that the proposed metric provides at once, without extensive numerical complications, directed information of the functional correlations, as well as a measure of temporal lags across regions, overall offering a different and complementary perspective in the analysis of brain co-activation patterns. In this study, we provide further details for the computations of these measures and for a proof of concept based on replicating existing results from an Autistic Syndrome database, and discuss the main features and advantages of the proposed strategy for the study of brain functional correlations. Frontiers Media S.A. 2021-10-12 /pmc/articles/PMC8546168/ /pubmed/34712111 http://dx.doi.org/10.3389/fnins.2021.700171 Text en Copyright © 2021 Cifre, Miller Flores, Penalba, Ochab and Chialvo. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Cifre, Ignacio Miller Flores, Maria T. Penalba, Lucia Ochab, Jeremi K. Chialvo, Dante R. Revisiting Nonlinear Functional Brain Co-activations: Directed, Dynamic, and Delayed |
title | Revisiting Nonlinear Functional Brain Co-activations: Directed, Dynamic, and Delayed |
title_full | Revisiting Nonlinear Functional Brain Co-activations: Directed, Dynamic, and Delayed |
title_fullStr | Revisiting Nonlinear Functional Brain Co-activations: Directed, Dynamic, and Delayed |
title_full_unstemmed | Revisiting Nonlinear Functional Brain Co-activations: Directed, Dynamic, and Delayed |
title_short | Revisiting Nonlinear Functional Brain Co-activations: Directed, Dynamic, and Delayed |
title_sort | revisiting nonlinear functional brain co-activations: directed, dynamic, and delayed |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8546168/ https://www.ncbi.nlm.nih.gov/pubmed/34712111 http://dx.doi.org/10.3389/fnins.2021.700171 |
work_keys_str_mv | AT cifreignacio revisitingnonlinearfunctionalbraincoactivationsdirecteddynamicanddelayed AT millerfloresmariat revisitingnonlinearfunctionalbraincoactivationsdirecteddynamicanddelayed AT penalbalucia revisitingnonlinearfunctionalbraincoactivationsdirecteddynamicanddelayed AT ochabjeremik revisitingnonlinearfunctionalbraincoactivationsdirecteddynamicanddelayed AT chialvodanter revisitingnonlinearfunctionalbraincoactivationsdirecteddynamicanddelayed |