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Brain hothubs and dark functional networks: correlation analysis between amplitude and connectivity for Broca’s aphasia
Source localization and functional brain network modeling are methods of identifying critical regions during cognitive tasks. The first activity estimates the relative differences of the signal amplitudes in regions of interest (ROI) and the second activity measures the statistical dependence among...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7533062/ https://www.ncbi.nlm.nih.gov/pubmed/33062446 http://dx.doi.org/10.7717/peerj.10057 |
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author | Lin, Feng Cheng, Shao-Qiang Qi, Dong-Qing Jiang, Yu-Er Lyu, Qian-Qian Zhong, Li-Juan Jiang, Zhong-Li |
author_facet | Lin, Feng Cheng, Shao-Qiang Qi, Dong-Qing Jiang, Yu-Er Lyu, Qian-Qian Zhong, Li-Juan Jiang, Zhong-Li |
author_sort | Lin, Feng |
collection | PubMed |
description | Source localization and functional brain network modeling are methods of identifying critical regions during cognitive tasks. The first activity estimates the relative differences of the signal amplitudes in regions of interest (ROI) and the second activity measures the statistical dependence among signal fluctuations. We hypothesized that the source amplitude–functional connectivity relationship decouples or reverses in persons having brain impairments. Five Broca’s aphasics with five matched cognitively healthy controls underwent overt picture-naming magnetoencephalography scans. The gamma-band (30–45 Hz) phase-locking values were calculated as connections among the ROIs. We calculated the partial correlation coefficients between the amplitudes and network measures and detected four node types, including hothubs with high amplitude and high connectivity, coldhubs with high connectivity but lower amplitude, non-hub hotspots, and non-hub coldspots. The results indicate that the high-amplitude regions are not necessarily highly connected hubs. Furthermore, the Broca aphasics utilized different hothub sets for the naming task. Both groups had dark functional networks composed of coldhubs. Thus, source amplitude–functional connectivity relationships could help reveal functional reorganizations in patients. The amplitude–connectivity combination provides a new perspective for pathological studies of the brain’s dark functional networks. |
format | Online Article Text |
id | pubmed-7533062 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75330622020-10-14 Brain hothubs and dark functional networks: correlation analysis between amplitude and connectivity for Broca’s aphasia Lin, Feng Cheng, Shao-Qiang Qi, Dong-Qing Jiang, Yu-Er Lyu, Qian-Qian Zhong, Li-Juan Jiang, Zhong-Li PeerJ Neuroscience Source localization and functional brain network modeling are methods of identifying critical regions during cognitive tasks. The first activity estimates the relative differences of the signal amplitudes in regions of interest (ROI) and the second activity measures the statistical dependence among signal fluctuations. We hypothesized that the source amplitude–functional connectivity relationship decouples or reverses in persons having brain impairments. Five Broca’s aphasics with five matched cognitively healthy controls underwent overt picture-naming magnetoencephalography scans. The gamma-band (30–45 Hz) phase-locking values were calculated as connections among the ROIs. We calculated the partial correlation coefficients between the amplitudes and network measures and detected four node types, including hothubs with high amplitude and high connectivity, coldhubs with high connectivity but lower amplitude, non-hub hotspots, and non-hub coldspots. The results indicate that the high-amplitude regions are not necessarily highly connected hubs. Furthermore, the Broca aphasics utilized different hothub sets for the naming task. Both groups had dark functional networks composed of coldhubs. Thus, source amplitude–functional connectivity relationships could help reveal functional reorganizations in patients. The amplitude–connectivity combination provides a new perspective for pathological studies of the brain’s dark functional networks. PeerJ Inc. 2020-10-01 /pmc/articles/PMC7533062/ /pubmed/33062446 http://dx.doi.org/10.7717/peerj.10057 Text en ©2020 Lin et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Neuroscience Lin, Feng Cheng, Shao-Qiang Qi, Dong-Qing Jiang, Yu-Er Lyu, Qian-Qian Zhong, Li-Juan Jiang, Zhong-Li Brain hothubs and dark functional networks: correlation analysis between amplitude and connectivity for Broca’s aphasia |
title | Brain hothubs and dark functional networks: correlation analysis between amplitude and connectivity for Broca’s aphasia |
title_full | Brain hothubs and dark functional networks: correlation analysis between amplitude and connectivity for Broca’s aphasia |
title_fullStr | Brain hothubs and dark functional networks: correlation analysis between amplitude and connectivity for Broca’s aphasia |
title_full_unstemmed | Brain hothubs and dark functional networks: correlation analysis between amplitude and connectivity for Broca’s aphasia |
title_short | Brain hothubs and dark functional networks: correlation analysis between amplitude and connectivity for Broca’s aphasia |
title_sort | brain hothubs and dark functional networks: correlation analysis between amplitude and connectivity for broca’s aphasia |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7533062/ https://www.ncbi.nlm.nih.gov/pubmed/33062446 http://dx.doi.org/10.7717/peerj.10057 |
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