Decomposition of Spontaneous Brain Activity into Distinct fMRI Co-activation Patterns
Recent fMRI studies have shown that analysis of the human brain’s spontaneous activity may provide a powerful approach to reveal its functional organization. Dedicated methods have been proposed to investigate co-variation of signals from different brain regions, with the goal of revealing neuronal...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2013-12-01
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| Series: | Frontiers in Systems Neuroscience |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fnsys.2013.00101/full |
| _version_ | 1811232011656888320 |
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| author | Xiao eLiu Catie eChang Jeff H. Duyn |
| author_facet | Xiao eLiu Catie eChang Jeff H. Duyn |
| author_sort | Xiao eLiu |
| collection | DOAJ |
| description | Recent fMRI studies have shown that analysis of the human brain’s spontaneous activity may provide a powerful approach to reveal its functional organization. Dedicated methods have been proposed to investigate co-variation of signals from different brain regions, with the goal of revealing neuronal networks that may serve specialized functions. However, these analysis methods generally do not take into account a potential non-stationary (variable) interaction between brain regions, and as a result have limited effectiveness. To address this, we propose a novel analysis method that uses clustering analysis to sort and selectively average fMRI activity time frames to produce a set of co-activation patterns. Compared to the established networks extracted with conventional analysis methods, these co-activation patterns demonstrate novel network features with apparent relevance to the brain’s functional organization. |
| first_indexed | 2024-04-12T10:54:48Z |
| format | Article |
| id | doaj.art-f281f8e06bce40d6a0531af23444c628 |
| institution | Directory Open Access Journal |
| issn | 1662-5137 |
| language | English |
| last_indexed | 2024-04-12T10:54:48Z |
| publishDate | 2013-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Systems Neuroscience |
| spelling | doaj.art-f281f8e06bce40d6a0531af23444c6282022-12-22T03:36:07ZengFrontiers Media S.A.Frontiers in Systems Neuroscience1662-51372013-12-01710.3389/fnsys.2013.0010162295Decomposition of Spontaneous Brain Activity into Distinct fMRI Co-activation PatternsXiao eLiu0Catie eChang1Jeff H. Duyn2Advanced MRI section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of HealthAdvanced MRI section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of HealthAdvanced MRI section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of HealthRecent fMRI studies have shown that analysis of the human brain’s spontaneous activity may provide a powerful approach to reveal its functional organization. Dedicated methods have been proposed to investigate co-variation of signals from different brain regions, with the goal of revealing neuronal networks that may serve specialized functions. However, these analysis methods generally do not take into account a potential non-stationary (variable) interaction between brain regions, and as a result have limited effectiveness. To address this, we propose a novel analysis method that uses clustering analysis to sort and selectively average fMRI activity time frames to produce a set of co-activation patterns. Compared to the established networks extracted with conventional analysis methods, these co-activation patterns demonstrate novel network features with apparent relevance to the brain’s functional organization.http://journal.frontiersin.org/Journal/10.3389/fnsys.2013.00101/fullnetwork dynamicsClustering analysisresting-state networksDynamic connectivityNonstationary Connectivity |
| spellingShingle | Xiao eLiu Catie eChang Jeff H. Duyn Decomposition of Spontaneous Brain Activity into Distinct fMRI Co-activation Patterns Frontiers in Systems Neuroscience network dynamics Clustering analysis resting-state networks Dynamic connectivity Nonstationary Connectivity |
| title | Decomposition of Spontaneous Brain Activity into Distinct fMRI Co-activation Patterns |
| title_full | Decomposition of Spontaneous Brain Activity into Distinct fMRI Co-activation Patterns |
| title_fullStr | Decomposition of Spontaneous Brain Activity into Distinct fMRI Co-activation Patterns |
| title_full_unstemmed | Decomposition of Spontaneous Brain Activity into Distinct fMRI Co-activation Patterns |
| title_short | Decomposition of Spontaneous Brain Activity into Distinct fMRI Co-activation Patterns |
| title_sort | decomposition of spontaneous brain activity into distinct fmri co activation patterns |
| topic | network dynamics Clustering analysis resting-state networks Dynamic connectivity Nonstationary Connectivity |
| url | http://journal.frontiersin.org/Journal/10.3389/fnsys.2013.00101/full |
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