Disentangling Multispectral Functional Connectivity With Wavelets
The field of brain connectomics develops our understanding of the brain's intrinsic organization by characterizing trends in spontaneous brain activity. Linear correlations in spontaneous blood-oxygen level dependent functional magnetic resonance imaging (BOLD-fMRI) fluctuations are often used...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2018-11-01
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| Series: | Frontiers in Neuroscience |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fnins.2018.00812/full |
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| author | Jacob C. W. Billings Jacob C. W. Billings Garth J. Thompson Garth J. Thompson Wen-Ju Pan Matthew E. Magnuson Alessio Medda Shella Keilholz Shella Keilholz |
| author_facet | Jacob C. W. Billings Jacob C. W. Billings Garth J. Thompson Garth J. Thompson Wen-Ju Pan Matthew E. Magnuson Alessio Medda Shella Keilholz Shella Keilholz |
| author_sort | Jacob C. W. Billings |
| collection | DOAJ |
| description | The field of brain connectomics develops our understanding of the brain's intrinsic organization by characterizing trends in spontaneous brain activity. Linear correlations in spontaneous blood-oxygen level dependent functional magnetic resonance imaging (BOLD-fMRI) fluctuations are often used as measures of functional connectivity (FC), that is, as a quantity describing how similarly two brain regions behave over time. Given the natural spectral scaling of BOLD-fMRI signals, it may be useful to represent BOLD-fMRI as multiple processes occurring over multiple scales. The wavelet domain presents a transform space well suited to the examination of multiscale systems as the wavelet basis set is constructed from a self-similar rescaling of a time and frequency delimited kernel. In the present study, we utilize wavelet transforms to examine fluctuations in whole-brain BOLD-fMRI connectivity as a function of wavelet spectral scale in a sample (N = 31) of resting healthy human volunteers. Information theoretic criteria measure relatedness between spectrally-delimited FC graphs. Voxelwise comparisons of between-spectra graph structures illustrate the development of preferential functional networks across spectral bands. |
| first_indexed | 2024-04-13T17:06:07Z |
| format | Article |
| id | doaj.art-7adbc4a167b5466ab06184bf911a5be3 |
| institution | Directory Open Access Journal |
| issn | 1662-453X |
| language | English |
| last_indexed | 2024-04-13T17:06:07Z |
| publishDate | 2018-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroscience |
| spelling | doaj.art-7adbc4a167b5466ab06184bf911a5be32022-12-22T02:38:27ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2018-11-011210.3389/fnins.2018.00812402323Disentangling Multispectral Functional Connectivity With WaveletsJacob C. W. Billings0Jacob C. W. Billings1Garth J. Thompson2Garth J. Thompson3Wen-Ju Pan4Matthew E. Magnuson5Alessio Medda6Shella Keilholz7Shella Keilholz8Graduate Division of Biological and Biomedical Sciences – Program in Neuroscience, Emory University, Atlanta, GA, United StatesBiomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United StatesBiomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United StatesiHuman Institute, ShanghaiTech University, Pudong, ChinaBiomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United StatesBiomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United StatesAerospace Transportation and Advanced Systems, Georgia Tech Research Institute, Atlanta, GA, United StatesGraduate Division of Biological and Biomedical Sciences – Program in Neuroscience, Emory University, Atlanta, GA, United StatesBiomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United StatesThe field of brain connectomics develops our understanding of the brain's intrinsic organization by characterizing trends in spontaneous brain activity. Linear correlations in spontaneous blood-oxygen level dependent functional magnetic resonance imaging (BOLD-fMRI) fluctuations are often used as measures of functional connectivity (FC), that is, as a quantity describing how similarly two brain regions behave over time. Given the natural spectral scaling of BOLD-fMRI signals, it may be useful to represent BOLD-fMRI as multiple processes occurring over multiple scales. The wavelet domain presents a transform space well suited to the examination of multiscale systems as the wavelet basis set is constructed from a self-similar rescaling of a time and frequency delimited kernel. In the present study, we utilize wavelet transforms to examine fluctuations in whole-brain BOLD-fMRI connectivity as a function of wavelet spectral scale in a sample (N = 31) of resting healthy human volunteers. Information theoretic criteria measure relatedness between spectrally-delimited FC graphs. Voxelwise comparisons of between-spectra graph structures illustrate the development of preferential functional networks across spectral bands.https://www.frontiersin.org/article/10.3389/fnins.2018.00812/fullresting statefunctional magnetic resonance imagingfunctional connectivitywavelet packet transformmutual informationclustering |
| spellingShingle | Jacob C. W. Billings Jacob C. W. Billings Garth J. Thompson Garth J. Thompson Wen-Ju Pan Matthew E. Magnuson Alessio Medda Shella Keilholz Shella Keilholz Disentangling Multispectral Functional Connectivity With Wavelets Frontiers in Neuroscience resting state functional magnetic resonance imaging functional connectivity wavelet packet transform mutual information clustering |
| title | Disentangling Multispectral Functional Connectivity With Wavelets |
| title_full | Disentangling Multispectral Functional Connectivity With Wavelets |
| title_fullStr | Disentangling Multispectral Functional Connectivity With Wavelets |
| title_full_unstemmed | Disentangling Multispectral Functional Connectivity With Wavelets |
| title_short | Disentangling Multispectral Functional Connectivity With Wavelets |
| title_sort | disentangling multispectral functional connectivity with wavelets |
| topic | resting state functional magnetic resonance imaging functional connectivity wavelet packet transform mutual information clustering |
| url | https://www.frontiersin.org/article/10.3389/fnins.2018.00812/full |
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